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Chapter 15. High Availability and Scalability

Table of Contents

15.1. Oracle VM Template for MySQL Enterprise Edition
15.2. Overview of MySQL with DRBD/Pacemaker/Corosync/Oracle Linux
15.3. Overview of MySQL with Windows Failover Clustering
15.4. Using MySQL within an Amazon EC2 Instance
15.4.1. Setting Up MySQL on an EC2 AMI
15.4.2. EC2 Instance Limitations
15.4.3. Deploying a MySQL Database Using EC2
15.5. Using ZFS Replication
15.5.1. Using ZFS for File System Replication
15.5.2. Configuring MySQL for ZFS Replication
15.5.3. Handling MySQL Recovery with ZFS
15.6. Using MySQL with memcached
15.6.1. Installing memcached
15.6.2. Using memcached
15.6.3. Developing a memcached Application
15.6.4. Getting memcached Statistics
15.6.5. memcached FAQ
15.7. MySQL Proxy
15.7.1. MySQL Proxy Supported Platforms
15.7.2. Installing MySQL Proxy
15.7.3. MySQL Proxy Command Options
15.7.4. MySQL Proxy Scripting
15.7.5. Using MySQL Proxy
15.7.6. MySQL Proxy FAQ

Data is the currency of today's web, mobile, social, enterprise and cloud applications. Ensuring data is always available is a top priority for any organization. Minutes of downtime can result in significant loss of revenue and reputation.

There is no one size fits all approach to delivering High Availability (HA). Unique application attributes, business requirements, operational capabilities and legacy infrastructure can all influence HA technology selection. And technology is only one element in delivering HA: people and processes are just as critical as the technology itself.

MySQL is deployed into many applications demanding availability and scalability. Availability refers to the ability to cope with, and if necessary recover from, failures on the host, including failures of MySQL, the operating system, or the hardware and maintenance activity that may otherwise cause downtime. Scalability refers to the ability to spread both the database and the load of your application queries across multiple MySQL servers.

Because each application has different operational and availability requirements, MySQL offers a range of certified and supported solutions, delivering the appropriate levels of High Availability (HA) and scalability to meet service level requirements. Such solutions extend from replication, through virtualization and geographically redundant, multi-data center solutions delivering 99.999% uptime.

Selecting the right high availability solution for an application largely depends on:

The primary solutions supported by MySQL include:

Each architecture used to achieve highly available database services is differentiated by the levels of uptime it offers. These architectures can be grouped into three main categories:

As illustrated in the following figure, each of these architectures offers progressively higher levels of uptime, which must be balanced against potentially greater levels of cost and complexity that each can incur. Simply deploying a high availability architecture is not a guarantee of actually delivering HA. In fact, a poorly implemented and maintained shared-nothing cluster could easily deliver lower levels of availability than a simple data replication solution.

Figure 15.1. Tradeoffs: Cost and Complexity versus Availability

As the number of “nines” in the uptime percentage increases, so does the cost and complexity, progressing from basic replication, to a clustered and virtualized configuration, to shared-nothing clusters replicated across geographic regions. Different kinds of organizations require different “nines” of availability, from Internet service providers and mainstream businesses at 3 nines, online services at 4 nines, and eCommerce, telecom, and military applications at 5 nines.

The following figure maps common application types to architectures, based on best practices observed from the MySQL user base. It serves as a reference point to investigate which HA architectures can best serve your requirements.

Figure 15.2. High Availability Architectures for Common Application Types

Data Replication is suitable for most types of mid-level applications. Clustered, Virtualized configurations are suitable for all but the highest-end telecom applications. Shared-Nothing, Geo-Replicated Clusters are suitable for the busiest applications such as telecom and OLTP, and the most high-value ones such as e-commerce and finance.

The following table compares the HA and Scalability capabilities of the various MySQL solutions:

Table 15.1. Feature Comparison of MySQL HA Solutions

RequirementMySQL ReplicationMySQL Replication + Linux HeartbeatHeartbeat + DRBDOracle VM TemplateMySQL Cluster
Availability     
Platform SupportAll Supported by MySQL ServerLinuxLinuxOracle LinuxAll Supported by MySQL Cluster
Automated IP FailoverNoYesYesYesDepends on Connector and Configuration
Automated Database FailoverNoNoYesYesYes
Automatic Data ResynchronizationNoNoYesN/A - Shared StorageYes
Typical Failover TimeUser / Script DependentConfiguration Dependent, 60 seconds and AboveConfiguration Dependent, 60 seconds and AboveConfiguration Dependent, 60 seconds and Above1 Second and Less
Synchronous ReplicationNo, Asynchronous and SemisynchronousNo, Asynchronous and SemisynchronousYesN/A - Shared StorageYes
Shared StorageNo, DistributedNo, DistributedNo, DistributedYesNo, Distributed
Geographic redundancy supportYesYesYes, via MySQL ReplicationYes, via MySQL ReplicationYes, via MySQL Replication
Update Schema On-LineNoNoNoNoYes
Scalability     
Number of NodesOne Master, Multiple SlavesOne Master, Multiple SlavesOne Active (primary), one Passive (secondary) NodeOne Active (primary), one Passive (secondary) Node255
Built-in Load BalancingReads, via MySQL ReplicationReads, via MySQL ReplicationReads, via MySQL ReplicationReads, via MySQL Replication & During FailoverYes, Reads and Writes
Supports Read-Intensive WorkloadsYesYesYesYesYes
Supports Write-Intensive WorkloadsYes, via Application-Level ShardingYes, via Application-Level ShardingYes, via Application-Level Sharding to Multiple Active/Passive PairsYes, via Application-Level Sharding to Multiple Active/Passive PairsYes, via Auto-Sharding
Scale On-Line (add nodes, repartition, etc.)NoNoNoNoYes

15.1. Oracle VM Template for MySQL Enterprise Edition

Virtualization is a key technology to enable data center efficiency and high availability while providing the foundation for cloud computing. Integrating MySQL Enterprise Edition with Oracle Linux, the Oracle VM Template is the fastest, easiest, and most reliable way to provision virtualized MySQL instances, enabling users to meet the explosive demand for highly available services.

The Oracle VM Template enables rapid deployment and eliminates manual configuration efforts. It provides a pre-installed and pre-configured virtualized MySQL 5.5 Enterprise Edition software image running on Oracle Linux and Oracle VM, certified for production use. The MySQL software image has undergone extensive integration and quality assurance testing as part of the development process.

In addition to rapid provisioning, MySQL users also benefit from the integrated high availability features of Oracle VM which are designed to enable organizations to meet stringent SLA (Service Level Agreement) demands through a combination of:

  • Automatic recovery from failures, with Oracle VM automatically restarting failed instances on available servers in the server pool after outages of the physical server, VM or MySQL database.

  • Live Migration, enabling operations staff to move running instances of MySQL to alternative hosts within a server pool during maintenance operations.

Instructions for the creation, deployment and use of the Oracle VM Template for MySQL Enterprise Edition are available from:

To download the Oracle VM Template for MySQL Enterprise, go to http://edelivery.oracle.com/oraclevm and follow these instructions:

  • Complete your registration information (Name, Company Name, Email Address and Country) and click on the download agreement.

  • Select "Oracle VM Templates" from the "Select a Product Pack" pull-down menu and click "Go".

  • Select MySQL Enterprise from the list of Oracle VM Templates.

  • Download and unzip the files and refer to the README for further instructions.

15.2. Overview of MySQL with DRBD/Pacemaker/Corosync/Oracle Linux

DRBD (Distributed Replication Block Device) is one of the leading solutions for MySQL HA (High Availability). When combined with Pacemaker and Corosync, users have:

  • An end-to-end, integrated stack of mature and proven open source technologies, fully supported by Oracle (as part of MySQL Enterprise Edition).

  • Automatic failover and recovery for service continuity.

  • Mirroring, via synchronous replication, to ensure failover between nodes without the risk of losing committed transactions.

  • Building of HA clusters from commodity hardware, without the requirement for shared-storage.

The following figure illustrates the stack that can be used to deliver a level of High Availability for the MySQL service.

At the lowest level, 2 hosts are required in order to provide physical redundancy; if using a virtual environment, those 2 hosts should be on different physical machines. It is an important feature that no shared storage is required. At any point in time, the services will be active on one host and in standby mode on the other.

Pacemaker and Corosync combine to provide the clustering layer that sits between the services and the underlying hosts and operating systems. Pacemaker is responsible for starting and stopping services, ensuring that they are running on exactly one host, thus delivering high availability and avoiding data corruption. Corosync provides the underlying messaging infrastructure between the nodes that enables Pacemaker to do its job; it also handles the nodes membership within the cluster and informs Pacemaker of any changes.

Figure 15.3. MySQL, DRBD, Pacemaker, and Corosync Stack

MySQL, DRBD, Pacemaker, and Corosync Stack

The core Pacemaker process does not have built-in knowledge of the specific services to be managed; instead, it uses agents that provide a wrapper for the service-specific actions. For example, in this solution we use agents for Virtual IP Addresses, MySQL and DRBD: these are all existing agents and come packaged with Pacemaker.

The essential services managed by Pacemaker in this configuration are DRBD, MySQL and the Virtual IP Address that applications use to connect to the active MySQL service.

DRBD synchronizes data at the block device (typically a spinning or solid state disk) – transparent to the application, database and even the file system. DRBD requires the use of a journaling file system such as ext3 or ext4. For this solution, it acts in an active-standby mode: at any point in time, the directories being managed by DRBD are accessible for reads and writes on exactly one of the two hosts and inaccessible (even for reads) on the other. Any changes made on the active host are synchronously replicated to the standby host by DRBD.

Download the following guide for detailed instructions on installing, configuring, provisioning and testing the complete MySQL and DRBD stack, including:

  • MySQL Database.

  • DRBD kernel module and userland utilities.

  • Pacemaker and Corosync cluster messaging and management processes.

  • Oracle Linux operating system.

Download the guide at: http://www.mysql.com/why-mysql/white-papers/mysql-high-availability-drbd-configuration-deployment-guide/.

Support for DRBD

The complete DRBD stack for MySQL has been certified by Oracle, and commercial support is available as part of MySQL Enterprise Edition and Oracle Linux Premier Support, providing a single point of contact for the entire stack, whether issues relate to the operating system, DRBD, clustering software or MySQL.

15.3. Overview of MySQL with Windows Failover Clustering

Microsoft Windows is consistently ranked as the top development platform for MySQL, based on surveys of the MySQL user community.

MySQL Enterprise Edition is certified and supported with Windows Server 2008 R2 Failover Clustering (WSFC), enabling organizations to safely deploy business-critical applications demanding high levels of availability using Microsoft's native Windows clustering services.

The following figure illustrates the integration of MySQL with Windows Server Failover Clustering to provide a highly available service:

Figure 15.4. Typical MySQL HA Configuration with Windows Server Failover Clustering

MySQL with Windows Failover Clustering

In this architecture, MySQL is deployed in an Active / Passive configuration. Failures of either MySQL or the underlying server are automatically detected and the MySQL instance is restarted on the Passive node. Applications accessing the database, as well as any MySQL replication slaves, can automatically reconnect to the new MySQL process using the same Virtual IP address once MySQL recovery has completed and it starts accepting connections.

MySQL with Windows Failover Clustering requires at least 2 servers within the cluster together with shared storage (for example, FC-AL SAN or iSCSI disks).

The MySQL binaries and data files are stored in the shared storage and Windows Failover Clustering ensures that only one of the cluster nodes will access those files at any point in time.

Clients connect to the MySQL service through a Virtual IP Address (VIP). In the event of failover they experience a brief loss of connection, but otherwise do not need to be aware that the failover has happened, other than to handle the failure of any transactions that were active when the failover occurred.

You can learn more about configuring MySQL with Windows Server Failover Clustering from the whitepaper posted here: http://www.mysql.com/why-mysql/white-papers/mysql_wp_windows_failover_clustering.php

For background and usage information about Windows Server Failover Clustering, see these pages on the Microsoft Technet site:

15.4. Using MySQL within an Amazon EC2 Instance

The Amazon Elastic Compute Cloud (EC2) service provides virtual servers that you can build and deploy to run a variety of different applications and services, including MySQL. The EC2 service is based around the Xen framework, supporting x86, Linux based, platforms with individual instances of a virtual machine referred to as an Amazon Machine Image (AMI). You have complete (root) access to the AMI instance that you create, enabling you to configure and install your AMI in any way you choose.

To use EC2, you create an AMI based on the configuration and applications that you intend to use, and upload the AMI to the Amazon Simple Storage Service (S3). From the S3 resource, you can deploy one or more copies of the AMI to run as an instance within the EC2 environment. The EC2 environment provides management and control of the instance and contextual information about the instance while it is running.

Because you can create and control the AMI, the configuration, and the applications, you can deploy and create any environment you choose. This includes a basic MySQL server in addition to more extensive replication, HA and scalability scenarios that enable you to take advantage of the EC2 environment, and the ability to deploy additional instances as the demand for your MySQL services and applications grow.

To aid the deployment and distribution of work, three different Amazon EC2 instances are available, small (identified as m1.small), large (m1.large) and extra large (m1.xlarge). The different types provide different levels of computing power measured in EC2 computer units (ECU). A summary of the different instance configurations is shown in the following table.

EC2 AttributeSmallLargeExtra Large
Platform32-bit64-bit64-bit
CPU cores124
ECUs148
RAM1.7GB7.5GB15GB
Storage150GB840GB1680GB
I/O PerformanceMediumHighHigh

The typical model for deploying and using MySQL within the EC2 environment is to create a basic AMI that you can use to hold your database data and application. Once the basic environment for your database and application has been created you can then choose to deploy the AMI to a suitable instance. Here the flexibility of having an AMI that can be re-deployed from the small to the large or extra large EC2 instance makes it easy to upgrade the hardware environment without rebuilding your application or database stack.

To get started with MySQL on EC2, including information on how to set up and install MySQL within an EC2 installation and how to port and migrate your data to the running instance, see Section 15.4.1, “Setting Up MySQL on an EC2 AMI”.

For tips and advice on how to create a scalable EC2 environment using MySQL, including guides on setting up replication, see Section 15.4.3, “Deploying a MySQL Database Using EC2”.

15.4.1. Setting Up MySQL on an EC2 AMI

There are many different ways of setting up an EC2 AMI with MySQL, including using any of the pre-configured AMIs supplied by Amazon.

The default Getting Started AMI provided by Amazon uses Fedora Core 4, and you can install MySQL by using yum:

shell> yum install mysql

This installs both the MySQL server and the Perl DBD::mysql driver for the Perl DBI API.

Alternatively, you can use one of the AMIs that include MySQL within the standard installation.

Finally, you can also install a standard version of MySQL downloaded from the MySQL Web site. The installation process and instructions are identical to any other installation of MySQL on Linux. See Chapter 2, Installing and Upgrading MySQL.

The standard configuration for MySQL places the data files in the default location, /var/lib/mysql. The default data directory on an EC2 instance is /mnt (although on the large and extra large instance you can alter this configuration). You must edit /etc/my.cnf to set the datadir option to point to the larger storage area.

Important

The first time you use the main storage location within an EC2 instance it needs to be initialized. The initialization process starts automatically the first time you write to the device. You can start using the device right away, but the write performance of the new device is significantly lower on the initial writes until the initialization process has finished.

To avoid this problem when setting up a new instance, you should start the initialization process before populating your MySQL database. One way to do this is to use dd to write to the file system:

root-shell> dd if=/dev/zero of=initialize bs=1024M count=50

The preceding creates a 50GB on the file system and starts the initialization process. Delete the file once the process has finished.

The initialization process can be time-consuming. On the small instance, initialization takes between two and three hours. For the large and extra large drives, the initialization can be 10 or 20 hours, respectively.

In addition to configuring the correct storage location for your MySQL data files, also consider setting the following other settings in your instance before you save the instance configuration for deployment:

  • Set the MySQL server ID, so that when you use it for replication, the ID information is set correctly.

  • Enabling binary logging, so that replication can be initialized without starting and stopping the server.

  • Set the caching and memory parameters for your storage engines. There are no limitations or restrictions on what storage engines you use in your EC2 environment. Choose a configuration, possibly using one of the standard configurations provided with MySQL appropriate for the instance on which you expect to deploy. The large and extra large instances have RAM that can be dedicated to caching. Be aware that if you choose to install memcached on the servers as part of your application stack you must ensure there is enough memory for both MySQL and memcached.

Once you have configured your AMI with MySQL and the rest of your application stack, save the AMI so that you can deploy and reuse the instance.

Once you have your application stack configured in an AMI, populating your MySQL database with data should be performed by creating a dump of your database using mysqldump, transferring the dump to the EC2 instance, and then reloading the information into the EC2 instance database.

Before using your instance with your application in a production situation, be aware of the limitations of the EC2 instance environment. See Section 15.4.2, “EC2 Instance Limitations”. To begin using your MySQL AMI, consult the notes on deployment. See Section 15.4.3, “Deploying a MySQL Database Using EC2”.

15.4.2. EC2 Instance Limitations

Be aware of the following limitations of the EC2 instances before deploying your applications. Although these shouldn't affect your ability to deploy within the Amazon EC2 environment, they may alter the way you setup and configure your environment to support your application.

  • Data stored within instances is not persistent. If you create an instance and populate the instance with data, then the data only remains in place while the machine is running, and does not survive a reboot. If you shut down the instance, any data it contained is lost.

    To ensure that you do not lose information, take regular backups using mysqldump. If the data being stored is critical, consider using replication to keep a live backup of your data in the event of a failure. When creating a backup, write the data to the Amazon S3 service to avoid the transfer charges applied when copying data offsite.

  • EC2 instances are not persistent. If the hardware on which an instance is running fails, the instance is shut down. This can lead to loss of data or service.

  • To replicate your EC2 instances to a non-EC2 environment, be aware of the transfer costs to and from the EC2 service. Data transfer between different EC2 instances is free, so using replication within the EC2 environment does not incur additional charges.

  • Certain HA features are either not directly supported, or have limiting factors or problems that could reduce their utility. For example, using DRBD or MySQL Cluster might not work. The default storage configuration is also not redundant. You can use software-based RAID to improve redundancy, but this implies a further performance hit.

15.4.3. Deploying a MySQL Database Using EC2

Because you cannot guarantee the uptime and availability of your EC2 instances, when deploying MySQL within the EC2 environment, use an approach that enables you to easily distribute work among your EC2 instances. There are a number of ways of doing this. Using sharding techniques, where you split the application across multiple servers dedicating specific blocks of your dataset and users to different servers is an effective way of doing this. As a general rule, it is easier to create more EC2 instances to support more users than to upgrade the instance to a larger machine.

The EC2 architecture works best when you treat the EC2 instances as temporary, cache-based solutions, rather than as a long-term, high availability solution. In addition to using multiple machines, take advantage of other services, such as memcached to provide additional caching for your application to help reduce the load on the MySQL server so that it can concentrate on writes. On the large and extra large instances within EC2, the RAM available can provide a large memory cache for data.

Most types of scale-out topology that you would use with your own hardware can be used and applied within the EC2 environment. However, use the limitations and advice already given to ensure that any potential failures do not lose you any data. Also, because the relative power of each EC2 instance is so low, be prepared to alter your application to use sharding and add further EC2 instances to improve the performance of your application.

For example, take the typical scale-out environment shown following, where a single master replicates to one or more slaves (three in this example), with a web server running on each replication slave.

Typical standard scale-out structure

You can reproduce this structure completely within the EC2 environment, using an EC2 instance for the master, and one instance for each of the web and MySQL slave servers.

Note

Within the EC2 environment, internal (private) IP addresses used by the EC2 instances are constant. Always use these internal addresses and names when communicating between instances. Only use public IP addresses when communicating with the outside world - for example, when publicizing your application.

To ensure reliability of your database, add at least one replication slave dedicated to providing an active backup and storage to the Amazon S3 facility. You can see an example of this in the following topology.

Typical standard scale-out structure with backup using EC2

Using memcached within your EC2 instances should provide better performance. The large and extra large instances have a significant amount of RAM. To use memcached in your application, when loading information from the database, first check whether the item exists in the cache. If the data you are looking for exists in the cache, use it. If not, reload the data from the database and populate the cache.

Sharding divides up data in your entire database by allocating individual machines or machine groups to provide a unique set of data according to an appropriate group. For example, you might put all users with a surname ending in the letters A-D onto a single server. When a user connects to the application and their surname is known, queries can be redirected to the appropriate MySQL server.

When using sharding with EC2, separate the web server and MySQL server into separate EC2 instances, and then apply the sharding decision logic into your application. Once you know which MySQL server you should be using for accessing the data you then distribute queries to the appropriate server. You can see a sample of this in the following illustration.

Using sharding in EC2 to spread the load
Warning

With sharding and EC2, be careful that the potential for failure of an instance does not affect your application. If the EC2 instance that provides the MySQL server for a particular shard fails, then all of the data on that shard becomes unavailable.

15.5. Using ZFS Replication

To support high availability environments, providing an instant copy of the information on both the currently active machine and the hot backup is a critical part of the HA solution. There are many solutions to this problem, including Chapter 16, Replication and Section 15.2, “Overview of MySQL with DRBD/Pacemaker/Corosync/Oracle Linux”.

The ZFS file system provides functionality to create a snapshot of the file system contents, transfer the snapshot to another machine, and extract the snapshot to recreate the file system. You can create a snapshot at any time, and you can create as many snapshots as you like. By continually creating, transferring, and restoring snapshots, you can provide synchronization between one or more machines in a fashion similar to DRBD.

The following example shows a simple Solaris system running with a single ZFS pool, mounted at /scratchpool:

Filesystem             size   used  avail capacity  Mounted on
/dev/dsk/c0d0s0        4.6G   3.7G   886M    82%    /
/devices                 0K     0K     0K     0%    /devices
ctfs                     0K     0K     0K     0%    /system/contract
proc                     0K     0K     0K     0%    /proc
mnttab                   0K     0K     0K     0%    /etc/mnttab
swap                   1.4G   892K   1.4G     1%    /etc/svc/volatile
objfs                    0K     0K     0K     0%    /system/object
/usr/lib/libc/libc_hwcap1.so.1
                       4.6G   3.7G   886M    82%    /lib/libc.so.1
fd                       0K     0K     0K     0%    /dev/fd
swap                   1.4G    40K   1.4G     1%    /tmp
swap                   1.4G    28K   1.4G     1%    /var/run
/dev/dsk/c0d0s7         26G   913M    25G     4%    /export/home
scratchpool             16G    24K    16G     1%    /scratchpool

The MySQL data is stored in a directory on /scratchpool. To help demonstrate some of the basic replication functionality, there are also other items stored in /scratchpool as well:

total 17
drwxr-xr-x  31 root     bin           50 Jul 21 07:32 DTT/
drwxr-xr-x   4 root     bin            5 Jul 21 07:32 SUNWmlib/
drwxr-xr-x  14 root     sys           16 Nov  5 09:56 SUNWspro/
drwxrwxrwx  19 1000     1000          40 Nov  6 19:16 emacs-22.1/

To create a snapshot of the file system, you use zfs snapshot, specifying the pool and the snapshot name:

root-shell> zfs snapshot scratchpool@snap1

To list the snapshots already taken:

root-shell> zfs list -t snapshot
NAME                USED  AVAIL  REFER  MOUNTPOINT
scratchpool@snap1      0      -  24.5K  -
scratchpool@snap2      0      -  24.5K  -

The snapshots themselves are stored within the file system metadata, and the space required to keep them varies as time goes on because of the way the snapshots are created. The initial creation of a snapshot is very quick, because instead of taking an entire copy of the data and metadata required to hold the entire snapshot, ZFS records only the point in time and metadata of when the snapshot was created.

As more changes to the original file system are made, the size of the snapshot increases because more space is required to keep the record of the old blocks. If you create lots of snapshots, say one per day, and then delete the snapshots from earlier in the week, the size of the newer snapshots might also increase, as the changes that make up the newer state have to be included in the more recent snapshots, rather than being spread over the seven snapshots that make up the week.

You cannot directly back up the snapshots because they exist within the file system metadata rather than as regular files. To get the snapshot into a format that you can copy to another file system, tape, and so on, you use the zfs send command to create a stream version of the snapshot.

For example, to write the snapshot out to a file:

root-shell> zfs send scratchpool@snap1 >/backup/scratchpool-snap1

Or tape:

root-shell> zfs send scratchpool@snap1 >/dev/rmt/0

You can also write out the incremental changes between two snapshots using zfs send:

root-shell> zfs send scratchpool@snap1 scratchpool@snap2 >/backup/scratchpool-changes

To recover a snapshot, you use zfs recv, which applies the snapshot information either to a new file system, or to an existing one.

15.5.1. Using ZFS for File System Replication

Because zfs send and zfs recv use streams to exchange data, you can use them to replicate information from one system to another by combining zfs send, ssh, and zfs recv.

For example, to copy a snapshot of the scratchpool file system to a new file system called slavepool on a new server, you would use the following command. This sequence combines the snapshot of scratchpool, the transmission to the slave machine (using ssh with login credentials), and the recovery of the snapshot on the slave using zfs recv:

root-shell> zfs send scratchpool@snap1 |ssh id@host pfexec zfs recv -F slavepool

The first part of the pipeline, zfs send scratchpool@snap1, streams the snapshot. The ssh command, and the command that it executes on the other server, pfexec zfs recv -F slavepool, receives the streamed snapshot data and writes it to slavepool. In this instance, I've specified the -F option which forces the snapshot data to be applied, and is therefore destructive. This is fine, as I'm creating the first version of my replicated file system.

On the slave machine, the replicated file system contains the exact same content:

root-shell> ls -al /slavepool/
total 23
drwxr-xr-x   6 root     root           7 Nov  8 09:13 ./
drwxr-xr-x  29 root     root          34 Nov  9 07:06 ../
drwxr-xr-x  31 root     bin           50 Jul 21 07:32 DTT/
drwxr-xr-x   4 root     bin            5 Jul 21 07:32 SUNWmlib/
drwxr-xr-x  14 root     sys           16 Nov  5 09:56 SUNWspro/
drwxrwxrwx  19 1000     1000          40 Nov  6 19:16 emacs-22.1/

Once a snapshot has been created, to synchronize the file system again, you create a new snapshot and then use the incremental snapshot feature of zfs send to send the changes between the two snapshots to the slave machine again:

root-shell> zfs send -i scratchpool@snapshot1 scratchpool@snapshot2 |ssh id@host pfexec zfs recv slavepool

This operation only succeeds if the file system on the slave machine has not been modified at all. You cannot apply the incremental changes to a destination file system that has changed. In the example above, the ls command would cause problems by changing the metadata, such as the last access time for files or directories.

To prevent changes on the slave file system, set the file system on the slave to be read-only:

root-shell> zfs set readonly=on slavepool

Setting readonly means that you cannot change the file system on the slave by normal means, including the file system metadata. Operations that would normally update metadata (like our ls) silently perform their function without attempting to update the file system state.

In essence, the slave file system is nothing but a static copy of the original file system. However, even when configured to to be read-only, a file system can have snapshots applied to it. With the file system set to read only, re-run the initial copy:

root-shell> zfs send scratchpool@snap1 |ssh id@host pfexec zfs recv -F slavepool

Now you can make changes to the original file system and replicate them to the slave.

15.5.2. Configuring MySQL for ZFS Replication

Configuring MySQL on the source file system is a case of creating the data on the file system that you intend to replicate. The configuration file in the example below has been updated to use /scratchpool/mysql-data as the data directory, and now you can initialize the tables:

root-shell> mysql_install_db --defaults-file=/etc/mysql/5.5/my.cnf --user=mysql

To synchronize the initial information, perform a new snapshot and then send an incremental snapshot to the slave using zfs send:

root-shell> zfs snapshot scratchpool@snap2
root-shell> zfs send -i scratchpool@snap1 scratchpool@snap2|ssh id@host pfexec zfs recv slavepool

Doublecheck that the slave has the data by looking at the MySQL data directory on the slavepool:

root-shell> ls -al /slavepool/mysql-data/

Now you can start up MySQL, create some data, and then replicate the changes using zfs send/ zfs recv to the slave to synchronize the changes.

The rate at which you perform the synchronization depends on your application and environment. The limitation is the speed required to perform the snapshot and then to send the changes over the network.

To automate the process, create a script that performs the snapshot, send, and receive operation, and use cron to synchronize the changes at set times or intervals.

15.5.3. Handling MySQL Recovery with ZFS

When using ZFS replication to provide a constant copy of your data, ensure that you can recover your tables, either manually or automatically, in the event of a failure of the original system.

In the event of a failure, follow this sequence:

  1. Stop the script on the master, if it is still up and running.

  2. Set the slave file system to be read/write:

    root-shell> zfs set readonly=off slavepool
  3. Start up mysqld on the slave. If you are using InnoDB, you get auto-recovery, if it is needed, to make sure the table data is correct, as shown here when I started up from our mid-INSERT snapshot:

    InnoDB: The log sequence number in ibdata files does not match
    InnoDB: the log sequence number in the ib_logfiles!
    081109 15:59:59  InnoDB: Database was not shut down normally!
    InnoDB: Starting crash recovery.
    InnoDB: Reading tablespace information from the .ibd files...
    InnoDB: Restoring possible half-written data pages from the doublewrite
    InnoDB: buffer...
    081109 16:00:03  InnoDB: Started; log sequence number 0 1142807951
    081109 16:00:03 [Note] /slavepool/mysql-5.0.67-solaris10-i386/bin/mysqld: ready for connections.
    Version: '5.0.67'  socket: '/tmp/mysql.sock'  port: 3306  MySQL Community Server (GPL)

Use InnoDB tables and a regular synchronization schedule to reduce the risk for significant data loss. On MyISAM tables, you might need to run REPAIR TABLE, and you might even have lost some information.

15.6. Using MySQL with memcached

memcached is a simple, highly scalable key-based cache that stores data and objects wherever dedicated or spare RAM is available for quick access by applications, without going through layers of parsing or disk I/O. To use, you run the memcached command on one or more hosts and then use the shared cache to store objects. For more usage instructions, see Section 15.6.2, “Using memcached

Benefits of using memcached include:

  • Because all information is stored in RAM, the access speed is faster than loading the information each time from disk.

  • Because the value portion of the key-value pair does not have any data type restrictions, you can cache data such as complex structures, documents, images, or a mixture of such things.

  • If you use the in-memory cache to hold transient information, or as a read-only cache for information also stored in a database, the failure of any memcached server is not critical. For persistent data, you can fall back to an alternative lookup method using database queries, and reload the data into RAM on a different server.

The typical usage environment is to modify your application so that information is read from the cache provided by memcached. If the information is not in memcached, then the data is loaded from the MySQL database and written into the cache so that future requests for the same object benefit from the cached data.

For a typical deployment layout, see Figure 15.5, “memcached Architecture Overview”.

Figure 15.5. memcached Architecture Overview

memcached Architecture Overview

In the example structure, any of the clients can contact one of the memcached servers to request a given key. Each client is configured to talk to all of the servers shown in the illustration. Within the client, when the request is made to store the information, the key used to reference the data is hashed and this hash is then used to select one of the memcached servers. The selection of the memcached server takes place on the client before the server is contacted, keeping the process lightweight.

The same algorithm is used again when a client requests the same key. The same key generates the same hash, and the same memcached server is selected as the source for the data. Using this method, the cached data is spread among all of the memcached servers, and the cached information is accessible from any client. The result is a distributed, memory-based, cache that can return information, particularly complex data and structures, much faster than natively reading the information from the database.

The data held within a traditional memcached server is never stored on disk (only in RAM, which means there is no persistence of data), and the RAM cache is always populated from the backing store (a MySQL database). If a memcached server fails, the data can always be recovered from the MySQL database.

memcached Integration with MySQL Storage Engines

In April 2011, MySQL announced the preview of a new memcached interface for the InnoDB and MySQL Cluster storage engines.

Using the memcached API, web services can directly access the InnoDB and MySQL Cluster storage engines without transformations to SQL, ensuring low latency and high throughput for read/write queries. Operations such as SQL parsing are eliminated and more of the server’s hardware resources (CPU, memory and I/O) are dedicated to servicing the query within the storage engine itself. The memcached data can be persisted to disk while still cached in memory for fast retrieval.

These are targeted to be incorporated into future MySQL 5.6 Milestone and MySQL Cluster Development Releases.

You can learn more about these interfaces from this Dev Zone article: http://dev.mysql.com/tech-resources/articles/nosql-to-mysql-with-memcached.html.

15.6.1. Installing memcached

You can build and install memcached from the source code directly, or you can use an existing operating system package or installation.

Installing memcached from a Binary Distribution

To install memcached on a Red Hat, or Fedora host, use yum:

root-shell> yum install memcached
Note

On CentOS, you may be able to obtain a suitable RPM from another source, or use the source tarball.

To install memcached on a Debian or Ubuntu host, use apt-get:

root-shell> apt-get install memcached

To install memcached on a Gentoo host, use emerge:

root-shell> emerge install memcached

Building memcached from Source

On other Unix-based platforms, including Solaris, AIX, HP-UX and Mac OS X, and Linux distributions not mentioned already, you must install from source. For Linux, make sure you have a 2.6-based kernel, which includes the improved epoll interface. For all platforms, ensure that you have libevent 1.1 or higher installed. You can obtain libevent from libevent web page.

You can obtain the source for memcached from memcached Web site.

To build memcached, follow these steps:

  1. Extract the memcached source package:

    shell> gunzip -c memcached-1.2.5.tar.gz | tar xf - 
    
  2. Change to the memcached-1.2.5 directory:

    shell> cd memcached-1.2.5
    
  3. Run configure

    shell> ./configure

    Some additional options you might specify to the configure:

    • --prefix

      To specify a different installation directory, use the --prefix option:

      shell> ./configure --prefix=/opt

      The default is to use the /usr/local directory.

    • --with-libevent

      If you have installed libevent and configure cannot find the library, use the --with-libevent option to specify the location of the installed library.

    • --enable-64bit

      To build a 64-bit version of memcached (which enables you to use a single instance with a large RAM allocation), use --enable-64bit.

    • --enable-threads

      To enable multi-threading support in memcached, which improves the response times on servers with a heavy load, use --enable-threads. You must have support for the POSIX threads within your operating system to enable thread support. For more information on the threading support, see Section 15.6.2.7, “memcached Thread Support”.

    • --enable-dtrace

      memcached includes a range of DTrace threads that can be used to monitor and benchmark a memcached instance. For more information, see Section 15.6.2.5, “Using memcached and DTrace”.

  4. Run make to build memcached:

    shell> make
  5. Run make install to install memcached:

    shell> make install

15.6.2. Using memcached

To start using memcached, start the memcached service on one or more servers. Running memcached sets up the server, allocates the memory and starts listening for connections from clients.

Note

You do not need to be a privileged user (root) to run memcached except to listen on one of the privileged TCP/IP ports (below 1024). You must, however, use a user that has not had their memory limits restricted using setrlimit or similar.

To start the server, run memcached as a nonprivileged (that is, non-root) user:

shell> memcached

By default, memcached uses the following settings:

  • Memory allocation of 64MB

  • Listens for connections on all network interfaces, using port 11211

  • Supports a maximum of 1024 simultaneous connections

Typically, you would specify the full combination of options that you want when starting memcached, and normally provide a startup script to handle the initialization of memcached. For example, the following line starts memcached with a maximum of 1024MB RAM for the cache, listening on port 11211 on the IP address 192.168.0.110, running as a background daemon:

shell> memcached -d -m 1024 -p 11211 -l 192.168.0.110

To ensure that memcached is started up on boot, check the init script and configuration parameters.

memcached supports the following options:

  • -u user

    If you start memcached as root, use the -u option to specify the user for executing memcached:

    shell> memcached -u memcache
  • -m memory

    Set the amount of memory allocated to memcached for object storage. Default is 64MB.

    To increase the amount of memory allocated for the cache, use the -m option to specify the amount of RAM to be allocated (in megabytes). The more RAM you allocate, the more data you can store and therefore the more effective your cache is.

    Warning

    Do not specify a memory allocation larger than your available RAM. If you specify too large a value, then some RAM allocated for memcached uses swap space, and not physical RAM. This may lead to delays when storing and retrieving values, because data is swapped to disk, instead of storing the data directly in RAM.

    You can use the output of the vmstat command to get the free memory, as shown in free column:

    shell> vmstat
    kthr      memory            page            disk          faults      cpu
    r b w   swap  free  re  mf pi po fr de sr s1 s2 -- --   in   sy   cs us sy id
    0 0 0 5170504 3450392 2  7  2  0  0  0  4  0  0  0  0  296   54  199  0  0 100

    For example, to allocate 3GB of RAM:

    shell> memcached -m 3072

    On 32-bit x86 systems where you are using PAE to access memory above the 4GB limit, you cannot allocate RAM beyond the maximum process size. You can get around this by running multiple instances of memcached, each listening on a different port:

    shell> memcached -m 1024 -p11211
    shell> memcached -m 1024 -p11212
    shell> memcached -m 1024 -p11213
    Note

    On all systems, particularly 32-bit, ensure that you leave enough room for both memcached application in addition to the memory setting. For example, if you have a dedicated memcached host with 4GB of RAM, do not set the memory size above 3500MB. Failure to do this may cause either a crash or severe performance issues.

  • -l interface

    Specify a network interface/address to listen for connections. The default is to listen on all available address (INADDR_ANY).

    shell> memcached -l 192.168.0.110

    Support for IPv6 address support was added in memcached 1.2.5.

  • -p port

    Specify the TCP port to use for connections. Default is 18080.

    shell> memcached -p 18080
  • -U port

    Specify the UDP port to use for connections. Default is 11211, 0 switches UDP off.

    shell> memcached -U 18080
  • -s socket

    Specify a Unix socket to listen on.

    If you are running memcached on the same server as the clients, you can disable the network interface and use a local UNIX socket using the -s option:

    shell> memcached -s /tmp/memcached

    Using a UNIX socket automatically disables network support, and saves network ports (allowing more ports to be used by your web server or other process).

  • -a mask

    Specify the access mask to be used for the Unix socket, in octal. Default is 0700.

  • -c connections

    Specify the maximum number of simultaneous connections to the memcached service. The default is 1024.

    shell> memcached -c 2048

    Use this option, either to reduce the number of connections (to prevent overloading memcached service) or to increase the number to make more effective use of the server running memcached server.

  • -t threads

    Specify the number of threads to use when processing incoming requests.

    By default, memcached is configured to use 4 concurrent threads. The threading improves the performance of storing and retrieving data in the cache, using a locking system to prevent different threads overwriting or updating the same values. To increase or decrease the number of threads, use the -t option:

    shell> memcached -t 8
  • -d

    Run memcached as a daemon (background) process:

    shell> memcached -d
  • -r

    Maximize the size of the core file limit. In the event of a failure, this attempts to dump the entire memory space to disk as a core file, up to any limits imposed by setrlimit.

  • -M

    Return an error to the client when the memory has been exhausted. This replaces the normal behavior of removing older items from the cache to make way for new items.

  • -k

    Lock down all paged memory. This reserves the memory before use, instead of allocating new slabs of memory as new items are stored in the cache.

    Note

    There is a user-level limit on how much memory you can lock. Trying to allocate more than the available memory fails. You can set the limit for the user you started the daemon with (not for the -u user user) within the shell by using ulimit -S -l NUM_KB

  • -v

    Verbose mode. Prints errors and warnings while executing the main event loop.

  • -vv

    Very verbose mode. In addition to information printed by -v, also prints each client command and the response.

  • -vvv

    Extremely verbose mode. In addition to information printed by -vv, also show the internal state transitions.

  • -h

    Print the help message and exit.

  • -i

    Print the memcached and libevent license.

  • -I mem

    Specify the maximum size permitted for storing an object within the memcached instance. The size supports a unit postfix (k for kilobytes, m for megabytes). For example, to increase the maximum supported object size to 32MB:

    shell> memcached -I 32m

    The maximum object size you can specify is 128MB, the default remains at 1MB.

    This option was added in 1.4.2.

  • -b

    Set the backlog queue limit. The backlog queue configures how many network connections can be waiting to be processed by memcached. Increasing this limit may reduce errors received by the client that it is not able to connect to the memcached instance, but does not improve the performance of the server. The default is 1024.

  • -P pidfile

    Save the process ID of the memcached instance into file.

  • -f

    Set the chunk size growth factor. When allocating new memory chunks, the allocated size of new chunks is determined by multiplying the default slab size by this factor.

    To see the effects of this option without extensive testing, use the -vv command-line option to show the calculated slab sizes. For more information, see Section 15.6.2.8, “memcached Logs”.

  • -n bytes

    The minimum space allocated for the key+value+flags information. The default is 48 bytes.

  • -L

    On systems that support large memory pages, enables large memory page use. Using large memory pages enables memcached to allocate the item cache in one large chunk, which can improve the performance by reducing the number misses when accessing memory.

  • -C

    Disable the use of compare and swap (CAS) operations.

    This option was added in memcached 1.3.x.

  • -D char

    Set the default character to be used as a delimiter between the key prefixes and IDs. This is used for the per-prefix statistics reporting (see Section 15.6.4, “Getting memcached Statistics”). The default is the colon (:). If this option is used, statistics collection is turned on automatically. If not used, you can enable stats collection by sending the stats detail on command to the server.

    This option was added in memcached 1.3.x.

  • -R num

    Sets the maximum number of requests per event process. The default is 20.

  • -B protocol

    Set the binding protocol, that is, the default memcached protocol support for client connections. Options are ascii, binary or auto. Automatic (auto) is the default.

    This option was added in memcached 1.4.0.

15.6.2.1. memcached Deployment

When using memcached you can use a number of different potential deployment strategies and topologies. The exact strategy to use depends on your application and environment. When developing a system for deploying memcached within your system, keep in mind the following points:

  • memcached is only a caching mechanism. It shouldn't be used to store information that you cannot otherwise afford to lose and then load from a different location.

  • There is no security built into the memcached protocol. At a minimum, make sure that the servers running memcached are only accessible from inside your network, and that the network ports being used are blocked (using a firewall or similar). If the information on the memcached servers that is being stored is any sensitive, then encrypt the information before storing it in memcached.

  • memcached does not provide any sort of failover. Because there is no communication between different memcached instances. If an instance fails, your application must capable of removing it from the list, reloading the data and then writing data to another memcached instance.

  • Latency between the clients and the memcached can be a problem if you are using different physical machines for these tasks. If you find that the latency is a problem, move the memcached instances to be on the clients.

  • Key length is determined by the memcached server. The default maximum key size is 250 bytes.

  • Try to use at least two memcached instances, especially for multiple clients, to avoid having a single point of failure. Ideally, create as many memcached nodes as possible. When adding and removing memcached instances from a pool, the hashing and distribution of key/value pairs may be affected. For information on how to avoid problems, see Section 15.6.2.4, “memcached Hashing/Distribution Types”.

15.6.2.2. Using Namespaces

The memcached cache is a very simple massive key/value storage system, and as such there is no way of compartmentalizing data automatically into different sections. For example, if you are storing information by the unique ID returned from a MySQL database, then storing the data from two different tables could run into issues because the same ID might be valid in both tables.

Some interfaces provide an automated mechanism for creating namespaces when storing information into the cache. In practice, these namespaces are merely a prefix before a given ID that is applied every time a value is stored or retrieve from the cache.

You can implement the same basic principle by using keys that describe the object and the unique identifier within the key that you supply when the object is stored. For example, when storing user data, prefix the ID of the user with user: or user-.

Note

Using namespaces or prefixes only controls the keys stored/retrieved. There is no security within memcached, and therefore no way to enforce that a particular client only accesses keys with a particular namespace. Namespaces are only useful as a method of identifying data and preventing corruption of key/value pairs.

15.6.2.3. Data Expiry

There are two types of data expiry within a memcached instance. The first type is applied at the point when you store a new key/value pair into the memcached instance. If there is not enough space within a suitable slab to store the value, then an existing least recently used (LRU) object is removed (evicted) from the cache to make room for the new item.

The LRU algorithm ensures that the object that is removed is one that is either no longer in active use or that was used so long ago that its data is potentially out of date or of little value. However, in a system where the memory allocated to memcached is smaller than the number of regularly used objects required in the cache, a lot of expired items could be removed from the cache even though they are in active use. You use the statistics mechanism to get a better idea of the level of evictions (expired objects). For more information, see Section 15.6.4, “Getting memcached Statistics”.

You can change this eviction behavior by setting the -M command-line option when starting memcached. This option forces an error to be returned when the memory has been exhausted, instead of automatically evicting older data.

The second type of expiry system is an explicit mechanism that you can set when a key/value pair is inserted into the cache, or when deleting an item from the cache. Using an expiration time can be a useful way of ensuring that the data in the cache is up to date and in line with your application needs and requirements.

A typical scenario for explicitly setting the expiry time might include caching session data for a user when accessing a Web site. memcached uses a lazy expiry mechanism where the explicit expiry time that has been set is compared with the current time when the object is requested. Only objects that have not expired are returned.

You can also set the expiry time when explicitly deleting an object from the cache. In this case, the expiry time is really a timeout and indicates the period when any attempts to set the value for a given key are rejected.

15.6.2.4. memcached Hashing/Distribution Types

The memcached client interface supports a number of different distribution algorithms that are used in multi-server configurations to determine which host should be used when setting or getting data from a given memcached instance. When you get or set a value, a hash is constructed from the supplied key and then used to select a host from the list of configured servers. Because the hashing mechanism uses the supplied key as the basis for the hash, the same server is selected during both set and get operations.

You can think of this process as follows. Given an array of servers (a, b, and c), the client uses a hashing algorithm that returns an integer based on the key being stored or retrieved. The resulting value is then used to select a server from the list of servers configured in the client. Most standard client hashing within memcache clients uses a simple modulus calculation on the value against the number of configured memcached servers. You can summarize the process in pseudocode as:

@memcservers = ['a.memc','b.memc','c.memc'];
$value = hash($key);
$chosen = $value % length(@memcservers);

Replacing the above with values:

@memcservers = ['a.memc','b.memc','c.memc'];
$value = hash('myid');
$chosen = 7009 % 3;

In the above example, the client hashing algorithm chooses the server at index 1 (7009 % 3 = 1), and store or retrieve the key and value with that server.

Note

This selection and hashing process is handled automatically by the memcached client you are using; you need only provide the list of memcached servers to use.

You can see a graphical representation of this below in Figure 15.6, “memcached Hash Selection”.

Figure 15.6. memcached Hash Selection

memcached Hash Selection

The same hashing and selection process takes place during any operation on the specified key within the memcached client.

Using this method provides a number of advantages:

  • The hashing and selection of the server to contact is handled entirely within the client. This eliminates the need to perform network communication to determine the right machine to contact.

  • Because the determination of the memcached server occurs entirely within the client, the server can be selected automatically regardless of the operation being executed (set, get, increment, etc.).

  • Because the determination is handled within the client, the hashing algorithm returns the same value for a given key; values are not affected or reset by differences in the server environment.

  • Selection is very fast. The hashing algorithm on the key value is quick and the resulting selection of the server is from a simple array of available machines.

  • Using client-side hashing simplifies the distribution of data over each memcached server. Natural distribution of the values returned by the hashing algorithm means that keys are automatically spread over the available servers.

Providing that the list of servers configured within the client remains the same, the same stored key returns the same value, and therefore selects the same server.

However, if you do not use the same hashing mechanism then the same data may be recorded on different servers by different interfaces, both wasting space on your memcached and leading to potential differences in the information.

Note

One way to use a multi-interface compatible hashing mechanism is to use the libmemcached library and the associated interfaces. Because the interfaces for the different languages (including C, Ruby, Perl and Python) use the same client library interface, they always generate the same hash code from the ID.

The problem with client-side selection of the server is that the list of the servers (including their sequential order) must remain consistent on each client using the memcached servers, and the servers must be available. If you try to perform an operation on a key when:

  • A new memcached instance has been added to the list of available instances

  • A memcached instance has been removed from the list of available instances

  • The order of the memcached instances has changed

If a new memcached instance is added into the list of servers, as new.memc is in the example below, then a GET operation using the same key, myid, can result in a cache-miss. This is because the same value is computed from the key, which selects the same index from the array of servers, but index 2 now points to the new server, not the server c.memc where the data was originally stored. This would result in a cache miss, even though the key exists within the cache on another memcached instance.

Figure 15.7. memcached Hash Selection with New memcached instance

memcached Hash Selection with New memcached instance

This means that servers c.memc and new.memc both contain the information for key myid, but the information stored against the key in eachs server may be different in each instance. A more significant problem is a much higher number of cache-misses when retrieving data, as the addition of a new server changes the distribution of keys, and this in turn requires rebuilding the cached data on the memcached instances, causing an increase in database reads.

The same effect can occur if you actively manage the list of servers configured in your clients, adding and removing the configured memcached instances as each instance is identified as being available. For example, removing a memcached instance when the client notices that the instance can no longer be contacted can cause the server selection to fail as described here.

To prevent this causing significant problems and invalidating your cache, you can select the hashing algorithm used to select the server. There are two common types of hashing algorithm, consistent and modula.

With consistent hashing algorithms, the same key when applied to a list of servers always uses the same server to store or retrieve the keys, even if the list of configured servers changes. This means that you can add and remove servers from the configure list and always use the same server for a given key. There are two types of consistent hashing algorithms available, Ketama and Wheel. Both types are supported by libmemcached, and implementations are available for PHP and Java.

Any consistent hashing algorithm has some limitations. When you add servers to an existing list of configured servers, keys are distributed to the new servers as part of the normal distribution. When you remove servers from the list, the keys are re-allocated to another server within the list, meaning that the cache needs to be re-populated with the information. Also, a consistent hashing algorithm does not resolve the issue where you want consistent selection of a server across multiple clients, but where each client contains a different list of servers. The consistency is enforced only within a single client.

With a modula hashing algorithm, the client selects a server by first computing the hash and then choosing a server from the list of configured servers. As the list of servers changes, so the server selected when using a modula hashing algorithm also changes. The result is the behavior described above; changes to the list of servers mean that different servers are selected when retrieving data, leading to cache misses and increase in database load as the cache is re-seeded with information.

If you use only a single memcached instance for each client, or your list of memcached servers configured for a client never changes, then the selection of a hashing algorithm is irrelevant, as it has no noticeable effect.

If you change your servers regularly, or you use a common set of servers that are shared among a large number of clients, then using a consistent hashing algorithm should help to ensure that your cache data is not duplicated and the data is evenly distributed.

15.6.2.5. Using memcached and DTrace

memcached includes a number of different DTrace probes that can be used to monitor the operation of the server. The probes included can monitor individual connections, slab allocations, and modifications to the hash table when a key/value pair is added, updated, or removed.

For more information on DTrace and writing DTrace scripts, read the DTrace User Guide.

Support for DTrace probes was added to memcached 1.2.6 includes a number of DTrace probes that can be used to help monitor your application. DTrace is supported on Solaris 10, OpenSolaris, Mac OS X 10.5 and FreeBSD. To enable the DTrace probes in memcached, build from source and use the --enable-dtrace option. For more information, see Section 15.6.1, “Installing memcached.

The probes supported by memcached are:

  • conn-allocate(connid)

    Fired when a connection object is allocated from the connection pool.

    • connid: The connection ID.

  • conn-release(connid)

    Fired when a connection object is released back to the connection pool.

    Arguments:

    • connid: The connection ID.

  • conn-create(ptr)

    Fired when a new connection object is being created (that is, there are no free connection objects in the connection pool).

    Arguments:

    • ptr: A pointer to the connection. object

  • conn-destroy(ptr)

    Fired when a connection object is being destroyed.

    Arguments:

    • ptr: A pointer to the connection object.

  • conn-dispatch(connid, threadid)

    Fired when a connection is dispatched from the main or connection-management thread to a worker thread.

    Arguments:

    • connid: The connection ID.

    • threadid: The thread ID.

  • slabs-allocate(size, slabclass, slabsize, ptr)

    Allocate memory from the slab allocator.

    Arguments:

    • size: The requested size.

    • slabclass: The allocation is fulfilled in this class.

    • slabsize: The size of each item in this class.

    • ptr: A pointer to allocated memory.

  • slabs-allocate-failed(size, slabclass)

    Failed to allocate memory (out of memory).

    Arguments:

    • size: The requested size.

    • slabclass: The class that failed to fulfill the request.

  • slabs-slabclass-allocate(slabclass)

    Fired when a slab class needs more space.

    Arguments:

    • slabclass: The class that needs more memory.

  • slabs-slabclass-allocate-failed(slabclass)

    Failed to allocate memory (out of memory).

    Arguments:

    • slabclass: The class that failed to grab more memory.

  • slabs-free(size, slabclass, ptr)

    Release memory.

    Arguments:

    • size: The amount of memory to release, in bytes.

    • slabclass: The class the memory belongs to.

    • ptr: A pointer to the memory to release.

  • assoc-find(key, depth)

    Fired when we have searched the hash table for a named key. These two elements provide an insight into how well the hash function operates. Traversals are a sign of a less optimal function, wasting CPU capacity.

    Arguments:

    • key: The key searched for.

    • depth: The depth in the list of hash table.

  • assoc-insert(key, nokeys)

    Fired when a new item has been inserted.

    Arguments:

    • key: The key just inserted.

    • nokeys: The total number of keys currently being stored, including the key for which insert was called.

  • assoc-delete(key, nokeys)

    Fired when a new item has been removed.

    Arguments:

    • key: The key just deleted.

    • nokeys: The total number of keys currently being stored, excluding the key for which delete was called.

  • item-link(key, size)

    Fired when an item is being linked in the cache.

    Arguments:

    • key: The items key.

    • size: The size of the data.

  • item-unlink(key, size)

    Fired when an item is being deleted.

    Arguments:

    • key: The items key.

    • size: The size of the data.

  • item-remove(key, size)

    Fired when the refcount for an item is reduced.

    Arguments:

    • key: The item's key.

    • size: The size of the data.

  • item-update(key, size)

    Fired when the "last referenced" time is updated.

    Arguments:

    • key: The item's key.

    • size: The size of the data.

  • item-replace(oldkey, oldsize, newkey, newsize)

    Fired when an item is being replaced with another item.

    Arguments:

    • oldkey: The key of the item to replace.

    • oldsize: The size of the old item.

    • newkey: The key of the new item.

    • newsize: The size of the new item.

  • process-command-start(connid, request, size)

    Fired when the processing of a command starts.

    Arguments:

    • connid: The connection ID.

    • request: The incoming request.

    • size: The size of the request.

  • process-command-end(connid, response, size)

    Fired when the processing of a command is done.

    Arguments:

    • connid: The connection ID.

    • response: The response to send back to the client.

    • size: The size of the response.

  • command-get(connid, key, size)

    Fired for a get command.

    Arguments:

    • connid: The connection ID.

    • key: The requested key.

    • size: The size of the key's data (or -1 if not found).

  • command-gets(connid, key, size, casid)

    Fired for a gets command.

    Arguments:

    • connid: The connection ID.

    • key: The requested key.

    • size: The size of the key's data (or -1 if not found).

    • casid: The casid for the item.

  • command-add(connid, key, size)

    Fired for a add command.

    Arguments:

    • connid: The connection ID.

    • key: The requested key.

    • size: The new size of the key's data (or -1 if not found).

  • command-set(connid, key, size)

    Fired for a set command.

    Arguments:

    • connid: The connection ID.

    • key: The requested key.

    • size: The new size of the key's data (or -1 if not found).

  • command-replace(connid, key, size)

    Fired for a replace command.

    Arguments:

    • connid: The connection ID.

    • key: The requested key.

    • size: The new size of the key's data (or -1 if not found).

  • command-prepend(connid, key, size)

    Fired for a prepend command.

    Arguments:

    • connid: The connection ID.

    • key: The requested key.

    • size: The new size of the key's data (or -1 if not found).

  • command-append(connid, key, size)

    Fired for a append command.

    Arguments:

    • connid: The connection ID.

    • key: The requested key.

    • size: The new size of the key's data (or -1 if not found).

  • command-cas(connid, key, size, casid)

    Fired for a cas command.

    Arguments:

    • connid: The connection ID.

    • key: The requested key.

    • size: The size of the key's data (or -1 if not found).

    • casid: The cas ID requested.

  • command-incr(connid, key, val)

    Fired for incr command.

    Arguments:

    • connid: The connection ID.

    • key: The requested key.

    • val: The new value.

  • command-decr(connid, key, val)

    Fired for decr command.

    Arguments:

    • connid: The connection ID.

    • key: The requested key.

    • val: The new value.

  • command-delete(connid, key, exptime)

    Fired for a delete command.

    Arguments:

    • connid: The connection ID.

    • key: The requested key.

    • exptime: The expiry time.

15.6.2.6. Memory Allocation within memcached

When you first start memcached, the memory that you have configured is not automatically allocated. Instead, memcached only starts allocating and reserving physical memory once you start saving information into the cache.

When you start to store data into the cache, memcached does not allocate the memory for the data on an item by item basis. Instead, a slab allocation is used to optimize memory usage and prevent memory fragmentation when information expires from the cache.

With slab allocation, memory is reserved in blocks of 1MB. The slab is divided up into a number of blocks of equal size. When you try to store a value into the cache, memcached checks the size of the value that you are adding to the cache and determines which slab contains the right size allocation for the item. If a slab with the item size already exists, the item is written to the block within the slab.

If the new item is bigger than the size of any existing blocks, then a new slab is created, divided up into blocks of a suitable size. If an existing slab with the right block size already exists, but there are no free blocks, a new slab is created. If you update an existing item with data that is larger than the existing block allocation for that key, then the key is re-allocated into a suitable slab.

For example, the default size for the smallest block is 88 bytes (40 bytes of value, and the default 48 bytes for the key and flag data). If the size of the first item you store into the cache is less than 40 bytes, then a slab with a block size of 88 bytes is created and the value stored.

If the size of the data that you intend to store is larger than this value, then the block size is increased by the chunk size factor until a block size large enough to hold the value is determined. The block size is always a function of the scale factor, rounded up to a block size which is exactly divisible into the chunk size.

For a sample of the structure, see Figure 15.8, “Memory Allocation in memcached.

Figure 15.8. Memory Allocation in memcached

Memory Allocation in memcached

The result is that you have multiple pages allocated within the range of memory allocated to memcached. Each page is 1MB in size (by default), and is split into a different number of chunks, according to the chunk size required to store the key/value pairs. Each instance has multiple pages allocated, and a page is always created when a new item needs to be created requiring a chunk of a particular size. A slab may consist of multiple pages, and each page within a slab contains an equal number of chunks.

The chunk size of a new slab is determined by the base chunk size combined with the chunk size growth factor. For example, if the initial chunks are 104 bytes in size, and the default chunk size growth factor is used (1.25), then the next chunk size allocated would be the best power of 2 fit for 104*1.25, or 136 bytes.

Allocating the pages in this way ensures that memory does not get fragmented. However, depending on the distribution of the objects that you store, it may lead to an inefficient distribution of the slabs and chunks if you have significantly different sized items. For example, having a relatively small number of items within each chunk size may waste a lot of memory with just few chunks in each allocated page.

You can tune the growth factor to reduce this effect by using the -f command line option, which adapts the growth factor applied to make more effective use of the chunks and slabs allocated. For information on how to determine the current slab allocation statistics, see Section 15.6.4.2, “memcached Slabs Statistics”.

If your operating system supports it, you can also start memcached with the -L command line option. This option preallocates all the memory during startup using large memory pages. This can improve performance by reducing the number of misses in the CPU memory cache.

15.6.2.7. memcached Thread Support

If you enable the thread implementation within when building memcached from source, then memcached uses multiple threads in addition to the libevent system to handle requests.

When enabled, the threading implementation operates as follows:

  • Threading is handled by wrapping functions within the code to provide basic protection from updating the same global structures at the same time.

  • Each thread uses its own instance of the libevent to help improve performance.

  • TCP/IP connections are handled with a single thread listening on the TCP/IP socket. Each connection is then distributed to one of the active threads on a simple round-robin basis. Each connection then operates solely within this thread while the connection remains open.

  • For UDP connections, all the threads listen to a single UDP socket for incoming requests. Threads that are not currently dealing with another request ignore the incoming packet. One of the remaining, nonbusy, threads reads the request and sends the response. This implementation can lead to increased CPU load as threads wake from sleep to potentially process the request.

Using threads can increase the performance on servers that have multiple CPU cores available, as the requests to update the hash table can be spread between the individual threads. To minimize overhead from the locking mechanism employed, experiment with different thread values to achieve the best performance based on the number and type of requests within your given workload.

15.6.2.8. memcached Logs

If you enable verbose mode, using the -v, -vv, or -vvv options, then the information output by memcached includes details of the operations being performed.

Without the verbose options, memcached normally produces no output during normal operating.

  • Output when using -v

    The lowest verbosity level shows you:

    • Errors and warnings

    • Transient errors

    • Protocol and socket errors, including exhausting available connections

    • Each registered client connection, including the socket descriptor number and the protocol used.

      For example:

      32: Client using the ascii protocol
      33: Client using the ascii protocol

      Note that the socket descriptor is only valid while the client remains connected. Non-persistent connections may not be effectively represented.

    Examples of the error messages output at this level include:

    <%d send buffer was %d, now %d
    Can't listen for events on fd %d
    Can't read from libevent pipe
    Catastrophic: event fd doesn't match conn fd!
    Couldn't build response
    Couldn't realloc input buffer
    Couldn't update event
    Failed to build UDP headers
    Failed to read, and not due to blocking
    Too many open connections
    Unexpected state %d
  • Output when using -vv

    When using the second level of verbosity, you get more detailed information about protocol operations, keys updated, chunk and network operatings and details.

    During the initial start-up of memcached with this level of verbosity, you are shown the sizes of the individual slab classes, the chunk sizes, and the number of entries per slab. These do not show the allocation of the slabs, just the slabs that would be created when data is added. You are also given information about the listen queues and buffers used to send information. A sample of the output generated for a TCP/IP based system with the default memory and growth factors is given below:

    shell> memcached -vv
    slab class   1: chunk size     80 perslab 13107
    slab class   2: chunk size    104 perslab 10082
    slab class   3: chunk size    136 perslab  7710
    slab class   4: chunk size    176 perslab  5957
    slab class   5: chunk size    224 perslab  4681
    slab class   6: chunk size    280 perslab  3744
    slab class   7: chunk size    352 perslab  2978
    slab class   8: chunk size    440 perslab  2383
    slab class   9: chunk size    552 perslab  1899
    slab class  10: chunk size    696 perslab  1506
    slab class  11: chunk size    872 perslab  1202
    slab class  12: chunk size   1096 perslab   956
    slab class  13: chunk size   1376 perslab   762
    slab class  14: chunk size   1720 perslab   609
    slab class  15: chunk size   2152 perslab   487
    slab class  16: chunk size   2696 perslab   388
    slab class  17: chunk size   3376 perslab   310
    slab class  18: chunk size   4224 perslab   248
    slab class  19: chunk size   5280 perslab   198
    slab class  20: chunk size   6600 perslab   158
    slab class  21: chunk size   8256 perslab   127
    slab class  22: chunk size  10320 perslab   101
    slab class  23: chunk size  12904 perslab    81
    slab class  24: chunk size  16136 perslab    64
    slab class  25: chunk size  20176 perslab    51
    slab class  26: chunk size  25224 perslab    41
    slab class  27: chunk size  31536 perslab    33
    slab class  28: chunk size  39424 perslab    26
    slab class  29: chunk size  49280 perslab    21
    slab class  30: chunk size  61600 perslab    17
    slab class  31: chunk size  77000 perslab    13
    slab class  32: chunk size  96256 perslab    10
    slab class  33: chunk size 120320 perslab     8
    slab class  34: chunk size 150400 perslab     6
    slab class  35: chunk size 188000 perslab     5
    slab class  36: chunk size 235000 perslab     4
    slab class  37: chunk size 293752 perslab     3
    slab class  38: chunk size 367192 perslab     2
    slab class  39: chunk size 458992 perslab     2
    <26 server listening (auto-negotiate)
    <29 server listening (auto-negotiate)
    <30 send buffer was 57344, now 2097152
    <31 send buffer was 57344, now 2097152
    <30 server listening (udp)
    <30 server listening (udp)
    <31 server listening (udp)
    <30 server listening (udp)
    <30 server listening (udp)
    <31 server listening (udp)
    <31 server listening (udp)
    <31 server listening (udp)

    Using this verbosity level can be a useful way to check the effects of the growth factor used on slabs with different memory allocations, which in turn can be used to better tune the growth factor to suit the data you are storing in the cache. For example, if you set the growth factor to 4 (quadrupling the size of each slab):

    shell> memcached -f 4 -m 1g -vv
    slab class   1: chunk size     80 perslab 13107
    slab class   2: chunk size    320 perslab  3276
    slab class   3: chunk size   1280 perslab   819
    slab class   4: chunk size   5120 perslab   204
    slab class   5: chunk size  20480 perslab    51
    slab class   6: chunk size  81920 perslab    12
    slab class   7: chunk size 327680 perslab     3
    ...

    During use of the cache, this verbosity level also prints out detailed information on the storage and recovery of keys and other information. An example of the output during a typical set/get and increment/decrement operation is shown below.

    32: Client using the ascii protocol
    <32 set my_key 0 0 10
    >32 STORED
    <32 set object_key 1 0 36
    >32 STORED
    <32 get my_key 
    >32 sending key my_key
    >32 END
    <32 get object_key 
    >32 sending key object_key
    >32 END
    <32 set key 0 0 6
    >32 STORED
    <32 incr key 1
    >32 789544
    <32 decr key 1
    >32 789543
    <32 incr key 2
    >32 789545
    <32 set my_key 0 0 10
    >32 STORED
    <32 set object_key 1 0 36
    >32 STORED
    <32 get my_key 
    >32 sending key my_key
    >32 END
    <32 get object_key 
    >32 sending key object_key1 1 36
    
    >32 END
    <32 set key 0 0 6
    >32 STORED
    <32 incr key 1
    >32 789544
    <32 decr key 1
    >32 789543
    <32 incr key 2
    >32 789545

    During client communication, for each line, the initial character shows the direction of flow of the information. The < for communication from the client to the memcached server and > for communication back to the client. The number is the numeric socket descriptor for the connection.

  • Output when using -vvv

    This level of verbosity includes the transitions of connections between different states in the event library while reading and writing content to/from the clients. It should be used to diagnose and identify issues in client communication. For example, you can use this information to determine if memcached is taking a long time to return information to the client, during the read of the client operation or before returning and completing the operation. An example of the typical sequence for a set operation is provided below:

    <32 new auto-negotiating client connection
    32: going from conn_new_cmd to conn_waiting
    32: going from conn_waiting to conn_read
    32: going from conn_read to conn_parse_cmd
    32: Client using the ascii protocol
    <32 set my_key 0 0 10
    32: going from conn_parse_cmd to conn_nread
    > NOT FOUND my_key
    >32 STORED
    32: going from conn_nread to conn_write
    32: going from conn_write to conn_new_cmd
    32: going from conn_new_cmd to conn_waiting
    32: going from conn_waiting to conn_read
    32: going from conn_read to conn_closing
    <32 connection closed.

All of the verbosity levels in memcached are designed to be used during debugging or examination of issues. The quantity of information generated, particularly when using -vvv, is significant, particularly on a busy server. Also be aware that writing the error information out, especially to disk, may negate some of the performance gains you achieve by using memcached. Therefore, use in production or deployment environments is not recommended.

15.6.3. Developing a memcached Application

A number of language interfaces let applications store and retrieve information with memcached servers. You can write memcached applications in popular languages such as Perl, PHP, Python, Ruby, C, and Java.

Data stored into a memcached server is referred to by a single string (the key), with storage into the cache and retrieval from the cache using the key as the reference. The cache therefore operates like a large associative array or hash table. It is not possible to structure or otherwise organize the information stored in the cache. To emulate database notions such as multiple tables or composite key values, you must use encode the extra information into the strings used as keys. For example, to store or look up the address corresponding to a specific latitude and longitude, you might turn those two numeric values into a single comma-separated string to use as a key.

15.6.3.1. Basic memcached Operations

The interface to memcached supports the following methods for storing and retrieving information in the cache, and these are consistent across all the different APIs, although the language specific mechanics might be different:

  • get(key): Retrieves information from the cache. Returns the value associated with the key if the specified key exists. Returns NULL, nil, undefined, or the closest equivalent in the corresponding language, if the specified key does not exist.

  • set(key, , value, [, expiry]): Sets the item associated with a key in the cache to the specified value. Note that this either updates an existing item if the key already exists, or adds a new key/value pair if the key doesn't exist. If the expiry time is specified, then the item expires (and is deleted) when the expiry time is reached. The time is specified in seconds, and is taken as a relative time if the value is less than 30 days (30*24*60*60), or an absolute time (epoch) if larger than this value.

  • add(key, , value, [, expiry]): Adds the key and associated value to the cache, if the specified key does not already exist.

  • replace(key, , value, [, expiry]): Replaces the item associated with the specified key, only if the key already exists. The new value is given by the value parameter.

  • delete(key, [, time]): Deletes the key and its associated item from the cache. If you supply a time, then adding another item with the specified key is blocked for the specified period.

  • incr(key, [, value]): Increments the item associated with the key by one or the optional value.

  • decr(key, [, value]): Decrements the item associated with the key by one or the optional value.

  • flush_all: Invalidates (or expires) all the current items in the cache. Technically they still exist (they are not deleted), but they are silently destroyed the next time you try to access them.

In all implementations, most or all of these functions are duplicated through the corresponding native language interface.

When practical, use memcached to store full items, rather than caching a single column value from the database. For example, when displaying a record about an object (invoice, user history, or blog post), load all the data for the associated entry from the database, and compile it into the internal structure that would normally be required by the application. Save the complete object in the cache.

Complex data structures cannot be stored directly. Most interfaces serialize the data for you, that is, put it in a textual form that can reconstruct the original pointers and nesting. Perl uses Storable, PHP uses serialize, Python uses cPickle (or Pickle) and Java uses the Serializable interface. In most cases, the serialization interface used is customizable. To share data stored in memcached instances between different language interfaces, consider using a common serialization solution such as JSON (Javascript Object Notation).

15.6.3.2. Using memcached as a MySQL Caching Layer

When using memcached to cache MySQL data, your application must retrieve data from the database and load the appropriate key-value pairs into the cache. Then, subsequent lookups can be done directly from the cache.

Because MySQL has its own in-memory caching mechanisms for queried data, such as the InnoDB buffer pool and the MySQL query cache, look for opportunities beyond loading individual column values or rows into the cache. Prefer to cache composite values, such as those retrieved from multiple tables through a join query, or result sets assembled from multiple rows.

Caution

Limit the information in the cache to non-sensitive data, because there is no security required to access or update the information within a memcached instance. Anybody with access to the machine has the ability to read, view and potentially update the information. To keep the data secure, encrypt the information before caching it. To restrict the users capable of connecting to the server, either disable network access, or use IPTables or similar techniques to restrict access to the memcached ports to a select set of hosts.

You can introduce memcached to an existing application, even if caching was not part of the original design. In many languages and environments the changes to the application will be just a few lines, first to attempt to read from the cache when loading data, fall back to the old method if the information is not cached, and to update the cache with information once the data has been read.

The general sequence for using memcached in any language as a caching solution for MySQL is as follows:

  1. Request the item from the cache.

  2. If the item exists, use the item data.

  3. If the item does not exist, load the data from MySQL, and store the value into the cache. This means the value is available to the next client that requests it from the cache.

For a flow diagram of this sequence, see Figure 15.9, “Typical memcached Application Flowchart”.

Figure 15.9. Typical memcached Application Flowchart

Typical memcached Application Flowchart

Adapting Database Best Practices to memcached Applications

The most direct way to cache MySQL data is to use a 2-column table, where the first column is a primary key. Because of the uniqueness requirements for memcached keys, make sure your database schema makes appropriate use of primary keys and unique constraints.

If you combine multiple column values into a single memcached item value, choose data types to make it easy to parse the value back into its components, for example by using a separator character between numeric values.

The queries that map most easily to memcached lookups are those with a single WHERE clause, using an = or IN operator. For complicated WHERE clauses, or those using operators such as <, >, BETWEEN, or LIKE, memcached does not provide a simple or efficient way to scan through or filter the keys or associated values, so typically you perform those operations as SQL queries on the underlying database.

15.6.3.3. Using libmemcached with C and C++

The libmemcached library provides both C and C++ interfaces to memcached and is also the basis for a number of different additional API implementations, including Perl, Python and Ruby. Understanding the core libmemcached functions can help when using these other interfaces.

The C library is the most comprehensive interface library for memcached and provides functions and operational systems not always exposed in interfaces not based on the libmemcached library.

The different functions can be divided up according to their basic operation. In addition to functions that interface to the core API, a number of utility functions provide extended functionality, such as appending and prepending data.

To build and install libmemcached, download the libmemcached package, run configure, and then build and install:

shell> tar xjf libmemcached-0.21.tar.gz
shell> cd libmemcached-0.21
shell> ./configure
shell> make
shell> make install

On many Linux operating systems, you can install the corresponding libmemcached package through the usual yum, apt-get, or similar commands.

To build an application that uses the library, first set the list of servers. Either directly manipulate the servers configured within the main memcached_st structure, or separately populate a list of servers, and then add this list to the memcached_st structure. The latter method is used in the following example. Once the server list has been set, you can call the functions to store or retrieve data. A simple application for setting a preset value to localhost is provided here:

#include <stdio.h>
#include <string.h>
#include <unistd.h>
#include <libmemcached/memcached.h>

int main(int argc, char *argv[])
{
  memcached_server_st *servers = NULL;
  memcached_st *memc;
  memcached_return rc;
  char *key= "keystring";
  char *value= "keyvalue";

  memcached_server_st *memcached_servers_parse (char *server_strings);
  memc= memcached_create(NULL);

  servers= memcached_server_list_append(servers, "localhost", 11211, &rc);
  rc= memcached_server_push(memc, servers);

  if (rc == MEMCACHED_SUCCESS)
    fprintf(stderr,"Added server successfully\n");
  else
    fprintf(stderr,"Couldn't add server: %s\n",memcached_strerror(memc, rc));

  rc= memcached_set(memc, key, strlen(key), value, strlen(value), (time_t)0, (uint32_t)0);

  if (rc == MEMCACHED_SUCCESS)
    fprintf(stderr,"Key stored successfully\n");
  else
    fprintf(stderr,"Couldn't store key: %s\n",memcached_strerror(memc, rc));

  return 0;
}

To test the success of an operation, use the return value, or populated result code, for a given function. The value is always set to MEMCACHED_SUCCESS if the operation succeeded. In the event of a failure, use the memcached_strerror() function to translate the result code into a printable string.

To build the application, specify the memcached library:

shell> gcc -o memc_basic memc_basic.c -lmemcached

Running the above sample application, after starting a memcached server, should return a success message:

shell> memc_basic
Added server successfully
Key stored successfully
15.6.3.3.1. libmemcached Base Functions

The base libmemcached functions let you create, destroy and clone the main memcached_st structure that is used to interface with the memcached servers. The main functions are defined below:

memcached_st *memcached_create (memcached_st *ptr);

Creates a new memcached_st structure for use with the other libmemcached API functions. You can supply an existing, static, memcached_st structure, or NULL to have a new structured allocated. Returns a pointer to the created structure, or NULL on failure.

void memcached_free (memcached_st *ptr);

Frees the structure and memory allocated to a previously created memcached_st structure.

memcached_st *memcached_clone(memcached_st *clone, memcached_st *source);

Clones an existing memcached structure from the specified source, copying the defaults and list of servers defined in the structure.

15.6.3.3.2. libmemcached Server Functions

The libmemcached API uses a list of servers, stored within the memcached_server_st structure, to act as the list of servers used by the rest of the functions. To use memcached, you first create the server list, and then apply the list of servers to a valid libmemcached object.

Because the list of servers, and the list of servers within an active libmemcached object can be manipulated separately, you can update and manage server lists while an active libmemcached interface is running.

The functions for manipulating the list of servers within a memcached_st structure are:

memcached_return
   memcached_server_add (memcached_st *ptr,
                         char *hostname,
                         unsigned int port);

Adds a server, using the given hostname and port into the memcached_st structure given in ptr.

memcached_return
   memcached_server_add_unix_socket (memcached_st *ptr,
                                     char *socket);

Adds a Unix socket to the list of servers configured in the memcached_st structure.

unsigned int memcached_server_count (memcached_st *ptr);

Returns a count of the number of configured servers within the memcached_st structure.

memcached_server_st *
   memcached_server_list (memcached_st *ptr);

Returns an array of all the defined hosts within a memcached_st structure.

memcached_return
   memcached_server_push (memcached_st *ptr,
                          memcached_server_st *list);

Pushes an existing list of servers onto list of servers configured for a current memcached_st structure. This adds servers to the end of the existing list, and duplicates are not checked.

The memcached_server_st structure can be used to create a list of memcached servers which can then be applied individually to memcached_st structures.

memcached_server_st *
   memcached_server_list_append (memcached_server_st *ptr,
                                 char *hostname,
                                 unsigned int port,
                                 memcached_return *error);

Adds a server, with hostname and port, to the server list in ptr. The result code is handled by the error argument, which should point to an existing memcached_return variable. The function returns a pointer to the returned list.

unsigned int memcached_server_list_count (memcached_server_st *ptr);

Returns the number of the servers in the server list.

void memcached_server_list_free (memcached_server_st *ptr);

Frees the memory associated with a server list.

memcached_server_st *memcached_servers_parse (char *server_strings);

Parses a string containing a list of servers, where individual servers are separated by a comma, space, or both, and where individual servers are of the form server[:port]. The return value is a server list structure.

15.6.3.3.3. libmemcached Set Functions

The set-related functions within libmemcached provide the same functionality as the core functions supported by the memcached protocol. The full definition for the different functions is the same for all the base functions (add, replace, prepend, append). For example, the function definition for memcached_set() is:

memcached_return
   memcached_set (memcached_st *ptr,
                  const char *key,
                  size_t key_length,
                  const char *value,
                  size_t value_length,
                  time_t expiration,
                  uint32_t flags);

The ptr is the memcached_st structure. The key and key_length define the key name and length, and value and value_length the corresponding value and length. You can also set the expiration and optional flags. For more information, see Section 15.6.3.3.5, “Controlling libmemcached Behaviors”.

This table outlines the remainder of the set-related libmemcached functions and the equivalent core functions supported by the memcached protocol.

libmemcached FunctionEquivalent Core Function
memcached_set(memc, key, key_length, value, value_length, expiration, flags)Generic set() operation.
memcached_add(memc, key, key_length, value, value_length, expiration, flags)Generic add() function.
memcached_replace(memc, key, key_length, value, value_length, expiration, flags)Generic replace().
memcached_prepend(memc, key, key_length, value, value_length, expiration, flags)Prepends the specified value before the current value of the specified key.
memcached_append(memc, key, key_length, value, value_length, expiration, flags)Appends the specified value after the current value of the specified key.
memcached_cas(memc, key, key_length, value, value_length, expiration, flags, cas)Overwrites the data for a given key as long as the corresponding cas value is still the same within the server.
memcached_set_by_key(memc, master_key, master_key_length, key, key_length, value, value_length, expiration, flags)Similar to the generic set(), but has the option of an additional master key that can be used to identify an individual server.
memcached_add_by_key(memc, master_key, master_key_length, key, key_length, value, value_length, expiration, flags)Similar to the generic add(), but has the option of an additional master key that can be used to identify an individual server.
memcached_replace_by_key(memc, master_key, master_key_length, key, key_length, value, value_length, expiration, flags)Similar to the generic replace(), but has the option of an additional master key that can be used to identify an individual server.
memcached_prepend_by_key(memc, master_key, master_key_length, key, key_length, value, value_length, expiration, flags)Similar to the memcached_prepend(), but has the option of an additional master key that can be used to identify an individual server.
memcached_append_by_key(memc, master_key, master_key_length, key, key_length, value, value_length, expiration, flags)Similar to the memcached_append(), but has the option of an additional master key that can be used to identify an individual server.
memcached_cas_by_key(memc, master_key, master_key_length, key, key_length, value, value_length, expiration, flags)Similar to the memcached_cas(), but has the option of an additional master key that can be used to identify an individual server.

The by_key methods add two further arguments that define the master key, to be used and applied during the hashing stage for selecting the servers. You can see this in the following definition:

memcached_return
   memcached_set_by_key(memcached_st *ptr,
                        const char *master_key,
                        size_t master_key_length,
                        const char *key,
                        size_t key_length,
                        const char *value,
                        size_t value_length,
                        time_t expiration,
                        uint32_t flags);

All the functions return a value of type memcached_return, which you can compare against the MEMCACHED_SUCCESS constant.

15.6.3.3.4. libmemcached Get Functions

The libmemcached functions provide both direct access to a single item, and a multiple-key request mechanism that provides much faster responses when fetching a large number of keys simultaneously.

The main get-style function, which is equivalent to the generic get() is memcached_get(). This function returns a string pointer, pointing to the value associated with the specified key.

char *memcached_get (memcached_st *ptr,
                     const char *key, size_t key_length,
                     size_t *value_length,
                     uint32_t *flags,
                     memcached_return *error);

A multi-key get, memcached_mget(), is also available. Using a multiple key get operation is much quicker to do in one block than retrieving the key values with individual calls to memcached_get(). To start the multi-key get, call memcached_mget():

memcached_return
    memcached_mget (memcached_st *ptr,
                    char **keys, size_t *key_length,
                    unsigned int number_of_keys);

The return value is the success of the operation. The keys parameter should be an array of strings containing the keys, and key_length an array containing the length of each corresponding key. number_of_keys is the number of keys supplied in the array.

To fetch the individual values, use memcached_fetch() to get each corresponding value.

char *memcached_fetch (memcached_st *ptr,
                       const char *key, size_t *key_length,
                       size_t *value_length,
                       uint32_t *flags,
                       memcached_return *error);

The function returns the key value, with the key, key_length and value_length parameters being populated with the corresponding key and length information. The function returns NULL when there are no more values to be returned. A full example, including the populating of the key data and the return of the information is provided here.

#include <stdio.h>
#include <sstring.h>
#include <unistd.h>
#include <libmemcached/memcached.h>

int main(int argc, char *argv[])
{
  memcached_server_st *servers = NULL;
  memcached_st *memc;
  memcached_return rc;
  char *keys[]= {"huey", "dewey", "louie"};
  size_t key_length[3];
  char *values[]= {"red", "blue", "green"};
  size_t value_length[3];
  unsigned int x;
  uint32_t flags;

  char return_key[MEMCACHED_MAX_KEY];
  size_t return_key_length;
  char *return_value;
  size_t return_value_length;

  memc= memcached_create(NULL);

  servers= memcached_server_list_append(servers, "localhost", 11211, &rc);
  rc= memcached_server_push(memc, servers);

  if (rc == MEMCACHED_SUCCESS)
    fprintf(stderr,"Added server successfully\n");
  else
    fprintf(stderr,"Couldn't add server: %s\n",memcached_strerror(memc, rc));

  for(x= 0; x < 3; x++)
    {
      key_length[x] = strlen(keys[x]);
      value_length[x] = strlen(values[x]);

      rc= memcached_set(memc, keys[x], key_length[x], values[x],
                        value_length[x], (time_t)0, (uint32_t)0);
      if (rc == MEMCACHED_SUCCESS)
        fprintf(stderr,"Key %s stored successfully\n",keys[x]);
      else
        fprintf(stderr,"Couldn't store key: %s\n",memcached_strerror(memc, rc));
    }

  rc= memcached_mget(memc, keys, key_length, 3);

  if (rc == MEMCACHED_SUCCESS)
    {
      while ((return_value= memcached_fetch(memc, return_key, &return_key_length,
                                            &return_value_length, &flags, &rc)) != NULL)
        {
          if (rc == MEMCACHED_SUCCESS)
            {
              fprintf(stderr,"Key %s returned %s\n",return_key, return_value);
            }
        }
    }

  return 0;
}

Running the above application produces the following output:

shell> memc_multi_fetch
Added server successfully
Key huey stored successfully
Key dewey stored successfully
Key louie stored successfully
Key huey returned red
Key dewey returned blue
Key louie returned green
15.6.3.3.5. Controlling libmemcached Behaviors

The behavior of libmemcached can be modified by setting one or more behavior flags. These can either be set globally, or they can be applied during the call to individual functions. Some behaviors also accept an additional setting, such as the hashing mechanism used when selecting servers.

To set global behaviors:

memcached_return
   memcached_behavior_set (memcached_st *ptr,
                           memcached_behavior flag,
                           uint64_t data);

To get the current behavior setting:

uint64_t
   memcached_behavior_get (memcached_st *ptr,
                           memcached_behavior flag);

The following table describes libmemcached behavior flags.

BehaviorDescription
MEMCACHED_BEHAVIOR_NO_BLOCKCaused libmemcached to use asynchronous I/O.
MEMCACHED_BEHAVIOR_TCP_NODELAYTurns on no-delay for network sockets.
MEMCACHED_BEHAVIOR_HASHWithout a value, sets the default hashing algorithm for keys to use MD5. Other valid values include MEMCACHED_HASH_DEFAULT, MEMCACHED_HASH_MD5, MEMCACHED_HASH_CRC, MEMCACHED_HASH_FNV1_64, MEMCACHED_HASH_FNV1A_64, MEMCACHED_HASH_FNV1_32, and MEMCACHED_HASH_FNV1A_32.
MEMCACHED_BEHAVIOR_DISTRIBUTIONChanges the method of selecting the server used to store a given value. The default method is MEMCACHED_DISTRIBUTION_MODULA. You can enable consistent hashing by setting MEMCACHED_DISTRIBUTION_CONSISTENT. MEMCACHED_DISTRIBUTION_CONSISTENT is an alias for the value MEMCACHED_DISTRIBUTION_CONSISTENT_KETAMA.
MEMCACHED_BEHAVIOR_CACHE_LOOKUPSCache the lookups made to the DNS service. This can improve the performance if you are using names instead of IP addresses for individual hosts.
MEMCACHED_BEHAVIOR_SUPPORT_CASSupport CAS operations. By default, this is disabled because it imposes a performance penalty.
MEMCACHED_BEHAVIOR_KETAMASets the default distribution to MEMCACHED_DISTRIBUTION_CONSISTENT_KETAMA and the hash to MEMCACHED_HASH_MD5.
MEMCACHED_BEHAVIOR_POLL_TIMEOUTModify the timeout value used by poll(). Supply a signed int pointer for the timeout value.
MEMCACHED_BEHAVIOR_BUFFER_REQUESTSBuffers IO requests instead of them being sent. A get operation, or closing the connection causes the data to be flushed.
MEMCACHED_BEHAVIOR_VERIFY_KEYForces libmemcached to verify that a specified key is valid.
MEMCACHED_BEHAVIOR_SORT_HOSTSIf set, hosts added to the list of configured hosts for a memcached_st structure are placed into the host list in sorted order. This breaks consistent hashing if that behavior has been enabled.
MEMCACHED_BEHAVIOR_CONNECT_TIMEOUTIn nonblocking mode this changes the value of the timeout during socket connection.
15.6.3.3.6. libmemcached Command-Line Utilities

In addition to the main C library interface, libmemcached also includes a number of command-line utilities that can be useful when working with and debugging memcached applications.

All of the command-line tools accept a number of arguments, the most critical of which is servers, which specifies the list of servers to connect to when returning information.

The main tools are:

  • memcat: Display the value for each ID given on the command line:

    shell> memcat --servers=localhost hwkey
    Hello world
  • memcp: Copy the contents of a file into the cache, using the file name as the key:

    shell> echo "Hello World" > hwkey
    shell> memcp --servers=localhost hwkey
    shell> memcat --servers=localhost hwkey
    Hello world
  • memrm: Remove an item from the cache:

    shell> memcat --servers=localhost hwkey
    Hello world
    shell> memrm --servers=localhost hwkey
    shell> memcat --servers=localhost hwkey
  • memslap: Test the load on one or more memcached servers, simulating get/set and multiple client operations. For example, you can simulate the load of 100 clients performing get operations:

    shell> memslap --servers=localhost --concurrency=100 --flush --test=get
    memslap --servers=localhost --concurrency=100 --flush --test=get	Threads connecting to servers 100
    	Took 13.571 seconds to read data
  • memflush: Flush (empty) the contents of the memcached cache.

    shell> memflush --servers=localhost

15.6.3.4. Using MySQL and memcached with Perl

The Cache::Memcached module provides a native interface to the Memcache protocol, and provides support for the core functions offered by memcached. Install the module using your operating system's package management system, or using CPAN:

root-shell> perl -MCPAN -e 'install Cache::Memcached'

To use memcached from Perl through the Cache::Memcached module, first create a new Cache::Memcached object that defines the list of servers and other parameters for the connection. The only argument is a hash containing the options for the cache interface. For example, to create a new instance that uses three memcached servers:

use Cache::Memcached;

my $cache = new Cache::Memcached {
    'servers' => [
        '192.168.0.100:11211',
        '192.168.0.101:11211',
        '192.168.0.102:11211',
	],
};
Note

When using the Cache::Memcached interface with multiple servers, the API automatically performs certain operations across all the servers in the group. For example, getting statistical information through Cache::Memcached returns a hash that contains data on a host-by-host basis, as well as generalized statistics for all the servers in the group.

You can set additional properties on the cache object instance when it is created by specifying the option as part of the option hash. Alternatively, you can use a corresponding method on the instance:

  • servers or method set_servers(): Specifies the list of the servers to be used. The servers list should be a reference to an array of servers, with each element as the address and port number combination (separated by a colon). You can also specify a local connection through a UNIX socket (for example /tmp/sock/memcached). To specify the server with a weight (indicating how much more frequently the server should be used during hashing), specify an array reference with the memcached server instance and a weight number. Higher numbers give higher priority.

  • compress_threshold or method set_compress_threshold(): Specifies the threshold when values are compressed. Values larger than the specified number are automatically compressed (using zlib) during storage and retrieval.

  • no_rehash or method set_norehash(): Disables finding a new server if the original choice is unavailable.

  • readonly or method set_readonly(): Disables writes to the memcached servers.

Once the Cache::Memcached object instance has been configured, you can use the set() and get() methods to store and retrieve information from the memcached servers. Objects stored in the cache are automatically serialized and deserialized using the Storable module.

The Cache::Memcached interface supports the following methods for storing/retrieving data, and relate to the generic methods as shown in the table.

Cache::Memcached FunctionEquivalent Generic Method
get()Generic get().
get_multi(keys)Gets multiple keys from memcache using just one query. Returns a hash reference of key/value pairs.
set()Generic set().
add()Generic add().
replace()Generic replace().
delete()Generic delete().
incr()Generic incr().
decr()Generic decr().

Below is a complete example for using memcached with Perl and the Cache::Memcached module:

#!/usr/bin/perl

use Cache::Memcached;
use DBI;
use Data::Dumper;

# Configure the memcached server

my $cache = new Cache::Memcached {
    'servers' => [
                   'localhost:11211',
                   ],
    };

# Get the film name from the command line
# memcached keys must not contain spaces, so create
# a key name by replacing spaces with underscores

my $filmname = shift or die "Must specify the film name\n";
my $filmkey = $filmname;
$filmkey =~ s/ /_/;

# Load the data from the cache

my $filmdata = $cache->get($filmkey);

# If the data wasn't in the cache, then we load it from the database

if (!defined($filmdata))
{
    $filmdata = load_filmdata($filmname);

    if (defined($filmdata))
    {

# Set the data into the cache, using the key

	if ($cache->set($filmkey,$filmdata))
        {
            print STDERR "Film data loaded from database and cached\n";
        }
        else
        {
            print STDERR "Couldn't store to cache\n";
	}
    }
    else
    {
     	die "Couldn't find $filmname\n";
    }
}
else
{
    print STDERR "Film data loaded from Memcached\n";
}

sub load_filmdata
{
    my ($filmname) = @_;

    my $dsn = "DBI:mysql:database=sakila;host=localhost;port=3306";

    $dbh = DBI->connect($dsn, 'sakila','password');

    my ($filmbase) = $dbh->selectrow_hashref(sprintf('select * from film where title = %s',
                                                     $dbh->quote($filmname)));

    if (!defined($filmname))
    {
     	return (undef);
    }

    $filmbase->{stars} =
	$dbh->selectall_arrayref(sprintf('select concat(first_name," ",last_name) ' .
                                         'from film_actor left join (actor) ' .
                                         'on (film_actor.actor_id = actor.actor_id) ' .
                                         ' where film_id=%s',
                                         $dbh->quote($filmbase->{film_id})));

    return($filmbase);
}

The example uses the Sakila database, obtaining film data from the database and writing a composite record of the film and actors to memcached. When calling it for a film does not exist, you get this result:

shell> memcached-sakila.pl "ROCK INSTINCT"
Film data loaded from database and cached

When accessing a film that has already been added to the cache:

shell> memcached-sakila.pl "ROCK INSTINCT"
Film data loaded from Memcached

15.6.3.5. Using MySQL and memcached with Python

The Python memcache module interfaces to memcached servers, and is written in pure Python (that is, without using one of the C APIs). You can download and install a copy from Python Memcached.

To install, download the package and then run the Python installer:

python setup.py install
running install
running bdist_egg
running egg_info
creating python_memcached.egg-info
...
removing 'build/bdist.linux-x86_64/egg' (and everything under it)
Processing python_memcached-1.43-py2.4.egg
creating /usr/lib64/python2.4/site-packages/python_memcached-1.43-py2.4.egg
Extracting python_memcached-1.43-py2.4.egg to /usr/lib64/python2.4/site-packages
Adding python-memcached 1.43 to easy-install.pth file

Installed /usr/lib64/python2.4/site-packages/python_memcached-1.43-py2.4.egg
Processing dependencies for python-memcached==1.43
Finished processing dependencies for python-memcached==1.43

Once installed, the memcache module provides a class-based interface to your memcached servers. When you store Python data structures as memcached items, they are automatically serialized (turned into string values) using the Python cPickle or pickle modules.

To create a new memcache interface, import the memcache module and create a new instance of the memcache.Client class. For example, if the memcached daemon is running on localhost using the default port:

import memcache
memc = memcache.Client(['127.0.0.1:11211'])

The first argument is an array of strings containing the server and port number for each memcached instance to use. To enable debugging, set the optional debug parameter to 1.

By default, the hashing mechanism used to divide the items among multiple servers is crc32. To change the function used, set the value of memcache.serverHashFunction to the alternate function to use. For example:

from zlib import adler32
memcache.serverHashFunction = adler32

Once you have defined the servers to use within the memcache instance, the core functions provide the same functionality as in the generic interface specification. The following table provides a summary of the supported functions:

Python memcache FunctionEquivalent Generic Function
get()Generic get().
get_multi(keys)Gets multiple values from the supplied array of keys. Returns a hash reference of key/value pairs.
set()Generic set().
set_multi(dict [, expiry [, key_prefix]])Sets multiple key/value pairs from the supplied dict.
add()Generic add().
replace()Generic replace().
prepend(key, value [, expiry])Prepends the supplied value to the value of the existing key.
append(key, value [, expiry[)Appends the supplied value to the value of the existing key.
delete()Generic delete().
delete_multi(keys [, expiry [, key_prefix]] )Deletes all the keys from the hash matching each string in the array keys.
incr()Generic incr().
decr()Generic decr().
Note

Within the Python memcache module, all the *_multi()functions support an optional key_prefix parameter. If supplied, then the string is used as a prefix to all key lookups. For example, if you call:

memc.get_multi(['a','b'], key_prefix='users:')

The function retrieves the keys users:a and users:b from the servers.

Here is an example showing the storage and retrieval of information to a memcache instance, loading the raw data from MySQL:

import sys
import MySQLdb
import memcache

memc = memcache.Client(['127.0.0.1:11211'], debug=1);

try:
    conn = MySQLdb.connect (host = "localhost",
                            user = "sakila",
                            passwd = "password",
                            db = "sakila")
except MySQLdb.Error, e:
     print "Error %d: %s" % (e.args[0], e.args[1])
     sys.exit (1)

popularfilms = memc.get('top5films')

if not popularfilms:
    cursor = conn.cursor()
    cursor.execute('select film_id,title from film order by rental_rate desc limit 5')
    rows = cursor.fetchall()
    memc.set('top5films',rows,60)
    print "Updated memcached with MySQL data"
else:
    print "Loaded data from memcached"
    for row in popularfilms:
        print "%s, %s" % (row[0], row[1])

When executed for the first time, the data is loaded from the MySQL database and stored to the memcached server.

shell> python memc_python.py
Updated memcached with MySQL data

Because the data is automatically serialized using cPickle/pickle, when you load the data back from memcached, you can use the object directly. In the example above, the information stored to memcached is in the form of rows from a Python DB cursor. When accessing the information (within the 60 second expiry time), the data is loaded from memcached and dumped:

shell> python memc_python.py
Loaded data from memcached
2, ACE GOLDFINGER
7, AIRPLANE SIERRA
8, AIRPORT POLLOCK
10, ALADDIN CALENDAR
13, ALI FOREVER

The serialization and deserialization happens automatically. Because serialization of Python data may be incompatible with other interfaces and languages, you can change the serialization module used during initialization. For example, you might use JSON format when you store complex data structures using a script written in one language, and access them in a script written in a different language.

15.6.3.6. Using MySQL and memcached with PHP

PHP provides support for the Memcache functions through a PECL extension. To enable the PHP memcache extensions, build PHP using the --enable-memcache option to configure when building from source.

If you are installing on a Red Hat-based server, you can install the php-pecl-memcache RPM:

root-shell> yum --install php-pecl-memcache

On Debian-based distributions, use the php-memcache package.

To set global runtime configuration options, specify the configuration option values within your php.ini file. The following table provides the name, default value, and a description for each global runtime configuration option.

Configuration optionDefaultDescription
memcache.allow_failover1Specifies whether another server in the list should be queried if the first server selected fails.
memcache.max_failover_attempts20Specifies the number of servers to try before returning a failure.
memcache.chunk_size8192Defines the size of network chunks used to exchange data with the memcached server.
memcache.default_port11211Defines the default port to use when communicating with the memcached servers.
memcache.hash_strategystandardSpecifies which hash strategy to use. Set to consistent to enable servers to be added or removed from the pool without causing the keys to be remapped to other servers. When set to standard, an older (modula) strategy is used that potentially uses different servers for storage.
memcache.hash_functioncrc32Specifies which function to use when mapping keys to servers. crc32 uses the standard CRC32 hash. fnv uses the FNV-1a hashing algorithm.

To create a connection to a memcached server, create a new Memcache object and then specify the connection options. For example:

<?php

$cache = new Memcache;
$cache->connect('localhost',11211);
?>

This opens an immediate connection to the specified server.

To use multiple memcached servers, you need to add servers to the memcache object using addServer():

bool Memcache::addServer ( string $host [, int $port [, bool $persistent
                 [, int $weight [, int $timeout [, int $retry_interval
                 [, bool $status [, callback $failure_callback
                 ]]]]]]] )

The server management mechanism within the php-memcache module is a critical part of the interface as it controls the main interface to the memcached instances and how the different instances are selected through the hashing mechanism.

To create a simple connection to two memcached instances:

<?php

$cache = new Memcache;
$cache->addServer('192.168.0.100',11211);
$cache->addServer('192.168.0.101',11211);
?>

In this scenario, the instance connection is not explicitly opened, but only opened when you try to store or retrieve a value. To enable persistent connections to memcached instances, set the $persistent argument to true. This is the default setting, and causes the connections to remain open.

To help control the distribution of keys to different instances, use the global memcache.hash_strategy setting. This sets the hashing mechanism used to select. You can also add another weight to each server, which effectively increases the number of times the instance entry appears in the instance list, therefore increasing the likelihood of the instance being chosen over other instances. To set the weight, set the value of the $weight argument to more than one.

The functions for setting and retrieving information are identical to the generic functional interface offered by memcached, as shown in this table:

PECL memcache FunctionGeneric Function
get()Generic get().
set()Generic set().
add()Generic add().
replace()Generic replace().
delete()Generic delete().
increment()Generic incr().
decrement()Generic decr().

A full example of the PECL memcache interface is provided below. The code loads film data from the Sakila database when the user provides a film name. The data stored into the memcached instance is recorded as a mysqli result row, and the API automatically serializes the information for you.

<?php

$memc = new Memcache;
$memc->addServer('localhost','11211');

if(empty($_POST['film'])) {
?>
  <html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en">
    <head>
      <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
      <title>Simple Memcache Lookup</title>
    </head>
    <body>
      <form method="post">
        <p><b>Film</b>: <input type="text" size="20" name="film"></p>
        <input type="submit">
      </form>
      <hr/>
<?php

} else {
    
    echo "Loading data...\n";
    
    $film   = htmlspecialchars($_POST['film'], ENT_QUOTES, 'UTF-8');
    $mfilms = $memc->get($film);

    if ($mfilms) {

        printf("<p>Film data for %s loaded from memcache</p>", $mfilms['title']);

        foreach (array_keys($mfilms) as $key) {
            printf("<p><b>%s</b>: %s</p>", $key, $mfilms[$key]);
        }

    } else {

        $mysqli = mysqli('localhost','sakila','password','sakila');
    
        if (mysqli_connect_error()) {
            sprintf("Database error: (%d) %s", mysqli_connect_errno(), mysqli_connect_error());
            exit;
        }
    
        $sql = sprintf('SELECT * FROM film WHERE title="%s"', $mysqli->real_escape_string($film));

        $result = $mysqli->query($sql);

        if (!$result) {
            sprintf("Database error: (%d) %s", $mysqli->errno, $mysqli->error);
            exit;
        }

        $row = $result->fetch_assoc();

        $memc->set($row['title'], $row);

        printf("<p>Loaded (%s) from MySQL</p>", htmlspecialchars($row['title'], ENT_QUOTES, 'UTF-8');
    }
}
?>
  </body>
</html>

With PHP, the connections to the memcached instances are kept open as long as the PHP and associated Apache instance remain running. When adding or removing servers from the list in a running instance (for example, when starting another script that mentions additional servers), the connections are shared, but the script only selects among the instances explicitly configured within the script.

To ensure that changes to the server list within a script do not cause problems, make sure to use the consistent hashing mechanism.

15.6.3.7. Using MySQL and memcached with Ruby

There are a number of different modules for interfacing to memcached within Ruby. The Ruby-MemCache client library provides a native interface to memcached that does not require any external libraries, such as libmemcached. You can obtain the installer package from http://www.deveiate.org/projects/RMemCache.

To install, extract the package and then run install.rb:

shell> install.rb

If you have RubyGems, you can install the Ruby-MemCache gem:

shell> gem install Ruby-MemCache
Bulk updating Gem source index for: http://gems.rubyforge.org
Install required dependency io-reactor? [Yn]  y
Successfully installed Ruby-MemCache-0.0.1
Successfully installed io-reactor-0.05
Installing ri documentation for io-reactor-0.05...
Installing RDoc documentation for io-reactor-0.05...

To use a memcached instance from within Ruby, create a new instance of the MemCache object.

require 'memcache'
memc = MemCache::new '192.168.0.100:11211'

You can add a weight to each server to increase the likelihood of the server being selected during hashing by appending the weight count to the server host name/port string:

require 'memcache'
memc = MemCache::new '192.168.0.100:11211:3'

To add servers to an existing list, you can append them directly to the MemCache object:

memc += ["192.168.0.101:11211"]

To set data into the cache, you can just assign a value to a key within the new cache object, which works just like a standard Ruby hash object:

memc["key"] = "value"

Or to retrieve the value:

print memc["key"]

For more explicit actions, you can use the method interface, which mimics the main memcached API functions, as summarized in the following table:

Ruby MemCache MethodEquivalent memcached API Functions
get()Generic get().
get_hash(keys)Get the values of multiple keys, returning the information as a hash of the keys and their values.
set()Generic set().
set_many(pairs)Set the values of the keys and values in the hash pairs.
add()Generic add().
replace()Generic replace().
delete()Generic delete().
incr()Generic incr().
decr()Generic decr().

15.6.3.8. Using MySQL and memcached with Java

The com.danga.MemCached class within Java provides a native interface to memcached instances. You can obtain the client from http://whalin.com/memcached/. The Java class uses hashes that are compatible with libmemcached, so you can mix and match Java and libmemcached applications accessing the same memcached instances. The serialization between Java and other interfaces are not compatible. If this is a problem, use JSON or a similar nonbinary serialization format.

On most systems, you can download the package and use the jar directly.

To use the com.danga.MemCached interface, you create a MemCachedClient instance and then configure the list of servers by configuring the SockIOPool. Through the pool specification you set up the server list, weighting, and the connection parameters to optimized the connections between your client and the memcached instances that you configure.

Generally, you can configure the memcached interface once within a single class, then use this interface throughout the rest of your application.

For example, to create a basic interface, first configure the MemCachedClient and base SockIOPool settings:

public class MyClass {

    protected static MemCachedClient mcc = new MemCachedClient();

    static {
	
        String[] servers =
            {
                "localhost:11211",
            };
	
        Integer[] weights = { 1 };
	
        SockIOPool pool = SockIOPool.getInstance();
	
        pool.setServers( servers );
        pool.setWeights( weights );

In the above sample, the list of servers is configured by creating an array of the memcached instances to use. You can then configure individual weights for each server.

The remainder of the properties for the connection are optional, but you can set the connection numbers (initial connections, minimum connections, maximum connections, and the idle timeout) by setting the pool parameters:

pool.setInitConn( 5 );
pool.setMinConn( 5 );
pool.setMaxConn( 250 );
pool.setMaxIdle( 1000 * 60 * 60 * 6 

Once the parameters have been configured, initialize the connection pool:

pool.initialize();

The pool, and the connection to your memcached instances should now be ready to use.

To set the hashing algorithm used to select the server used when storing a given key, use pool.setHashingAlg():

pool.setHashingAlg( SockIOPool.NEW_COMPAT_HASH );

Valid values are NEW_COMPAT_HASH, OLD_COMPAT_HASH and NATIVE_HASH are also basic modula hashing algorithms. For a consistent hashing algorithm, use CONSISTENT_HASH. These constants are equivalent to the corresponding hash settings within libmemcached.

The following table outlines the Java com.danga.MemCached methods and the equivalent generic methods in the memcached interface specification.

Java com.danga.MemCached MethodEquivalent Generic Method
get()Generic get().
getMulti(keys)Get the values of multiple keys, returning the information as Hash map using java.lang.String for the keys and java.lang.Object for the corresponding values.
set()Generic set().
add()Generic add().
replace()Generic replace().
delete()Generic delete().
incr()Generic incr().
decr()Generic decr().

15.6.3.9. Using the MySQL memcached User-Defined Functions

The memcached MySQL User-Defined Functions (UDFs) enable you to set and retrieve objects through a SQL interface, in MySQL 5.0 or greater. This technique has the following benefits:

  • You can update and retrieve cached items directly from within SQL scripts, stored procedures, and triggers. For example, you might already have triggers in place to increment counters and set status flags based on general database activity.

  • You can pass information back and forth with other applications that use memcached, without adding database connection and query code to them.

  • You can avoid installing and configuring a memcached client on every combination of language and server that you use for your MySQL applications. The applications can relay memcached requests through the database server they connect to.

  • You can access memcached servers from languages that do not have a memcached client.

To install the MySQL memcached UDFs, download the UDF package from https://launchpad.net/memcached-udfs. Unpack the package and run configure to configure the build process. When running configure, use the --with-mysql option and specify the location of the mysql_config command.

shell> tar zxf memcached_functions_mysql-1.1.tar.gz
shell> cd memcached_functions_mysql-1.1
shell> # If memcached library is not found, set LDFLAGS=-Llibrary_directory before next command.
shell> ./configure --with-mysql=/usr/local/mysql/bin/mysql_config

Now build and install the functions:

shell> make
shell> make install

Copy the MySQL memcached UDFs into your MySQL plugins directory:

shell> cp /usr/local/lib/libmemcached_functions_mysql* /usr/local/mysql/lib/mysql/plugins/

The plugin directory is given by the value of the plugin_dir system variable. For more information, see Section 23.3.2.5, “Compiling and Installing User-Defined Functions”.

Once installed, you must initialize the function within MySQL using CREATE and specifying the return value and library. For example, to add the memc_get() function:

mysql> CREATE FUNCTION memc_get RETURNS STRING SONAME "libmemcached_functions_mysql.so";

Repeat this process for each function to provide access to within MySQL. Once you have created the association, the information is retained, even over restarts of the MySQL server. To simplify the process, use the SQL script provided in the memcached UDFs package:

shell> mysql <sql/install_functions.sql

Alternatively, if you have Perl installed, then you can use the supplied Perl script, which checks for the existence of each function and creates the function/library association if it is not already defined:

shell> utils/install.pl --silent

The --silent option installs everything automatically. Without this option, the script asks whether to install each of the available functions.

The interface remains consistent with the other APIs and interfaces. To set up a list of servers, use the memc_servers_set() function, which accepts a single string containing and comma-separated list of servers:

mysql> SELECT memc_servers_set('192.168.0.1:11211,192.168.0.2:11211');
Note

The list of servers used by the memcached UDFs is not persistent over restarts of the MySQL server. If the MySQL server fails, then you must re-set the list of memcached servers.

To set a value, use memc_set:

mysql> SELECT memc_set('myid', 'myvalue');

To retrieve a stored value:

mysql> SELECT memc_get('myid');

The list of functions supported by the UDFs, in relation to the standard protocol functions, is shown in the following table:

MySQL memcached UDF FunctionEquivalent Standard Function
memc_get()Generic get().
memc_get_by_key(master_key, key, value)Like the generic get(), but uses the supplied master key to select the server to use.
memc_set()Generic set().
memc_set_by_key(master_key, key, value)Like the generic set(), but uses the supplied master key to select the server to use.
memc_add()Generic add().
memc_add_by_key(master_key, key, value)Like the generic add(), but uses the supplied master key to select the server to use.
memc_replace()Generic replace().
memc_replace_by_key(master_key, key, value)Like the generic replace(), but uses the supplied master key to select the server to use.
memc_prepend(key, value)Prepend the specified value to the current value of the specified key.
memc_prepend_by_key(master_key, key, value)Prepend the specified value to the current value of the specified key, but uses the supplied master key to select the server to use.
memc_append(key, value)Append the specified value to the current value of the specified key.
memc_append_by_key(master_key, key, value)Append the specified value to the current value of the specified key, but uses the supplied master key to select the server to use.
memc_delete()Generic delete().
memc_delete_by_key(master_key, key, value)Like the generic delete(), but uses the supplied master key to select the server to use.
memc_increment()Generic incr().
memc_decrement()Generic decr().

The respective *_by_key() functions are useful to store a specific value into a specific memcached server, possibly based on a differently calculated or constructed key.

The memcached UDFs include some additional functions:

  • memc_server_count()

    Returns a count of the number of servers in the list of registered servers.

  • memc_servers_set_behavior(behavior_type, value), memc_set_behavior(behavior_type, value)

    Sets behaviors for the list of servers. These behaviors are identical to those provided by the libmemcached library. For more information on libmemcached behaviors, see Section 15.6.3.3, “Using libmemcached with C and C++”.

    You can use the behavior name as the behavior_type:

    mysql> SELECT memc_servers_behavior_set("MEMCACHED_BEHAVIOR_KETAMA",1);
  • memc_servers_behavior_get(behavior_type), memc_get_behavior(behavior_type, value)

    Returns the value for a given behavior.

  • memc_list_behaviors()

    Returns a list of the known behaviors.

  • memc_list_hash_types()

    Returns a list of the supported key-hashing algorithms.

  • memc_list_distribution_types()

    Returns a list of the supported distribution types to be used when selecting a server to use when storing a particular key.

  • memc_libmemcached_version()

    Returns the version of the libmemcached library.

  • memc_stats()

    Returns the general statistics information from the server.

15.6.3.10. Using the memcached TCP Text Protocol

Communicating with a memcached server can be achieved through either the TCP or UDP protocols. When using the TCP protocol, you can use a simple text based interface for the exchange of information.

When communicating with memcached, you can connect to the server using the port configured for the server. You can open a connection with the server without requiring authorization or login. As soon as you have connected, you can start to send commands to the server. When you have finished, you can terminate the connection without sending any specific disconnection command. Clients are encouraged to keep their connections open to decrease latency and improve performance.

Data is sent to the memcached server in two forms:

  • Text lines, which are used to send commands to the server, and receive responses from the server.

  • Unstructured data, which is used to receive or send the value information for a given key. Data is returned to the client in exactly the format it was provided.

Both text lines (commands and responses) and unstructured data are always terminated with the string \r\n. Because the data being stored may contain this sequence, the length of the data (returned by the client before the unstructured data is transmitted should be used to determine the end of the data.

Commands to the server are structured according to their operation:

  • Storage commands: set, add, replace, append, prepend, cas

    Storage commands to the server take the form:

    command key [flags] [exptime] length [noreply]

    Or when using compare and swap (cas):

    cas key [flags] [exptime] length [casunique] [noreply]

    Where:

    • command: The command name.

      • set: Store value against key

      • add: Store this value against key if the key does not already exist

      • replace: Store this value against key if the key already exists

      • append: Append the supplied value to the end of the value for the specified key. The flags and exptime arguments should not be used.

      • prepend: Append value currently in the cache to the end of the supplied value for the specified key. The flags and exptime arguments should not be used.

      • cas: Set the specified key to the supplied value, only if the supplied casunique matches. This is effectively the equivalent of change the information if nobody has updated it since I last fetched it.

    • key: The key. All data is stored using a the specific key. The key cannot contain control characters or whitespace, and can be up to 250 characters in size.

    • flags: The flags for the operation (as an integer). Flags in memcached are transparent. The memcached server ignores the contents of the flags. They can be used by the client to indicate any type of information. In memcached 1.2.0 and lower the value is a 16-bit integer value. In memcached 1.2.1 and higher the value is a 32-bit integer.

    • exptime: The expiry time, or zero for no expiry.

    • length: The length of the supplied value block in bytes, excluding the terminating \r\n characters.

    • casunique: A unique 64-bit value of an existing entry. This is used to compare against the existing value. Use the value returned by the gets command when issuing cas updates.

    • noreply: Tells the server not to reply to the command.

    For example, to store the value abcdef into the key xyzkey, you would use:

    set xyzkey 0 0 6\r\nabcdef\r\n

    The return value from the server is one line, specifying the status or error information. For more information, see Table 15.3, “memcached Protocol Responses”.

  • Retrieval commands: get, gets

    Retrieval commands take the form:

    get key1 [key2 .... keyn]
    gets key1 [key2 ... keyn]

    You can supply multiple keys to the commands, with each requested key separated by whitespace.

    The server responds with an information line of the form:

    VALUE key flags bytes [casunique]

    Where:

    • key: The key name.

    • flags: The value of the flag integer supplied to the memcached server when the value was stored.

    • bytes: The size (excluding the terminating \r\n character sequence) of the stored value.

    • casunique: The unique 64-bit integer that identifies the item.

    The information line is immediately followed by the value data block. For example:

    get xyzkey\r\n
    VALUE xyzkey 0 6\r\n
    abcdef\r\n

    If you have requested multiple keys, an information line and data block is returned for each key found. If a requested key does not exist in the cache, no information is returned.

  • Delete commands: delete

    Deletion commands take the form:

    delete key [time] [noreply]

    Where:

    • key: The key name.

    • time: The time in seconds (or a specific Unix time) for which the client wishes the server to refuse add or replace commands on this key. All add, replace, get, and gets commands fail during this period. set operations succeed. After this period, the key is deleted permanently and all commands are accepted.

      If not supplied, the value is assumed to be zero (delete immediately).

    • noreply: Tells the server not to reply to the command.

    Responses to the command are either DELETED to indicate that the key was successfully removed, or NOT_FOUND to indicate that the specified key could not be found.

  • Increment/Decrement: incr, decr

    The increment and decrement commands change the value of a key within the server without performing a separate get/set sequence. The operations assume that the currently stored value is a 64-bit integer. If the stored value is not a 64-bit integer, then the value is assumed to be zero before the increment or decrement operation is applied.

    Increment and decrement commands take the form:

    incr key value [noreply]
    decr key value [noreply]

    Where:

    • key: The key name.

    • value: An integer to be used as the increment or decrement value.

    • noreply: Tells the server not to reply to the command.

    The response is:

    • NOT_FOUND: The specified key could not be located.

    • value: The new value associated with the specified key.

    Values are assumed to be unsigned. For decr operations, the value is never decremented below 0. For incr operations, the value wraps around the 64-bit maximum.

  • Statistics commands: stats

    The stats command provides detailed statistical information about the current status of the memcached instance and the data it is storing.

    Statistics commands take the form:

    STAT [name] [value]

    Where:

    • name: The optional name of the statistics to return. If not specified, the general statistics are returned.

    • value: A specific value to be used when performing certain statistics operations.

    The return value is a list of statistics data, formatted as follows:

    STAT name value

    The statistics are terminated with a single line, END.

    For more information, see Section 15.6.4, “Getting memcached Statistics”.

For reference, a list of the different commands supported and their formats is provided below.

Table 15.2. memcached Command Reference

CommandCommand Formats
setset key flags exptime length, set key flags exptime length noreply
addadd key flags exptime length, add key flags exptime length noreply
replacereplace key flags exptime length, replace key flags exptime length noreply
appendappend key length, append key length noreply
prependprepend key length, prepend key length noreply
cascas key flags exptime length casunique, cas key flags exptime length casunique noreply
getget key1 [key2 ... keyn]
gets
deletedelete key, delete key noreply, delete key expiry, delete key expiry noreply
incrincr key, incr key noreply, incr key value, incr key value noreply
decrdecr key, decr key noreply, decr key value, decr key value noreply
statstat, stat name, stat name value

When sending a command to the server, the response from the server is one of the settings in the following table. All response values from the server are terminated by \r\n:

Table 15.3. memcached Protocol Responses

StringDescription
STOREDValue has successfully been stored.
NOT_STOREDThe value was not stored, but not because of an error. For commands where you are adding a or updating a value if it exists (such as add and replace), or where the item has already been set to be deleted.
EXISTSWhen using a cas command, the item you are trying to store already exists and has been modified since you last checked it.
NOT_FOUNDThe item you are trying to store, update or delete does not exist or has already been deleted.
ERRORYou submitted a nonexistent command name.
CLIENT_ERROR errorstringThere was an error in the input line, the detail is contained in errorstring.
SERVER_ERROR errorstringThere was an error in the server that prevents it from returning the information. In extreme conditions, the server may disconnect the client after this error occurs.
VALUE keys flags lengthThe requested key has been found, and the stored key, flags and data block are returned, of the specified length.
DELETEDThe requested key was deleted from the server.
STAT name valueA line of statistics data.
ENDThe end of the statistics data.

15.6.4. Getting memcached Statistics

The memcached system has a built-in statistics system that collects information about the data being stored into the cache, cache hit ratios, and detailed information on the memory usage and distribution of information through the slab allocation used to store individual items. Statistics are provided at both a basic level that provide the core statistics, and more specific statistics for specific areas of the memcached server.

This information can be useful to ensure that you are getting the correct level of cache and memory usage, and that your slab allocation and configuration properties are set at an optimal level.

The stats interface is available through the standard memcached protocol, so the reports can be accessed by using telnet to connect to the memcached. The supplied memcached-tool includes support for obtaining the Section 15.6.4.2, “memcached Slabs Statistics” and Section 15.6.4.1, “memcached General Statistics” information. For more information, see Section 15.6.4.6, “Using memcached-tool.

Alternatively, most of the language API interfaces provide a function for obtaining the statistics from the server.

For example, to get the basic stats using telnet:

shell> telnet localhost 11211
Trying ::1...
Connected to localhost.
Escape character is '^]'.
stats
STAT pid 23599
STAT uptime 675
STAT time 1211439587
STAT version 1.2.5
STAT pointer_size 32
STAT rusage_user 1.404992
STAT rusage_system 4.694685
STAT curr_items 32
STAT total_items 56361
STAT bytes 2642
STAT curr_connections 53
STAT total_connections 438
STAT connection_structures 55
STAT cmd_get 113482
STAT cmd_set 80519
STAT get_hits 78926
STAT get_misses 34556
STAT evictions 0
STAT bytes_read 6379783
STAT bytes_written 4860179
STAT limit_maxbytes 67108864
STAT threads 1
END

When using Perl and the Cache::Memcached module, the stats() function returns information about all the servers currently configured in the connection object, and total statistics for all the memcached servers as a whole.

For example, the following Perl script obtains the stats and dumps the hash reference that is returned:

use Cache::Memcached;
use Data::Dumper;

my $memc = new Cache::Memcached;
$memc->set_servers(\@ARGV);

print Dumper($memc->stats());

When executed on the same memcached as used in the Telnet example above we get a hash reference with the host by host and total statistics:

$VAR1 = {
    'hosts' => {
           'localhost:11211' => {
                      'misc' => {
                            'bytes' => '2421',
                            'curr_connections' => '3',
                            'connection_structures' => '56',
                            'pointer_size' => '32',
                            'time' => '1211440166',
                            'total_items' => '410956',
                            'cmd_set' => '588167',
                            'bytes_written' => '35715151',
                            'evictions' => '0',
                            'curr_items' => '31',
                            'pid' => '23599',
                            'limit_maxbytes' => '67108864',
                            'uptime' => '1254',
                            'rusage_user' => '9.857805',
                            'cmd_get' => '838451',
                            'rusage_system' => '34.096988',
                            'version' => '1.2.5',
                            'get_hits' => '581511',
                            'bytes_read' => '46665716',
                            'threads' => '1',
                            'total_connections' => '3104',
                            'get_misses' => '256940'
                          },
                      'sizes' => {
                             '128' => '16',
                             '64' => '15'
                           }
                    }
         },
    'self' => {},
    'total' => {
           'cmd_get' => 838451,
           'bytes' => 2421,
           'get_hits' => 581511,
           'connection_structures' => 56,
           'bytes_read' => 46665716,
           'total_items' => 410956,
           'total_connections' => 3104,
           'cmd_set' => 588167,
           'bytes_written' => 35715151,
           'curr_items' => 31,
           'get_misses' => 256940
         }
        };

The statistics are divided up into a number of distinct sections, and then can be requested by adding the type to the stats command. Each statistics output is covered in more detail in the following sections.

15.6.4.1. memcached General Statistics

The output of the general statistics provides an overview of the performance and use of the memcached instance. The statistics returned by the command and their meaning is shown in the following table.

The following terms are used to define the value type for each statistics value:

  • 32u: 32-bit unsigned integer

  • 64u: 64-bit unsigned integer

  • 32u:32u: Two 32-bit unsigned integers separated by a colon

  • String: Character string

StatisticData typeDescriptionVersion
pid32uProcess ID of the memcached instance. 
uptime32uUptime (in seconds) for this memcached instance. 
time32uCurrent time (as epoch). 
versionstringVersion string of this instance. 
pointer_sizestringSize of pointers for this host specified in bits (32 or 64). 
rusage_user32u:32uTotal user time for this instance (seconds:microseconds). 
rusage_system32u:32uTotal system time for this instance (seconds:microseconds). 
curr_items32uCurrent number of items stored by this instance. 
total_items32uTotal number of items stored during the life of this instance. 
bytes64uCurrent number of bytes used by this server to store items. 
curr_connections32uCurrent number of open connections. 
total_connections32uTotal number of connections opened since the server started running. 
connection_structures32uNumber of connection structures allocated by the server. 
cmd_get64uTotal number of retrieval requests (get operations). 
cmd_set64uTotal number of storage requests (set operations). 
get_hits64uNumber of keys that have been requested and found present. 
get_misses64uNumber of items that have been requested and not found. 
delete_hits64uNumber of keys that have been deleted and found present.1.3.x
delete_misses64uNumber of items that have been delete and not found.1.3.x
incr_hits64uNumber of keys that have been incremented and found present.1.3.x
incr_misses64uNumber of items that have been incremented and not found.1.3.x
decr_hits64uNumber of keys that have been decremented and found present.1.3.x
decr_misses64uNumber of items that have been decremented and not found.1.3.x
cas_hits64uNumber of keys that have been compared and swapped and found present.1.3.x
cas_misses64uNumber of items that have been compared and swapped and not found.1.3.x
cas_badvalue64uNumber of keys that have been compared and swapped, but the comparison (original) value did not match the supplied value.1.3.x
evictions64uNumber of valid items removed from cache to free memory for new items. 
bytes_read64uTotal number of bytes read by this server from network. 
bytes_written64uTotal number of bytes sent by this server to network. 
limit_maxbytes32uNumber of bytes this server is permitted to use for storage. 
threads32uNumber of worker threads requested. 
conn_yields64uNumber of yields for connections (related to the -R option).1.4.0

The most useful statistics from those given here are the number of cache hits, misses, and evictions.

A large number of get_misses may just be an indication that the cache is still being populated with information. The number should, over time, decrease in comparison to the number of cache get_hits. If, however, you have a large number of cache misses compared to cache hits after an extended period of execution, it may be an indication that the size of the cache is too small and you either need to increase the total memory size, or increase the number of the memcached instances to improve the hit ratio.

A large number of evictions from the cache, particularly in comparison to the number of items stored is a sign that your cache is too small to hold the amount of information that you regularly want to keep cached. Instead of items being retained in the cache, items are being evicted to make way for new items keeping the turnover of items in the cache high, reducing the efficiency of the cache.

15.6.4.2. memcached Slabs Statistics

To get the slabs statistics, use the stats slabs command, or the API equivalent.

The slab statistics provide you with information about the slabs that have created and allocated for storing information within the cache. You get information both on each individual slab-class and total statistics for the whole slab.

STAT 1:chunk_size 104
STAT 1:chunks_per_page 10082
STAT 1:total_pages 1
STAT 1:total_chunks 10082
STAT 1:used_chunks 10081
STAT 1:free_chunks 1
STAT 1:free_chunks_end 10079
STAT 9:chunk_size 696
STAT 9:chunks_per_page 1506
STAT 9:total_pages 63
STAT 9:total_chunks 94878
STAT 9:used_chunks 94878
STAT 9:free_chunks 0
STAT 9:free_chunks_end 0
STAT active_slabs 2
STAT total_malloced 67083616
END

Individual stats for each slab class are prefixed with the slab ID. A unique ID is given to each allocated slab from the smallest size up to the largest. The prefix number indicates the slab class number in relation to the calculated chunk from the specified growth factor. Hence in the example, 1 is the first chunk size and 9 is the 9th chunk allocated size.

The parameters returned for each chunk size and a description of each parameter are provided in the following table.

StatisticDescriptionVersion
chunk_sizeSpace allocated to each chunk within this slab class. 
chunks_per_pageNumber of chunks within a single page for this slab class. 
total_pagesNumber of pages allocated to this slab class. 
total_chunksNumber of chunks allocated to the slab class. 
used_chunksNumber of chunks allocated to an item.. 
free_chunksNumber of chunks not yet allocated to items. 
free_chunks_endNumber of free chunks at the end of the last allocated page. 
get_hitsNumber of get hits to this chunk1.3.x
cmd_setNumber of set commands on this chunk1.3.x
delete_hitsNumber of delete hits to this chunk1.3.x
incr_hitsNumber of increment hits to this chunk1.3.x
decr_hitsNumber of decrement hits to this chunk1.3.x
cas_hitsNumber of CAS hits to this chunk1.3.x
cas_badvalNumber of CAS hits on this chunk where the existing value did not match1.3.x
mem_requestedThe true amount of memory of memory requested within this chunk1.4.1

The following additional statistics cover the information for the entire server, rather than on a chunk by chunk basis:

StatisticDescriptionVersion
active_slabsTotal number of slab classes allocated. 
total_mallocedTotal amount of memory allocated to slab pages. 

The key values in the slab statistics are the chunk_size, and the corresponding total_chunks and used_chunks parameters. These given an indication of the size usage of the chunks within the system. Remember that one key/value pair is placed into a chunk of a suitable size.

From these stats, you can get an idea of your size and chunk allocation and distribution. If you store many items with a number of largely different sizes, consider adjusting the chunk size growth factor to increase in larger steps to prevent chunk and memory wastage. A good indication of a bad growth factor is a high number of different slab classes, but with relatively few chunks actually in use within each slab. Increasing the growth factor creates fewer slab classes and therefore makes better use of the allocated pages.

15.6.4.3. memcached Item Statistics

To get the items statistics, use the stats items command, or the API equivalent.

The items statistics give information about the individual items allocated within a given slab class.

STAT items:2:number 1
STAT items:2:age 452
STAT items:2:evicted 0
STAT items:2:evicted_nonzero 0
STAT items:2:evicted_time 2
STAT items:2:outofmemory 0
STAT items:2:tailrepairs 0
...
STAT items:27:number 1
STAT items:27:age 452
STAT items:27:evicted 0
STAT items:27:evicted_nonzero 0
STAT items:27:evicted_time 2
STAT items:27:outofmemory 0
STAT items:27:tailrepairs 0

The prefix number against each statistics relates to the corresponding chunk size, as returned by the stats slabs statistics. The result is a display of the number of items stored within each chunk within each slab size, and specific statistics about their age, eviction counts, and out of memory counts. A summary of the statistics is given in the following table.

StatisticDescription 
numberThe number of items currently stored in this slab class. 
ageThe age of the oldest item within the slab class, in seconds. 
evictedThe number of items evicted to make way for new entries. 
evicted_timeThe time of the last evicted entry 
evicted_nonzeroThe time of the last evicted non-zero entry1.4.0
outofmemoryThe number of items for this slab class that have triggered an out of memory error (only value when the -M command line option is in effect). 
tailrepairsNumber of times the entries for a particular ID need repairing 

Item level statistics can be used to determine how many items are stored within a given slab and their freshness and recycle rate. You can use this to help identify whether there are certain slab classes that are triggering a much larger number of evictions that others.

15.6.4.4. memcached Size Statistics

To get size statistics, use the stats sizes command, or the API equivalent.

The size statistics provide information about the sizes and number of items of each size within the cache. The information is returned as two columns, the first column is the size of the item (rounded up to the nearest 32 byte boundary), and the second column is the count of the number of items of that size within the cache:

96 35
128 38
160 807
192 804
224 410
256 222
288 83
320 39
352 53
384 33
416 64
448 51
480 30
512 54
544 39
576 10065
Caution

Running this statistic locks up your cache as each item is read from the cache and its size calculated. On a large cache, this may take some time and prevent any set or get operations until the process completes.

The item size statistics are useful only to determine the sizes of the objects you are storing. Since the actual memory allocation is relevant only in terms of the chunk size and page size, the information is only useful during a careful debugging or diagnostic session.

15.6.4.5. memcached Detail Statistics

For memcached 1.3.x and higher, you can enable and obtain detailed statistics about the get, set, and del operations on theindividual keys stored in the cache, and determine whether the attempts hit (found) a particular key. These operations are only recorded while the detailed stats analysis is turned on.

To enable detailed statistics, you must send the stats detail on command to the memcached server:

$ telnet localhost 11211
Trying 127.0.0.1...
Connected to tiger.
Escape character is '^]'.stats detail on
OK

Individual statistics are recorded for every get, set and del operation on a key, including keys that are not currently stored in the server. For example, if an attempt is made to obtain the value of key abckey and it does not exist, the get operating on the specified key are recorded while detailed statistics are in effect, even if the key is not currently stored. The hits, that is, the number of get or del operations for a key that exists in the server are also counted.

To turn detailed statistics off, send the stats detail off command to the memcached server:

$ telnet localhost 11211
Trying 127.0.0.1...
Connected to tiger.
Escape character is '^]'.stats detail on
OK

To obtain the detailed statistics recorded during the process, send the stats detail dump command to the memcached server:

stats detail dump
PREFIX hykkey get 0 hit 0 set 1 del 0
PREFIX xyzkey get 0 hit 0 set 1 del 0
PREFIX yukkey get 1 hit 0 set 0 del 0
PREFIX abckey get 3 hit 3 set 1 del 0
END

You can use the detailed statistics information to determine whether your memcached clients are using a large number of keys that do not exist in the server by comparing the hit and get or del counts. Because the information is recorded by key, you can also determine whether the failures or operations are clustered around specific keys.

15.6.4.6. Using memcached-tool

The memcached-tool, located within the scripts directory within the memcached source directory. The tool provides convenient access to some reports and statistics from any memcached instance.

The basic format of the command is:

shell> ./memcached-tool hostname:port [command]

The default output produces a list of the slab allocations and usage. For example:

shell> memcached-tool localhost:11211 display
  #  Item_Size  Max_age   Pages   Count   Full?  Evicted Evict_Time OOM
  1      80B        93s       1      20      no        0        0    0
  2     104B        93s       1      16      no        0        0    0
  3     136B      1335s       1      28      no        0        0    0
  4     176B      1335s       1      24      no        0        0    0
  5     224B      1335s       1      32      no        0        0    0
  6     280B      1335s       1      34      no        0        0    0
  7     352B      1335s       1      36      no        0        0    0
  8     440B      1335s       1      46      no        0        0    0
  9     552B      1335s       1      58      no        0        0    0
 10     696B      1335s       1      66      no        0        0    0
 11     872B      1335s       1      89      no        0        0    0
 12     1.1K      1335s       1     112      no        0        0    0
 13     1.3K      1335s       1     145      no        0        0    0
 14     1.7K      1335s       1     123      no        0        0    0
 15     2.1K      1335s       1     198      no        0        0    0
 16     2.6K      1335s       1     199      no        0        0    0
 17     3.3K      1335s       1     229      no        0        0    0
 18     4.1K      1335s       1     248     yes       36        2    0
 19     5.2K      1335s       2     328      no        0        0    0
 20     6.4K      1335s       2     316     yes      387        1    0
 21     8.1K      1335s       3     381     yes      492        1    0
 22    10.1K      1335s       3     303     yes      598        2    0
 23    12.6K      1335s       5     405     yes      605        1    0
 24    15.8K      1335s       6     384     yes      766        2    0
 25    19.7K      1335s       7     357     yes      908      170    0
 26    24.6K      1336s       7     287     yes     1012        1    0
 27    30.8K      1336s       7     231     yes     1193      169    0
 28    38.5K      1336s       4     104     yes     1323      169    0
 29    48.1K      1336s       1      21     yes     1287        1    0
 30    60.2K      1336s       1      17     yes     1093      169    0
 31    75.2K      1337s       1      13     yes      713      168    0
 32    94.0K      1337s       1      10     yes      278      168    0
 33   117.5K      1336s       1       3      no        0        0    0

This output is the same if you specify the command as display:

shell> memcached-tool localhost:11211 display
  #  Item_Size  Max_age   Pages   Count   Full?  Evicted Evict_Time OOM
  1      80B        93s       1      20      no        0        0    0
  2     104B        93s       1      16      no        0        0    0
...

The output shows a summarized version of the output from the slabs statistics. The columns provided in the output are shown below:

  • #: The slab number

  • Item_Size: The size of the slab

  • Max_age: The age of the oldest item in the slab

  • Pages: The number of pages allocated to the slab

  • Count: The number of items in this slab

  • Full?: Whether the slab is fully populated

  • Evicted: The number of objects evicted from this slab

  • Evict_Time: The time (in seconds) since the last eviction

  • OOM: The number of items that have triggered an out of memory error

You can also obtain a dump of the general statistics for the server using the stats command:

shell> memcached-tool localhost:11211 stats  
#localhost:11211   Field       Value
         accepting_conns           1
                   bytes         162
              bytes_read         485
           bytes_written        6820
              cas_badval           0
                cas_hits           0
              cas_misses           0
               cmd_flush           0
                 cmd_get           4
                 cmd_set           2
             conn_yields           0
   connection_structures          11
        curr_connections          10
              curr_items           2
               decr_hits           0
             decr_misses           1
             delete_hits           0
           delete_misses           0
               evictions           0
                get_hits           4
              get_misses           0
               incr_hits           0
             incr_misses           2
          limit_maxbytes    67108864
     listen_disabled_num           0
                     pid       12981
            pointer_size          32
           rusage_system    0.013911
             rusage_user    0.011876
                 threads           4
                    time  1255518565
       total_connections          20
             total_items           2
                  uptime         880
version       1.4.2

15.6.5. memcached FAQ

Questions

  • 16.6.5.1: Can MySQL actually trigger/store the changed data to memcached?

  • 16.6.5.2: Can memcached be run on a Windows environment?

  • 16.6.5.3: What is the maximum size of an object you can store in memcached? Is that configurable?

  • 16.6.5.4: Is it true memcached will be much more effective with db-read-intensive applications than with db-write-intensive applications?

  • 16.6.5.5: Is there any overhead in not using persistent connections? If persistent is always recommended, what are the downsides (for example, locking up)?

  • 16.6.5.6: How is an event such as a crash of one of the memcached servers handled by the memcached client?

  • 16.6.5.7: What is a recommended hardware configuration for a memcached server?

  • 16.6.5.8: Is memcached more effective for video and audio as opposed to textual read/writes?

  • 16.6.5.9: Can memcached work with ASPX?

  • 16.6.5.10: How expensive is it to establish a memcache connection? Should those connections be pooled?

  • 16.6.5.11: How is the data handled when the memcached server is down?

  • 16.6.5.12: How are auto-increment columns in the MySQL database coordinated across multiple instances of memcached?

  • 16.6.5.13: Is compression available?

  • 16.6.5.14: Can we implement different types of memcached as different nodes in the same server, so can there be deterministic and non-deterministic in the same server?

  • 16.6.5.15: What are best practices for testing an implementation, to ensure that it improves performance, and to measure the impact of memcached configuration changes? And would you recommend keeping the configuration very simple to start?

Questions and Answers

16.6.5.1: Can MySQL actually trigger/store the changed data to memcached?

Yes. You can use the MySQL UDFs for memcached and either write statements that directly set the values in the memcached server, or use triggers or stored procedures to do it for you. For more information, see Section 15.6.3.9, “Using the MySQL memcached User-Defined Functions”

16.6.5.2: Can memcached be run on a Windows environment?

No. Currently memcached is available only on the Unix/Linux platform. There is an unofficial port available, see http://www.codeplex.com/memcachedproviders.

16.6.5.3: What is the maximum size of an object you can store in memcached? Is that configurable?

The default maximum object size is 1MB. In memcached 1.4.2 and later, you can change the maximum size of an object using the -I command line option.

For versions before this, to increase this size, you have to re-compile memcached. You can modify the value of the POWER_BLOCK within the slabs.c file within the source.

In memcached 1.4.2 and higher, you can configure the maximum supported object size by using the -I command-line option. For example, to increase the maximum object size to 5MB:

$ memcached -I 5m

If an object is larger than the maximum object size, you must manually split it. memcached is very simple: you give it a key and some data, it tries to cache it in RAM. If you try to store more than the default maximum size, the value is just truncated for speed reasons.

16.6.5.4: Is it true memcached will be much more effective with db-read-intensive applications than with db-write-intensive applications?

Yes. memcached plays no role in database writes, it is a method of caching data already read from the database in RAM.

16.6.5.5: Is there any overhead in not using persistent connections? If persistent is always recommended, what are the downsides (for example, locking up)?

If you don't use persistent connections when communicating with memcached, there will be a small increase in the latency of opening the connection each time. The effect is comparable to use nonpersistent connections with MySQL.

In general, the chance of locking or other issues with persistent connections is minimal, because there is very little locking within memcached. If there is a problem, eventually your request will time out and return no result, so your application will need to load from MySQL again.

16.6.5.6: How is an event such as a crash of one of the memcached servers handled by the memcached client?

There is no automatic handling of this. If your client fails to get a response from a server, code a fallback mechanism to load the data from the MySQL database.

The client APIs all provide the ability to add and remove memcached instances on the fly. If within your application you notice that memcached server is no longer responding, you can remove the server from the list of servers, and keys will automatically be redistributed to another memcached server in the list. If retaining the cache content on all your servers is important, make sure you use an API that supports a consistent hashing algorithm. For more information, see Section 15.6.2.4, “memcached Hashing/Distribution Types”.

16.6.5.7: What is a recommended hardware configuration for a memcached server?

memcached has a very low processing overhead. All that is required is spare physical RAM capacity. A memcached server does not require a dedicated machine. If you have web, application, or database servers that have spare RAM capacity, then use them with memcached.

To build and deploy a dedicated memcached server, use a relatively low-power CPU, lots of RAM, and one or more Gigabit Ethernet interfaces.

16.6.5.8: Is memcached more effective for video and audio as opposed to textual read/writes?

memcached works equally well for all kinds of data. To memcached, any value you store is just a stream of data. Remember, though, that the maximum size of an object you can store in memcached is 1MB, but can be configured to be larger by using the -I option in memcached 1.4.2 and later, or by modifying the source in versions before 1.4.2. If you plan on using memcached with audio and video content, you will probably want to increase the maximum object size. Also remember that memcached is a solution for caching information for reading. It shouldn't be used for writes, except when updating the information in the cache.

16.6.5.9: Can memcached work with ASPX?

There are ports and interfaces for many languages and environments. ASPX relies on an underlying language such as C# or VisualBasic, and if you are using ASP.NET then there is a C# memcached library. For more information, see https://sourceforge.net/projects/memcacheddotnet/.

16.6.5.10: How expensive is it to establish a memcache connection? Should those connections be pooled?

Opening the connection is relatively inexpensive, because there is no security, authentication or other handshake taking place before you can start sending requests and getting results. Most APIs support a persistent connection to a memcached instance to reduce the latency. Connection pooling would depend on the API you are using, but if you are communicating directly over TCP/IP, then connection pooling would provide some small performance benefit.

16.6.5.11: How is the data handled when the memcached server is down?

The behavior is entirely application dependent. Most applications fall back to loading the data from the database (just as if they were updating the memcached information). If you are using multiple memcached servers, you might also remove a downed server from the list to prevent it from affecting performance. Otherwise, the client will still attempt to communicate with the memcached server that corresponds to the key you are trying to load.

16.6.5.12: How are auto-increment columns in the MySQL database coordinated across multiple instances of memcached?

They aren't. There is no relationship between MySQL and memcached unless your application (or, if you are using the MySQL UDFs for memcached, your database definition) creates one.

If you are storing information based on an auto-increment key into multiple instances of memcached, the information is only stored on one of the memcached instances anyway. The client uses the key value to determine which memcached instance to store the information. It doesn't store the same information across all the instances, as that would be a waste of cache memory.

16.6.5.13: Is compression available?

Yes. Most of the client APIs support some sort of compression, and some even allow you to specify the threshold at which a value is deemed appropriate for compression during storage.

16.6.5.14: Can we implement different types of memcached as different nodes in the same server, so can there be deterministic and non-deterministic in the same server?

Yes. You can run multiple instances of memcached on a single server, and in your client configuration you choose the list of servers you want to use.

16.6.5.15: What are best practices for testing an implementation, to ensure that it improves performance, and to measure the impact of memcached configuration changes? And would you recommend keeping the configuration very simple to start?

The best way to test the performance is to start up a memcached instance. First, modify your application so that it stores the data just before the data is about to be used or displayed into memcached. Since the APIs handle the serialization of the data, it should just be a one-line modification to your code. Then, modify the start of the process that would normally load that information from MySQL with the code that requests the data from memcached. If the data cannot be loaded from memcached, default to the MySQL process.

All of the changes required will probably amount to just a few lines of code. To get the best benefit, make sure you cache entire objects (for example, all the components of a web page, blog post, discussion thread, and so on), rather than using memcached as a simple cache of individual rows of MySQL tables.

Keeping the configuration simple at the start, or even over the long term, is easy with memcached. Once you have the basic structure up and running, often the only ongoing change is to add more servers into the list of servers used by your applications. You don't need to manage the memcached servers, and there is no complex configuration; just add more servers to the list and let the client API and the memcached servers make the decisions.

15.7. MySQL Proxy

The MySQL Proxy is an application that communicates over the network using the MySQL network protocol and provides communication between one or more MySQL servers and one or more MySQL clients. Because MySQL Proxy uses the MySQL network protocol, it can be used without modification with any MySQL-compatible client that uses the protocol. This includes the mysql command-line client, any clients that uses the MySQL client libraries, and any connector that supports the MySQL network protocol.

In the most basic configuration, MySQL Proxy simply interposes itself between the server and clients, passing queries from the clients to the MySQL Server and returning the responses from the MySQL Server to the appropriate client. In more advanced configurations, the MySQL Proxy can also monitor and alter the communication between the client and the server. Query interception enables you to add profiling, and interception of the exchanges is scriptable using the Lua scripting language.

By intercepting the queries from the client, the proxy can insert additional queries into the list of queries sent to the server, and remove the additional results when they are returned by the server. Using this functionality you can return the results from the original query to the client while adding informational statements to each query, for example, to monitor their execution time or progress, and separately log the results.

The proxy enables you to perform additional monitoring, filtering, or manipulation of queries without requiring you to make any modifications to the client and without the client even being aware that it is communicating with anything but a genuine MySQL server.

This documentation covers MySQL Proxy 0.8.2. And MySQL Proxy contains third-party code. For license information on third-party code, see Appendix A, Licenses for Third-Party Components.

Warning

MySQL Proxy is currently an Alpha release and should not be used within production environments.

Important

MySQL Proxy is compatible with MySQL 5.0 or later. Testing has not been performed with Version 4.1. Please provide feedback on your experiences using the MySQL Proxy Forum.

For release notes detailing the changes in each release of MySQL Proxy, see MySQL Proxy Release Notes.

15.7.1. MySQL Proxy Supported Platforms

MySQL Proxy is currently available as a precompiled binary for the following platforms:

  • Linux (including Red Hat, Fedora, Debian, SuSE) and derivatives

  • Mac OS X

  • FreeBSD

  • IBM AIX

  • Sun Solaris

  • Microsoft Windows (including Microsoft Windows XP, Microsoft Windows Vista, Microsoft Windows Server 2003, Microsoft Windows Server 2008)

    Note

    You must have the .NET Framework 1.1 or higher installed.

Other Unix/Linux platforms not listed should be compatible by using the source package and building MySQL Proxy locally.

System requirements for the MySQL Proxy application are the same as the main MySQL server. Currently MySQL Proxy is compatible only with MySQL 5.0.1 and later. MySQL Proxy is provided as a standalone, statically linked binary. You need not have MySQL or Lua installed.

15.7.2. Installing MySQL Proxy

You have three choices for installing MySQL Proxy:

15.7.2.1. Installing MySQL Proxy from a Binary Distribution

If you download a binary package, you must extract and copy the package contents to your desired installation directory. The package contains files required by MySQL Proxy, including additional Lua scripts and other components required for execution.

To install, unpack the archive into the desired directory, then modify your PATH environment variable so that you can use the mysql-proxy command directly:

shell> cd /usr/local
shell> tar zxf mysql-proxy-0.8.2-platform.tar.gz
shell> PATH=$PATH:/usr/local/mysql-proxy-0.8.2-platform/sbin

To update the path globally on a system, you might need administrator privileges to modify the appropriate /etc/profile, /etc/bashrc, or other system configuration file.

On Windows, you can update the PATH environment variable using this procedure:

  1. On the Windows desktop, right-click the My Computer icon, and select Properties.

  2. Next select the Advanced tab from the System Properties menu that appears, and click the Environment Variables button.

  3. Under System Variables, select Path, then click the Edit button. The Edit System Variable dialogue should appear.

The Microsoft Visual C++ runtime libraries are a requirement for running MySQL Proxy as of version 0.8.2. Users that do not have these libraries must download and install the Microsoft Visual C++ 2008 Service Pack 1 Redistributable Package MFC Security Update. Use the following link to obtain the package:

http://www.microsoft.com/download/en/details.aspx?id=26368

15.7.2.2. Installing MySQL Proxy from a Source Distribution

You can download a source package and compile the MySQL Proxy yourself. To build from source, you must have the following prerequisite components installed:

  • libevent 1.x or higher (1.3b or later is preferred).

  • lua 5.1.x or higher.

  • glib2 2.6.0 or higher.

  • pkg-config.

  • libtool 1.5 or higher.

  • MySQL 5.0.x or higher developer files.

Note

On some operating systems, you might need to manually build the required components to get the latest version. If you have trouble compiling MySQL Proxy, consider using a binary distributions instead.

After verifying that the prerequisite components are installed, configure and build MySQL Proxy:

shell> tar zxf mysql-proxy-0.8.2.tar.gz
shell> cd mysql-proxy-0.8.2
shell> ./configure
shell> make

To test the build, use the check target to make:

shell> make check

The tests try to connect to localhost using the root user. To provide a password, set the MYSQL_PASSWORD environment variable:

shell> MYSQL_PASSWORD=root_pwd make check

You can install using the install target:

shell> make install

By default, mysql-proxy is installed into /usr/local/sbin/mysql-proxy. The Lua example scripts are installed into /usr/local/share.

15.7.2.3. Installing MySQL Proxy from the Bazaar Repository

The MySQL Proxy source is available through a public Bazaar repository and is the quickest way to get the latest releases and fixes.

A build from the Bazaar repository requires that the following prerequisite components be installed:

  • Bazaar 1.10.0 or later.

  • libtool 1.5 or higher.

  • autoconf 2.56 or higher.

  • automake 1.10 or higher.

  • libevent 1.x or higher (1.3b or later is preferred).

  • lua 5.1.x or higher.

  • glib2 2.4.0 or higher.

  • pkg-config.

  • MySQL 5.0.x or higher developer files.

The mysql-proxy source is hosted on Launchpad. To check out a local copy of the Bazaar repository, use bzr:

shell> bzr branch lp:mysql-proxy

The preceding command downloads a complete version of the Bazaar repository for mysql-proxy. The main source files are located within the trunk subdirectory. The configuration scripts must be generated before you can configure and build mysql-proxy. The autogen.sh script generates the required configuration scripts for you:

shell> sh ./autogen.sh

The autogen.sh script creates the standard configure script, which you then use to configure and build with make:

shell> ./configure
shell> make
shell> make install

To create a standalone source distribution, identical to the source distribution available for download, use this command:

shell> make distcheck

The preceding command creates the file mysql-proxy-0.8.2.tar.gz (with the corresponding current version) within the current directory.

15.7.2.4. Setting Up MySQL Proxy as a Windows Service

The MySQL distribution on Windows includes the mysql-proxy-svc.exe command that enables a MySQL Proxy instance to be managed by the Windows service control manager. You can control the service, including automatically starting and stopping it during boot, reboot and shutdown, without separately running the MySQL Proxy application.

To set up a MySQL Proxy service, use the sc command to create a new service using the MySQL Proxy service command. Specify the MySQL Proxy options on the sc command line, and identify the service with a unique name. For example, to configure a new MySQL Proxy instance that will automatically start when your system boots, redirecting queries to the local MySQL server:

C:\> sc create "Proxy" DisplayName= "MySQL Proxy" start= "auto" »
  binPath= "C:\Program Files\MySQL\mysql-proxy-0.8.2\bin\mysql-proxy-svc.exe »
  --proxy-backend-addresses=127.0.0.1:3306"
Note

The space following the equal sign after each property is required; failure to include it results in an error.

The preceding command creates a new service called Proxy. You can start and stop the service using the net start|stop command with the service name. The service is not automatically started after it is created. To start the service:

C:\> net start proxy
The MySQL Proxy service is starting.
The MySQL Proxy service was started successfully.

You can specify additional command-line options to the sc command. You can also set up multiple MySQL Proxy services on the same machine (providing they are configured to listen on different ports and/or IP addresses.

You can delete a service that you have created:

C:\> sc delete proxy

For more information on creating services using sc, see How to create a Windows service by using Sc.exe.

15.7.3. MySQL Proxy Command Options

To start MySQL Proxy, you can run it directly from the command line:

shell> mysql-proxy

For most situations, you specify at least the host name or address and the port number of the backend MySQL server to which the MySQL Proxy should pass queries.

You can specify options to mysql-proxy either on the command line, or by using a configuration file and the --defaults-file command-line option to specify the file location.

If you use a configuration file, format it as follows:

  • Specify the options within a [mysql-proxy] configuration group. For example:

    [mysql-proxy]
    admin-address = host:port
    
  • Specify all configuration options in the form of a configuration name and the value to set.

  • For options that are a simple toggle on the command line (for example, --proxy-skip-profiling), use true or false. For example, the following is invalid:

    [mysql-proxy]
    proxy-skip-profiling

    But this is valid:

    [mysql-proxy]
    proxy-skip-profiling = true
  • Give the configuration file Unix permissions of 0660 (readable and writable by user and group, no access for others).

Failure to adhere to any of these requirements causes mysql-proxy to generate an error during startup.

The following tables list the supported configuration file and command-line options.

Table 15.4. mysql-proxy Help Options

FormatOption FileDescription
--help Show help options
--help-admin Show admin module options
--help-all Show all help options
--help-proxy Show proxy module options

Table 15.5. mysql-proxy Admin Options

FormatOption FileDescription
--admin-address=host:portadmin-address=host:portThe admin module listening host and port
--admin-lua-script=file_nameadmin-lua-script=file_nameScript to execute by the admin module
--admin-password=passwordadmin-password=passwordAuthentication password for admin module
--admin-username=user_nameadmin-username=user_nameAuthentication user name for admin module
--proxy-address=host:portproxy-address=host:portThe listening proxy server host and port

Table 15.6. mysql-proxy Proxy Options

FormatOption FileDescriptionRemoved
--no-proxyno-proxyDo not start the proxy module 
--proxy-backend-addresses=host:portproxy-backend-addresses=host:portThe MySQL server host and port 
--proxy-fix-bug-25371proxy-fix-bug-25371Enable the fix for Bug #25371 for older libmysql versions0.8.1
--proxy-lua-script=file_nameproxy-lua-script=file_nameFilename for Lua script for proxy operations 
--proxy-pool-no-change-userproxy-pool-no-change-userDo not use the protocol CHANGE_USER command to reset the connection when coming from the connection pool 
--proxy-read-only-backend-addresses=host:portproxy-read-only-backend-addresses=host:portThe MySQL server host and port (read only) 
--proxy-skip-profilingproxy-skip-profilingDisable query profiling 

Table 15.7. mysql-proxy Applications Options

FormatOption FileDescription
--basedir=dir_namebasedir=dir_nameThe base directory prefix for paths in the configuration
--daemondaemonStart in daemon mode
--defaults-file=file_name The configuration file to use
--event-threads=countevent-threads=countThe number of event-handling threads
--keepalivekeepaliveTry to restart the proxy if a crash occurs
--log-backtrace-on-crashlog-backtrace-on-crashTry to invoke the debugger and generate a backtrace on crash
--log-file=file_namelog-file=file_nameThe file where error messages are logged
--log-level=levellog-level=levelThe logging level
--log-use-sysloglog-use-syslogLog errors to syslog
--lua-cpath=dir_namelua-cpath=dir_nameSet the LUA_CPATH
--lua-path=dir_namelua-path=dir_nameSet the LUA_PATH
--max-open-files=countmax-open-files=countThe maximum number of open files to support
--pid-file=file_namepid-file=file_nameFile in which to store the process ID
--plugin-dir=dir_nameplugin-dir=dir_nameDirectory containing plugin files
--plugins=plugin,...plugins=plugin,...List of plugins to load
--user=user_nameuser=user_nameThe user to use when running mysql-proxy
--version Show version information

Except as noted in the following details, all of the options can be used within the configuration file by supplying the option and the corresponding value. For example:

[mysql-proxy]
log-file = /var/log/mysql-proxy.log
log-level = message
  • --help, -h

    Command-Line Format--help
    -h

    Show available help options.

  • --help-admin

    Command-Line Format--help-admin

    Show options for the admin module.

  • --help-all

    Command-Line Format--help-all

    Show all help options.

  • --help-proxy

    Command-Line Format--help-proxy

    Show options for the proxy module.

  • --admin-address=host:port

    Command-Line Format--admin-address=host:port
    Option-File Formatadmin-address=host:port
     Permitted Values
    Typestring
    Default:4041

    The host name (or IP address) and port for the administration port. The default is localhost:4041.

  • --admin-lua-script=file_name

    Command-Line Format--admin-lua-script=file_name
    Option-File Formatadmin-lua-script=file_name
     Permitted Values
    Typefile name
    Default

    The script to use for the proxy administration module.

  • --admin-password=password

    Command-Line Format--admin-password=password
    Option-File Formatadmin-password=password
     Permitted Values
    Typestring
    Default

    The password to use to authenticate users wanting to connect to the MySQL Proxy administration module. This module uses the MySQL protocol to request a user name and password for connections.

  • --admin-username=user_name

    Command-Line Format--admin-username=user_name
    Option-File Formatadmin-username=user_name
     Permitted Values
    Typestring
    Defaultroot

    The user name to use to authenticate users wanting to connect to the MySQL Proxy administration module. This module uses the MySQL protocol to request a user name and password for connections. The default user name is root.

  • --basedir=dir_name

    Command-Line Format--basedir=dir_name
    Option-File Formatbasedir=dir_name
     Permitted Values
    Typedirectory name

    The base directory to use as a prefix for all other file name configuration options. The base name should be an absolute (not relative) directory. If you specify a relative directory, mysql-proxy generates an error during startup.

  • --daemon

    Command-Line Format--daemon
    Option-File Formatdaemon

    Starts the proxy in daemon mode.

  • --defaults-file=file_name

    Command-Line Format--defaults-file=file_name

    The file to read for configuration options. If not specified, MySQL Proxy takes options only from the command line.

  • --event-threads=count

    Command-Line Format--event-threads=count
    Option-File Formatevent-threads=count
     Permitted Values
    Typenumeric
    Default1

    The number of event threads to reserve to handle incoming requests.

  • --keepalive

    Command-Line Format--keepalive
    Option-File Formatkeepalive

    Create a process surrounding the main mysql-proxy process that attempts to restart the main mysql-proxy process in the event of a crash or other failure.

    Note

    The --keepalive option is not available on Microsoft Windows. When running as a service, mysql-proxy automatically restarts.

  • --log-backtrace-on-crash

    Command-Line Format--log-backtrace-on-crash
    Option-File Formatlog-backtrace-on-crash

    Log a backtrace to the error log and try to initialize the debugger in the event of a failure.

  • --log-file=file_name

    Command-Line Format--log-file=file_name
    Option-File Formatlog-file=file_name
     Permitted Values
    Typefile name

    The file to use to record log information. If this option is not given, mysql-proxy logs to the standard error output.

  • --log-level=level

    Command-Line Format--log-level=level
    Option-File Formatlog-level=level
     Permitted Values
    Typeenumeration
    Valid Values

    error

    warning

    info

    message

    debug

    The log level to use when outputting error messages. Messages with that level (or lower) are output. For example, message level also outputs message with info, warning, and error levels.

  • --log-use-syslog

    Command-Line Format--log-use-syslog
    Option-File Formatlog-use-syslog

    Log errors to the syslog (Unix/Linux only).

  • --lua-cpath=dir_name

    Command-Line Format--lua-cpath=dir_name
    Option-File Formatlua-cpath=dir_name
     Permitted Values
    Typedirectory name

    The LUA_CPATH to use when loading compiled modules or libraries for Lua scripts.

  • --lua-path=dir_name

    Command-Line Format--lua-path=dir_name
    Option-File Formatlua-path=dir_name
     Permitted Values
    Typedirectory name

    The LUA_CPATH to use when loading modules for Lua.

  • --max-open-files=count

    Command-Line Format--max-open-files=count
    Option-File Formatmax-open-files=count
     Permitted Values
    Typenumeric

    The maximum number of open files and sockets supported by the mysql-proxy process. Certain scripts might require a higher value.

  • --no-proxy

    Command-Line Format--no-proxy
    Option-File Formatno-proxy

    Disable the proxy module.

  • --plugin-dir=dir_name

    Command-Line Format--plugin-dir=dir_name
    Option-File Formatplugin-dir=dir_name
     Permitted Values
    Typedirectory name

    The directory to use when loading plugins for mysql-proxy.

  • --plugins=plugin

    Command-Line Format--plugins=plugin,...
    Option-File Formatplugins=plugin,...
     Permitted Values
    Typestring

    Loads a plugin.

    When using this option on the command line, you can specify the option multiple times to specify multiple plugins. For example:

    shell> mysql-proxy --plugins=proxy --plugins=admin
    

    When using the option within the configuration file, you should separate multiple plugins by commas. The equivalent of the preceding example would be:

    ...
    plugins=proxy,admin
  • --proxy-address=host:port, -P host:port

    Command-Line Format--proxy-address=host:port
    -P host:port
    Option-File Formatproxy-address=host:port
     Permitted Values
    Typestring
    Default:4040

    The listening host name (or IP address) and port of the proxy server. The default is :4040 (all IPs on port 4040).

  • --proxy-read-only-backend-addresses=host:port, -r host:port

    Command-Line Format--proxy-read-only-backend-addresses=host:port
    -r host:port
    Option-File Formatproxy-read-only-backend-addresses=host:port
     Permitted Values
    Typestring

    The listening host name (or IP address) and port of the proxy server for read-only connections. The default is for this information not to be set.

    Note

    Setting this value only configures the servers within the corresponding internal structure (see proxy.global.backends). You can determine the backend type by checking the type field for each connection.

    You should therefore only use this option in combination with a script designed to make use of the different backend types.

    When using this option on the command line, you can specify the option and the server multiple times to specify multiple backends. For example:

    shell> mysql-proxy --proxy-read-only-backend-addresses=192.168.0.1:3306 --proxy-read-only-backend-addresses=192.168.0.2:3306
    

    When using the option within the configuration file, you should separate multiple servers by commas. The equivalent of the preceding example would be:

    ...
    proxy-read-only-backend-addresses = 192.168.0.1:3306,192.168.0.2:3306
  • --proxy-backend-addresses=host:port, -b host:port

    Command-Line Format--proxy-backend-addresses=host:port
    -b host:port
    Option-File Formatproxy-backend-addresses=host:port
     Permitted Values
    Typestring
    Default127.0.0.1:3306

    The host name (or IP address) and port of the MySQL server to connect to. You can specify multiple backend servers by supplying multiple options. Clients are connected to each backend server in round-robin fashion. For example, if you specify two servers A and B, the first client connection will go to server A; the second client connection to server B and the third client connection to server A.

    When using this option on the command line, you can specify the option and the server multiple times to specify multiple backends. For example:

    shell> mysql-proxy --proxy-backend-addresses 192.168.0.1:3306 --proxy-backend-addresses 192.168.0.2:3306
    

    When using the option within the configuration file, you should separate multiple servers by commas. The equivalent of the preceding example would be:

    ...
    proxy-backend-addresses = 192.168.0.1:3306,192.168.0.2:3306
  • --proxy-pool-no-change-user

    Command-Line Format--proxy-pool-no-change-user
    Option-File Formatproxy-pool-no-change-user

    Disable use of the MySQL protocol CHANGE_USER command when reusing a connection from the pool of connections specified by the proxy-backend-addresses list.

  • --proxy-skip-profiling

    Command-Line Format--proxy-skip-profiling
    Option-File Formatproxy-skip-profiling

    Disable query profiling (statistics time tracking). The default is for tracking to be enabled.

  • --proxy-fix-bug-25371

    Version Removed0.8.1
    Command-Line Format--proxy-fix-bug-25371
    Option-File Formatproxy-fix-bug-25371

    Enable a workaround for an issue when connecting to a MySQL server later than 5.1.12 when using a MySQL client library of any earlier version.

    This option was removed in mysql-proxy 0.8.1. Now, mysql-proxy returns an error message at the protocol level if it sees a COM_CHANGE_USER being sent to a server that has a version from 5.1.14 to 5.1.17.

  • --proxy-lua-script=file_name, -s file_name

    Command-Line Format--proxy-lua-script=file_name
    -s file_name
    Option-File Formatproxy-lua-script=file_name
     Permitted Values
    Typefile name

    The Lua script file to be loaded. Note that the script file is not physically loaded and parsed until a connection is made. Also note that the specified Lua script is reloaded for each connection; if the content of the Lua script changes while mysql-proxy is running, the updated content is automatically used when a new connection is made.

  • --pid-file=file_name

    Command-Line Format--pid-file=file_name
    Option-File Formatpid-file=file_name
     Permitted Values
    Typefile name

    The name of the file in which to store the process ID.

  • --user=user_name

    Command-Line Format--user=user_name
    Option-File Formatuser=user_name
     Permitted Values
    Typestring

    Run mysql-proxy as the specified user.

  • --version, -V

    Command-Line Format--version
    -V

    Show the version number.

The most common usage is as a simple proxy service (that is, without additional scripting). For basic proxy operation, you must specify at least one proxy-backend-addresses option to specify the MySQL server to connect to by default:

shell> mysql-proxy --proxy-backend-addresses=MySQL.example.com:3306

The default proxy port is 4040, so you can connect to your MySQL server through the proxy by specifying the host name and port details:

shell> mysql --host=localhost --port=4040

If your server requires authentication information, this will be passed through natively without alteration by mysql-proxy, so you must also specify the required authentication information:

shell> mysql --host=localhost --port=4040 \
   --user=user_name --password=password

You can also connect to a read-only port (which filters out UPDATE and INSERT queries) by connecting to the read-only port. By default the host name is the default, and the port is 4042, but you can alter the host/port information by using the --proxy-read-only-backend-addresses command-line option.

For more detailed information on how to use these command-line options, and mysql-proxy in general in combination with Lua scripts, see Section 15.7.5, “Using MySQL Proxy”.

15.7.4. MySQL Proxy Scripting

You can control how MySQL Proxy manipulates and works with the queries and results that are passed on to the MySQL server through the use of the embedded Lua scripting language. You can find out more about the Lua programming language from the Lua Web site.

The following diagram shows an overview of the classes exposed by MySQL Proxy.

MySQL Proxy architecture

The primary interaction between MySQL Proxy and the server is provided by defining one or more functions through an Lua script. A number of functions are supported, according to different events and operations in the communication sequence between a client and one or more backend MySQL servers:

  • connect_server(): This function is called each time a connection is made to MySQL Proxy from a client. You can use this function during load-balancing to intercept the original connection and decide which server the client should ultimately be attached to. If you do not define a special solution, a simple round-robin style distribution is used by default.

  • read_handshake(): This function is called when the initial handshake information is returned by the server. You can capture the handshake information returned and provide additional checks before the authorization exchange takes place.

  • read_auth(): This function is called when the authorization packet (user name, password, default database) are submitted by the client to the server for authentication.

  • read_auth_result(): This function is called when the server returns an authorization packet to the client indicating whether the authorization succeeded.

  • read_query(): This function is called each time a query is sent by the client to the server. You can use this to edit and manipulate the original query, including adding new queries before and after the original statement. You can also use this function to return information directly to the client, bypassing the server, which can be useful to filter unwanted queries or queries that exceed known limits.

  • read_query_result(): This function is called each time a result is returned from the server, providing you have manually injected queries into the query queue. If you have not explicitly injected queries within the read_query() function, this function is not triggered. You can use this to edit the result set, or to remove or filter the result sets generated from additional queries you injected into the queue when using read_query().

The following table lists MySQL proxy and server communication functions, the supplied information, and the direction of information flow when the function is triggered.

FunctionSupplied InformationDirection
connect_server()NoneClient to Server
read_handshake()NoneServer to Client
read_auth()NoneClient to Server
read_auth_result()NoneServer to Client
read_query()QueryClient to Server
read_query_result()Query resultServer to Client

By default, all functions return a result that indicates whether the data should be passed on to the client or server (depending on the direction of the information being transferred). This return value can be overridden by explicitly returning a constant indicating that a particular response should be sent. For example, it is possible to construct result set information by hand within read_query() and to return the result set directly to the client without ever sending the original query to the server.

In addition to these functions, a number of built-in structures provide control over how MySQL Proxy forwards queries and returns the results by providing a simplified interface to elements such as the list of queries and the groups of result sets that are returned.

15.7.4.1. Proxy Scripting Sequence During Query Injection

The following figure gives an example of how the proxy might be used when injecting queries into the query queue. Because the proxy sits between the client and MySQL server, what the proxy sends to the server, and the information that the proxy ultimately returns to the client, need not match or correlate. Once the client has connected to the proxy, the sequence shown in the following diagram occurs for each individual query sent by the client.

MySQL Proxy architecture
  1. When the client submits one query to the proxy, the read_query() function within the proxy is triggered. The function adds the query to the query queue.

  2. Once manipulation by read_query() has completed, the queries are submitted, sequentially, to the MySQL server.

  3. The MySQL server returns the results from each query, one result set for each query submitted. The read_query_result() function is triggered for each result set, and each invocation can decide which result set to return to the client

For example, you can queue additional queries into the global query queue to be processed by the server. This can be used to add statistical information by adding queries before and after the original query, changing the original query:

SELECT * FROM City;

Into a sequence of queries:

SELECT NOW();
SELECT * FROM City;
SELECT NOW();

You can also modify the original statement; for example, to add EXPLAIN to each statement executed to get information on how the statement was processed, again altering our original SQL statement into a number of statements:

SELECT * FROM City;
EXPLAIN SELECT * FROM City;

In both of these examples, the client would have received more result sets than expected. Regardless of how you manipulate the incoming query and the returned result, the number of queries returned by the proxy must match the number of original queries sent by the client.

You could adjust the client to handle the multiple result sets sent by the proxy, but in most cases you will want the existence of the proxy to remain transparent. To ensure that the number of queries and result sets match, you can use the MySQL Proxy read_query_result() to extract the additional result set information and return only the result set the client originally requested back to the client. You can achieve this by giving each query that you add to the query queue a unique ID, then filter out queries that do not match the original query ID when processing them with read_query_result().

15.7.4.2. Internal Structures

There are a number of internal structures within the scripting element of MySQL Proxy. The primary structure is proxy and this provides an interface to the many common structures used throughout the script, such as connection lists and configured backend servers. Other structures, such as the incoming packet from the client and result sets are only available within the context of one of the scriptable functions.

The following table describes common attributes of the MySQL proxy scripting element.

AttributeDescription
connectionA structure containing the active client connections. For a list of attributes, see proxy.connection.
serversA structure containing the list of configured backend servers. For a list of attributes, see proxy.global.backends.
queriesA structure containing the queue of queries that will be sent to the server during a single client query. For a list of attributes, see proxy.queries.
PROXY_VERSIONThe version number of MySQL Proxy, encoded in hex. You can use this to check that the version number supports a particular option from within the Lua script. Note that the value is encoded as a hex value, so to check the version is at least 0.5.1 you compare against 0x00501.

proxy.connection

The proxy.connection object is read only, and provides information about the current connection, and is split into a client and server tables. This enables you to examine information about both the incoming client connections to the proxy (client), and to the backend servers (server).

The following table describes the client and server attributes of the proxy.connection object.

AttributeDescription
client.default_dbDefault database requested by the client
client.usernameUser name used to authenticate
client.scrambled_passwordThe scrambled version of the password used to authenticate
client.dst.nameThe combined address:port of the Proxy port used by this client (should match the --proxy-address configuration parameter)
client.dst.addressThe IP address of the of the Proxy port used by this client
client.dst.portThe port number of the of the Proxy port used by this client
client.src.nameThe combined address:port of the client (originating) TCP/IP endpoint
client.src.addressThe IP address of the client (originating) TCP/IP port
client.src.portThe port of the client (originating) TCP/IP endpoint
server.scramble_bufferThe scramble buffer used to scramble the password
server.mysqld_versionThe MySQL version number of the server
server.thread_idThe ID of the thread handling the connection to the current server
server.dst.nameThe combined address:port for the backend server for the current connection (i.e. the connection to the MySQL server)
server.dst.addressThe address for the backend server
server.dst.portThe port for the backend server
server.src.nameThe combined address:port for the TCP/IP endpoint used by the Proxy to connect to the backend server
server.src.addressThe address of the endpoint for the proxy-side connection to the MySQL server
server.src.portThe port of the endpoint for the proxy-side connection to the MySQL server

proxy.global.backends

The proxy.global.backends table is partially writable and contains an array of all the configured backend servers and the server metadata (IP address, status, etc.). You can determine the array index of the current connection using proxy.connection["backend_ndx"] which is the index into this table of the backend server being used by the active connection.

The attributes for each entry within the proxy.global.backends table are shown in the following table.

AttributeDescription
dst.nameThe combined address:port of the backend server.
dst.addressThe IP address of the backend server.
dst.portThe port of the backend server.
connected_clientsThe number of clients currently connected.
stateThe status of the backend server. See Backend State/Type Constants.
typeThe type of the backend server. You can use this to identify whether the backed was configured as a standard read/write backend, or a read-only backend. You can compare this value to the proxy.BACKEND_TYPE_RW and proxy.BACKEND_TYPE_RO.

proxy.queries

The proxy.queries object is a queue representing the list of queries to be sent to the server. The queue is not populated automatically, but if you do not explicitly populate the queue, queries are passed on to the backend server verbatim. Also, if you do not populate the query queue by hand, the read_query_result() function is not triggered.

The following functions are supported for populating the proxy.queries object.

FunctionDescription
append(id,packet,[options])Appends a query to the end of the query queue. The id is an integer identifier that you can use to recognize the query results when they are returned by the server. The packet should be a properly formatted query packet. The optional options should be a table containing the options specific to this packet.
prepend(id,packet)Prepends a query to the query queue. The id is an identifier that you can use to recognize the query results when they are returned by the server. The packet should be a properly formatted query packet.
reset()Empties the query queue.
len()Returns the number of query packets in the queue.

For example, you could append a query packet to the proxy.queries queue by using the append():

proxy.queries:append(1,packet)

The optional third argument to append() should contain the options for the packet. To have access to the result set through the read_query_result() function, set the resultset_is_needed flag to true:

proxy.queries:append( 1, packet, { resultset_is_needed = true } )

If that flag is false (the default), proxy will:

  • Send the result set to the client as soon as it is received

  • Reduce memory usage (because the result set is not stored internally for processing)

  • Reduce latency of returning results to the client

  • Pass data from server to client unaltered

The default mode is therefore quicker and useful if you only want to monitor the queries sent, and the basic statistics.

To perform any kind of manipulation on the returned data, you must set the flag to true, which will:

  • Store the result set so that it can be processed.

  • Enable modification of the result set before it is returned to the client.

  • Enable you to discard the result set instead of returning it to the client.

proxy.response

The proxy.response structure is used when you want to return your own MySQL response, instead of forwarding a packet that you have received a backend server. The structure holds the response type information, an optional error message, and the result set (rows/columns) to return.

The following table describes the attributes of the proxy.response structure.

AttributeDescription
typeThe type of the response. The type must be either MYSQLD_PACKET_OK or MYSQLD_PACKET_ERR. If the MYSQLD_PACKET_ERR, you should set the value of the mysql.response.errmsg with a suitable error message.
errmsgA string containing the error message that will be returned to the client.
resultsetA structure containing the result set information (columns and rows), identical to what would be returned when returning a results from a SELECT query.

When using proxy.response you either set proxy.response.type to proxy.MYSQLD_PACKET_OK and then build resultset to contain the results to return, or set proxy.response.type to proxy.MYSQLD_PACKET_ERR and set the proxy.response.errmsg to a string with the error message. To send the completed result set or error message, you should return the proxy.PROXY_SEND_RESULT to trigger the return of the packet information.

An example of this can be seen in the tutorial-resultset.lua script within the MySQL Proxy package:

if string.lower(command) == "show" and string.lower(option) == "querycounter" then
        ---
        -- proxy.PROXY_SEND_RESULT requires
        --
        -- proxy.response.type to be either
        -- * proxy.MYSQLD_PACKET_OK or
        -- * proxy.MYSQLD_PACKET_ERR
        --
        -- for proxy.MYSQLD_PACKET_OK you need a resultset
        -- * fields
        -- * rows
        --
        -- for proxy.MYSQLD_PACKET_ERR
        -- * errmsg
        proxy.response.type = proxy.MYSQLD_PACKET_OK
        proxy.response.resultset = {
                fields = {
                        { type = proxy.MYSQL_TYPE_LONG, name = "global_query_counter", },
                        { type = proxy.MYSQL_TYPE_LONG, name = "query_counter", },
                },
                rows = {
                        { proxy.global.query_counter, query_counter }
                }
        }

        -- we have our result, send it back
        return proxy.PROXY_SEND_RESULT
elseif string.lower(command) == "show" and string.lower(option) == "myerror" then
        proxy.response.type = proxy.MYSQLD_PACKET_ERR
        proxy.response.errmsg = "my first error"

        return proxy.PROXY_SEND_RESULT

proxy.response.resultset

The proxy.response.resultset structure should be populated with the rows and columns of data to return. The structure contains the information about the entire result set, with the individual elements of the data shown in the following table.

The following table describes the attributes of the proxy.response.resultset structure.

AttributeDescription
fieldsThe definition of the columns being returned. This should be a dictionary structure with the type specifying the MySQL data type, and the name specifying the column name. Columns should be listed in the order of the column data that will be returned.
flagsA number of flags related to the result set. Valid flags include auto_commit (whether an automatic commit was triggered), no_good_index_used (the query executed without using an appropriate index), and no_index_used (the query executed without using any index).
rowsThe actual row data. The information should be returned as an array of arrays. Each inner array should contain the column data, with the outer array making up the entire result set.
warning_countThe number of warnings for this result set.
affected_rowsThe number of rows affected by the original statement.
insert_idThe last insert ID for an auto-incremented column in a table.
query_statusThe status of the query operation. You can use the MYSQLD_PACKET_OK or MYSQLD_PACKET_ERR constants to populate this parameter.

For an example showing how to use this structure, see proxy.response.

Proxy Return State Constants

The following constants are used internally by the proxy to specify the response to send to the client or server. All constants are exposed as values within the main proxy table.

ConstantDescription
PROXY_SEND_QUERYCauses the proxy to send the current contents of the queries queue to the server.
PROXY_SEND_RESULTCauses the proxy to send a result set back to the client.
PROXY_IGNORE_RESULTCauses the proxy to drop the result set (nothing is returned to the client).

As constants, these entities are available without qualification in the Lua scripts. For example, at the end of the read_query_result() you might return PROXY_IGNORE_RESULT:

return proxy.PROXY_IGNORE_RESULT

Packet State Constants

The following states describe the status of a network packet. These items are entries within the main proxy table.

ConstantDescription
MYSQLD_PACKET_OKThe packet is OK
MYSQLD_PACKET_ERRThe packet contains error information
MYSQLD_PACKET_RAWThe packet contains raw data

Backend State/Type Constants

The following constants are used either to define the status or type of the backend MySQL server to which the proxy is connected. These items are entries within the main proxy table.

ConstantDescription
BACKEND_STATE_UNKNOWNThe current status is unknown
BACKEND_STATE_UPThe backend is known to be up (available)
BACKEND_STATE_DOWNThe backend is known to be down (unavailable)
BACKEND_TYPE_UNKNOWNBackend type is unknown
BACKEND_TYPE_RWBackend is available for read/write
BACKEND_TYPE_ROBackend is available only for read-only use

Server Command Constants

The values described in the table below are used in the packets exchanged between the client and server to identify the information in the rest of the packet. These items are entries within the main proxy table. The packet type is defined as the first character in the sent packet. For example, when intercepting packets from the client to edit or monitor a query, you would check that the first byte of the packet was of type proxy.COM_QUERY.

ConstantDescription
COM_SLEEPSleep
COM_QUITQuit
COM_INIT_DBInitialize database
COM_QUERYQuery
COM_FIELD_LISTField List
COM_CREATE_DBCreate database
COM_DROP_DBDrop database
COM_REFRESHRefresh
COM_SHUTDOWNShutdown
COM_STATISTICSStatistics
COM_PROCESS_INFOProcess List
COM_CONNECTConnect
COM_PROCESS_KILLKill
COM_DEBUGDebug
COM_PINGPing
COM_TIMETime
COM_DELAYED_INSERTDelayed insert
COM_CHANGE_USERChange user
COM_BINLOG_DUMPBinlog dump
COM_TABLE_DUMPTable dump
COM_CONNECT_OUTConnect out
COM_REGISTER_SLAVERegister slave
COM_STMT_PREPAREPrepare server-side statement
COM_STMT_EXECUTEExecute server-side statement
COM_STMT_SEND_LONG_DATALong data
COM_STMT_CLOSEClose server-side statement
COM_STMT_RESETReset statement
COM_SET_OPTIONSet option
COM_STMT_FETCHFetch statement
COM_DAEMONDaemon (MySQL 5.1 only)
COM_ERRORError

MySQL Type Constants

These constants are used to identify the field types in the query result data returned to clients from the result of a query. These items are entries within the main proxy table.

ConstantField Type
MYSQL_TYPE_DECIMALDecimal
MYSQL_TYPE_NEWDECIMALDecimal (MySQL 5.0 or later)
MYSQL_TYPE_TINYTiny
MYSQL_TYPE_SHORTShort
MYSQL_TYPE_LONGLong
MYSQL_TYPE_FLOATFloat
MYSQL_TYPE_DOUBLEDouble
MYSQL_TYPE_NULLNull
MYSQL_TYPE_TIMESTAMPTimestamp
MYSQL_TYPE_LONGLONGLong long
MYSQL_TYPE_INT24Integer
MYSQL_TYPE_DATEDate
MYSQL_TYPE_TIMETime
MYSQL_TYPE_DATETIMEDatetime
MYSQL_TYPE_YEARYear
MYSQL_TYPE_NEWDATEDate (MySQL 5.0 or later)
MYSQL_TYPE_ENUMEnumeration
MYSQL_TYPE_SETSet
MYSQL_TYPE_TINY_BLOBTiny Blob
MYSQL_TYPE_MEDIUM_BLOBMedium Blob
MYSQL_TYPE_LONG_BLOBLong Blob
MYSQL_TYPE_BLOBBlob
MYSQL_TYPE_VAR_STRINGVarstring
MYSQL_TYPE_STRINGString
MYSQL_TYPE_TINYTiny (compatible with MYSQL_TYPE_CHAR)
MYSQL_TYPE_ENUMEnumeration (compatible with MYSQL_TYPE_INTERVAL)
MYSQL_TYPE_GEOMETRYGeometry
MYSQL_TYPE_BITBit

15.7.4.3. Capturing a Connection with connect_server()

When the proxy accepts a connection from a MySQL client, the connect_server() function is called.

There are no arguments to the function, but you can use and if necessary manipulate the information in the proxy.connection table, which is unique to each client session.

For example, if you have multiple backend servers, you can specify which server that connection should use by setting the value of proxy.connection.backend_ndx to a valid server number. The following code chooses between two servers based on whether the current time in minutes is odd or even:

function connect_server()
        print("--> a client really wants to talk to a server")
        if (tonumber(os.date("%M")) % 2 == 0) then
                proxy.connection.backend_ndx = 2
                print("Choosing backend 2")
        else
                proxy.connection.backend_ndx = 1
                print("Choosing backend 1")
        end
        print("Using " .. proxy.global.backends[proxy.connection.backend_ndx].dst.name)
end

This example also displays the IP address/port combination by accessing the information from the internal proxy.global.backends table.

15.7.4.4. Examining the Handshake with read_handshake()

Handshake information is sent by the server to the client after the initial connection (through connect_server()) has been made. The handshake information contains details about the MySQL version, the ID of the thread that will handle the connection information, and the IP address of the client and server. This information is exposed through the proxy.connection structure.

  • proxy.connection.server.mysqld_version: The version of the MySQL server.

  • proxy.connection.server.thread_id: The thread ID.

  • proxy.connection.server.scramble_buffer: The password scramble buffer.

  • proxy.connection.server.dst.name: The IP address of the server.

  • proxy.connection.client.src.name: The IP address of the client.

For example, you can print out the handshake data and refuse clients by IP address with the following function:

function read_handshake()
        print("<-- let's send him some information about us")
        print("    mysqld-version: " .. proxy.connection.server.mysqld_version)
        print("    thread-id     : " .. proxy.connection.server.thread_id)
        print("    scramble-buf  : " .. string.format("%q",proxy.connection.server.scramble_buffer))
        print("    server-addr   : " .. proxy.connection.server.dst.name)
        print("    client-addr   : " .. proxy.connection.client.dst.name)

        if not proxy.connection.client.src.name:match("^127.0.0.1:") then
                proxy.response.type = proxy.MYSQLD_PACKET_ERR
                proxy.response.errmsg = "only local connects are allowed"

                print("we don't like this client");

                return proxy.PROXY_SEND_RESULT
        end
end

Note that you must return an error packet to the client by using proxy.PROXY_SEND_RESULT.

15.7.4.5. Examining the Authentication Credentials with read_auth()

The read_auth() function is triggered when an authentication handshake is initiated by the client. In the execution sequence, read_auth() occurs immediately after read_handshake(), so the server selection has already been made, but the connection and authorization information has not yet been provided to the backend server.

You can obtain the authentication information by examining the proxy.connection.client structure. For more information, see proxy.connection.

For example, you can print the user name and password supplied during authorization using:

function read_auth()
        print("    username      : " .. proxy.connection.client.username)
        print("    password      : " .. string.format("%q", proxy.connection.client.scrambled_password))
end

You can interrupt the authentication process within this function and return an error packet back to the client by constructing a new packet and returning proxy.PROXY_SEND_RESULT:

proxy.response.type = proxy.MYSQLD_PACKET_ERR
proxy.response.errmsg = "Logins are not allowed"
return proxy.PROXY_SEND_RESULT

15.7.4.6. Accessing Authentication Information with read_auth_result()

The return packet from the server during authentication is captured by read_auth_result(). The only argument to this function is the authentication packet returned by the server. As the packet is a raw MySQL network protocol packet, you must access the first byte to identify the packet type and contents. The MYSQLD_PACKET_ERR and MYSQLD_PACKET_OK constants can be used to identify whether the authentication was successful:

function read_auth_result(auth)
        local state = auth.packet:byte()

        if state == proxy.MYSQLD_PACKET_OK then
                print("<-- auth ok");
        elseif state == proxy.MYSQLD_PACKET_ERR then
                print("<-- auth failed");
        else
                print("<-- auth ... don't know: " .. string.format("%q", auth.packet));
        end
end

If a long-password capable client tries to authenticate to a server that supports long passwords, but the user password provided is actually short, read_auth_result() will be called twice. The first time, auth.packet:byte() will equal 254, indicating that the client should try again using the old password protocol. The second time time read_auth_result()/ is called, auth.packet:byte() will indicate whether the authentication actually succeeded.

15.7.4.7. Manipulating Queries with read_query()

The read_query() function is called once for each query submitted by the client and accepts a single argument, the query packet that was provided. To access the content of the packet, you must parse the packet contents manually.

For example, you can intercept a query packet and print out the contents using the following function definition:

function read_query( packet )
        if packet:byte() == proxy.COM_QUERY then
                print("we got a normal query: " .. packet:sub(2))
        end
end

This example checks the first byte of the packet to determine the type. If the type is COM_QUERY (see Server Command Constants), we extract the query from the packet and print it. The structure of the packet type supplied is important. In the case of a COM_QUERY packet, the remaining contents of the packet are the text of the query string. In this example, no changes have been made to the query or the list of queries that will ultimately be sent to the MySQL server.

To modify a query, or add new queries, you must populate the query queue (proxy.queries), then execute the queries that you have placed into the queue. If you do not modify the original query or the queue, the query received from the client is sent to the MySQL server verbatim.

When adding queries to the queue, you should follow these guidelines:

  • The packets inserted into the queue must be valid query packets. For each packet, you must set the initial byte to the packet type. If you are appending a query, you can append the query statement to the rest of the packet.

  • Once you add a query to the queue, the queue is used as the source for queries sent to the server. If you add a query to the queue to add more information, you must also add the original query to the queue or it will not be executed.

  • Once the queue has been populated, you must set the return value from read_query() to indicate whether the query queue should be sent to the server.

  • When you add queries to the queue, you should add an ID. The ID you specify is returned with the result set so that you identify each query and corresponding result set. The ID has no other purpose than as an identifier for correlating the query and result set. When operating in a passive mode, during profiling for example, you identify the original query and the corresponding result set so that the results expected by the client can be returned correctly.

  • Unless your client is designed to cope with more result sets than queries, you should ensure that the number of queries from the client match the number of results sets returned to the client. Using the unique ID and removing result sets you inserted will help.

Normally, the read_query() and read_query_result() function are used in conjunction with each other to inject additional queries and remove the additional result sets. However, read_query_result() is only called if you populate the query queue within read_query().

15.7.4.8. Manipulating Results with read_query_result()

The read_query_result() is called for each result set returned by the server only if you have manually injected queries into the query queue. If you have not manipulated the query queue, this function is not called. The function supports a single argument, the result packet, which provides a number of properties:

  • id: The ID of the result set, which corresponds to the ID that was set when the query packet was submitted to the server when using append(id) on the query queue. You must have set the resultset_is_needed flag to append to intercept the result set before it is returned to the client. See proxy.queries.

  • query: The text of the original query.

  • query_time: The number of microseconds required to receive the first row of a result set since the query was sent to the server.

  • response_time: The number of microseconds required to receive the last row of the result set since the query was sent to the server.

  • resultset: The content of the result set data.

By accessing the result information from the MySQL server, you can extract the results that match the queries that you injected, return different result sets (for example, from a modified query), and even create your own result sets.

The following Lua script, for example, will output the query, followed by the query time and response time (that is, the time to execute the query and the time to return the data for the query) for each query sent to the server:

function read_query( packet )
        if packet:byte() == proxy.COM_QUERY then
                print("we got a normal query: " .. packet:sub(2))

                proxy.queries:append(1, packet )

                return proxy.PROXY_SEND_QUERY
        end
end

function read_query_result(inj)
        print("query-time: " .. (inj.query_time / 1000) .. "ms")
        print("response-time: " .. (inj.response_time / 1000) .. "ms")
end

You can access the rows of returned results from the result set by accessing the rows property of the resultset property of the result that is exposed through read_query_result(). For example, you can iterate over the results showing the first column from each row using this Lua fragment:

for row in inj.resultset.rows do
        print("injected query returned: " .. row[1])
end

Just like read_query(), read_query_result() can return different values for each result according to the result returned. If you have injected additional queries into the query queue, for example, remove the results returned from those additional queries and return only the results from the query originally submitted by the client.

The following example injects additional SELECT NOW() statements into the query queue, giving them a different ID to the ID of the original query. Within read_query_result(), if the ID for the injected queries is identified, we display the result row, and return the proxy.PROXY_IGNORE_RESULT from the function so that the result is not returned to the client. If the result is from any other query, we print out the query time information for the query and return the default, which passes on the result set unchanged. We could also have explicitly returned proxy.PROXY_IGNORE_RESULT to the MySQL client.

function read_query( packet )
        if packet:byte() == proxy.COM_QUERY then
                proxy.queries:append(2, string.char(proxy.COM_QUERY) .. "SELECT NOW()", {resultset_is_needed = true} )
                proxy.queries:append(1, packet, {resultset_is_needed = true})
                proxy.queries:append(2, string.char(proxy.COM_QUERY) .. "SELECT NOW()", {resultset_is_needed = true} )

                return proxy.PROXY_SEND_QUERY
        end
end


function read_query_result(inj)
        if inj.id == 2 then
                for row in inj.resultset.rows do
                        print("injected query returned: " .. row[1])
                end
                return proxy.PROXY_IGNORE_RESULT
        else
                print("query-time: " .. (inj.query_time / 1000) .. "ms")
                print("response-time: " .. (inj.response_time / 1000) .. "ms")
        end
end

For further examples, see Section 15.7.5, “Using MySQL Proxy”.

15.7.5. Using MySQL Proxy

There are a number of different ways to use MySQL Proxy. At the most basic level, you can allow MySQL Proxy to pass queries from clients to a single server. To use MySQL Proxy in this mode, you just have to specify on the command line the backend server to which the proxy should connect:

shell> mysql-proxy --proxy-backend-addresses=sakila:3306

If you specify multiple backend MySQL servers, the proxy connects each client to each server in a round-robin fashion. Suppose that you have two MySQL servers, A and B. The first client to connect is connected to server A, the second to server B, the third to server A. For example:

shell> mysql-proxy \
     --proxy-backend-addresses=narcissus:3306 \
     --proxy-backend-addresses=nostromo:3306

When you specify multiple servers in this way, the proxy automatically identifies when a MySQL server has become unavailable and marks it accordingly. New connections are automatically attached to a server that is available, and a warning is reported to the standard output from mysql-proxy:

network-mysqld.c.367: connect(nostromo:3306) failed: Connection refused
network-mysqld-proxy.c.2405: connecting to backend (nostromo:3306) failed, marking it as down for ...

Lua scripts enable a finer level of control, both over the connections and their distribution and how queries and result sets are processed. When using an Lua script, you must specify the name of the script on the command line using the --proxy-lua-script option:

shell> mysql-proxy --proxy-lua-script=mc.lua --proxy-backend-addresses=sakila:3306

When you specify a script, the script is not executed until a connection is made. This means that faults with the script are not raised until the script is executed. Script faults will not affect the distribution of queries to backend MySQL servers.

Note

Because a script is not read until the connection is made, you can modify the contents of the Lua script file while the proxy is still running and the modified script is automatically used for the next connection. This ensures that MySQL Proxy remains available because it need not be restarted for the changes to take effect.

15.7.5.1. Using the Administration Interface

The mysql-proxy administration interface can be accessed using any MySQL client using the standard protocols. You can use the administration interface to gain information about the proxy server as a whole - standard connections to the proxy are isolated to operate as if you were connected directly to the backend MySQL server.

In mysql-proxy 0.8.0 and earlier, a rudimentary interface was built into the proxy. In later versions this was replaced so that you must specify an administration script to be used when users connect to the administration interface.

To use the administration interface, specify the user name and password required to connect to the admin service, using the --admin-username and --admin-password options. You must also specify the Lua script to be used as the interface to the administration service by using the admin-lua-script script option to point to a Lua script.

For example, you can create a basic interface to the internal components of the mysql-proxy system using the following script, written by Diego Medina:

--[[

   Copyright 2008, 2010, Oracle and/or its affiliates. All rights reserved.
   
   This program is free software; you can redistribute it and/or modify
   it under the terms of the GNU General Public License as published by
   the Free Software Foundation; version 2 of the License.

   This program is distributed in the hope that it will be useful,
   but WITHOUT ANY WARRANTY; without even the implied warranty of
   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
   GNU General Public License for more details.

   You should have received a copy of the GNU General Public License
   along with this program; if not, write to the Free Software
   Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA

--]]

-- admin.lua

--[[

    See http://www.chriscalender.com/?p=41
    (Thanks to Chris Calender)
    See http://datacharmer.blogspot.com/2009/01/mysql-proxy-is-back.html
    (Thanks Giuseppe Maxia)

--]]

function set_error(errmsg) 
    proxy.response = {
        type = proxy.MYSQLD_PACKET_ERR,
        errmsg = errmsg or "error"
    }
end

function read_query(packet)
    if packet:byte() ~= proxy.COM_QUERY then
        set_error("[admin] we only handle text-based queries (COM_QUERY)")
        return proxy.PROXY_SEND_RESULT
    end

    local query = packet:sub(2)
    local rows = { }
    local fields = { }

    -- try to match the string up to the first non-alphanum
    local f_s, f_e, command = string.find(packet, "^%s*(%w+)", 2)
    local option

    if f_e then
            -- if that match, take the next sub-string as option
            f_s, f_e, option = string.find(packet, "^%s+(%w+)", f_e + 1)
    end

    -- we got our commands, execute it
    if command == "show" and option == "querycounter" then
            ---
            -- proxy.PROXY_SEND_RESULT requires
            --
            -- proxy.response.type to be either
            -- * proxy.MYSQLD_PACKET_OK or
            -- * proxy.MYSQLD_PACKET_ERR
            --
            -- for proxy.MYSQLD_PACKET_OK you need a resultset
            -- * fields
            -- * rows
            --
            -- for proxy.MYSQLD_PACKET_ERR
            -- * errmsg
            proxy.response.type = proxy.MYSQLD_PACKET_OK
            proxy.response.resultset = {
                    fields = {
                            { type = proxy.MYSQL_TYPE_LONG, name = "query_counter", },
                    },
                    rows = {
                            { proxy.global.query_counter }
                    }
            }

            -- we have our result, send it back
            return proxy.PROXY_SEND_RESULT
    elseif command == "show" and option == "myerror" then
            proxy.response.type = proxy.MYSQLD_PACKET_ERR
            proxy.response.errmsg = "my first error"

            return proxy.PROXY_SEND_RESULT
            
    elseif string.sub(packet, 2):lower() == 'select help' then
            return show_process_help()
    
    elseif string.sub(packet, 2):lower() == 'show proxy processlist' then
            return show_process_table()

    elseif query == "SELECT * FROM backends" then
        fields = { 
            { name = "backend_ndx", 
              type = proxy.MYSQL_TYPE_LONG },

            { name = "address",
              type = proxy.MYSQL_TYPE_STRING },
            { name = "state",
              type = proxy.MYSQL_TYPE_STRING },
            { name = "type",
              type = proxy.MYSQL_TYPE_STRING },
        }

        for i = 1, #proxy.global.backends do
            local b = proxy.global.backends[i]

            rows[#rows + 1] = {
                i, b.dst.name, b.state, b.type 
            }
        end
    else
        set_error()
        return proxy.PROXY_SEND_RESULT
    end

    proxy.response = {
        type = proxy.MYSQLD_PACKET_OK,
        resultset = {
            fields = fields,
            rows = rows
        }
    }
    return proxy.PROXY_SEND_RESULT
end


function make_dataset (header, dataset)
    proxy.response.type = proxy.MYSQLD_PACKET_OK

    proxy.response.resultset = {
        fields = {},
        rows = {}
    }
    for i,v in pairs (header) do
        table.insert(proxy.response.resultset.fields, {type = proxy.MYSQL_TYPE_STRING, name = v})
    end
    for i,v in pairs (dataset) do
        table.insert(proxy.response.resultset.rows, v )
    end
    return proxy.PROXY_SEND_RESULT
end

function show_process_table()
    local dataset = {}
    local header = { 'Id', 'IP Address', 'Time' }
    local rows = {}
    for t_i, t_v in pairs (proxy.global.process) do
        for s_i, s_v in pairs ( t_v ) do
            table.insert(rows, { t_i, s_v.ip, os.date('%c',s_v.ts) })
        end
    end
    return make_dataset(header,rows)
end

function show_process_help()
    local dataset = {}
    local header = { 'command',  'description' }
    local rows = {
        {'SELECT HELP',                 'This command.'},
        {'SHOW PROXY PROCESSLIST',      'Show all connections and their true IP Address.'},
    }
    return make_dataset(header,rows)
end

function dump_process_table()
    proxy.global.initialize_process_table()
    print('current contents of process table')
    for t_i, t_v in pairs (proxy.global.process) do
        print ('session id: ', t_i)
        for s_i, s_v in pairs ( t_v ) do
            print ( '\t', s_i, s_v.ip, s_v.ts )
        end
    end
    print ('---END PROCESS TABLE---')
end

--[[    Help

we use a simple string-match to split commands are word-boundaries

mysql> show querycounter

is split into
command = "show"
option  = "querycounter"

spaces are ignored, the case has to be as is.

mysql> show myerror

returns a error-packet

--]]

The script works in combination with a main proxy script, reporter.lua:

--[[

   Copyright 2008, 2010, Oracle and/or its affiliates. All rights reserved.
   
   This program is free software; you can redistribute it and/or modify
   it under the terms of the GNU General Public License as published by
   the Free Software Foundation; version 2 of the License.

   This program is distributed in the hope that it will be useful,
   but WITHOUT ANY WARRANTY; without even the implied warranty of
   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
   GNU General Public License for more details.

   You should have received a copy of the GNU General Public License
   along with this program; if not, write to the Free Software
   Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA

--]]

-- reporter.lua

--[[

    See http://www.chriscalender.com/?p=41
    (Thanks to Chris Calender)
    See http://datacharmer.blogspot.com/2009/01/mysql-proxy-is-back.html
    (Thanks Giuseppe Maxia)

--]]

proxy.global.query_counter = proxy.global.query_counter or 0

function proxy.global.initialize_process_table()
    if proxy.global.process == nil then
        proxy.global.process = {}
    end
    if proxy.global.process[proxy.connection.server.thread_id] == nil then
        proxy.global.process[proxy.connection.server.thread_id] = {}
    end
end

function read_auth_result( auth )
    local state = auth.packet:byte()
    if state == proxy.MYSQLD_PACKET_OK then
        proxy.global.initialize_process_table()
        table.insert( proxy.global.process[proxy.connection.server.thread_id],
            { ip = proxy.connection.client.src.name, ts = os.time() } )
    end
end

function disconnect_client()
    local connection_id = proxy.connection.server.thread_id
    if connection_id then
        -- client has disconnected, set this to nil
        proxy.global.process[connection_id] = nil
    end
end


---
-- read_query() can return a resultset
--
-- You can use read_query() to return a result-set.
--
-- @param packet the mysql-packet sent by the client
--
-- @return
--   * nothing to pass on the packet as is,
--   * proxy.PROXY_SEND_QUERY to send the queries from the proxy.queries queue
--   * proxy.PROXY_SEND_RESULT to send your own result-set
--
function read_query( packet )
        -- a new query came in in this connection
        -- using proxy.global.* to make it available to the admin plugin
        proxy.global.query_counter = proxy.global.query_counter + 1

end

To use the script, save the first script to a file (admin.lua in the following example) and the other to reporter.lua, then run mysql-proxy specifying the admin script and a backend MySQL server:

shell> mysql-proxy --admin-lua-script=admin.lua --admin-password=password \ »
     --admin-username=root --proxy-backend-addresses=127.0.0.1:3306 -proxy-lua-script=reporter.lua

In a different window, connect to the MySQL server through the proxy:

shell> mysql --user=root --password=password --port=4040
Welcome to the MySQL monitor.  Commands end with ; or \g.
Your MySQL connection id is 1798669
Server version: 5.0.70-log Gentoo Linux mysql-5.0.70-r1

Type 'help;' or '\h' for help. Type '\c' to clear the buffer.

mysql> 

In another different window, connect to the mysql-proxy admin service using the specified user name and password:

shell> mysql --user=root --password=password --port=4041 --host=localhost
Welcome to the MySQL monitor.  Commands end with ; or \g.
Your MySQL connection id is 1
Server version: 5.0.99-agent-admin

Type 'help;' or '\h' for help. Type '\c' to clear the buffer.

mysql>

To monitor the status of the proxy, ask for a list of the current active processes:

mysql> show proxy processlist;
+---------+---------------------+--------------------------+
| Id      | IP Address          | Time                     |
+---------+---------------------+--------------------------+
| 1798669 | 192.168.0.112:52592 | Wed Jan 20 16:58:00 2010 | 
+---------+---------------------+--------------------------+
1 row in set (0.00 sec)

mysql>

For more information on the example, see MySQL Proxy Admin Example.

15.7.6. MySQL Proxy FAQ

Questions

  • 16.7.6.1: In load balancing, how can I separate reads from writes?

  • 16.7.6.2: How do I use a socket with MySQL Proxy? Proxy change logs mention that support for UNIX sockets has been added.

  • 16.7.6.3: Can I use MySQL Proxy with all versions of MySQL?

  • 16.7.6.4: Can I run MySQL Proxy as a daemon?

  • 16.7.6.5: Do proxy applications run on a separate server? If not, what is the overhead incurred by Proxy on the DB server side?

  • 16.7.6.6: With load balancing, what happens to transactions? Are all queries sent to the same server?

  • 16.7.6.7: Is it possible to use MySQL Proxy with updating a Lucene index (or Solr) by making TCP calls to that server to update?

  • 16.7.6.8: Is the system context switch expensive, how much overhead does the Lua script add?

  • 16.7.6.9: How much latency does a proxy add to a connection?

  • 16.7.6.10: Do you have to make one large script and call it at proxy startup, can I change scripts without stopping and restarting (interrupting) the proxy?

  • 16.7.6.11: If MySQL Proxy has to live on same machine as MySQL, are there any tuning considerations to ensure both perform optimally?

  • 16.7.6.12: I currently use SQL Relay for efficient connection pooling with a number of Apache processes connecting to a MySQL server. Can MySQL Proxy currently accomplish this? My goal is to minimize connection latency while keeping temporary tables available.

  • 16.7.6.13: Are these reserved function names (for example, error_result()) that get automatically called?

  • 16.7.6.14: As the script is re-read by MySQL Proxy, does it cache this or is it looking at the file system with each request?

  • 16.7.6.15: Given that there is a connect_server() function, can a Lua script link up with multiple servers?

  • 16.7.6.16: Is the MySQL Proxy an API?

  • 16.7.6.17: The global namespace variable example with quotas does not persist after a reboot, is that correct?

  • 16.7.6.18: Can MySQL Proxy handle SSL connections?

  • 16.7.6.19: Could MySQL Proxy be used to capture passwords?

  • 16.7.6.20: Are there tools for isolating problems? How can someone figure out whether a problem is in the client, the database, or the proxy?

  • 16.7.6.21: Is MySQL Proxy similar to what is provided by Java connection pools?

  • 16.7.6.22: So authentication with connection pooling has to be done at every connection? What is the authentication latency?

  • 16.7.6.23: If you have multiple databases on the same box, can you use proxy to connect to databases on default port 3306?

  • 16.7.6.24: What about caching the authorization information so clients connecting are given back-end connections that were established with identical authorization information, thus saving a few more round trips?

  • 16.7.6.25: Is there any big web site using MySQL Proxy? For what purpose and what transaction rate have they achieved?

  • 16.7.6.26: How does MySQL Proxy compare to DBSlayer?

  • 16.7.6.27: I tried using MySQL Proxy without any Lua script to try a round-robin type load balancing. In this case, if the first database in the list is down, MySQL Proxy would not connect the client to the second database in the list.

  • 16.7.6.28: Is it safe to use LuaSocket with proxy scripts?

  • 16.7.6.29: How different is MySQL Proxy from DBCP (Database connection pooling) for Apache in terms of connection pooling?

  • 16.7.6.30: MySQL Proxy can handle about 5000 connections, what is the limit on a MySQL server?

  • 16.7.6.31: Would the Java-only connection pooling solution work for multiple web servers? With this, I would assume that you can pool across many web servers at once?

Questions and Answers

16.7.6.1: In load balancing, how can I separate reads from writes?

There is no automatic separation of queries that perform reads or writes to the different backend servers. However, you can specify to mysql-proxy that one or more of the backend MySQL servers are read only.

shell> mysql-proxy \
--proxy-backend-addresses=10.0.1.2:3306 \
--proxy-read-only-backend-addresses=10.0.1.3:3306 &

16.7.6.2: How do I use a socket with MySQL Proxy? Proxy change logs mention that support for UNIX sockets has been added.

Specify the path to the socket:

--proxy-backend-addresses=/path/to/socket

16.7.6.3: Can I use MySQL Proxy with all versions of MySQL?

MySQL Proxy is designed to work with MySQL 5.0 or higher, and supports the MySQL network protocol for 5.0 and higher.

16.7.6.4: Can I run MySQL Proxy as a daemon?

Use the --daemon option. To keep track of the process ID, the daemon can be started with the --pid-file=file option to save the PID to a known file name. On version 0.5.x, the Proxy cannot be started natively as a daemon.

16.7.6.5: Do proxy applications run on a separate server? If not, what is the overhead incurred by Proxy on the DB server side?

You can run the proxy on the application server, on its own box, or on the DB-server depending on the use case.

16.7.6.6: With load balancing, what happens to transactions? Are all queries sent to the same server?

Without any special customization the whole connection is sent to the same server. That keeps the whole connection state intact.

16.7.6.7: Is it possible to use MySQL Proxy with updating a Lucene index (or Solr) by making TCP calls to that server to update?

Yes, but it is not advised for now.

16.7.6.8: Is the system context switch expensive, how much overhead does the Lua script add?

Lua is fast and the overhead should be small enough for most applications. The raw packet overhead is around 400 microseconds.

16.7.6.9: How much latency does a proxy add to a connection?

In the range of 400 microseconds per request.

16.7.6.10: Do you have to make one large script and call it at proxy startup, can I change scripts without stopping and restarting (interrupting) the proxy?

You can just change the script and the proxy will reload it when a client connects.

16.7.6.11: If MySQL Proxy has to live on same machine as MySQL, are there any tuning considerations to ensure both perform optimally?

MySQL Proxy can live on any box: application, database, or its own box. MySQL Proxy uses comparatively little CPU or RAM, with negligible additional requirements or overhead.

16.7.6.12: I currently use SQL Relay for efficient connection pooling with a number of Apache processes connecting to a MySQL server. Can MySQL Proxy currently accomplish this? My goal is to minimize connection latency while keeping temporary tables available.

Yes.

16.7.6.13: Are these reserved function names (for example, error_result()) that get automatically called?

Only functions and values starting with proxy.* are provided by the proxy. All others are user provided.

16.7.6.14: As the script is re-read by MySQL Proxy, does it cache this or is it looking at the file system with each request?

It looks for the script at client-connect and reads it if it has changed, otherwise it uses the cached version.

16.7.6.15: Given that there is a connect_server() function, can a Lua script link up with multiple servers?

MySQL Proxy provides some tutorials in the source package; one is examples/tutorial-keepalive.lua.

16.7.6.16: Is the MySQL Proxy an API?

No, MySQL Proxy is an application that forwards packets from a client to a server using the MySQL network protocol. The MySQL Proxy provides a API allowing you to change its behavior.

16.7.6.17: The global namespace variable example with quotas does not persist after a reboot, is that correct?

Yes. If you restart the proxy, you lose the results, unless you save them in a file.

16.7.6.18: Can MySQL Proxy handle SSL connections?

No, being the man-in-the-middle, Proxy cannot handle encrypted sessions because it cannot share the SSL information.

16.7.6.19: Could MySQL Proxy be used to capture passwords?

The MySQL network protocol does not allow passwords to be sent in cleartext, all you could capture is the encrypted version.

16.7.6.20: Are there tools for isolating problems? How can someone figure out whether a problem is in the client, the database, or the proxy?

You can set a debug script in the proxy, which is an exceptionally good tool for this purpose. You can see very clearly which component is causing the problem, if you set the right breakpoints.

16.7.6.21: Is MySQL Proxy similar to what is provided by Java connection pools?

Yes and no. Java connection pools are specific to Java applications, MySQL Proxy works with any client API that talks the MySQL network protocol. Also, connection pools do not provide any functionality for intelligently examining the network packets and modifying the contents.

16.7.6.22: So authentication with connection pooling has to be done at every connection? What is the authentication latency?

You can skip the round-trip and use the connection as it was added to the pool. As long as the application cleans up the temporary tables it used. The overhead is (as always) around 400 microseconds.

16.7.6.23: If you have multiple databases on the same box, can you use proxy to connect to databases on default port 3306?

Yes, MySQL Proxy can listen on any port, provided that none of the MySQL servers are listening on the same port.

16.7.6.24: What about caching the authorization information so clients connecting are given back-end connections that were established with identical authorization information, thus saving a few more round trips?

There is an --proxy-pool-no-change-user option that provides this functionality.

16.7.6.25: Is there any big web site using MySQL Proxy? For what purpose and what transaction rate have they achieved?

Yes, gaiaonline. They have tested MySQL Proxy and seen it handle 2400 queries per second through the proxy.

16.7.6.26: How does MySQL Proxy compare to DBSlayer?

DBSlayer is a REST->MySQL tool, MySQL Proxy is transparent to your application. No change to the application is needed.

16.7.6.27: I tried using MySQL Proxy without any Lua script to try a round-robin type load balancing. In this case, if the first database in the list is down, MySQL Proxy would not connect the client to the second database in the list.

This issue is fixed in version 0.7.0.

16.7.6.28: Is it safe to use LuaSocket with proxy scripts?

You can, but it is not advised because it may block.

16.7.6.29: How different is MySQL Proxy from DBCP (Database connection pooling) for Apache in terms of connection pooling?

Connection Pooling is just one use case of the MySQL Proxy. You can use it for a lot more and it works in cases where you cannot use DBCP (for example, if you do not have Java).

16.7.6.30: MySQL Proxy can handle about 5000 connections, what is the limit on a MySQL server?

The server limit is given by the value of the max_connections system variable. The default value is version dependent.

16.7.6.31: Would the Java-only connection pooling solution work for multiple web servers? With this, I would assume that you can pool across many web servers at once?

Yes. But you can also start one proxy on each application server to get a similar behavior as you have it already.