]]>
]]>

Latest MySQL Performance Blog posts

You are here

Subscribe to Latest MySQL Performance Blog posts feed
Percona's MySQL & InnoDB performance and scalability blog
Updated: 13 min 50 sec ago

Database auditing alternatives for MySQL

May 20, 2014 - 8:08am

Database auditing is the monitoring of selected actions of database users. It doesn’t protect the database in case privileges are set incorrectly, but it can help the administrator detect mistakes.

Audits are needed for security. You can track data access and be alerted to suspicious activity. Audits are required for data integrity. They are the only way to validate that changes made to data are correct and legal.

There are several regulations that require database audits:

  • Sarbanes-Oxley (SOX) Act of 2002 is a US federal law that regulates how financial data must be handled and protected.
  • Payment Card Industry Data Security Standard, otherwise known as PCI-DSS is an international standard developed to protect cardholder’s data.
  • Health Insurance Portability and Accountability Act (HIPAA) enacted by the U.S. Congress to protect medical and personal information.

MySQL since version 5.5.3 provides the Audit Plugin API which can be used to write an Audit Plugin. The API provides notification for the following events:

  • messages written to general log (LOG)
  • messages written to error log (ERROR)
  • query results sent to client (RESULT)
  • logins (including failed) and disconnects (CONNECT)

All current audit plugins for MySQL provide an audit log as result of their work. They differ in record format, filtering capabilities and verbosity of log records.

McAfee MySQL Audit Plugin
This plugin is available for MySQL versions 5.1, 5.5, 5.6. It does not officially support Percona Server and MariaDB. It doesn’t use the Audit API and has better verbosity and better filtering features. This is achieved by binary patching the server at runtime inserting the hooks which extract data stored in known offsets in memory. Thus, the plugin is sensitive to any changes of server code.

Summary:

  • json log format
  • log to file or UNIX socket (allows to log with syslog-ng)
  • filter logged events by users, databases and tables, commands (insert, update, delete)

Oracle Enterprise Audit Log Plugin
Oracle provides this audit plugin as a part of the MySQL Enterprise pack. It uses the MySQL Audit API and is able to log RESULT and CONNECT events. The plugin has support for two XML-based formats.

Summary:

  • XML format
  • log to file
  • filter by event type

MariaDB Audit Plugin
MariaDB developers extended the MySQL Audit API by adding fields for existing events and adding new TABLE event which notifies of operation with tables (read, write, create, drop, alter). The plugin can still be used with MySQL and Percona Server but MariaDB’s additions will not be available.

Summary:

  • CSV log format
  • log to file or syslog
  • filter by users, event types

Percona Server Audit Log feature
Percona has developed an audit log feature that is a part of Percona Server since 5.5.35-37.0 and 5.6.17-65.0. It’s goal is to be compatible with Oracle’s Enterprise Audit Plugin providing a similar set of features for Percona Server users. It asynchronously logs all queries and connections in order to “audit” Percona Server usage, without the overhead of the General Query Log. The Audit Log feature can be very beneficial for web applications that deal with sensitive data (e.g., credit card numbers or medical records) and require security compliance (e.g., HIPAA or SOX). Administrators of multi-tenant applications or MySQL as a service can easily audit data access from a security and performance standpoint when using the Audit Log feature in Percona Server. The Audit Log feature is helpful for investigating and troubleshooting issues and auditing performance, too. The Audit Log feature can be dynamically enabled (does not require a server restart).

The post Database auditing alternatives for MySQL appeared first on MySQL Performance Blog.

Errant transactions: Major hurdle for GTID-based failover in MySQL 5.6

May 19, 2014 - 12:00am

I have previously written about the new replication protocol that comes with GTIDs in MySQL 5.6. Because of this new replication protocol, you can inadvertently create errant transactions that may turn any failover to a nightmare. Let’s see the problems and the potential solutions.

In short
  • Errant transactions may cause all kinds of data corruption/replication errors when failing over.
  • Detection of errant transactions can be done with the GTID_SUBSET() and GTID_SUBTRACT() functions.
  • If you find an errant transaction on one server, commit an empty transaction with the GTID of the errant one on all other servers.
  • If you are using a tool to perform the failover for you, make sure it can detect errant transactions. At the time of writing, only mysqlfailover and mysqlrpladmin from MySQL Utilities can do that.
What are errant transactions?

Simply stated, they are transactions executed directly on a slave. Thus they only exist on a specific slave. This could result from a mistake (the application wrote to a slave instead of writing to the master) or this could be by design (you need additional tables for reports).

Why can they create problems that did not exist before GTIDs?

Errant transactions have been existing forever. However because of the new replication protocol for GTID-based replication, they can have a significant impact on all servers if a slave holding an errant transaction is promoted as the new master.

Compare what happens in this master-slave setup, first with position-based replication and then with GTID-based replication. A is the master, B is the slave:

# POSITION-BASED REPLICATION # Creating an errant transaction on B mysql> create database mydb; # Make B the master, and A the slave # What are the databases on A now? mysql> show databases like 'mydb'; Empty set (0.01 sec)

As expected, the mydb database is not created on A.

# GTID-BASED REPLICATION # Creating an errant transaction on B mysql> create database mydb; # Make B the master, and A the slave # What are the databases on A now? mysql> show databases like 'mydb'; +-----------------+ | Database (mydb) | +-----------------+ | mydb | +-----------------+

mydb has been recreated on A because of the new replication protocol: when A connects to B, they exchange their own set of executed GTIDs and the master (B) sends any missing transaction. Here it is the create database statement.

As you can see, the main issue with errant transactions is that when failing over you may execute transactions ‘coming from nowhere’ that can silently corrupt your data or break replication.

How to detect them?

If the master is running, it is quite easy with the GTID_SUBSET() function. As all writes should go to the master, the GTIDs executed on any slave should always be a subset of the GTIDs executed on the master. For instance:

# Master mysql> show master status\G *************************** 1. row *************************** File: mysql-bin.000017 Position: 376 Binlog_Do_DB: Binlog_Ignore_DB: Executed_Gtid_Set: 8e349184-bc14-11e3-8d4c-0800272864ba:1-30, 8e3648e4-bc14-11e3-8d4c-0800272864ba:1-7 # Slave mysql> show slave status\G [...] Executed_Gtid_Set: 8e349184-bc14-11e3-8d4c-0800272864ba:1-29, 8e3648e4-bc14-11e3-8d4c-0800272864ba:1-9 # Now, let's compare the 2 sets mysql> > select gtid_subset('8e349184-bc14-11e3-8d4c-0800272864ba:1-29, 8e3648e4-bc14-11e3-8d4c-0800272864ba:1-9','8e349184-bc14-11e3-8d4c-0800272864ba:1-30, 8e3648e4-bc14-11e3-8d4c-0800272864ba:1-7') as slave_is_subset; +-----------------+ | slave_is_subset | +-----------------+ | 0 | +-----------------+

Hum, it looks like the slave has executed more transactions than the master, this indicates that the slave has executed at least 1 errant transaction. Could we know the GTID of these transactions? Sure, let’s use GTID_SUBTRACT():

select gtid_subtract('8e349184-bc14-11e3-8d4c-0800272864ba:1-29, 8e3648e4-bc14-11e3-8d4c-0800272864ba:1-9','8e349184-bc14-11e3-8d4c-0800272864ba:1-30, 8e3648e4-bc14-11e3-8d4c-0800272864ba:1-7') as errant_transactions; +------------------------------------------+ | errant_transactions | +------------------------------------------+ | 8e3648e4-bc14-11e3-8d4c-0800272864ba:8-9 | +------------------------------------------+

This means that the slave has 2 errant transactions.

Now, how can we check errant transactions if the master is not running (like master has crashed, and we want to fail over to one of the slaves)? In this case, we will have to follow these steps:

  • Check all slaves to see if they have executed transactions that are not found on any other slave: this is the list of potential errant transactions.
  • Discard all transactions originating from the master: now you have the list of errant transactions of each slave

Some of you may wonder how you can know which transactions come from the master as it is not available: SHOW SLAVE STATUS gives you the master’s UUID which is used in the GTIDs of all transactions coming from the master.

How to get rid of them?

This is pretty easy, but it can be tedious if you have many slaves: just inject an empty transaction on all the other servers with the GTID of the errant transaction.

For instance, if you have 3 servers, A (the master), B (slave with an errant transaction: XXX:3), and C (slave with 2 errant transactions: YYY:18-19), you will have to inject the following empty transactions in pseudo-code:

# A - Inject empty trx(XXX:3) - Inject empty trx(YYY:18) - Inject empty trx(YYY:19) # B - Inject empty trx(YYY:18) - Inject empty trx(YYY:19) # C - Inject empty trx(XXX:3)

Conclusion

If you want to switch to GTID-based replication, make sure to check errant transactions before any planned or unplanned replication topology change. And be specifically careful if you use a tool that reconfigures replication for you: at the time of writing, only mysqlrpladmin and mysqlfailover from MySQL Utilities can warn you if you are trying to perform an unsafe topology change.

The post Errant transactions: Major hurdle for GTID-based failover in MySQL 5.6 appeared first on MySQL Performance Blog.

Introduction to the Percona MySQL Audit Log Plugin

May 16, 2014 - 6:00am

Percona has developed a MySQL Audit Log plugin that is now included in Percona Server since the recent 5.5 and 5.6 releases. This implementation is alternative to the MySQL Enterprise Audit Log Plugin: Percona re-implemented the Audit Plugin code as GPL as Oracle’s code was closed source. This post is a quick introduction to this plugin.

Installation
There are two ways to install the Percona MySQL Audit Plugin:

INSTALL PLUGIN audit_log SONAME 'audit_log.so';

or in my.cnf

[mysqld] plugin-load="audit_log=audit_log.so"

Verify installation

mysql> SHOW PLUGINS\G ... *************************** 38. row ***************************   Name: audit_log Status: ACTIVE   Type: AUDIT Library: audit_log.so License: GPL 38 rows in set (0.00 sec)

Configuration
Let’s see variables provided by the Percona MySQL Audit Plugin:

mysql> show global variables like 'audit%'; +--------------------------+--------------+ | Variable_name            | Value        | +--------------------------+--------------+ | audit_log_buffer_size    | 1048576      | | audit_log_file           | audit.log    | | audit_log_flush          | OFF          | | audit_log_format         | OLD          | | audit_log_policy         | ALL          | | audit_log_rotate_on_size | 0            | | audit_log_rotations      | 0            | | audit_log_strategy       | ASYNCHRONOUS | +--------------------------+--------------+ 7 rows in set (0.00 sec)

The Percona MySQL Audit Plugin can log using the memory buffer to deliver better performance. Messages will be written into memory buffer first and then flushed to file in background. A certain amount of events can be lost in case of server crash or power outage. Another option is to log directly to file without using memory buffer. There is also an option to fsync every event.

Set audit_log_strategy to control log flushing:

  • ASYNCHRONOUS log using memory buffer, do not drop events if buffer is full
  • PERFORMANCE log using memory buffer, drop events if buffer is full
  • SEMISYNCHRONOUS log directly to file, do not fsync every event
  • SYNCHRONOUS log directly to file, fsync every event

audit_log_buffer_size specifies the size of memory buffer, it makes sense only for ASYNCHRONOUS and PERFORMANCE strategy.

Variable audit_log_file specifies the file to log into. It’s value can be path relative to datadir or absolute path.

The Percona MySQL Audit Plugin can automatically rotate log file based on size. Set audit_log_rotate_size to enable this feature. File is rotated when log grew in size to specified amount of bytes. Set audit_log_rotations to limit the number of log files to keep.

It is possible to log only logins or only queries by setting audit_log_policy value.

Log file format
Lets see how audit records look like

OLD format (audit_log_format = OLD):

<AUDIT_RECORD  "NAME"="Connect"  "RECORD"="2_2014-04-21T12:34:32"  "TIMESTAMP"="2014-04-21T12:34:32 UTC"  "CONNECTION_ID"="1"  "STATUS"="0"  "USER"="root"  "PRIV_USER"="root"  "OS_LOGIN"=""  "PROXY_USER"=""  "HOST"="localhost"  "IP"=""  "DB"="" />

NEW format (audit_log_format = NEW):

<AUDIT_RECORD>  <NAME>Connect</NAME>  <RECORD>17481_2014-04-21T12:39:03</RECORD>  <TIMESTAMP>2014-04-21T12:39:05 UTC</TIMESTAMP>  <CONNECTION_ID>4</CONNECTION_ID>  <STATUS>0</STATUS>  <USER>root</USER>  <PRIV_USER>root</PRIV_USER>  <OS_LOGIN></OS_LOGIN>  <PROXY_USER></PROXY_USER>  <HOST>localhost</HOST>  <IP></IP>  <DB>test</DB> </AUDIT_RECORD>

The difference is that the audit record in the OLD format was written as a single element with attributes, while in the NEW format it is written as a single element with sub-elements.

A good idea of what each sub-element means can be found in Audit Plugin API documentation here: https://dev.mysql.com/doc/refman/5.6/en/writing-audit-plugins.html.

Performance
Lets compare performance of different audit_log_strategy modes. I used readonly sysbench on my laptop for it. Workload is CPU-bound with dataset fit in buffer pool and I set number of sysbench threads to the amount for which count of transactions per seconds is maximum.

I got TPS drop for PERFORMANCE and ASYNCHRONOUS strategies around 7%, 9% for SEMISYNCHRONOUS and 98% for SYNCHRONOUS which shows that syncing every logged statement to disk is not the best thing for performance.

 

Conclusion
Of course any software has bugs and this plugin has plenty of them. Please give it a try and provide us your feedback. Report any issues here: https://bugs.launchpad.net/percona-server.

The post Introduction to the Percona MySQL Audit Log Plugin appeared first on MySQL Performance Blog.

Benchmark: SimpleHTTPServer vs pyclustercheck (twisted implementation)

May 16, 2014 - 12:00am

Github user Arianlzt provided a python-twisted alternative version of pyclustercheck per discussion on issue 7.

Due to sporadic performance issues noted with the original implementation in SimpleHTTPserver, the benchmarks which I’ve included as part of the project on github use mutli-mechanize library,

  • cache time 1 sec
  • 2 x 100 thread pools
  • 60s ramp up time
  • 600s total duration
  • testing simulated node fail (always returns 503, rechecks mysql node on cache expiry)
  • AMD FX(tm)-8350 Eight-Core Processor
  • Intel 330 SSD
  • local loop back test (127.0.0.1)

The SimpleHTTPServer instance faired as follows:

Right away we can see around 500TPS throughput, however as can be seen in both response time graphs there are “outlying” transactions, something is causing the response time to spike dramatically  SimpleHTTPServer, how does the twisted alternative compare? (note the benchmarks are from the current HEAD with features re-added to avoid regression, caching and ipv6 support)

 

Ouch! We appear to have taken a performance hit, at least in terms of TPS -19% rough estimates however compare the response time graphs to find a much more consistent plot, we had outliers hitting near  70s for SimpleHTTP server, we’re always under 1s within twisted.

Great! So why isn’t this merged into the master branch as the main project and therfor bundled with Percona XtraDB Cluster (PXC)? The issue here is the required version of python-twisted; ipv6 support was introduced in issue 8 by user Nibler999 and to avoid regression I re-added support for ipv6 in this commit for twisted

ipv6 support for python-twisted is not in the version distributed to main server OS’s such as

  • EL6 python-twisted 8.x
  • Ubuntu 10.04 LTS python-twisted 11.x

What’s the issue here? Attempting to bind / listen to an ipv6 interface yields the following error: twisted.internet.error.CannotListenError: Couldn't listen on :::8000: [Errno -9] Address family for hostname not supported.

Due to this regression (breaking of ipv6 support) the twisted version can not at this time be merged into master, the twisted version however as can be seen from above is much more consistent and if you have the “cycles” to implement it (e.g. install twisted from pypy via pip / easy_install to get >= 12.x) and test it’s a promising alternative.

To illustrate this further the benchmark was made more gruling:

  • 5 x 100 thread pools
  • 60s ramp up
  • 600s total duration

First the twisted results, note the initial spike is due to a local python issue where it locked up creating a new thread in multi-mechanize:

Now the SimpleHTTPServer results:

Oh dear, as the load increases clearly we get some stability issues inside SimpleHTTP server…

Also worth noting is the timeouts

  • twisted: grep 'timed out' results.csv | wc -l == 0
  • SimpleHTTPServer: grep 'timed out' results.csv | wc -l == 470

 

… in the case of increased load the twisted model performs far more consistently under the same test conditions when compared against SimpleHTTPServer. I include the multi-mechanize scripts as part of the project on GitHub – as such you can recreate these tests yourself and gauge the performance to see if twisted or SimpleHTTP suits your needs.

The post Benchmark: SimpleHTTPServer vs pyclustercheck (twisted implementation) appeared first on MySQL Performance Blog.

High Availability with MySQL Fabric: Part I

May 15, 2014 - 6:00am

In our previous post, we introduced the MySQL Fabric utility and said we would dig deeper into it. This post is the first part of our test of MySQL Fabric’s High Availability (HA) functionality.

Today, we’ll review MySQL Fabric’s HA concepts, and then walk you through the setup of a 3-node cluster with one Primary and two Secondaries, doing a few basic tests with it. In a second post, we will spend more time generating failure scenarios and documenting how Fabric handles them. (MySQL Fabric is an extensible framework to manage large farms of MySQL servers, with support for high-availability and sharding.)

Before we begin, we recommend you read this post by Oracle’s Mats Kindahl, which, among other things, addresses the issues we raised on our first post. Mats leads the MySQL Fabric team.

Our lab

All our tests will be using our test environment with Vagrant (https://github.com/martinarrieta/vagrant-fabric)

If you want to play with MySQL Fabric, you can have these VMs running in your desktop following the instructions in the README file. If you don’t want full VMs, our colleague Jervin Real created a set of wrapper scripts that let you test MySQL Fabric using sandboxes.

Here is a basic representation of our environment.

Set up

To set up MyQSL Fabric without using our Vagrant environment, you can follow the official documentation, or check the ansible playbooks in our lab repo. If you follow the manual, the only caveat is that when creating the user, you should either disable binary logging for your session, or use a GRANT statement instead of CREATE USER. You can read here for more info on why this is the case.

A description of all the options in the configuration file can be found here. For HA tests, the one thing to mention is that, in our experience, the failure detector will only trigger an automatic failover if the value for failover_interval in the [failure_tracking] section is greater than 0. Otherwise, failures will be detected and written to the log, but no action will be taken.

MySQL configuration

In order to manage a mysqld instance with MySQL Fabric, the following options need to be set in the [mysqld] section of its my.cnf file:

log_bin gtid-mode=ON enforce-gtid-consistency log_slave_updates

Additionally, as in any replication setup, you must make sure that all servers have a distinct server_id.

When everything is in place, you can setup and start MySQL Fabric with the following commands:

[vagrant@store ~]$ mysqlfabric manage setup [vagrant@store ~]$ mysqlfabric manage start --daemon

The setup command creates the database schema used by MySQL Fabric to store information about managed servers, and the start one, well, starts the daemon. The –daemon option makes Fabric start as a daemon, logging to a file instead of to standard output. Depending on the port and file name you configured in fabric.cfg, this may need to be run as root.

While testing, you can make MySQL Fabric reset its state at any time (though it won’t change existing node configurations such as replication) by running:

[vagrant@store ~]$ mysqlfabric manage teardown [vagrant@store ~]$ mysqlfabric manage setup

If you’re using our Vagrant environment, you can run the reinit_cluster.sh script from your host OS (from the root of the vagrant-fabric repo) to do this for you, and also initialise the datadir of the three instances.

Creating a High Availability Cluster:

A High Availability Cluster is a set of servers using the standard Asynchronous MySQL Replication with GTID.

Creating a group

The first step is to create the group by running mysqlfabric with this syntax:

$ mysqlfabric group create <group_name>

In our example, to create the cluster “mycluster” you can run:

[vagrant@store ~]$ mysqlfabric group create mycluster Procedure : { uuid = 605b02fb-a6a1-4a00-8e24-619cad8ec4c7, finished = True, success = True, return = True, activities = }

Add the servers to the group

The second step is add the servers to the group. The syntax to add a server to a group is:

$ mysqlfabric group add <group_name> <host_name or IP>[:port]

The port number is optional and only required if distinct from 3306. It is important to mention that the clients that will use this cluster must be able to resolve this host or IP. This is because clients will connect directly both with MySQL Fabric’s XML-PRC server and with the managed mysqld servers. Let’s add the nodes to our group.

[vagrant@store ~]$ for i in 1 2 3; do mysqlfabric group add mycluster node$i; done Procedure : { uuid = 9d65c81c-e28a-437f-b5de-1d47e746a318, finished = True, success = True, return = True, activities = } Procedure : { uuid = 235a7c34-52a6-40ad-8e30-418dcee28f1e, finished = True, success = True, return = True, activities = } Procedure : { uuid = 4da3b1c3-87cc-461f-9705-28a59a2a4f67, finished = True, success = True, return = True, activities = }

Promote a node as a master

Now that we have all our nodes in the group, we have to promote one of them. You can promote one specific node or you can let MySQL Fabric to choose one for you.

The syntax to promote a specific node is:

$ mysqlfabric group promote <group_name> --slave_uuid='<node_uuid>'

or to let MySQL Fabric pick one:

$ mysqlfabric group promote <group_name>

Let’s do that:

[vagrant@store ~]$ mysqlfabric group promote mycluster Procedure : { uuid = c4afd2e7-3864-4b53-84e9-04a40f403ba9, finished = True, success = True, return = True, activities = }

You can then check the health of the group like this:

[vagrant@store ~]$ mysqlfabric group health mycluster Command : { success = True return = {'e245ec83-d889-11e3-86df-0800274fb806': {'status': 'SECONDARY', 'is_alive': True, 'threads': {}}, 'e826d4ab-d889-11e3-86df-0800274fb806': {'status': 'SECONDARY', 'is_alive': True, 'threads': {}}, 'edf2c45b-d889-11e3-86df-0800274fb806': {'status': 'PRIMARY', 'is_alive': True, 'threads': {}}} activities = }

One current limitation of the ‘health’ command is that it only identifies servers by their uuid. To get a list of the servers in a group, along with quick status summary, and their host names, use lookup_servers instead:

[vagrant@store ~]$ mysqlfabric group lookup_servers mycluster Command : { success = True return = [{'status': 'SECONDARY', 'server_uuid': 'e245ec83-d889-11e3-86df-0800274fb806', 'mode': 'READ_ONLY', 'weight': 1.0, 'address': 'node1'}, {'status': 'SECONDARY', 'server_uuid': 'e826d4ab-d889-11e3-86df-0800274fb806', 'mode': 'READ_ONLY', 'weight': 1.0, 'address': 'node2'}, {'status': 'PRIMARY', 'server_uuid': 'edf2c45b-d889-11e3-86df-0800274fb806', 'mode': 'READ_WRITE', 'weight': 1.0, 'address': 'node3'}] activities = }

We sent a merge request to use a Json string instead of the “print” of the object in the “return” field from the XML-RPC in order to be able to use that information to display the results in a friendly way. In the same merge, we have added the address of the servers in the health command too.

Failure detection

Now we have the three lab machines set up in a replication topology of one master (the PRIMARY server) and two slaves (the SECONDARY ones). To make MySQL Fabric start monitoring the group for problems, you need to activate it:

[vagrant@store ~]$ mysqlfabric group activate mycluster Procedure : { uuid = 230835fc-6ec4-4b35-b0a9-97944c18e21f, finished = True, success = True, return = True, activities = }

Now MySQL Fabric will monitor the group’s servers, and depending on the configuration (remember the failover_interval we mentioned before) it may trigger an automatic failover. But let’s start testing a simpler case, by stopping mysql on one of the secondary nodes:

[vagrant@node2 ~]$ sudo service mysqld stop Stopping mysqld: [ OK ]

And checking how MySQL Fabric report’s the group’s health after this:

[vagrant@store ~]$ mysqlfabric group health mycluster Command : { success = True return = {'e245ec83-d889-11e3-86df-0800274fb806': {'status': 'SECONDARY', 'is_alive': True, 'threads': {}}, 'e826d4ab-d889-11e3-86df-0800274fb806': {'status': 'FAULTY', 'is_alive': False, 'threads': {}}, 'edf2c45b-d889-11e3-86df-0800274fb806': {'status': 'PRIMARY', 'is_alive': True, 'threads': {}}} activities = }

We can see that MySQL Fabric successfully marks the server as faulty. In our next post we’ll show an example of this by using one of the supported connectors to handle failures in a group, but for now, let’s keep on the DBA/sysadmin side of things, and try to bring the server back online:

[vagrant@node2 ~]$ sudo service mysqld start Starting mysqld: [ OK ] [vagrant@store ~]$ mysqlfabric group health mycluster Command : { success = True return = {'e245ec83-d889-11e3-86df-0800274fb806': {'status': 'SECONDARY', 'is_alive': True, 'threads': {}}, 'e826d4ab-d889-11e3-86df-0800274fb806': {'status': 'FAULTY', 'is_alive': True, 'threads': {}}, 'edf2c45b-d889-11e3-86df-0800274fb806': {'status': 'PRIMARY', 'is_alive': True, 'threads': {}}} activities = }

So the server is back online, but Fabric still considers it faulty. To add the server back into rotation, we need to look at the server commands:

[vagrant@store ~]$ mysqlfabric help server Commands available in group 'server' are: server set_weight uuid weight [--synchronous] server lookup_uuid address server set_mode uuid mode [--synchronous] server set_status uuid status [--update_only] [--synchronous]

The specific command we need is set_status, and in order to add the server back to the group, we need to change it’s status twice: first to SPARE and then back to SECONDARY. You can see what happens if we try to set it to SECONDARY directly:

[vagrant@store ~]$ mysqlfabric server set_status e826d4ab-d889-11e3-86df-0800274fb806 SECONDARY Procedure : { uuid = 9a6f2273-d206-4fa8-80fb-6bce1e5262c8, finished = True, success = False, return = ServerError: Cannot change server's (e826d4ab-d889-11e3-86df-0800274fb806) status from (FAULTY) to (SECONDARY)., activities = }

So let’s try it the right way:

[vagrant@store ~]$ mysqlfabric server set_status e826d4ab-d889-11e3-86df-0800274fb806 SPARE Procedure : { uuid = c3a1c244-ea8f-4270-93ed-3f9dfbe879ea, finished = True, success = True, return = True, activities = } [vagrant@store ~]$ mysqlfabric server set_status e826d4ab-d889-11e3-86df-0800274fb806 SECONDARY Procedure : { uuid = 556f59ec-5556-4225-93c9-b9b29b577061, finished = True, success = True, return = True, activities = }

And check the group’s health again:

[vagrant@store ~]$ mysqlfabric group health mycluster Command : { success = True return = {'e245ec83-d889-11e3-86df-0800274fb806': {'status': 'SECONDARY', 'is_alive': True, 'threads': {}}, 'e826d4ab-d889-11e3-86df-0800274fb806': {'status': 'SECONDARY', 'is_alive': True, 'threads': {}}, 'edf2c45b-d889-11e3-86df-0800274fb806': {'status': 'PRIMARY', 'is_alive': True, 'threads': {}}} activities = }

In our next post, when we discuss how to use the Fabric aware connectors, we’ll also test other failure scenarios like hard VM shutdown and network errors, but for now, let’s try the same thing but on the PRIMARY node instead:

[vagrant@node3 ~]$ sudo service mysqld stop Stopping mysqld: [ OK ]

And let’s check the servers again:

[vagrant@store ~]$ mysqlfabric group lookup_servers mycluster Command : { success = True return = [{'status': 'SECONDARY', 'server_uuid': 'e245ec83-d889-11e3-86df-0800274fb806', 'mode': 'READ_ONLY', 'weight': 1.0, 'address': 'node1'}, {'status': 'PRIMARY', 'server_uuid': 'e826d4ab-d889-11e3-86df-0800274fb806', 'mode': 'READ_WRITE', 'weight': 1.0, 'address': 'node2'}, {'status': 'FAULTY', 'server_uuid': 'edf2c45b-d889-11e3-86df-0800274fb806', 'mode': 'READ_WRITE', 'weight': 1.0, 'address': 'node3'}] activities = }

We can see that MySQL Fabric successfully marked node3 as FAULTY, and promoted node2 to PRIMARY to resolve this. Once we start mysqld again on node3, we can add it back as SECONDARY using the same process of setting it’s status to SPARE first, as we did for node2 above.

Remember that unless failover_interval is greater than 0, MySQL Fabric will detect problems in an active group, but it won’t take any automatic action. We think it’s a good thing that the value for this variable in the documentation is 0, so that automatic failover is not enabled by default (if people follow the manual, of course), as even in mature HA solutions like Pacemaker, automatic failover is something that’s tricky to get right. But even without this, we believe the main benefit of using MySQL Fabric for promotion is that it takes care of reconfiguring replication for you, which should reduce the risk for error in this process, specially once the project becomes GA.

What’s next

In this post we’ve presented a basic replication setup managed by MySQL Fabric and reviewed a couple of failure scenarios, but many questions are left unanswered, among them:

  • What happens to clients connected with a Fabric aware driver when there is a status change in the cluster?
  • What happens when the XML-RPC server goes down?
  • How can we improve its availability?

We’ll try to answer these and other questions in our next post. If you have some questions of your own, please leave them in the comments section and we’ll address them in the next or other posts, depending on the topic.

The post High Availability with MySQL Fabric: Part I appeared first on MySQL Performance Blog.

Why ALTER TABLE runs faster on Percona Server 5.5 vs. MySQL 5.5

May 15, 2014 - 3:00am

Some of us Perconians are at OpenStack summit this week in Atlanta. Matt Griffin, our director of product management, tweeted about the turbo-hipster CI talk about their experience of ALTER TABLEs running faster on Percona Server. Oracle’s Morgan Tocker then tweeted in response, asking why this was the case. I decided that the simplest way to answer that was here in this post.

The reason for this is the expand_fast_index_creation feature of Percona Server. I did a quick schema change on MySQL 5.5 and Percona Server 5.5 to demonstrate this (in the talk, the speaker mentioned that these versions were used).

The schema modifications in the talk could fall in 2 categories, the ones that could use fast index creation and the ones that could not.

I did the following tests on my laptop, on a sysbench tale with 300k records.

Vanilla MySQL 5.5:

mysql> alter table sbtest1 add index idx_c(c); Query OK, 0 rows affected (4.37 sec)

Percona Server 5.5:

mysql> alter table sbtest1 add index idx_c(c); Query OK, 0 rows affected (3.90 sec)

We know that this used fast index creation from the 0 rows affected. In this case, there is nor substantial difference between the 2 servers, also probably my laptop with CPU frewquency scaling doesn’t have the most consistent performance in the world.

For the second schema change, I added a column which copies the table.

Vanilla MySQL 5.5:

mysql> alter table sbtest1 add column d int default 0; Query OK, 300000 rows affected (37.05 sec) Records: 300000 Duplicates: 0 Warnings: 0

Percona Server 5.5:

mysql> alter table sbtest1 add column d int default 0; Query OK, 300000 rows affected (9.51 sec) Records: 300000 Duplicates: 0 Warnings: 0

The reason for this speed difference is that in case of Percona Server, for the table copy, the table is created only with a primary key, and the secondary indexes are built at the end of the process (rather than on the fly). For more details, check Alexey’s blog post on this topic.

This can be tuned further, by tuning innodb_merge_sort_block_size (in Percona Server 5.6, this is replaced by innodb_sort_buffer_size).

mysql> select @@innodb_merge_sort_block_size/1024/1024; +------------------------------------------+ | @@innodb_merge_sort_block_size/1024/1024 | +------------------------------------------+ | 1.00000000 | +------------------------------------------+ 1 row in set (0.00 sec) mysql> set innodb_merge_sort_block_size=8*1024*1024; Query OK, 0 rows affected (0.00 sec) mysql> alter table sbtest1 add column d int default 0; Query OK, 300000 rows affected (8.61 sec) Records: 300000 Duplicates: 0 Warnings: 0

So, in order to be accurate, schema changes are faster in Percona Server if they are table copies and if the tables have secondary indexes.

The post Why ALTER TABLE runs faster on Percona Server 5.5 vs. MySQL 5.5 appeared first on MySQL Performance Blog.

Tips on benchmarking Go + MySQL

May 14, 2014 - 9:00am

We just released, as an open source release, our new percona-agent (https://github.com/percona/percona-agent), the agent to work with Percona Cloud Tools. This agent is written in Go.

I will give a webinar titled “Monitoring All MySQL Metrics with Percona Cloud Tools” on June 25 that will cover the new features in percona-agent and Percona Cloud Tools, where I will also explain how it works. You are welcome to register now and join me.

There will be more posts about percona-agent, but in the meantime I want to dedicate this one to Go, Go with MySQL and some performance topics.

I have had an interest in the Go programming language for a long time, but in initial versions I did not quite like the performance of the gorountine scheduler. See my report from more than two years ago on runtime: reduce scheduling contention for large $GOMAXPROCS.

Supposedly this performance issue was fixed in Go 1.1, so this is a good time to revisit my benchmark experiment.

A simple run of prime or fibonachi numbers calculation in N threas is quite boring, so I am going to run queries against Percona Server. Of course it adds some complication as there are more moving parts (i.e. go scheduler, go sql driver, MySQL by itself), but it just makes the experiment more interesting.

Source code of my benchmark: Go-pk-bench:
This is probably not the best example of how to code in Go, but that was not the point of this exercise. This post is really about some tips to take into account when writing an application in Go using a MySQL (Percona Server) database.

So, first, we will need a MySQL driver for Go. The one I used two years ago (https://github.com/Philio/GoMySQL) is quite outdated. It seems the most popular choice today is Go-MySQL-Driver, and this is the one we use for internal development. This driver is based on the standard Go “database/sql” package. This package kind of provides a standard Go-way to deal with SQL-like databases. “database/sql” seems to work out OK, with some questionable design decisions as for my taste. So using “database/sql” and Go-MySQL-Driver you will need to deal with some quirks like almost unmanageable connection pool.

The first thing you should take into account it is a proper setting of
runtime.GOMAXPROCS().

If you do not do that, Go scheduler will use the default, which is 1. That binary will use one and only 1 CPU (so much for a modern concurrent language).

The command runtime.GOMAXPROCS(runtime.NumCPU())
will prescribe to use all available CPUs. Always remember to use this if you care about multi-threaded performance.

The next problem I faced in the benchmark is that when I ran queries in a loop, i.e. to repeat as much possible…

rows, err := db.Query("select k from sbtest"+strconv.Itoa(tab+1)+" where id = "+strconv.Itoa(i))

… very soon we ran out of TCP ports. Apparently “database/sql” and Go-MySQL-Driver and its smart connection pool creates a NEW CONNECTION for each query. I can explain why this happens, but using the following statement:

'db.SetMaxIdleConns(10000)'

helps (I hope somebody with “database/sql” knowledge will explain what it is doing).

So after these adjustments we now can run the benchmark, which by query you see is quite simple – run primary key lookups against Percona Server which we know scales perfectly in this scenario (I used sysbench to create 64 tables 1mln rows each, all this fits into memory). I am going to run this benchmark with 1, 2, 4, 8, 16, 24, 32, 48, 64 user threads.

Below you can see graphs for MySQL Throughput and CPU Usage (both graph are built using new metrics graphing in Percona Cloud Tools)

MySQL Throughput (user threads are increasing from 1 to 64)

CPU Usage (user threads are increasing from 1 to 64)

I would say the result scales quite nicely, at least it is really much better than it was two years ago. It is interesting to compare with something, so there is a graph from an identical run, but now I will use sysbench + lua for main workload driver.

MySQL Throughput (sysbench, user threads are increasing from 1 to 64)

CPU Usage (sysbench, user threads are increasing from 1 to 64)

From the graphs (this is what I like them for), we can clearly see increases in User CPU utilization (and actually we are able to use CPUs on 100% in user+system usage) and it clearly corresponds to increased throughput.

And if you are a fan of raw numbers:

MySQL Throughput, q/s (more is better) Threads | Go-MySQL | sysbench 1 | 13,189 | 16,765 2 | 26,837 | 33,534 4 | 52,629 | 65,943 8 | 95,553 | 116,953 16 | 146,979 | 182,781 24 | 169,739 | 231,895 32 | 181,334 | 245,939 48 | 198,238 | 250,497 64 | 207,732 | 251,972

(one with a knowledge of Universal Scalability Law can draw a prediction till 1000 threads, I leave it as a homework)

So, in conclusion, I can say that Go+MySQL is able to show decent results, but it is still not as effective as plan raw C (sysbench), as it seems it spends some extra CPU time in system calls.

If you want to try these new graphs in Percona Cloud Tools and see how it works with your system – join the free beta!

The post Tips on benchmarking Go + MySQL appeared first on MySQL Performance Blog.

max_allowed_packet and binary log corruption in MySQL

May 14, 2014 - 1:00am

The combination of max_allowed_packet variable and replication in MySQL is a common source of headaches. In a nutshell, max_allowed_packet is the maximum size of a MySQL network protocol packet that the server can create or read. It has a default value of 1MB (<= 5.6.5) or 4MB (>= 5.6.6) and a maximum size of 1GB. This adds some constraints in our replication environment:

  • The master server shouldn’t write events to the binary log larger than max_allowed_packet
  • All the slaves in the replication chain should have the same max_allowed_packet as the master server

Sometimes, even following those two basic rules we can have problems.

For example, there are situations (also called bugs) where the master writes more data than the max_allowed_packet limit causing the slaves to stop working. In order to fix this Oracle created a new variable called slave_max_allowed_packet. This new configuration variable available from 5.1.64, 5.5.26 and 5.6.6 overrides the max_allowed_packet value for slave threads. Therefore, regardless of the max_allowed_packet value the slaves’ threads will have 1GB limit, the default value of slave_max_allowed_packet. Nice trick that works as expected.

Sometimes even with that workaround we can get the max_allowed_packet error in the slave servers. That means that there is a packet larger than 1GB, something that shouldn’t happen in a normal situation. Why? Usually it is caused by a binary log corruption. Let’s see the following example:

Slave stops working with the following message:

Last_IO_Error: Got fatal error 1236 from master when reading data from binary log: 'log event entry exceeded max_allowed_packet; Increase max_allowed_packet on master'

The important part is “got fatal error 1236 from master”. The master cannot read the event it wrote to the binary log seconds ago. To check the problem we can:

  • Use mysqlbinlog to read the binary log from the position it failed with –start-position.

This is an example taken from our Percona Forums:

#121003 5:22:26 server id 1 end_log_pos 398528 # Unknown event # at 398528 #960218 6:48:44 server id 1813111337 end_log_pos 1835008 # Unknown event ERROR: Error in Log_event::read_log_event(): 'Event too big', data_len: 1953066613, event_type: 8 DELIMITER ; # End of log file

Check the size of the event, 1953066613 bytes. Or the “Unknown event” messages. Something is clearly wrong there. Another usual thing to check is the server id that sometimes doesn’t correspond with the real value. In this example the person who posted the binary log event confirmed that the server id was wrong.

  • Check master’s error log.

[ERROR] Error in Log_event::read_log_event(): 'Event too big', data_len: 1953066613, event_type: 8

Again, the event is bigger than expected. There is no way the master and slave can read/write it, so the solution is to skip that event in the slave and rotate the logs on the master. Then, use pt-table-checksum to check data consistency.

MySQL 5.6 includes replication checksums to avoid problems with log corruptions. You can read more about it in Stephan’s blog post.

Conclusion

Errors on slave servers about max_allowed_packet can be caused by very different reasons. Although binary log corruption is not a common one, it is something worth checking when you have run out of ideas.

The post max_allowed_packet and binary log corruption in MySQL appeared first on MySQL Performance Blog.

Using Percona Server 5.6 with the Docker open-source engine

May 13, 2014 - 12:00am

There are a couple of posts about setting up Percona XtraDB Cluster on Vagrant and Percona Server on MySQL Sandbox – those are two of the top tools used by the Percona Support team for testing and bug processing among other things.

In this post, however, I will show you how to use Docker with Percona Server on Ubuntu 12.04.

As per Docker’s official site:

Docker is an open-source engine that automates the deployment of any application as a lightweight, portable, self-sufficient container that will run virtually anywhere.

Docker containers can encapsulate any payload, and will run consistently on and between virtually any server. The same container that a developer builds and tests on a laptop will run at scale, in production*, on VMs, bare-metal servers, OpenStack clusters, public instances, or combinations of the above.

To install Docker on Ubuntu 12.04 you need to follow instructions from Docker’s official documentation:
http://docs.docker.io/installation/ubuntulinux/#ubuntu-precise-1204-lts-64-bit

After installing Docker, you may either download docker images via ‘docker pull’ and store docker images on your server so you can spin a new docker container in an instance or you may choose to do a ‘docker run’ on the terminal and implicitly download/store the specific docker image from index.docker.io and run the image afterward.

root@Perconallc-Support / # docker images | grep centos centos centos6 0b443ba03958 2 weeks ago 297.6 MB centos latest 0b443ba03958 2 weeks ago 297.6 MB centos 6.4 539c0211cd76 13 months ago 300.6 MB

Let us create a CentOS docker container by running the following command:

root@Perconallc-Support / # docker run -i -t centos:latest bash bash-4.1# cat /etc/redhat-release CentOS release 6.5 (Final)

As you may have noticed, we have just created a new interactive (-i) CentOS 6.5 docker container and ran bash in a single line of command. Detaching from the container is as easy as typing CTRL+p – CTRL+q, you’ll get to your terminal if you typed the right keys.

Verify the active containers:

root@Perconallc-Support / # docker ps CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES 202765d754b7 centos:centos6 bash 11 minutes ago Up 11 minutes elegant_rosalind

To list all existing containers active or not use the following command:

root@Perconallc-Support / # docker ps -a CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES 202765d754b7 centos:centos6 bash 12 minutes ago Up 12 minutes elegant_rosalind aae47d193a22 centos:6.4 bash 2 hours ago Exited (1) 2 hours ago boring_bardeen

To attach to the active docker container:

root@Perconallc-Support / # docker attach 202765d754b7 bash-4.1#

*Tip: Hit enter twice to get to the container’s bash prompt.*

Install Percona Server 5.6

Now that you have a working docker container you will then have to install the needed packages and repository.

bash-4.1# rpm -Uhv http://www.percona.com/downloads/percona-release/percona-release-0.0-1.x86_64.rpm Retrieving http://www.percona.com/downloads/percona-release/percona-release-0.0-1.x86_64.rpm Preparing... ########################################### [100%] 1:percona-release ########################################### [100%] bash-4.1# yum install Percona-Server-server-56 Percona-Server-client-56 Percona-Server-shared-56 Loaded plugins: fastestmirror Loading mirror speeds from cached hostfile * base: ftp.hosteurope.de * extras: ftp.plusline.de * updates: ftp.plusline.de Setting up Install Process Resolving Dependencies --> Running transaction check ---> Package Percona-Server-client-56.x86_64 0:5.6.17-rel65.0.el6 will be installed --> Processing Dependency: /usr/bin/perl for package: Percona-Server-client-56-5.6.17-rel65.0.el6.x86_64 ---> Package Percona-Server-server-56.x86_64 0:5.6.17-rel65.0.el6 will be installed --> Processing Dependency: libaio.so.1(LIBAIO_0.1)(64bit) for package: Percona-Server-server-56-5.6.17-rel65.0.el6.x86_64 --> Processing Dependency: libaio.so.1(LIBAIO_0.4)(64bit) for package: Percona-Server-server-56-5.6.17-rel65.0.el6.x86_64 --> Processing Dependency: libaio.so.1()(64bit) for package: Percona-Server-server-56-5.6.17-rel65.0.el6.x86_64 ---> Package Percona-Server-shared-56.x86_64 0:5.6.17-rel65.0.el6 will be installed --> Running transaction check ---> Package libaio.x86_64 0:0.3.107-10.el6 will be installed ---> Package perl.x86_64 4:5.10.1-136.el6 will be installed --> Processing Dependency: perl-libs = 4:5.10.1-136.el6 for package: 4:perl-5.10.1-136.el6.x86_64 --> Processing Dependency: perl-libs for package: 4:perl-5.10.1-136.el6.x86_64 --> Processing Dependency: perl(version) for package: 4:perl-5.10.1-136.el6.x86_64 --> Processing Dependency: perl(Pod::Simple) for package: 4:perl-5.10.1-136.el6.x86_64 --> Processing Dependency: perl(Module::Pluggable) for package: 4:perl-5.10.1-136.el6.x86_64 --> Processing Dependency: libperl.so()(64bit) for package: 4:perl-5.10.1-136.el6.x86_64 --> Running transaction check ---> Package perl-Module-Pluggable.x86_64 1:3.90-136.el6 will be installed ---> Package perl-Pod-Simple.x86_64 1:3.13-136.el6 will be installed --> Processing Dependency: perl(Pod::Escapes) >= 1.04 for package: 1:perl-Pod-Simple-3.13-136.el6.x86_64 ---> Package perl-libs.x86_64 4:5.10.1-136.el6 will be installed ---> Package perl-version.x86_64 3:0.77-136.el6 will be installed --> Running transaction check ---> Package perl-Pod-Escapes.x86_64 1:1.04-136.el6 will be installed --> Finished Dependency Resolution Dependencies Resolved ======================================================================================================================================================================== Package Arch Version Repository Size ======================================================================================================================================================================== Installing: Percona-Server-client-56 x86_64 5.6.17-rel65.0.el6 percona 6.8 M Percona-Server-server-56 x86_64 5.6.17-rel65.0.el6 percona 19 M Percona-Server-shared-56 x86_64 5.6.17-rel65.0.el6 percona 714 k Installing for dependencies: libaio x86_64 0.3.107-10.el6 base 21 k perl x86_64 4:5.10.1-136.el6 base 10 M perl-Module-Pluggable x86_64 1:3.90-136.el6 base 40 k perl-Pod-Escapes x86_64 1:1.04-136.el6 base 32 k perl-Pod-Simple x86_64 1:3.13-136.el6 base 212 k perl-libs x86_64 4:5.10.1-136.el6 base 578 k perl-version x86_64 3:0.77-136.el6 base 51 k Transaction Summary ======================================================================================================================================================================== Install 10 Package(s) Total download size: 38 M Installed size: 158 M Is this ok [y/N]: y Downloading Packages: (1/10): Percona-Server-client-56-5.6.17-rel65.0.el6.x86_64.rpm | 6.8 MB 00:02 (2/10): Percona-Server-server-56-5.6.17-rel65.0.el6.x86_64.rpm | 19 MB 00:00 (3/10): Percona-Server-shared-56-5.6.17-rel65.0.el6.x86_64.rpm | 714 kB 00:00 (4/10): libaio-0.3.107-10.el6.x86_64.rpm | 21 kB 00:00 (5/10): perl-5.10.1-136.el6.x86_64.rpm | 10 MB 00:00 (6/10): perl-Module-Pluggable-3.90-136.el6.x86_64.rpm | 40 kB 00:00 (7/10): perl-Pod-Escapes-1.04-136.el6.x86_64.rpm | 32 kB 00:00 (8/10): perl-Pod-Simple-3.13-136.el6.x86_64.rpm | 212 kB 00:00 (9/10): perl-libs-5.10.1-136.el6.x86_64.rpm | 578 kB 00:00 (10/10): perl-version-0.77-136.el6.x86_64.rpm | 51 kB 00:00 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ Total 7.4 MB/s | 38 MB 00:05 Running rpm_check_debug Running Transaction Test Transaction Test Succeeded Running Transaction Warning: RPMDB altered outside of yum. ** Found 2 pre-existing rpmdb problem(s), 'yum check' output follows: udev-147-2.51.el6.x86_64 has missing requires of /sbin/service udev-147-2.51.el6.x86_64 has missing requires of MAKEDEV >= ('0', '3.11', None) Installing : Percona-Server-shared-56-5.6.17-rel65.0.el6.x86_64 1/10 Installing : 1:perl-Pod-Escapes-1.04-136.el6.x86_64 2/10 Installing : 1:perl-Module-Pluggable-3.90-136.el6.x86_64 3/10 Installing : 4:perl-libs-5.10.1-136.el6.x86_64 4/10 Installing : 3:perl-version-0.77-136.el6.x86_64 5/10 Installing : 1:perl-Pod-Simple-3.13-136.el6.x86_64 6/10 Installing : 4:perl-5.10.1-136.el6.x86_64 7/10 Installing : Percona-Server-client-56-5.6.17-rel65.0.el6.x86_64 8/10 Installing : libaio-0.3.107-10.el6.x86_64 9/10 Installing : Percona-Server-server-56-5.6.17-rel65.0.el6.x86_64 10/10 ... Installed: Percona-Server-client-56.x86_64 0:5.6.17-rel65.0.el6 Percona-Server-server-56.x86_64 0:5.6.17-rel65.0.el6 Percona-Server-shared-56.x86_64 0:5.6.17-rel65.0.el6 Dependency Installed: libaio.x86_64 0:0.3.107-10.el6 perl.x86_64 4:5.10.1-136.el6 perl-Module-Pluggable.x86_64 1:3.90-136.el6 perl-Pod-Escapes.x86_64 1:1.04-136.el6 perl-Pod-Simple.x86_64 1:3.13-136.el6 perl-libs.x86_64 4:5.10.1-136.el6 perl-version.x86_64 3:0.77-136.el6 Complete! bash-4.1# /etc/init.d/mysql start Starting MySQL (Percona Server). SUCCESS! bash-4.1# mysql Welcome to the MySQL monitor. Commands end with ; or \g. Your MySQL connection id is 1 Server version: 5.6.17-65.0-56 Percona Server (GPL), Release 65.0, Revision 587 Copyright (c) 2009-2014 Percona LLC and/or its affiliates Copyright (c) 2000, 2014, Oracle and/or its affiliates. All rights reserved. Oracle is a registered trademark of Oracle Corporation and/or its affiliates. Other names may be trademarks of their respective owners. Type 'help;' or '\h' for help. Type '\c' to clear the current input statement. mysql>

There you have it, a freshly installed Percona Server 5.6.17 on CentOS 6.5 Linux container. Yay!

You can now create a new MySQL user to access the server outside the container:

mysql> grant all privileges on *.* to 'test_user'@'%' identified by 'test_pass'; Query OK, 0 rows affected (0.00 sec) mysql> flush privileges; Query OK, 0 rows affected (0.00 sec) root@Perconallc-Support / # mysql -h 172.17.0.2 -utest_user -p Enter password: Welcome to the MySQL monitor. Commands end with ; or \g. Your MySQL connection id is 4 Server version: 5.6.17-65.0-56 Percona Server (GPL), Release 65.0, Revision 587 Copyright (c) 2009-2014 Percona LLC and/or its affiliates Copyright (c) 2000, 2014, Oracle and/or its affiliates. All rights reserved. Oracle is a registered trademark of Oracle Corporation and/or its affiliates. Other names may be trademarks of their respective owners. Type 'help;' or '\h' for help. Type '\c' to clear the current input statement. mysql>

We’re basically following installation instructions for Percona Server from the documentation.

Just the same way as you would do on any server, you can install other equally important Percona software on the same container to complete your docker environment.

As an added bonus, you can contribute to the Docker Community by commiting your container and pushing it to the docker registry.

Summary

I’ve shown you how easy it is to spin a docker container and install Percona Server 5.6 in it. This is by far one of the fastest ways to create test/staging environments to simulate production servers. For further reading you may want to read Docker’s official documentation here.

I hope that this has piqued your interest to try it out yourself. And if that happens we would love to know how Percona Server and other Percona software perform on your docker environment. Cheers!

The post Using Percona Server 5.6 with the Docker open-source engine appeared first on MySQL Performance Blog.

Practical MySQL performance optimization: May 14 Webinar

May 12, 2014 - 3:00am

Achieving the best possible MySQL Performance doesn’t have to be complicated. It’s all about knowing which tools are designed for the task at hand – along with some basic (yet often overlooked) best practices.

Join me Wednesday, May 14 at 10 a.m. Pacific for a free webinar titled, “Practical MySQL performance optimization.” I’ll be sharing the main areas for improving MySQL performance – along with what to specifically focus on in each. These will include:

  • Hardware
  • MySQL Configuration
  • Schema and Queries
  • Application Architecture

And as I mentioned earlier, I’ll also show you the best tools for the job and how to use them efficiently. This will help you optimize your time by focusing on the queries that are most important for your application.

At the end of this webinar, you will know how to optimize MySQL performance in the most practical way possible. The webinar is free but I recommend registering now to reserve your spot. I hope to see you on May 14!

The post Practical MySQL performance optimization: May 14 Webinar appeared first on MySQL Performance Blog.

Pages

Contact Us 24 Hours A Day
Support Contact us 24×7
Emergency? Contact us for help now!
Sales North America (888) 316-9775 or
(208) 473-2904
Sales
Europe
+44-208-133-0309 (UK)
0-800-051-8984 (UK Toll Free)
0-800-181-0665 (GER Toll Free)
More Numbers
Training (855) 55TRAIN or
(925) 271-5054

 

Share This
]]>