Configuring MySQL for Best Results

PMM supports all commonly used variants of MySQL, including Percona Server, MariaDB, and Amazon RDS. To prevent data loss and performance issues, PMM does not automatically change MySQL configuration. However, there are certain recommended settings that help maximize monitoring efficiency. These recommendations depend on the variant and version of MySQL you are using, and mostly apply to very high loads.

PMM can collect query data either from the slow query log or from Performance Schema. The slow query log provides maximum details, but can impact performance on heavily loaded systems. On Percona Server the query sampling feature may reduce the performance impact.

Performance Schema is generally better for recent versions of other MySQL variants. For older MySQL variants, which have neither sampling, nor Performance Schema, configure logging only slow queries.

You can add configuration examples provided in this guide to my.cnf and restart the server or change variables dynamically using the following syntax:

SET GLOBAL <var_name>=<var_value>

The following sample configurations can be used depending on the variant and version of MySQL:

  • If you are running Percona Server (or XtraDB Cluster), configure the slow query log to capture all queries and enable sampling. This will provide the most amount of information with the lowest overhead.

    log_output=file
    slow_query_log=ON
    long_query_time=0
    log_slow_rate_limit=100
    log_slow_rate_type=query
    log_slow_verbosity=full
    log_slow_admin_statements=ON
    log_slow_slave_statements=ON
    slow_query_log_always_write_time=1
    slow_query_log_use_global_control=all
    innodb_monitor_enable=all
    userstat=1
    
  • If you are running MySQL 5.6+ or MariaDB 10.0+, configure Configuring Performance Schema.

    innodb_monitor_enable=all
    performance_schema=ON
    
  • If you are running MySQL 5.5 or MariaDB 5.5, configure logging only slow queries to avoid high performance overhead.

    Note

    This may affect the quality of monitoring data gathered by QAN.

    log_output=file
    slow_query_log=ON
    long_query_time=0
    log_slow_admin_statements=ON
    log_slow_slave_statements=ON
    

Creating a MySQL User Account to Be Used with PMM

When adding a MySQL instance to monitoring, you can specify the MySQL server superuser account credentials. However, monitoring with the superuser account is not secure. If you also specify the --create-user option, it will create a user with only the necessary privileges for collecting data.

See also

Using the pmm-admin add command to add a monitoring service
Adding MySQL metrics service

You can also set up the pmm user manually with necessary privileges and pass its credentials when adding the instance.

To enable complete MySQL instance monitoring, a command similar to the following is recommended:

sudo pmm-admin add mysql --user root --password root --create-user

The superuser credentials are required only to set up the pmm user with necessary privileges for collecting data. If you want to create this user yourself, the following privileges are required:

GRANT SELECT, PROCESS, SUPER, REPLICATION CLIENT, RELOAD ON *.* TO 'pmm'@' localhost' IDENTIFIED BY 'pass' WITH MAX_USER_CONNECTIONS 10;
GRANT SELECT, UPDATE, DELETE, DROP ON performance_schema.* TO 'pmm'@'localhost';

If the pmm user already exists, simply pass its credential when you add the instance:

sudo pmm-admin add mysql --user pmm --password pass

For more information, run as root pmm-admin add mysql --help.

Configuring the slow query log in Percona Server

If you are running Percona Server, a properly configured slow query log will provide the most amount of information with the lowest overhead. In other cases, use Performance Schema if it is supported.

By definition, the slow query log is supposed to capture only slow queries. These are the queries the execution time of which is above a certain threshold. The threshold is defined by the long_query_time variable.

In heavily loaded applications, frequent fast queries can actually have a much bigger impact on performance than rare slow queries. To ensure comprehensive analysis of your query traffic, set the long_query_time to 0 so that all queries are captured.

However, capturing all queries can consume I/O bandwidth and cause the slow query log file to quickly grow very large. To limit the amount of queries captured by the slow query log, use the query sampling feature available in Percona Server.

The log_slow_rate_limit variable defines the fraction of queries captured by the slow query log. A good rule of thumb is to have approximately 100 queries logged per second. For example, if your Percona Server instance processes 10_000 queries per second, you should set log_slow_rate_limit to 100 and capture every 100th query for the slow query log.

Note

When using query sampling, set log_slow_rate_type to query so that it applies to queries, rather than sessions.

It is also a good idea to set log_slow_verbosity to full so that maximum amount of information about each captured query is stored in the slow query log.

A possible problem with query sampling is that rare slow queries might not get captured at all. To avoid this, use the slow_query_log_always_write_time variable to specify which queries should ignore sampling. That is, queries with longer execution time will always be captured by the slow query log.

By default, slow query log settings apply only to new sessions. If you want to configure the slow query log during runtime and apply these settings to existing connections, set the slow_query_log_use_global_control variable to all.

Configuring Performance Schema

The default source of query data for PMM is the slow query log. It is available in MySQL 5.1 and later versions. Starting from MySQL 5.6 (including Percona Server 5.6 and later), you can choose to parse query data from the Performance Schema instead of slow query log. Starting from MySQL 5.6.6, Performance Schema is enabled by default.

Performance Schema is not as data-rich as the slow query log, but it has all the critical data and is generally faster to parse. If you are not running Percona Server (which supports sampling for the slow query log), then Performance Schema is a better alternative.

To use Performance Schema, set the performance_schema variable to ON:

mysql> SHOW VARIABLES LIKE 'performance_schema';
+--------------------+-------+
| Variable_name      | Value |
+--------------------+-------+
| performance_schema | ON    |
+--------------------+-------+

If this variable is not set to ON, add the the following lines to the MySQL configuration file my.cnf and restart MySQL:

[mysql]
performance_schema=ON

If you are running a custom Performance Schema configuration, make sure that the statements_digest consumer is enabled:

mysql> select * from setup_consumers;
+----------------------------------+---------+
| NAME                             | ENABLED |
+----------------------------------+---------+
| events_stages_current            | NO      |
| events_stages_history            | NO      |
| events_stages_history_long       | NO      |
| events_statements_current        | YES     |
| events_statements_history        | YES     |
| events_statements_history_long   | NO      |
| events_transactions_current      | NO      |
| events_transactions_history      | NO      |
| events_transactions_history_long | NO      |
| events_waits_current             | NO      |
| events_waits_history             | NO      |
| events_waits_history_long        | NO      |
| global_instrumentation           | YES     |
| thread_instrumentation           | YES     |
| statements_digest                | YES     |
+----------------------------------+---------+
15 rows in set (0.00 sec)

Important

Performance Schema instrumentation is enabled by default in MySQL 5.6.6 and later versions. It is not available at all in MySQL versions prior to 5.6.

If certain instruments are not enabled, you will not see the corresponding graphs in the MySQL Performance Schema Dashboard dashboard. To enable full instrumentation, set the option --performance_schema_instrument to '%=on' when starting the MySQL server.

$ mysqld --performance-schema-instrument='%=on'

This option can cause additional overhead and should be used with care.

If the instance is already running, configure the QAN agent to collect data from Performance Schema:

  1. Open the PMM Query Analytics dashboard.
  2. Click the Settings button.
  3. Open the Settings section.
  4. Select Performance Schema in the Collect from drop-down list.
  5. Click Apply to save changes.

If you are adding a new monitoring instance with the pmm-admin tool, use the --query-source perfschema option:

Run this command as root or by using the sudo command

pmm-admin add mysql --user root --password root --create-user --query-source perfschema

For more information, run pmm-admin add mysql --help.

Configuring MySQL 8.0 for PMM

MySQL 8 (in version 8.0.4) changes the way clients are authenticated by default. The default_authentication_plugin parameter is set to caching_sha2_password. This change of the default value implies that MySQL drivers must support the SHA-256 authentication. Also, the communication channel with MySQL 8 must be encrypted when using caching_sha2_password.

The MySQL driver used with PMM does not yet support the SHA-256 authentication.

With currently supported versions of MySQL, PMM requires that a dedicated MySQL user be set up. This MySQL user should be authenticated using the mysql_native_password plugin. Although MySQL is configured to support SSL clients, connections to MySQL Server are not encrypted.

There are two workarounds to be able to add MySQL Server version 8.0.4 or higher as a monitoring service to PMM:

  1. Alter the MySQL user that you plan to use with PMM
  2. Change the global MySQL configuration

Altering the MySQL User

Provided you have already created the MySQL user that you plan to use with PMM, alter this user as follows:

mysql> ALTER USER pmm@'localhost' IDENTIFIED WITH mysql_native_password BY '$eCR8Tp@s$w*rD';

Then, pass this user to pmm-admin add as the value of the --user parameter.

This is a preferred approach as it only weakens the security of one user.

Changing the global MySQL Configuration

A less secure approach is to set default_authentication_plugin to the value mysql_native_password before adding it as a monitoring service. Then, restart your MySQL Server to apply this change.

[mysqld]
default_authentication_plugin=mysql_native_password

See also

Creating a MySQL User for PMM
What privileges are required to monitor a MySQL instance?
More information about adding the MySQL query analytics monitoring service
Adding MySQL query analytics service
MySQL Server Blog: MySQL 8.0.4 : New Default Authentication Plugin : caching_sha2_password
https://mysqlserverteam.com/mysql-8-0-4-new-default-authentication-plugin-caching_sha2_password/
MySQL Documentation: Authentication Plugins
https://dev.mysql.com/doc/refman/8.0/en/authentication-plugins.html
MySQL Documentation: Native Pluggable Authentication
https://dev.mysql.com/doc/refman/8.0/en/native-pluggable-authentication.html

Settings for Dashboards

Not all dashboards in Metrics Monitor are available by default for all MySQL variants and configurations: Oracle‘s MySQL, Percona Server. or MariaDB. Some graphs require Percona Server, specialized plugins, or additional configuration.

Collecting metrics and statistics for graphs increases overhead. You can keep collecting and graphing low-overhead metrics all the time, and enable high-overhead metrics only when troubleshooting problems.

See also

More information about PMM dashboards
Metrics Monitor

MySQL InnoDB Metrics

InnoDB metrics provide detailed insight about InnoDB operation. Although you can select to capture only specific counters, their overhead is low even when they all are enabled all the time. To enable all InnoDB metrics, set the global variable innodb_monitor_enable to all:

mysql> SET GLOBAL innodb_monitor_enable=all

See also

MySQL Documentation: innodb_monitor_enable variable
https://dev.mysql.com/doc/refman/5.7/en/innodb-parameters.html#sysvar_innodb_monitor_enable

MySQL User Statistics

User statistics is a feature of Percona Server and MariaDB. It provides information about user activity, individual table and index access. In some cases, collecting user statistics can lead to high overhead, so use this feature sparingly.

To enable user statistics, set the userstat variable to 1.

See also

Percona Server Documentation: userstat
https://www.percona.com/doc/percona-server/5.7/diagnostics/user_stats.html#userstat
MySQL Documentation
Setting variables

Percona Server Query Response Time Distribution

Query response time distribution is a feature available in Percona Server. It provides information about changes in query response time for different groups of queries, often allowing to spot performance problems before they lead to serious issues.

To enable collection of query response time:

  1. Install the QUERY_RESPONSE_TIME plugins:

    mysql> INSTALL PLUGIN QUERY_RESPONSE_TIME_AUDIT SONAME 'query_response_time.so';
    mysql> INSTALL PLUGIN QUERY_RESPONSE_TIME SONAME 'query_response_time.so';
    mysql> INSTALL PLUGIN QUERY_RESPONSE_TIME_READ SONAME 'query_response_time.so';
    mysql> INSTALL PLUGIN QUERY_RESPONSE_TIME_WRITE SONAME 'query_response_time.so';
    
  2. Set the global varible query_response_time_stats to ON:

    mysql> SET GLOBAL query_response_time_stats=ON;
    

Executing Custom Queries

Starting from the version 1.15.0, PMM provides user the ability to take a SQL SELECT statement and turn the result set into metric series in PMM. The queries are executed at the LOW RESOLUTION level, which by default is every 60 seconds. A key advantage is that you can extend PMM to profile metrics unique to your environment (see users table example below), or to introduce support for a table that isn’t part of PMM yet. This feature is on by default and only requires that you edit the configuration file and use vaild YAML syntax. The default configuration file location is /usr/local/percona/pmm-client/queries-mysqld.yml.

Example - Application users table

We’re going to take a users table of upvotes and downvotes and turn this into two metric series, with a set of labels. Labels can also store a value. You can filter against labels.

Browsing metrics series using Advanced Data Exploration Dashboard

Lets look at the output so we understand the goal - take data from a MySQL table and store in PMM, then display as a metric series. Using the Advanced Data Exploration Dashboard you can review your metric series.

MySQL table

Lets assume you have the following users table that includes true/false, string, and integer types.

SELECT * FROM `users`
+----+------+--------------+-----------+------------+-----------+---------------------+--------+---------+-----------+
| id | app  | user_type    | last_name | first_name | logged_in | active_subscription | banned | upvotes | downvotes |
+----+------+--------------+-----------+------------+-----------+---------------------+--------+---------+-----------+
|  1 | app2 | unprivileged | Marley    | Bob        |         1 |                   1 |      0 |     100 |        25 |
|  2 | app3 | moderator    | Young     | Neil       |         1 |                   1 |      1 |     150 |        10 |
|  3 | app4 | unprivileged | OConnor   | Sinead     |         1 |                   1 |      0 |      25 |        50 |
|  4 | app1 | unprivileged | Yorke     | Thom       |         0 |                   1 |      0 |     100 |       100 |
|  5 | app5 | admin        | Buckley   | Jeff       |         1 |                   1 |      0 |     175 |         0 |
+----+------+--------------+-----------+------------+-----------+---------------------+--------+---------+-----------+

Explaining the YAML syntax

We’ll go through a simple example and mention what’s required for each line. The metric series is constructed based on the first line and appends the column name to form metric series. Therefore the number of metric series per table will be the count of columns that are of type GAUGE or COUNTER. This metric series will be called app1_users_metrics_downvotes:

app1_users_metrics:                                 ## leading section of your metric series.
  query: "SELECT * FROM app1.users"                 ## Your query. Don't forget the schema name.
  metrics:                                          ## Required line to start the list of metric items
    - downvotes:                                    ## Name of the column returned by the query. Will be appended to the metric series.
        usage: "COUNTER"                            ## Column value type.  COUNTER will make this a metric series.
        description: "Number of upvotes"            ## Helpful description of the column.

Full queries-mysqld.yml example

Each column in the SELECT is named in this example, but that isn’t required, you can use a SELECT * as well. Notice the format of schema.table for the query is included.

---
app1_users_metrics:
  query: "SELECT app,first_name,last_name,logged_in,active_subscription,banned,upvotes,downvotes FROM app1.users"
  metrics:
    - app:
        usage: "LABEL"
        description: "Name of the Application"
    - user_type:
        usage: "LABEL"
        description: "User's privilege level within the Application"
    - first_name:
        usage: "LABEL"
        description: "User's First Name"
    - last_name:
        usage: "LABEL"
        description: "User's Last Name"
    - logged_in:
        usage: "LABEL"
        description: "User's logged in or out status"
    - active_subscription:
        usage: "LABEL"
        description: "Whether User has an active subscription or not"
    - banned:
        usage: "LABEL"
        description: "Whether user is banned or not"
    - upvotes:
        usage: "COUNTER"
        description: "Count of upvotes the User has earned. Upvotes once granted cannot be revoked, so the number can only increase."
    - downvotes:
        usage: "GAUGE"
        description: "Count of downvotes the User has earned. Downvotes can be revoked so the number can increase as well as decrease."
...

This custom query description should be placed in a YAML file (queries-mysqld.yml by default) on the corresponding server with MySQL.

In order to modify the location of the queries file, for example if you have multiple mysqld instances per server, you need to explicitly identify to the PMM Server MySQL with the pmm-admin add command after the double dash:

pmm-admin add mysql:metrics ... -- --queries-file-name=/usr/local/percona/pmm-client/query.yml