MySQL connector#

The MySQL connector allows querying and creating tables in an external MySQL instance. This can be used to join data between different systems like MySQL and Hive, or between two different MySQL instances.

Requirements#

To connect to MySQL, you need:

MySQL 5.7, 8.0 or higher.
Network access from the Trino coordinator and workers to MySQL. Port 3306 is the default port.

Configuration#

To configure the MySQL connector, create a catalog properties file in etc/catalog named, for example, example.properties, to mount the MySQL connector as the mysql catalog. Create the file with the following contents, replacing the connection properties as appropriate for your setup:

connector.name=mysql
connection-url=jdbc:mysql://example.net:3306
connection-user=root
connection-password=secret

The connection-url defines the connection information and parameters to pass to the MySQL JDBC driver. The supported parameters for the URL are available in the MySQL Developer Guide.

For example, the following connection-url allows you to require encrypted connections to the MySQL server:

connection-url=jdbc:mysql://example.net:3306?sslMode=REQUIRED

The connection-user and connection-password are typically required and determine the user credentials for the connection, often a service user. You can use secrets to avoid actual values in the catalog properties files.

Connection security#

If you have TLS configured with a globally-trusted certificate installed on your data source, you can enable TLS between your cluster and the data source by appending a parameter to the JDBC connection string set in the connection-url catalog configuration property.

For example, with version 8.0 of MySQL Connector/J, use the sslMode parameter to secure the connection with TLS. By default the parameter is set to PREFERRED which secures the connection if enabled by the server. You can also set this parameter to REQUIRED which causes the connection to fail if TLS is not established.

You can set the sslMode parameter in the catalog configuration file by appending it to the connection-url configuration property:

connection-url=jdbc:mysql://example.net:3306/?sslMode=REQUIRED

For more information on TLS configuration options, see the MySQL JDBC security documentation.

Data source authentication#

The connector can provide credentials for the data source connection in multiple ways:

inline, in the connector configuration file
in a separate properties file
in a key store file
as extra credentials set when connecting to Trino

You can use secrets to avoid storing sensitive values in the catalog properties files.

The following table describes configuration properties for connection credentials:

Property name	Description
`credential-provider.type`	Type of the credential provider. Must be one of `INLINE`, `FILE`, or `KEYSTORE`; defaults to `INLINE`.
`connection-user`	Connection user name.
`connection-password`	Connection password.
`user-credential-name`	Name of the extra credentials property, whose value to use as the user name. See `extraCredentials` in Parameter reference.
`password-credential-name`	Name of the extra credentials property, whose value to use as the password.
`connection-credential-file`	Location of the properties file where credentials are present. It must contain the `connection-user` and `connection-password` properties.
`keystore-file-path`	The location of the Java Keystore file, from which to read credentials.
`keystore-type`	File format of the keystore file, for example `JKS` or `PEM`.
`keystore-password`	Password for the key store.
`keystore-user-credential-name`	Name of the key store entity to use as the user name.
`keystore-user-credential-password`	Password for the user name key store entity.
`keystore-password-credential-name`	Name of the key store entity to use as the password.
`keystore-password-credential-password`	Password for the password key store entity.

Multiple MySQL servers#

You can have as many catalogs as you need, so if you have additional MySQL servers, simply add another properties file to etc/catalog with a different name, making sure it ends in .properties. For example, if you name the property file sales.properties, Trino creates a catalog named sales using the configured connector.

General configuration properties#

The following table describes general catalog configuration properties for the connector:

Property name	Description	Default value
`case-insensitive-name-matching`	Support case insensitive schema and table names.	`false`
`case-insensitive-name-matching.cache-ttl`	This value should be a duration.	`1m`
`case-insensitive-name-matching.config-file`	Path to a name mapping configuration file in JSON format that allows Trino to disambiguate between schemas and tables with similar names in different cases.	`null`
`case-insensitive-name-matching.config-file.refresh-period`	Frequency with which Trino checks the name matching configuration file for changes. This value should be a duration.	(refresh disabled)
`metadata.cache-ttl`	The duration for which metadata, including table and column statistics, is cached.	`0s` (caching disabled)
`metadata.cache-missing`	Cache the fact that metadata, including table and column statistics, is not available	`false`
`metadata.cache-maximum-size`	Maximum number of objects stored in the metadata cache	`10000`
`write.batch-size`	Maximum number of statements in a batched execution. Do not change this setting from the default. Non-default values may negatively impact performance.	`1000`
`dynamic-filtering.enabled`	Push down dynamic filters into JDBC queries	`true`
`dynamic-filtering.wait-timeout`	Maximum duration for which Trino will wait for dynamic filters to be collected from the build side of joins before starting a JDBC query. Using a large timeout can potentially result in more detailed dynamic filters. However, it can also increase latency for some queries.	`20s`

Appending query metadata#

The optional parameter query.comment-format allows you to configure a SQL comment that is sent to the datasource with each query. The format of this comment can contain any characters and the following metadata:

$QUERY_ID: The identifier of the query.
$USER: The name of the user who submits the query to Trino.
$SOURCE: The identifier of the client tool used to submit the query, for example trino-cli.
$TRACE_TOKEN: The trace token configured with the client tool.

The comment can provide more context about the query. This additional information is available in the logs of the datasource. To include environment variables from the Trino cluster with the comment , use the ${ENV:VARIABLE-NAME} syntax.

The following example sets a simple comment that identifies each query sent by Trino:

query.comment-format=Query sent by Trino.

With this configuration, a query such as SELECT * FROM example_table; is sent to the datasource with the comment appended:

SELECT * FROM example_table; /*Query sent by Trino.*/

The following example improves on the preceding example by using metadata:

query.comment-format=Query $QUERY_ID sent by user $USER from Trino.

If Jane sent the query with the query identifier 20230622_180528_00000_bkizg, the following comment string is sent to the datasource:

SELECT * FROM example_table; /*Query 20230622_180528_00000_bkizg sent by user Jane from Trino.*/

Note

Certain JDBC driver settings and logging configurations might cause the comment to be removed.

Domain compaction threshold#

Pushing down a large list of predicates to the data source can compromise performance. Trino compacts large predicates into a simpler range predicate by default to ensure a balance between performance and predicate pushdown. If necessary, the threshold for this compaction can be increased to improve performance when the data source is capable of taking advantage of large predicates. Increasing this threshold may improve pushdown of large dynamic filters. The domain-compaction-threshold catalog configuration property or the domain_compaction_threshold catalog session property can be used to adjust the default value of 32 for this threshold.

Procedures#

system.flush_metadata_cache()

Flush JDBC metadata caches. For example, the following system call flushes the metadata caches for all schemas in the example catalog
```
USE example.example_schema;
CALL system.flush_metadata_cache();
```

Case insensitive matching#

When case-insensitive-name-matching is set to true, Trino is able to query non-lowercase schemas and tables by maintaining a mapping of the lowercase name to the actual name in the remote system. However, if two schemas and/or tables have names that differ only in case (such as “customers” and “Customers”) then Trino fails to query them due to ambiguity.

In these cases, use the case-insensitive-name-matching.config-file catalog configuration property to specify a configuration file that maps these remote schemas/tables to their respective Trino schemas/tables:

{
  "schemas": [
    {
      "remoteSchema": "CaseSensitiveName",
      "mapping": "case_insensitive_1"
    },
    {
      "remoteSchema": "cASEsENSITIVEnAME",
      "mapping": "case_insensitive_2"
    }],
  "tables": [
    {
      "remoteSchema": "CaseSensitiveName",
      "remoteTable": "tablex",
      "mapping": "table_1"
    },
    {
      "remoteSchema": "CaseSensitiveName",
      "remoteTable": "TABLEX",
      "mapping": "table_2"
    }]
}

Queries against one of the tables or schemes defined in the mapping attributes are run against the corresponding remote entity. For example, a query against tables in the case_insensitive_1 schema is forwarded to the CaseSensitiveName schema and a query against case_insensitive_2 is forwarded to the cASEsENSITIVEnAME schema.

At the table mapping level, a query on case_insensitive_1.table_1 as configured above is forwarded to CaseSensitiveName.tablex, and a query on case_insensitive_1.table_2 is forwarded to CaseSensitiveName.TABLEX.

By default, when a change is made to the mapping configuration file, Trino must be restarted to load the changes. Optionally, you can set the case-insensitive-name-mapping.refresh-period to have Trino refresh the properties without requiring a restart:

case-insensitive-name-mapping.refresh-period=30s

Non-transactional INSERT#

The connector supports adding rows using INSERT statements. By default, data insertion is performed by writing data to a temporary table. You can skip this step to improve performance and write directly to the target table. Set the insert.non-transactional-insert.enabled catalog property or the corresponding non_transactional_insert catalog session property to true.

Note that with this property enabled, data can be corrupted in rare cases where exceptions occur during the insert operation. With transactions disabled, no rollback can be performed.

Type mapping#

Because Trino and MySQL each support types that the other does not, this connector modifies some types when reading or writing data. Data types may not map the same way in both directions between Trino and the data source. Refer to the following sections for type mapping in each direction.

MySQL to Trino type mapping#

The connector maps MySQL types to the corresponding Trino types following this table:

MySQL to Trino type mapping#
MySQL database type	Trino type	Notes
`BIT`	`BOOLEAN`
`BOOLEAN`	`TINYINT`
`TINYINT`	`TINYINT`
`TINYINT UNSIGNED`	`SMALLINT`
`SMALLINT`	`SMALLINT`
`SMALLINT UNSIGNED`	`INTEGER`
`INTEGER`	`INTEGER`
`INTEGER UNSIGNED`	`BIGINT`
`BIGINT`	`BIGINT`
`BIGINT UNSIGNED`	`DECIMAL(20, 0)`
`DOUBLE PRECISION`	`DOUBLE`
`FLOAT`	`REAL`
`REAL`	`REAL`
`DECIMAL(p, s)`	`DECIMAL(p, s)`	See MySQL DECIMAL type handling
`CHAR(n)`	`CHAR(n)`
`VARCHAR(n)`	`VARCHAR(n)`
`TINYTEXT`	`VARCHAR(255)`
`TEXT`	`VARCHAR(65535)`
`MEDIUMTEXT`	`VARCHAR(16777215)`
`LONGTEXT`	`VARCHAR`
`ENUM(n)`	`VARCHAR(n)`
`BINARY`, `VARBINARY`, `TINYBLOB`, `BLOB`, `MEDIUMBLOB`, `LONGBLOB`	`VARBINARY`
`JSON`	`JSON`
`DATE`	`DATE`
`TIME(n)`	`TIME(n)`
`DATETIME(n)`	`TIMESTAMP(n)`
`TIMESTAMP(n)`	`TIMESTAMP(n) WITH TIME ZONE`

No other types are supported.

Trino to MySQL type mapping#

The connector maps Trino types to the corresponding MySQL types following this table:

Trino to MySQL type mapping#
Trino type	MySQL type	Notes
`BOOLEAN`	`TINYINT`
`TINYINT`	`TINYINT`
`SMALLINT`	`SMALLINT`
`INTEGER`	`INTEGER`
`BIGINT`	`BIGINT`
`REAL`	`REAL`
`DOUBLE`	`DOUBLE PRECISION`
`DECIMAL(p, s)`	`DECIMAL(p, s)`	MySQL DECIMAL type handling
`CHAR(n)`	`CHAR(n)`
`VARCHAR(n)`	`VARCHAR(n)`
`JSON`	`JSON`
`DATE`	`DATE`
`TIME(n)`	`TIME(n)`
`TIMESTAMP(n)`	`DATETIME(n)`
`TIMESTAMP(n) WITH TIME ZONE`	`TIMESTAMP(n)`

No other types are supported.

Timestamp type handling#

MySQL TIMESTAMP types are mapped to Trino TIMESTAMP WITH TIME ZONE. To preserve time instants, Trino sets the session time zone of the MySQL connection to match the JVM time zone. As a result, error messages similar to the following example occur when a timezone from the JVM does not exist on the MySQL server:

com.mysql.cj.exceptions.CJException: Unknown or incorrect time zone: 'UTC'

To avoid the errors, you must use a time zone that is known on both systems, or install the missing time zone on the MySQL server.

Decimal type handling#

DECIMAL types with unspecified precision or scale are mapped to a Trino DECIMAL with a default precision of 38 and default scale of 0. The scale can be changed by setting the decimal-mapping configuration property or the decimal_mapping session property to allow_overflow. The scale of the resulting type is controlled via the decimal-default-scale configuration property or the decimal-rounding-mode session property. The precision is always 38.

By default, values that require rounding or truncation to fit will cause a failure at runtime. This behavior is controlled via the decimal-rounding-mode configuration property or the decimal_rounding_mode session property, which can be set to UNNECESSARY (the default), UP, DOWN, CEILING, FLOOR, HALF_UP, HALF_DOWN, or HALF_EVEN (see RoundingMode).

Type mapping configuration properties#

The following properties can be used to configure how data types from the connected data source are mapped to Trino data types and how the metadata is cached in Trino.

Property name

Description

Default value

unsupported-type-handling

Configure how unsupported column data types are handled:

IGNORE, column is not accessible.
CONVERT_TO_VARCHAR, column is converted to unbounded VARCHAR.

The respective catalog session property is unsupported_type_handling.

IGNORE

jdbc-types-mapped-to-varchar

Allow forced mapping of comma separated lists of data types to convert to unbounded VARCHAR

Querying MySQL#

The MySQL connector provides a schema for every MySQL database. You can see the available MySQL databases by running SHOW SCHEMAS:

SHOW SCHEMAS FROM example;

If you have a MySQL database named web, you can view the tables in this database by running SHOW TABLES:

SHOW TABLES FROM example.web;

You can see a list of the columns in the clicks table in the web database using either of the following:

DESCRIBE example.web.clicks;
SHOW COLUMNS FROM example.web.clicks;

Finally, you can access the clicks table in the web database:

SELECT * FROM example.web.clicks;

If you used a different name for your catalog properties file, use that catalog name instead of example in the above examples.

SQL support#

The connector provides read access and write access to data and metadata in the MySQL database. In addition to the globally available and read operation statements, the connector supports the following statements:

SQL DELETE#

If a WHERE clause is specified, the DELETE operation only works if the predicate in the clause can be fully pushed down to the data source.

Fault-tolerant execution support#

The connector supports Fault-tolerant execution of query processing. Read and write operations are both supported with any retry policy.

Table functions#

The connector provides specific table functions to access MySQL.

`query(varchar) -> table`#

The query function allows you to query the underlying database directly. It requires syntax native to MySQL, because the full query is pushed down and processed in MySQL. This can be useful for accessing native features which are not available in Trino or for improving query performance in situations where running a query natively may be faster.

The native query passed to the underlying data source is required to return a table as a result set. Only the data source performs validation or security checks for these queries using its own configuration. Trino does not perform these tasks. Only use passthrough queries to read data.

For example, query the example catalog and group and concatenate all employee IDs by manager ID:

SELECT
  *
FROM
  TABLE(
    example.system.query(
      query => 'SELECT
        manager_id, GROUP_CONCAT(employee_id)
      FROM
        company.employees
      GROUP BY
        manager_id'
    )
  );

Note

The query engine does not preserve the order of the results of this function. If the passed query contains an ORDER BY clause, the function result may not be ordered as expected.

Performance#

The connector includes a number of performance improvements, detailed in the following sections.

Table statistics#

The MySQL connector can use table and column statistics for cost based optimizations, to improve query processing performance based on the actual data in the data source.

The statistics are collected by MySQL and retrieved by the connector.

The table-level statistics are based on MySQL’s INFORMATION_SCHEMA.TABLES table. The column-level statistics are based on MySQL’s index statistics INFORMATION_SCHEMA.STATISTICS table. The connector can return column-level statistics only when the column is the first column in some index.

MySQL database can automatically update its table and index statistics. In some cases, you may want to force statistics update, for example after creating new index, or after changing data in the table. You can do that by executing the following statement in MySQL Database.

ANALYZE TABLE table_name;

Note

MySQL and Trino may use statistics information in different ways. For this reason, the accuracy of table and column statistics returned by the MySQL connector might be lower than than that of others connectors.

Improving statistics accuracy

You can improve statistics accuracy with histogram statistics (available since MySQL 8.0). To create histogram statistics execute the following statement in MySQL Database.

ANALYZE TABLE table_name UPDATE HISTOGRAM ON column_name1, column_name2, ...;

Refer to MySQL documentation for information about options, limitations and additional considerations.

Pushdown#

The connector supports pushdown for a number of operations:

Aggregate pushdown for the following functions:

Note

The connector performs pushdown where performance may be improved, but in order to preserve correctness an operation may not be pushed down. When pushdown of an operation may result in better performance but risks correctness, the connector prioritizes correctness.

Cost-based join pushdown#

The connector supports cost-based Join pushdown to make intelligent decisions about whether to push down a join operation to the data source.

When cost-based join pushdown is enabled, the connector only pushes down join operations if the available Table statistics suggest that doing so improves performance. Note that if no table statistics are available, join operation pushdown does not occur to avoid a potential decrease in query performance.

The following table describes catalog configuration properties for join pushdown:

Property name	Description	Default value
`join-pushdown.enabled`	Enable join pushdown. Equivalent catalog session property is `join_pushdown_enabled`.	`true`
`join-pushdown.strategy`	Strategy used to evaluate whether join operations are pushed down. Set to `AUTOMATIC` to enable cost-based join pushdown, or `EAGER` to push down joins whenever possible. Note that `EAGER` can push down joins even when table statistics are unavailable, which may result in degraded query performance. Because of this, `EAGER` is only recommended for testing and troubleshooting purposes.	`AUTOMATIC`

Predicate pushdown support#

The connector does not support pushdown of any predicates on columns with textual types like CHAR or VARCHAR. This ensures correctness of results since the data source may compare strings case-insensitively.

In the following example, the predicate is not pushed down for either query since name is a column of type VARCHAR:

SELECT * FROM nation WHERE name > 'CANADA';
SELECT * FROM nation WHERE name = 'CANADA';

MySQL connector#

Requirements#

Configuration#

Connection security#

Data source authentication#

Multiple MySQL servers#

General configuration properties#

Appending query metadata#

Domain compaction threshold#

Procedures#

Case insensitive matching#

Non-transactional INSERT#

Type mapping#

MySQL to Trino type mapping#

Trino to MySQL type mapping#

Timestamp type handling#

Decimal type handling#

Type mapping configuration properties#

Querying MySQL#

SQL support#

SQL DELETE#

Fault-tolerant execution support#

Table functions#

query(varchar) -> table#

Performance#

Table statistics#

Pushdown#

Cost-based join pushdown#

Predicate pushdown support#

`query(varchar) -> table`#