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 |
|---|---|
|
Type of the credential provider. Must be one of |
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Connection user name. |
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Connection password. |
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Name of the extra credentials property, whose value to use as the user
name. See |
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Name of the extra credentials property, whose value to use as the password. |
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Location of the properties file where credentials are present. It must
contain the |
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The location of the Java Keystore file, from which to read credentials. |
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File format of the keystore file, for example |
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Password for the key store. |
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Name of the key store entity to use as the user name. |
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Password for the user name key store entity. |
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Name of the key store entity to use as the password. |
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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 |
|---|---|
|
Support case insensitive schema and table names. Defaults to |
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Duration for which case insensitive schema and table
names are cached. Defaults to |
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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. Defaults to |
|
Frequency with which Trino checks the name matching configuration file
for changes. The duration value defaults to |
|
Duration for which metadata, including table and
column statistics, is cached. Defaults to |
|
Cache the fact that metadata, including table and column statistics, is
not available. Defaults to |
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Duration for which schema metadata is cached.
Defaults to the value of |
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Duration for which table metadata is cached.
Defaults to the value of |
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Duration for which tables statistics are cached.
Defaults to the value of |
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Maximum number of objects stored in the metadata cache. Defaults to |
|
Maximum number of statements in a batched execution. Do not change
this setting from the default. Non-default values may negatively
impact performance. Defaults to |
|
Push down dynamic filters into JDBC queries. Defaults to |
|
Maximum duration for which Trino waits 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.
Defaults to |
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.$SOURCE: The identifier of the client tool used to submit the query, for exampletrino-cli.$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
256 for this threshold.
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.
Fault-tolerant execution support#
The connector supports Fault-tolerant execution of query processing. Read and write operations are both supported with any retry policy.
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 database type |
Trino type |
Notes |
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No other types are supported.
Trino to MySQL type mapping#
The connector maps Trino types to the corresponding MySQL types following this table:
Trino type |
MySQL type |
Notes |
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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 ignored unless the
decimal-mapping configuration property or the decimal_mapping session
property is set to allow_overflow. Then such types are mapped to a Trino
DECIMAL with a default precision of 38 and default scale of 0. To change the
scale of the resulting type, use the decimal-default-scale configuration
property or the decimal_default_scale 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 |
|---|---|---|
|
Configure how unsupported column data types are handled:
The respective catalog session property is |
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|
Allow forced mapping of comma separated lists of data types to convert to
unbounded |
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:
UPDATE#
Only UPDATE statements with constant assignments and predicates are
supported. For example, the following statement is supported because the values
assigned are constants:
UPDATE table SET col1 = 1 WHERE col3 = 1
Arithmetic expressions, function calls, and other non-constant UPDATE
statements are not supported. For example, the following statement is not
supported because arithmetic expressions cannot be used with the SET
command:
UPDATE table SET col1 = col2 + 2 WHERE col3 = 1
All column values of a table row cannot be updated simultaneously. For a three column table, the following statement is not supported:
UPDATE table SET col1 = 1, col2 = 2, col3 = 3 WHERE col3 = 1
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.
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();
system.execute('query')#
The execute procedure allows you to execute a query in the underlying data
source directly. The query must use supported syntax of the connected data
source. Use the procedure to access features which are not available in Trino
or to execute queries that return no result set and therefore can not be used
with the query or raw_query pass-through table function. Typical use cases
are statements that create or alter objects, and require native feature such
as constraints, default values, automatic identifier creation, or indexes.
Queries can also invoke statements that insert, update, or delete data, and do
not return any data as a result.
The query text is not parsed by Trino, only passed through, and therefore only subject to any security or access control of the underlying data source.
The following example sets the current database to the example_schema of the
example catalog. Then it calls the procedure in that schema to drop the
default value from your_column on your_table table using the standard SQL
syntax in the parameter value assigned for query:
USE example.example_schema;
CALL system.execute(query => 'ALTER TABLE your_table ALTER COLUMN your_column DROP DEFAULT');
Verify that the specific database supports this syntax, and adapt as necessary based on the documentation for the specific connected database and database version.
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 |
|---|---|---|
|
Enable join pushdown. Equivalent catalog
session property is
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Strategy used to evaluate whether join operations are pushed down. Set to
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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';