MySQL connector#

The MySQL connector lets you query and create 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.

SEP includes additional enterprise features that are built on top of the existing Trino connector functionality. For more information on connector key feature differences between Trino and SEP, see the connectors feature matrix.

Requirements#

To connect to MySQL, you need:

MySQL 5.7, 8.0 or higher.
Network access from the SEP coordinator and workers to MySQL. Port 3306 is the default port.
A valid Starburst Enterprise license.

Configuration#

To configure the MySQL connector, create a catalog properties file that specifies the MySQL connector by setting the connector.name to mysql.

For example, to access a database as the example catalog, create the file etc/catalog/example.properties. Replace 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 gives you the ability 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 exposing 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. If you have additional MySQL servers, 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, SEP 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
`case-insensitive-name-matching`	Support case insensitive schema and table names. Defaults to `false`.
`case-insensitive-name-matching.cache-ttl`	Duration for which case insensitive schema and table names are cached. Defaults to `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. Defaults to `null`.
`case-insensitive-name-matching.config-file.refresh-period`	Frequency with which Trino checks the name matching configuration file for changes. The duration value defaults to `0s` (refresh disabled).
`metadata.cache-ttl`	Duration for which metadata, including table and column statistics, is cached. Defaults to `0s` (caching disabled).
`metadata.cache-missing`	Cache the fact that metadata, including table and column statistics, is not available. Defaults to `false`.
`metadata.schemas.cache-ttl`	Duration for which schema metadata is cached. Defaults to the value of `metadata.cache-ttl`.
`metadata.tables.cache-ttl`	Duration for which table metadata is cached. Defaults to the value of `metadata.cache-ttl`.
`metadata.statistics.cache-ttl`	Duration for which tables statistics are cached. Defaults to the value of `metadata.cache-ttl`.
`metadata.cache-maximum-size`	Maximum number of objects stored in the metadata cache. Defaults to `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. Defaults to `1000`.
`dynamic-filtering.enabled`	Push down dynamic filters into JDBC queries. Defaults to `true`.
`dynamic-filtering.wait-timeout`	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 `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 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 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)`	See 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 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

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 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.

ALTER TABLE EXECUTE#

This connector supports the following commands for use with ALTER TABLE EXECUTE:

collect_statistics#

The collect_statistics command is used with Managed statistics to collect statistics for a table and its columns.

The following statement collects statistics for the example_table table and all of its columns:

ALTER TABLE example_table EXECUTE collect_statistics;

Collecting statistics for all columns in a table may be unnecessarily performance-intensive, especially for wide tables. To only collect statistics for a subset of columns, you can include the columns parameter with an array of column names. For example:

ALTER TABLE example_table
    EXECUTE collect_statistics(columns => ARRAY['customer','line_item']);

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 lets you 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 SEP 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 features, 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 an 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 SEP 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 that of other 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.

Managed statistics#

The connector supports Managed statistics which lets SEP collect and store its own table and column statistics that can then be used for performance optimizations in query planning.

Statistics must be collected manually using the built-in collect_statistics command, see collect_statistics for details and examples.

Pushdown#

The connector supports pushdown for the following 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';

Dynamic filtering#

Dynamic filtering is enabled by default. It causes the connector to wait for dynamic filtering to complete before starting a JDBC query.

You can disable dynamic filtering by setting the dynamic-filtering.enabled property in your catalog configuration file to false.

Wait timeout#

By default, table scans on the connector are delayed up to 20 seconds until dynamic filters are collected from the build side of joins. Using a large timeout can potentially result in more detailed dynamic filters. However, it can also increase latency for some queries.

You can configure the dynamic-filtering.wait-timeout property in your catalog properties file:

dynamic-filtering.wait-timeout=1m

You can use the dynamic_filtering_wait_timeout catalog session property in a specific session:

SET SESSION example.dynamic_filtering_wait_timeout = 1s;

Compaction#

The maximum size of dynamic filter predicate, that is pushed down to the connector during table scan for a column, is configured using the domain-compaction-threshold property in the catalog properties file:

domain-compaction-threshold=100

You can use the domain_compaction_threshold catalog session property:

SET SESSION domain_compaction_threshold = 10;

By default, domain-compaction-threshold is set to 32. When the dynamic predicate for a column exceeds this threshold, it is compacted into a single range predicate.

For example, if the dynamic filter collected for a date column dt on the fact table selects more than 32 days, the filtering condition is simplified from dt IN ('2020-01-10', '2020-01-12',..., '2020-05-30') to dt BETWEEN '2020-01-10' AND '2020-05-30'. Using a large threshold can result in increased table scan overhead due to a large IN list getting pushed down to the data source.

Metrics#

Metrics about dynamic filtering are reported in a JMX table for each catalog:

jmx.current."io.trino.plugin.jdbc:name=example,type=dynamicfilteringstats"

Metrics include information about the total number of dynamic filters, the number of completed dynamic filters, the number of available dynamic filters and the time spent waiting for dynamic filters.

Starburst Cached Views#

The connector supports table scan redirection, which improves performance and reduces load on the data source.

JDBC connection pooling#

When JDBC connection pooling is enabled, each node creates and maintains a connection pool instead of opening and closing separate connections to the data source. Each connection is available to connect to the data source and retrieve data. After completion of an operation, the connection is returned to the pool and can be reused. This improves performance by a small amount, reduces the load on any required authentication system used for establishing the connection, and helps avoid running into connection limits on data sources.

JDBC connection pooling is disabled by default. You can enable JDBC connection pooling by setting the connection-pool.enabled property to true in your catalog configuration file:

connection-pool.enabled=true

The following catalog configuration properties can be used to tune connection pooling:

JDBC connection pooling catalog configuration properties#
Property name	Description	Default value
`connection-pool.enabled`	Enable connection pooling for the catalog.	`false`
`connection-pool.max-size`	The maximum number of idle and active connections in the pool.	`10`
`connection-pool.max-connection-lifetime`	The maximum lifetime of a connection. When a connection reaches this lifetime it is removed, regardless of how recently it has been active.	`30m`
`connection-pool.pool-cache-max-size`	The maximum size of the JDBC data source cache.	`1000`
`connection-pool.pool-cache-ttl`	The expiration time of a cached data source when it is no longer accessed.	`30m`

Security#

The connector includes a number of security-related features, detailed in the following sections.

AWS IAM authentication#

When the MySQL database is deployed as an AWS RDS instance, the connector can use IAM authentication. This feature lets you manage access control from SEP with IAM policies.

Configuration#

To enable IAM authentication, add the following configuration properties to the catalog configuration file:

mysql.authentication.type=AWS
connection-user=<RDS username>
aws.region-name=<AWS region>
aws.token-expiration-timeout=10m

You can also configure the connector to assume a specific IAM role for authentication before creating the access token, in order to apply policies specific to SEP. Alongside this role, you must include an (informal) external identifier of a user to assume this role.

To apply an IAM role to the connector, add the following configuration properties:

aws.iam-role=<role_arn>
aws.external-id=<external_id>

This table describes the configuration properties for IAM authentication:

IAM configuration properties#
Property name	Description
`connection-user`	The database account used to access the RDS database instance.
`aws.region-name`	The name of the AWS region in which the RDS instance is deployed.
`aws.iam-role`	(Optional) Set an IAM role to assume for authentication before creating the access token. If set, `aws.external-id` must be configured as well.
`aws.external-id`	(Optional) The informal identifier of the user who assumes the IAM role set in `aws.iam-role`.
`aws.token-expiration-timeout`	The amount of time to keep the generated RDS access tokens for each user before they are regenerated. The maximum value is 15 minutes. Defaults to `10m`.
`aws.access-key`	The access key of the principal to authenticate with for the token generator service. Used for fixed authentication, setting this property disables automatic authentication.
`aws.secret-key`	The secret key of the principal to authenticate with for the token generator service. Used for fixed authentication, setting this property disables automatic authentication.
`aws.session-token`	(Optional) A session token for temporary credentials, such as credentials obtained from SSO. Used for fixed authentication, setting this property disables automatic authentication.

Authentication#

By default the connector attempts to automatically obtain its authentication credentials from the environment. The default credential provider chain attempts to obtain credentials from the following sources, in order:

Environment variables: AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY, or AWS_ACCESS_KEY and AWS_SECRET_KEY.
Java system properties: aws.accessKeyId and aws.secretKey.
Web identity token: credentials from the environment or container.
Credential profiles file: a profiles file at the default location (~/.aws/credentials) shared by all AWS SDKs and the AWS CLI.
EC2 service credentials: credentials delivered through the Amazon EC2 container service, assuming the security manager has permission to access the value of the AWS_CONTAINER_CREDENTIALS_RELATIVE_URI environment variable.
Instance profile credentials: credentials delievered through the Amazon EC2 metadata service.

If the SEP cluster is running on an EC2 instance, these credentials most likely come from the metadata service.

Alternatively, you can set fixed credentials for authentication. This option disables the container’s automatic attempt to locate credentials. To use fixed credentials for authentication, set the following configuration properties:

aws.access-key=<access_key>
aws.secret-key=<secret_key>

# (Optional) You can use temporary credentials. For example, you can use temporary credentials from SSO
aws.session-token=<session_token>

MySQL connector#

Requirements#

Configuration#

Connection security#

Data source authentication#

Multiple MySQL servers#

General configuration properties#

Appending query metadata#

Domain compaction threshold#

Case insensitive matching#

Non-transactional INSERT#

Fault-tolerant execution support#

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#

UPDATE#

SQL DELETE#

ALTER TABLE EXECUTE#

collect_statistics#

Procedures#

system.flush_metadata_cache()#

system.execute('query')#

Table functions#

query(varchar) -> table#

Performance#

Table statistics#

Managed statistics#

Pushdown#

Cost-based join pushdown#

Predicate pushdown support#

Dynamic filtering#

Wait timeout#

Compaction#

Metrics#

Starburst Cached Views#

JDBC connection pooling#

Security#

AWS IAM authentication#

Configuration#

Authentication#

`system.flush_metadata_cache()`#

`system.execute('query')`#

`query(varchar) -> table`#