Redshift connector#

The Redshift connector allows querying and creating tables in an external Amazon Redshift cluster. This can be used to join data between different systems like Redshift and Hive, or between two different Redshift clusters.

Requirements#

To connect to Redshift, you need:

Network access from the Trino coordinator and workers to Redshift. Port 5439 is the default port.

Configuration#

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

connector.name=redshift
connection-url=jdbc:redshift://example.net:5439/database
connection-user=root
connection-password=secret

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, on version 2.1 of the Redshift JDBC driver, TLS/SSL is enabled by default with the SSL parameter. You can disable or further configure TLS by appending parameters to the connection-url configuration property:

connection-url=jdbc:redshift://example.net:5439/database;SSL=TRUE;

For more information on TLS configuration options, see the Redshift JDBC driver 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 Redshift databases or clusters#

The Redshift connector can only access a single database within a Redshift cluster. Thus, if you have multiple Redshift databases, or want to connect to multiple Redshift clusters, you must configure multiple instances of the Redshift connector.

To add another catalog, 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
`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 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.

Querying Redshift#

The Redshift connector provides a schema for every Redshift schema. You can see the available Redshift schemas by running SHOW SCHEMAS:

SHOW SCHEMAS FROM example;

If you have a Redshift schema named web, you can view the tables in this schema 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 schema:

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.

Type mapping#

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

SQL support#

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

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

The =, !=, >, <, >=, <=, IN, NOT IN operators are supported in predicates. The following statement is not supported because the AND operator cannot be used in predicates:

UPDATE table SET col1 = 1 WHERE col3 = 1 AND col2 = 3

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 RENAME TO#

The connector does not support renaming tables across multiple schemas. For example, the following statement is supported:

ALTER TABLE example.schema_one.table_one RENAME TO example.schema_one.table_two

The following statement attempts to rename a table across schemas, and therefore is not supported:

ALTER TABLE example.schema_one.table_one RENAME TO example.schema_two.table_two

ALTER SCHEMA#

The connector supports renaming a schema with the ALTER SCHEMA RENAME statement. ALTER SCHEMA SET AUTHORIZATION is not supported.

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 Redshift.

`query(varchar) -> table`#

The query function allows you to query the underlying database directly. It requires syntax native to Redshift, because the full query is pushed down and processed in Redshift. This can be useful for accessing native features which are not implemented 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 select the top 10 nations by population:

SELECT
  *
FROM
  TABLE(
    example.system.query(
      query => 'SELECT
        TOP 10 *
      FROM
        tpch.nation
      ORDER BY
        population DESC'
    )
  );