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, redshift.properties, to mount the Redshift connector as the redshift 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

General configuration properties#

The following table describes general configuration properties for the connector:

Property name

Description

Default value

case-insensitive-name-matching

Support case insensitive database and collection names

False

case-insensitive-name-matching.cache-ttl

1 minute

metadata.cache-ttl

Duration for which metadata, including table and column statistics, is cached

0 (disabled caching)

metadata.cache-missing

Cache the fact that metadata, including table and column statistics, is not available

False

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.

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.

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 redshift;

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

SHOW TABLES FROM redshift.web;

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

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

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

SELECT * FROM redshift.web.clicks;

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

Type mapping#

General 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:

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.