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PostgreSQL connector

docs/src/main/sphinx/connector/postgresql.md

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PostgreSQL connector

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

Requirements

To connect to PostgreSQL, you need:

  • PostgreSQL 12.x or higher.
  • Network access from the Trino coordinator and workers to PostgreSQL. Port 5432 is the default port.

Configuration

The connector can query a database on a PostgreSQL server. Create a catalog properties file that specifies the PostgreSQL connector by setting the connector.name to postgresql.

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:

text
connector.name=postgresql
connection-url=jdbc:postgresql://example.net:5432/database
connection-user=root
connection-password=secret

The connection-url defines the connection information and parameters to pass to the PostgreSQL JDBC driver. The parameters for the URL are available in the PostgreSQL JDBC driver documentation. Some parameters can have adverse effects on the connector behavior or not work with the connector.

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

Access to system tables

The PostgreSQL connector supports reading PostgreSQL catalog tables, such as pg_namespace. The functionality is turned off by default, and can be enabled using the postgresql.include-system-tables configuration property.

You can see more details in the pg_catalog schema in the example catalog, for example about the pg_namespace system table:

sql
SHOW TABLES FROM example.pg_catalog;
SELECT * FROM example.pg_catalog.pg_namespace;

(postgresql-tls)=

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 42 of the PostgreSQL JDBC driver, enable TLS by appending the ssl=true parameter to the connection-url configuration property:

properties
connection-url=jdbc:postgresql://example.net:5432/database?ssl=true

For more information on TLS configuration options, see the PostgreSQL JDBC driver documentation.

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Multiple PostgreSQL databases or servers

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

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(postgresql-fte-support)=

Fault-tolerant execution support

The connector supports {doc}/admin/fault-tolerant-execution of query processing. Read and write operations are both supported with any retry policy.

(postgresql-type-mapping)=

Type mapping

Because Trino and PostgreSQL each support types that the other does not, this connector {ref}modifies some types <type-mapping-overview> 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.

PostgreSQL type to Trino type mapping

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

:::{list-table} PostgreSQL type to Trino type mapping :widths: 30, 30, 40 :header-rows: 1

    • PostgreSQL type
    • Trino type
    • Notes
    • BIT
    • BOOLEAN
    • BOOLEAN
    • BOOLEAN
    • SMALLINT
    • SMALLINT
    • INTEGER
    • INTEGER
    • BIGINT
    • BIGINT
    • REAL
    • REAL
    • DOUBLE
    • DOUBLE
    • NUMERIC(p, s)
      DECIMAL(p, s)
    • DECIMAL(pʹ, sʹ) or NUMBER
    • Maps to Trino DECIMAL when input data can be represented as Trino DECIMAL losslessly. When 1 ≤ p ≤ 38 and 0 ≤ s ≤ p, then pʹ = p and sʹ = s, otherwise, a wider type is used.
      When input cannot be represented as Trino DECIMAL losslessly, maps to NUMBER.
    • NUMERIC
      DECIMAL
    • NUMBER
    • CHAR(n)
    • CHAR(n)
    • VARCHAR(n)
    • VARCHAR(n)
    • ENUM
    • VARCHAR
    • BYTEA
    • VARBINARY
    • DATE
    • DATE
    • TIME(n)
    • TIME(n)
    • TIMESTAMP(n)
    • TIMESTAMP(n)
    • TIMESTAMPTZ(n)
    • TIMESTAMP(n) WITH TIME ZONE
    • MONEY
    • VARCHAR
    • UUID
    • UUID
    • JSON
    • JSON
    • JSONB
    • JSON
    • VECTOR
    • ARRAY(REAL)
    • HSTORE
    • MAP(VARCHAR, VARCHAR)
    • ARRAY
    • Disabled, ARRAY, or JSON
    • See for more information.
    • GEOMETRY, GEOMETRY(GEOMETRY TYPE, SRID)
    • GEOMETRY

:::

No other types are supported.

Trino type to PostgreSQL type mapping

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

:::{list-table} Trino type to PostgreSQL type mapping :widths: 30, 30, 40 :header-rows: 1

    • Trino type
    • PostgreSQL type
    • Notes
    • BOOLEAN
    • BOOLEAN
    • SMALLINT
    • SMALLINT
    • TINYINT
    • SMALLINT
    • INTEGER
    • INTEGER
    • BIGINT
    • BIGINT
    • DOUBLE
    • DOUBLE
    • DECIMAL(p, s)
    • NUMERIC(p, s)
    • NUMBER
    • NUMERIC
    • CHAR(n)
    • CHAR(n)
    • VARCHAR(n)
    • VARCHAR(n)
    • VARBINARY
    • BYTEA
    • DATE
    • DATE
    • TIME(n)
    • TIME(n)
    • TIMESTAMP(n)
    • TIMESTAMP(n)
    • TIMESTAMP(n) WITH TIME ZONE
    • TIMESTAMPTZ(n)
    • UUID
    • UUID
    • JSON
    • JSONB
    • ARRAY
    • ARRAY
    • See for more information.
    • GEOMETRY
    • GEOMETRY

::::

No other types are supported.

(postgresql-array-type-handling)=

Array type handling

The PostgreSQL array implementation does not support fixed dimensions whereas Trino support only arrays with fixed dimensions. You can configure how the PostgreSQL connector handles arrays with the postgresql.array-mapping configuration property in your catalog file or the array_mapping session property. The following values are accepted for this property:

  • DISABLED (default): array columns are skipped.
  • AS_ARRAY: array columns are interpreted as Trino ARRAY type, for array columns with fixed dimensions.
  • AS_JSON: array columns are interpreted as Trino JSON type, with no constraint on dimensions.
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Querying PostgreSQL

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

SHOW SCHEMAS FROM example;

If you have a PostgreSQL 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.

(postgresql-sql-support)=

SQL support

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

  • , see also
  • , see also
  • , see also
  • , see also
  • , see also:

(postgresql-insert)=

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(postgresql-update)=

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(postgresql-delete)=

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(postgresql-merge)=

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(postgresql-alter-table)=

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(postgresql-alter-schema)=

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(postgresql-procedures)=

Procedures

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(postgresql-table-functions)=

Table functions

The connector provides specific {doc}table functions </functions/table> to access PostgreSQL.

(postgresql-query-function)=

query(varchar) -> table

The query function allows you to query the underlying database directly. It requires syntax native to PostgreSQL, because the full query is pushed down and processed in PostgreSQL. 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.

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As a simple example, query the example catalog and select an entire table:

SELECT
  *
FROM
  TABLE(
    example.system.query(
      query => 'SELECT
        *
      FROM
        tpch.nation'
    )
  );

As a practical example, you can leverage frame exclusion from PostgresQL when using window functions:

SELECT
  *
FROM
  TABLE(
    example.system.query(
      query => 'SELECT
        *,
        array_agg(week) OVER (
          ORDER BY
            week
          ROWS
            BETWEEN 2 PRECEDING
            AND 2 FOLLOWING
            EXCLUDE GROUP
        ) AS week,
        array_agg(week) OVER (
          ORDER BY
            day
          ROWS
            BETWEEN 2 PRECEDING
            AND 2 FOLLOWING
            EXCLUDE GROUP
        ) AS all
      FROM
        test.time_data'
    )
  );
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Performance

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

(postgresql-table-statistics)=

Table statistics

The PostgreSQL connector can use {doc}table and column statistics </optimizer/statistics> for {doc}cost based optimizations </optimizer/cost-based-optimizations>, to improve query processing performance based on the actual data in the data source.

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

To collect statistics for a table, execute the following statement in PostgreSQL.

text
ANALYZE table_schema.table_name;

Refer to PostgreSQL documentation for additional ANALYZE options.

(postgresql-pushdown)=

Pushdown

The connector supports pushdown for a number of operations:

  • {ref}join-pushdown
  • {ref}limit-pushdown
  • {ref}topn-pushdown

{ref}Aggregate pushdown <aggregation-pushdown> for the following functions:

  • {func}avg
  • {func}count
  • {func}max
  • {func}min
  • {func}sum
  • {func}stddev
  • {func}stddev_pop
  • {func}stddev_samp
  • {func}variance
  • {func}var_pop
  • {func}var_samp
  • {func}covar_pop
  • {func}covar_samp
  • {func}corr
  • {func}regr_intercept
  • {func}regr_slope
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Predicate pushdown support

Predicates are pushed down for most types, including UUID and temporal types, such as DATE.

The connector does not support pushdown of range predicates, such as >, <, or BETWEEN, on columns with {ref}character string types <string-data-types> like CHAR or VARCHAR. Equality predicates, such as IN or =, and inequality predicates, such as != on columns with textual types are pushed down. This ensures correctness of results since the remote data source may sort strings differently than Trino.

In the following example, the predicate of the first query is not pushed down since name is a column of type VARCHAR and > is a range predicate. The other queries are pushed down.

sql
-- Not pushed down
SELECT * FROM nation WHERE name > 'CANADA';
-- Pushed down
SELECT * FROM nation WHERE name != 'CANADA';
SELECT * FROM nation WHERE name = 'CANADA';

There is experimental support to enable pushdown of range predicates on columns with character string types which can be enabled by setting the postgresql.experimental.enable-string-pushdown-with-collate catalog configuration property or the corresponding enable_string_pushdown_with_collate session property to true. Enabling this configuration will make the predicate of all the queries in the above example get pushed down.