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Run federated queries on PostgreSQL

This article describes how to set up Lakehouse Federation to run federated queries on Run queries on PostgreSQL data that is not managed by Databricks. To learn more about Lakehouse Federation, see What is Lakehouse Federation?.

To connect to your Run queries on PostgreSQL database using Lakehouse Federation, you must create the following in your Databricks Unity Catalog metastore:

  • A connection to your Run queries on PostgreSQL database.
  • A foreign catalog that mirrors your Run queries on PostgreSQL database in Unity Catalog so that you can use Unity Catalog query syntax and data governance tools to manage Databricks user access to the database.

Before you begin​

Workspace requirements:

  • Workspace enabled for Unity Catalog.

Compute requirements:

  • Network connectivity from your compute resource to the target database systems. See Networking recommendations for Lakehouse Federation.
  • Databricks compute must use Databricks Runtime 13.3 LTS or above and Standard or Dedicated access mode.
  • SQL warehouses must be pro or serverless and must use 2023.40 or above.

Permissions required:

  • To create a connection, you must be a metastore admin or a user with the CREATE CONNECTION privilege on the Unity Catalog metastore attached to the workspace.
  • To create a foreign catalog, you must have the CREATE CATALOG permission on the metastore and be either the owner of the connection or have the CREATE FOREIGN CATALOG privilege on the connection.

Additional permission requirements are specified in each task-based section that follows.

Create a connection​

A connection specifies a path and credentials for accessing an external database system. To create a connection, you can use Catalog Explorer or the CREATE CONNECTION SQL command in a Databricks notebook or the Databricks SQL query editor.

note

You can also use the Databricks REST API or the Databricks CLI to create a connection. See POST /api/2.1/unity-catalog/connections and Unity Catalog commands.

Permissions required: Metastore admin or user with the CREATE CONNECTION privilege.

  1. In your Databricks workspace, click Catalog icon Catalog.

  2. At the top of the Catalog pane, click the Add or plus icon Add icon and select Add a connection from the menu.

    Alternatively, from the Quick access page, click the External data > button, go to the Connections tab, and click Create connection.

  3. On the Connection basics page of the Set up connection wizard, enter a user-friendly Connection name.

  4. Select a Connection type of PostgreSQL.

  5. (Optional) Add a comment.

  6. Click Next.

  7. On the Authentication page, enter the following connection properties for your PostgreSQL instance.

    • Host: For example, postgres-demo.lb123.us-west-2.rds.amazonaws.com
    • Port: For example, 5432
    • User: For example, postgres_user
    • Password: For example, password123

  8. Click Create connection.

  9. On the Catalog basics page, enter a name for the foreign catalog. A foreign catalog mirrors a database in an external data system so that you can query and manage access to data in that database using Databricks and Unity Catalog.

  10. (Optional) Click Test connection to confirm that it works.

  11. Click Create catalog.

  12. On the Access page, select the workspaces in which users can access the catalog you created. You can select All workspaces have access, or click Assign to workspaces, select the workspaces, and then click Assign.

  13. Change the Owner who will be able to manage access to all objects in the catalog. Start typing a principal in the text box, and then click the principal in the returned results.

  14. Grant Privileges on the catalog. Click Grant:

    1. Specify the Principals who will have access to objects in the catalog. Start typing a principal in the text box, and then click the principal in the returned results.
    2. Select the Privilege presets to grant to each principal. All account users are granted BROWSE by default.
      • Select Data Reader from the drop-down menu to grant read privileges on objects in the catalog.
      • Select Data Editor from the drop-down menu to grant read and modify privileges on objects in the catalog.
      • Manually select the privileges to grant.
    3. Click Grant.

  15. Click Next.

  16. On the Metadata page, specify tags key-value pairs. For more information, see Apply tags to Unity Catalog securable objects.

  17. (Optional) Add a comment.

  18. Click Save.

Create a foreign catalog​

note

If you use the UI to create a connection to the data source, foreign catalog creation is included and you can skip this step.

A foreign catalog mirrors a database in an external data system so that you can query and manage access to data in that database using Databricks and Unity Catalog. To create a foreign catalog, you use a connection to the data source that has already been defined.

To create a foreign catalog, you can use Catalog Explorer or the CREATE FOREIGN CATALOG SQL command in a Databricks notebook or the SQL query editor. You can also use the Databricks REST API or the Databricks CLI to create a catalog. See POST /api/2.1/unity-catalog/catalogs and Unity Catalog commands.

Permissions required: CREATE CATALOG permission on the metastore and either ownership of the connection or the CREATE FOREIGN CATALOG privilege on the connection.

  1. In your Databricks workspace, click Catalog icon Catalog to open Catalog Explorer.

  2. At the top of the Catalog pane, click the Add or plus icon Add icon and select Add a catalog from the menu.

    Alternatively, from the Quick access page, click the Catalogs button, and then click the Create catalog button.

  3. Follow the instructions for creating foreign catalogs in Create catalogs.

Supported pushdowns​

The following pushdowns are supported on all compute:

  • Filters
  • Projections
  • Limit
  • Functions: partial, only for filter expressions. (String functions, Mathematical functions, and other miscellaneous functions, such as Alias, Cast, SortOrder)

The following pushdowns are supported on Databricks Runtime 13.3 LTS and above, and on SQL warehouses:

  • The following aggregation functions: MIN, MAX, COUNT, SUM, AVG, VAR_POP, VAR_SAMP, STDDEV_POP, STDDEV_SAMP, GREATEST, LEAST, COVAR_POP, COVAR_SAMP, CORR, REGR_INTERCEPT, REGR_R2, REGR_SLOPE, REGR_SXY
  • The following Boolean functions: =, <, <, =>, >=, <=>
  • The following mathematical functions (not supported if ANSI is disabled): +, -, *, %, /
  • Miscellaneous operators | and ~
  • Sorting, when used with limit

The following pushdowns are not supported:

  • Joins
  • Windows functions

Data type mappings​

When you read from PostgreSQL to Spark, data types map as follows:

PostgreSQL type

Spark type

numeric

DecimalType

int2

ShortType

int4 (if not signed)

IntegerType

int8, oid, xid, int4 (if signed)

LongType

float4

FloatType

double precision, float8

DoubleType

char

CharType

name, varchar, tid

VarcharType

bpchar, character varying, json, money, point, super, text

StringType

bytea, geometry, varbyte

BinaryType

bit, bool

BooleanType

date

DateType

tabstime, time, time with time zone, timetz, time without time zone, timestamp with time zone, timestamp, timestamptz, timestamp without time zone*

TimestampType/TimestampNTZType

Postgresql array type**

ArrayType

*When you read from Postgresql, Postgresql Timestamp is mapped to Spark TimestampType if preferTimestampNTZ = false (default). Postgresql Timestamp is mapped to TimestampNTZType if preferTimestampNTZ = true.

**Limited array types are supported.

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