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Query PostgreSQL with Databricks

This example queries PostgreSQL using its JDBC driver. For more details on reading, writing, configuring parallelism, and query pushdown, see Query databases using JDBC.

Experimental

The configurations described in this article are Experimental. Experimental features are provided as-is and are not supported by Databricks through customer technical support. To get full query federation support, you should instead use Lakehouse Federation, which enables your Databricks users to take advantage of Unity Catalog syntax and data governance tools.

Using JDBC

Python
driver = "org.postgresql.Driver"

database_host = "<database-host-url>"
database_port = "5432" # update if you use a non-default port
database_name = "<database-name>"
table = "<table-name>"
user = "<username>"
password = "<password>"

url = f"jdbc:postgresql://{database_host}:{database_port}/{database_name}"

remote_table = (spark.read
.format("jdbc")
.option("driver", driver)
.option("url", url)
.option("dbtable", table)
.option("user", user)
.option("password", password)
.load()
)

Using the PostgreSQL connector in Databricks Runtime

In Databricks Runtime 11.3 LTS and above, you can use the named connector to query PosgresQL. See the following examples:

Python
remote_table = (spark.read
.format("postgresql")
.option("dbtable", "schema_name.table_name") # if schema_name not provided, default to "public".
.option("host", "database_hostname")
.option("port", "5432") # Optional - will use default port 5432 if not specified.
.option("database", "database_name")
.option("user", "username")
.option("password", "password")
.load()
)