Query MySQL with Azure Databricks

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

Important

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 Azure Databricks users to take advantage of Unity Catalog syntax and data governance tools.

Using JDBC

Python

driver = "com.mysql.cj.jdbc.Driver"

database_host = "<database-host-url>"
database_port = "3306" # update if you use a non-default port
database_name = "<database-name>"
table = "<table-name>"
user = "<username>"
password = "<password>"

url = f"jdbc:mysql://{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()
)

Scala

val driver = "com.mysql.cj.jdbc.Driver"

val database_host = "<database-host-url>"
val database_port = "3306" # update if you use a non-default port
val database_name = "<database-name>"
val table = "<table-name>"
val user = "<username>"
val password = "<password>"

val url = s"jdbc:mysql://${database_host}:${database_port}/${database_name}"

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

Using the MySQL connector in Databricks Runtime

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

Python

remote_table = (spark.read
  .format("mysql")
  .option("dbtable", "table_name")
  .option("host", "database_hostname")
  .option("port", "3306") # Optional - will use default port 3306 if not specified.
  .option("database", "database_name")
  .option("user", "username")
  .option("password", "password")
  .load()
)

SQL

DROP TABLE IF EXISTS mysql_table;
CREATE TABLE mysql_table
USING mysql
OPTIONS (
  dbtable '<table-name>',
  host '<database-host-url>',
  port '3306', /* Optional - will use default port 3306 if not specified. */
  database '<database-name>',
  user '<username>',
  password '<password>'
);
SELECT * from mysql_table;

Scala

val remote_table = spark.read
  .format("mysql")
  .option("dbtable", "table_name")
  .option("host", "database_hostname")
  .option("port", "3306") # Optional - will use default port 3306 if not specified.
  .option("database", "database_name")
  .option("user", "username")
  .option("password", "password")
  .load()