Apache Spark Connection¶

The Apache Spark connection type enables connection to Apache Spark.

Default Connection IDs¶

Spark Submit and Spark JDBC hooks and operators use spark_default by default. Spark SQL hooks and operators point to spark_sql_default by default.

Configuring the Connection¶

Host (required)

The host to connect to, it can be local, yarn or an URL.

Port (optional)

Specify the port in case of host be an URL.

Extra (optional)

Specify the extra parameters (as json dictionary) that can be used in spark connection. The following parameters out of the standard python parameters are supported:

queue - The name of the YARN queue to which the application is submitted.
deploy-mode - Whether to deploy your driver on the worker nodes (cluster) or locally as an external client (client).
spark-binary - The command to use for Spark submit. Some distros may use spark2-submit. Default spark-submit. Only spark-submit, spark2-submit or spark3-submit are allowed as value.
namespace - Kubernetes namespace (spark.kubernetes.namespace) to divide cluster resources between multiple users (via resource quota).

When specifying the connection in environment variable you should specify it using URI syntax.

Note that all components of the URI should be URL-encoded. The URI and and the mongo connection string are not the same.

For example:

export AIRFLOW_CONN_SPARK_DEFAULT='spark://mysparkcluster.com:80?deploy-mode=cluster&spark_binary=command&namespace=kube+namespace'

Warning

Make sure you trust your users with the ability to configure the host settings as it may enable the connection to establish communication with external servers. It’s crucial to understand that directing the connection towards a malicious server can lead to significant security vulnerabilities, including the risk of encountering Remote Code Execution (RCE) attacks.