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Databricks Spark Connector

Creates a connection to an existing Databricks cluster that can be used to run Spark nodes. See AWS or Azure Databricks documentation for more information.

Note: To avoid an accidental cluster startup, this node creates a dummy Spark port if loaded in executed state from a stored workflow. Reset and execute the node to start the cluster and create a Spark execution context.

Cluster access control: KNIME uploads additional libraries to the cluster. This requires manage cluster-level permissions if your cluster is secured with access control. See the Databricks documentation on how to set up the permission.

Options

Cluster ID: Unique identifier of a cluster in the databricks workspace.
Spark Version: Version of Spark running on the cluster.
Staging area for Spark jobs: Specify a directory in the Unity File System, that will be used to transfer temporary files between KNIME and the Spark context.
Terminate cluster on context destroy: If selected, the cluster will be destroyed when the node will be reset, the Destroy Spark Context node executed on the context, the workflow or KNIME is closed. This way, resources are released, but all data cached inside the cluster are lost, unless they have been saved to persistent storage such as DBFS.
Job status polling interval (seconds): The frequency with which KNIME polls the status of a job in seconds.

Input Ports

: Databricks Workspace connection

Output Ports

: Spark context, that can be connected to all Spark nodes.
: Databricks Unity File System connection, that can be connected to the Spark nodes to read/write files.

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Installation

To use this node in KNIME, install the extension KNIME Databricks Integration from the below update site following our NodePit Product and Node Installation Guide:

v5.12

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.12.0.v202603171725

On NodePit since: 2026-03-18

Last update: 2026-03-18

Tags: StreamableModern UI

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