This node is currently not available in KNIME v5.4 — instead we’re showing this page for KNIME v3.6. You can use the version menu in the title bar to permanently switch your preferred version. This will also show the link to the update site.

Create Spark Context via Livy (preview)

Creates a new Spark context via Apache Livy.

This node requires access to a remote file system such as HDFS/webHDFs/httpFS or S3/Blob Store in order to exchange temporary files between KNIME and the Spark context (running on the cluster).

Note: Executing this node always creates a new Spark context. Resetting the node or closing the KNIME workflow will destroy the Spark context. Spark contexts created by this node cannot be shared between KNIME workflows.

Options

General

Spark version

The version of the Spark context.

Livy URL

The URL of Livy including protocol and port e.g. http://localhost:8998.

Auhtentication

Select

None, if Livy does not require any credentials.
Kerberos, if Livy uses Kerberos based authentication.

Spark executor resources

Select the "Override default Spark executor resources" option to manually set the resources for the Spark executors. If enabled you can specify the amount of memory and the number of cores for each executor.
In addition you can specify the Spark executor allocation strategy:

Default allocation uses the cluster default allocation strategy.
Fixed allocation allows you to specify a fixed number of Spark executors.
Dynamic allocation allows you to specify the minimum and maximum number of executors that Spark can use. Executors are allocated up to the maximum number and destroyed if no longer needed until the minimum number of executors is reached.

Estimated resources

An estimation of the resources that are allocated in your cluster by the Spark context. The calculation uses default settings for memory overheads etc. and is thus only an estimate. The exact resources might be different depending on your specific cluster settings.

Advanced

Override default Spark driver resources: If enabled you can specify the amount of memory and number of cores the Spark driver process will allocate.
Set staging area for Spark jobs: If enabled you can specify a directory in the connected remote file system, that will be used to transfer temporary files between KNIME and the Spark context. If no directory is set, then a default directory will be chosen, e.g. the HDFS user home directory. However, if the remote file system is Amazon S3 or Azure Blob Store, then a staging directory must be provided.
Set custom Spark settings: If enabled you can specify additional Spark setting. A tooltip is provided for the keys if available. For further information about the Spark settings refer to the Spark documentation.

Input Ports

A connection to a remote file system to exchange temporary files between KNIME and the Spark context (running on the cluster). Supported file systems are:

HDFS, webHDFS and httpFS. Note that here KNIME must access the remote file system with the same user as Spark, otherwise Spark context creation fails. When authenticating with Kerberos against both HDFS/webHDFs/httpFS and Livy, then usually the same user will be used. Otherwise, this must be ensured manually.
Amazon S3 and Azure Blob Store (recommended when using Spark on Amazon EMR/Azure HDInsight). Note that for these file systems a staging area must be specified (see above).

Output Ports

: Spark context.

Popular Predecessors

Popular Successors

Views

Spark log: Displays the log messages returned by the spark-submit process on the Livy server machine. This view does not provide the YARN container logs.

Workflows

No workflows found

Developers

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Installation

To use this node in KNIME, install the extension KNIME Extension for Apache Spark from the below update site following our NodePit Product and Node Installation Guide:

v3.6

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

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 2.3.2.v201811051556

On NodePit since: 2019-06-25

Last update: 2024-12-11

KNIME versions: From v3.6 to v3.7

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