Create Local Big Data Environment (Legacy)

Options

Settings

Context name

The unique name of the context. Only one Spark context will be created when you execute several Create Local Big Data Environment nodes with the same context name.

Number of threads

The number of threads the local Spark runtime can be use.

Action to perform on dispose

Decides what happens with the Spark context when the workflow or KNIME is closed.

• Destroy Spark context: Will destroy the Spark context and free up all allocated resources.
• Delete Spark DataFrames: Will delete all Spark DataFrames but keeps the Spark context with all the allocated resources open.
• Do nothing: Leaves the Spark context and all created Spark DataFrames as is.

Use custom Spark settings

Select this option to specify additional Spark settings. For more details see Custom Spark settings description.

Custom Spark settings

Allows you to pass on any settings to the Spark context. Especially interesting if you want to add additional jars e.g. to test your own UDFs.

SQL Support

• Spark SQL only: The Spark SQL node will only support Spark SQL syntax. The Hive connection port will be disabled.
• HiveQL: The Spark SQL node will support HiveQL syntax. The Hive connection port will be disabled.
• HiveQL and provide JDBC connection: The Spark SQL node will support HiveQL syntax. The Hive connection port will be enabled, which allows you to also work with a local Hive instance using the KNIME database nodes.

Use custom Hive data folder (Metastore DB & Warehouse)

If selected, the Hive table definitions and data files are stored in the specified location and will be also available after a KNIME restart. If not selected, all Hive related information is stored in a temporary location which will be deleted when the local Spark context is destroyed.

Hide warning about an existing local Spark context

Enable this option to suppress a warning message shown when the Spark context to be created by this node already exists. For further details see the Context name option.

Time

This tab allows to set a time zone that is applied in two cases:

• To set the Spark SQL session time zone, which is relevant in Spark SQL, when parsing Strings such as '2020-03-27 08:00:00' into Timestamps (to_timestamp) and vice versa, as well as datetime manipulations.
• In KNIME, when mapping between Spark Timestamps and the KNIME (legacy) Date and Time type column type. Here, the specified time zone will be used to make the Date and Time value in KNIME equal to what would be displayed when displaying a Timestamp in Spark.

Do not set

Leaves the Spark SQL session time zone unchanged and does not align the display of KNIME (legacy) Date and Time columns.

Use default time zone from Spark cluster

Leaves the Spark SQL session time zone unchanged but aligns the display of KNIME (legacy) Date and Time columns, based on the Spark SQL session timezone. This is the default.

Use fixed time zone

Allows to specify a time zone that will be set as the Spark SQL session time zone. The same time zone and which will be used to align the display of KNIME (legacy) Date and Time columns.

Fail on different cluster default time zone

Allows to specify whether this node should fail, when the cluster-side default time zone is different from the fixed time zone that was specified.

Views

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Workflows

• 2.Modelling - solutionKNIME Hub

Links

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