tMap properties in Spark Batch Jobs - 6.1

Talend Components Reference Guide

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Basic settings

Map editor

It allows you to define the tMap routing and transformation properties but note that only the Load once lookup model is supported by the Spark Batch Jobs.

For further information about this Load once lookup model, see

When you click the Property Settings button at the top of the input area, a [Property Settings] dialog box is displayed in which you can set the following parameters:

  • If you do not want to handle execution errors, select the Die on error check box (selected by default). It will kill the Job if there is an error.

  • To maximize the data transformation performance in a Job that handles multiple lookup input flows with large amounts of data, you can select the Lookup in parallel check box.

  • Temp data directory path: enter the path where you want to store the temporary data generated for lookup loading. For more information on this folder, see Talend Studio User Guide.

  • Max buffer size (nb of rows): enter the size of physical memory, in number of rows, you want to allocate to processed data.


Mapping links display as

Auto: the default setting is curves links

Curves: the mapping display as curves

Lines: the mapping displays as straight lines. This last option allows to slightly enhance performance.



The preview is an instant shot of the Mapper data. It becomes available when Mapper properties have been filled in with data. The preview synchronization takes effect only after saving changes.


Use replicated join

Select this check box to perform a replicated join between the input flows. By replicating each lookup table into memory, this type of join doesn't require an additional shuffle-and-sort step, thus speeding up the whole process.

You need to ensure that the entire lookup tables fit in memory.

  Max buffer size (nb of rows) Type in the size of physical memory, in number of rows, you want to allocate to processed data.

Usage in Spark Batch Jobs

In a Talend Spark Batch Job, this component is used as an intermediate step and other components used along with it must be Spark Batch components, too. They generate native Spark Batch code that can be executed directly in a Spark cluster.

This component, along with the Spark Batch component Palette it belongs to, appears only when you are creating a Spark Batch Job.

Note that in this documentation, unless otherwise explicitly stated, a scenario presents only Standard Jobs, that is to say traditional Talend data integration Jobs.

Spark Connection

You need to use the Spark Configuration tab in the Run view to define the connection to a given Spark cluster for the whole Job. In addition, since the Job expects its dependent jar files for execution, one and only one file system related component from the Storage family is required in the same Job so that Spark can use this component to connect to the file system to which the jar files dependent on the Job are transferred:

This connection is effective on a per-Job basis.


If you are using a subscription-based version of the Studio, the activity of this component can be logged using the log4j feature. For more information on this feature, see Talend Studio User Guide.

For more information on the log4j logging levels, see the Apache documentation at