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Big Data

Feature

Description

Available in

Support for Spark Universal 3.4.x in Local mode You can now run your Spark Batch and Spark Streaming Jobs using Spark Universal with Spark 3.4.x in Local mode. You can configure it either in the Spark Configuration view of your Spark Jobs or in the Hadoop Cluster Connection metadata wizard.

All subscription-based Talend products with Big Data

Support for custom settings on AWS EMR Serverless with Spark Universal 3.2.x and 3.3.x in Spark Batch Jobs You now have the possibility to custom the settings of your Spark Batch Jobs on AWS EMR Serverless with Spark Universal 3.2.x and 3.3.x. You can configure it in the Spark Configuration view of your Spark Batch Jobs by selecting the Custom settings check box.

This new parameter allows you to control all the settings including pre-initialized capacity, or network connection for example.

All subscription-based Talend products with Big Data

Support for Dataproc 2.1 onwards with Spark Universal 3.3.x in Spark Batch Jobs You can now run your Spark Batch Jobs on Dataproc with Spark Universal 3.3.x. You can configure it in the Spark Configuration view of your Spark Batch Jobs.

When you select this mode, Talend Studio is compatible with Dataproc 2.1 onwards versions.

All subscription-based Talend products with Big Data

Support for Dataproc 2.1 onwards with Spark Universal 3.3.x in Standard Jobs Standard Jobs with Hive components now support Dataproc 2.1 onwards with Spark Universal 3.3.x.

All subscription-based Talend products with Big Data

Support for Spark-submit scripts with Universal 3.3.x in Spark Batch Jobs The Spark-submit scripts mode allows you to leverage a HPE Ezmeral Data Fabric v9.1.x cluster to run your Spark Batch Jobs.

You can also use this mode with other clusters than HPE Data Fabric. This is because a Spark-submit script is designed to work with all of Spark’s supported cluster managers, as documented in cluster managers from the Spark documentation.

All subscription-based Talend products with Big Data

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