tLibraryLoad properties for Apache Spark Batch - 7.3

Library import

EnrichVersion
Cloud
7.3
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Talend Big Data
Talend Big Data Platform
Talend Data Fabric
Talend Data Integration
Talend Data Management Platform
Talend Data Services Platform
Talend ESB
Talend MDM Platform
Talend Open Studio for Big Data
Talend Open Studio for Data Integration
Talend Open Studio for ESB
Talend Real-Time Big Data Platform
EnrichPlatform
Talend Studio
task
Data Governance > Third-party systems > Custom code components (Integration) > Library import component
Data Quality and Preparation > Third-party systems > Custom code components (Integration) > Library import component
Design and Development > Third-party systems > Custom code components (Integration) > Library import component

These properties are used to configure tLibraryLoad running in the Spark Batch Job framework.

The Spark Batch tLibraryLoad component belongs to the Custom Code family.

The component in this framework is available in all subscription-based Talend products with Big Data and Talend Data Fabric.

Basic settings

Library

Click on the [...] button to to open the Module dialog box from which you can import the library to be used.

For more information, see Importing an external library.

Advanced settings

Import

Enter the Java code required to import, if required, the external library used in the code editing field of the Basic settings tab of the components such as tJavaMR in a Map/Reduce Job.

Usage

Usage rule

This component is used with no need to be connected to other components.

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

In the Spark Configuration tab in the Run view, define the connection to a given Spark cluster for the whole Job. In addition, since the Job expects its dependent jar files for execution, you must specify the directory in the file system to which these jar files are transferred so that Spark can access these files:
  • Yarn mode (Yarn client or Yarn cluster):
    • When using Google Dataproc, specify a bucket in the Google Storage staging bucket field in the Spark configuration tab.

    • When using HDInsight, specify the blob to be used for Job deployment in the Windows Azure Storage configuration area in the Spark configuration tab.

    • When using Altus, specify the S3 bucket or the Azure Data Lake Storage for Job deployment in the Spark configuration tab.
    • When using Qubole, add a tS3Configuration to your Job to write your actual business data in the S3 system with Qubole. Without tS3Configuration, this business data is written in the Qubole HDFS system and destroyed once you shut down your cluster.
    • When using on-premise distributions, use the configuration component corresponding to the file system your cluster is using. Typically, this system is HDFS and so use bix1550477842760.html.

  • Standalone mode: use the configuration component corresponding to the file system your cluster is using, such as bix1550477842760.html or tS3Configuration.

    If you are using Databricks without any configuration component present in your Job, your business data is written directly in DBFS (Databricks Filesystem).

This connection is effective on a per-Job basis.

Limitation

The library is loaded locally.