July 30, 2023

tTachyonConfiguration – Docs for ESB 7.x

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  4. tTachyonConfiguration – Docs for ESB 7.x

tTachyonConfiguration

Defines a connection to Tachyon storage system and enables the reuse of the
configuration in the same Job.

You define a connection to Tachyon in tTachyonConfiguration and configure the file system
related components to reused this connection. At runtime, the Spark
cluster to be used reads this configuration to connect to
Tachyon.

Depending on the Talend
product you are using, this component can be used in one, some or all of the following
Job frameworks:

tTachyonConfiguration properties for Apache Spark Batch

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

The Spark Batch
tTachyonConfiguration component belongs to the Storage family.

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

Basic settings

Tachyon master URI

Enter the address of the master server of the Tachyon cluster to be used.

This information can be found in the conf/tachyon-env.sh file of your Tachyon system.

For details about the version compatibility between Tachyon and Spark, see Tachyon
documentation at http://tachyon-project.org/documentation/Running-Spark-on-Tachyon.html.

UnderFS username

Enter the credential required by the file system (underlayer storage system in terms of Tachyon) used by your Tachyon cluster. The default file system is HDFS.

This information can be found in the conf/tachyon-env.sh file of your Tachyon system.

Usage

Usage rule

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

You need to drop tTachyonConfiguration along with the file system related Subjob to be run in the
same Job so that the configuration is used by the whole Job at runtime.

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 tHDFSConfiguration.

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

Related scenarios

For a scenario about how to use the same type of component in a Spark Batch Job, see Writing and reading data from MongoDB using a Spark Batch Job.

tTachyonConfiguration properties for Apache Spark Streaming

These properties are used to configure tTachyonConfiguration running in the Spark Streaming Job framework.

The Spark Streaming
tTachyonConfiguration component belongs to the Storage family.

This component is available in Talend Real Time Big Data Platform and Talend Data Fabric.

Basic settings

Tachyon master URI

Enter the address of the master server of the Tachyon cluster to be used.

This information can be found in the conf/tachyon-env.sh file of your Tachyon system.

For details about the version compatibility between Tachyon and Spark, see Tachyon
documentation at http://tachyon-project.org/documentation/Running-Spark-on-Tachyon.html.

UnderFS username

Enter the credential required by the file system (underlayer storage system in terms of Tachyon) used by your Tachyon cluster. The default file system is HDFS.

This information can be found in the conf/tachyon-env.sh file of your Tachyon system.

Usage

Usage rule

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

You need to drop tTachyonConfiguration along with the file system related Subjob to be run in the
same Job so that the configuration is used by the whole Job at runtime.

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

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

Related scenarios

For a scenario about how to use the same type of component in a Spark Streaming Job, see
Reading and writing data in MongoDB using a Spark Streaming Job.

Document get from Talend https://help.talend.com
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Docs 7.x
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