July 30, 2023

tElasticSearchConfiguration – Docs for ESB 7.x

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tElasticSearchConfiguration

Enables the reuse of the connection configuration to ElasticSearch in the same
Job.

tElasticSearchConfiguration provides ElasticSearch
connection information for the ElasticSearch components used in the same Spark
Job. The Spark cluster to be used reads this configuration to eventually
connect to ElasticSearch.

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

tElasticSearchConfiguration properties for Apache Spark Batch

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

The Spark Batch
tElasticSearchConfiguration component belongs to the ElasticSearch family.

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

Basic settings

Nodes

Enter the location of the cluster hosting the Elasticsearch system to be used.

Transport addresses and
Cluster name

 Enter empty double quotation marks (“”) in these fields.

Use SSL/TLS

Select this check box to enable the SSL or TLS encrypted connection.

Then you need to use the tSetKeystore
component in the same Job to specify the encryption information.

User authentication

If the ElasticSearch system to be used requires authentication information, select this
check box and enter the credentials.

Configuration

Add the parameters accepted by Elasticsearch to perform more customized actions.

For example, enter es.mapping.id in the Key column and true in the
Value column to make the document field/property name
contain the document id. Note that you must put double quotation marks around the entered
information.

For a list of the parameters you can use, see https://www.elastic.co/guide/en/elasticsearch/hadoop/master/configuration.html.

Usage

Usage rule

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

Drop tElasticSearchConfiguration along with the ElasticSearch-related Subjob
to be run in the same Job so that the configuration is used by the whole Job at
runtime.

  • Note that the Talend components for Spark Jobs support the
    Elasticsearch versions up to 6.4.2.

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

No scenario is available for the Spark Batch version of this component
yet.

tElasticSearchConfiguration properties for Apache Spark Streaming

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

The Spark Streaming
tElasticSearchConfiguration component belongs to the ElasticSearch family.

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

Basic settings

Nodes

Enter the location of the cluster hosting the Elasticsearch system to be used.

The Nodes parameter is mandatory and eventually taken
into account only when the ElasticSearch component to be connected to ElasticSearch uses the
ElasticSearch Node Client, that is to say, the tElasticSearchInput component and the tElasticSearchOutput component.

For further information about the ElasticSearch Node Client and the ElasticSearch
Transport Client, see https://www.elastic.co/guide/en/elasticsearch/guide/current/_transport_client_versus_node_client.html.

Transport addresses

Enter the addresses of the ElasticSearch nodes you need the component to connect
to.

This parameter is required when your ElasticSearch Job, exactly
speaking, tElasticSearchLookupInput in your Job, to use the
ElasticSearch Transport Client to connect to the ElasticSearch cluster to be used. If
you do not use ElasticSearch Transport Client, leave empty double quoation marks (“”) in
this field.

For further information about the ElasticSearch Node Client and the ElasticSearch
Transport Client, see https://www.elastic.co/guide/en/elasticsearch/guide/current/_transport_client_versus_node_client.html.

Cluster name

Enter the name the ElasticSearch cluster to be used.

This parameter is required when your ElasticSearch Job, exactly
speaking, tElasticSearchLookupInput in your Job, to use the
ElasticSearch Transport Client to connect to the ElasticSearch cluster to be used. If
you do not use ElasticSearch Transport Client, leave empty double quoation marks (“”) in
this field.

Use SSL/TLS

Select this check box to enable the SSL or TLS encrypted connection.

Then you need to use the tSetKeystore
component in the same Job to specify the encryption information.

User authentication

If the ElasticSearch system to be used requires authentication information, select this
check box and enter the credentials.

To enter the password, click the […] button next to the
password field, and then in the pop-up dialog box enter the password between double quotes
and click OK to save the settings.

Configuration

Add the parameters accepted by Elasticsearch to perform more customized actions.

For example, enter es.mapping.id in the Key column and true in the
Value column to make the document field/property name
contain the document id. Note that you must put double quotation marks around the entered
information.

For a list of the parameters you can use, see https://www.elastic.co/guide/en/elasticsearch/hadoop/master/configuration.html.

Advanced settings

Connection pool

In this area, you configure, for each Spark executor, the connection pool used to control
the number of connections that stay open simultaneously. The default values given to the
following connection pool parameters are good enough for most use cases.

  • Max total number of connections: enter the maximum number
    of connections (idle or active) that are allowed to stay open simultaneously.

    The default number is 8. If you enter -1, you allow unlimited number of open connections at the same
    time.

  • Max waiting time (ms): enter the maximum amount of time
    at the end of which the response to a demand for using a connection should be returned by
    the connection pool. By default, it is -1, that is to say, infinite.

  • Min number of idle connections: enter the minimum number
    of idle connections (connections not used) maintained in the connection pool.

  • Max number of idle connections: enter the maximum number
    of idle connections (connections not used) maintained in the connection pool.

Evict connections

Select this check box to define criteria to destroy connections in the connection pool. The
following fields are displayed once you have selected it.

  • Time between two eviction runs: enter the time interval
    (in milliseconds) at the end of which the component checks the status of the connections and
    destroys the idle ones.

  • Min idle time for a connection to be eligible to
    eviction    : enter the time interval (in milliseconds) at the end of which the idle
    connections are destroyed.

  • Soft min idle time for a connection to be eligible to
    eviction    : this parameter works the same way as Min idle
    time for a connection to be eligible to eviction     but it keeps the minimum number
    of idle connections, the number you define in the Min number of idle
    connections     field.

Usage

Usage rule

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

Drop tElasticSearchConfiguration along with the ElasticSearch-related Subjob
to be run in the same Job so that the configuration is used by the whole Job at
runtime.

  • Note that the Talend components for Spark Jobs support the
    Elasticsearch versions up to 6.4.2.

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

No scenario is available for the Spark Streaming version of this component
yet.

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