tElasticSearchOutput properties in Spark Streaming Jobs - 6.1

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The streaming version of this component is available in the Palette of the studio on the condition that you have subscribed to Talend Real-time Big Data Platform or Talend Data Fabric.

Component family



Basic settings

Schema and Edit Schema

A schema is a row description. It defines the number of fields (columns) to be processed and passed on to the next component. The schema is either Built-In or stored remotely in the Repository.



Built-In: You create and store the schema locally for this component only. Related topic: see Talend Studio User Guide.



Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. Related topic: see Talend Studio User Guide.


Click Edit schema to make changes to the schema. If the current schema is of the Repository type, three options are available:

  • View schema: choose this option to view the schema only.

  • Change to built-in property: choose this option to change the schema to Built-in for local changes.

  • Update repository connection: choose this option to change the schema stored in the repository and decide whether to propagate the changes to all the Jobs upon completion. If you just want to propagate the changes to the current Job, you can select No upon completion and choose this schema metadata again in the [Repository Content] window.


Use an existing configuration

Select this check box and in the Component List click the relevant connection component to reuse the connection details you already defined.



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



Enter the name of the index in which you want to write documents.

An index is the largest unit of storage in the Elastisearch system.



Enter the name of the type the documents to be written belong to.

For example, blogpost_en and blogpost_fr can be two types that represent given English blog posts and French blog posts, respectively.

You can dynamically uses the values of a given column to be document types. If you need to do so, enter the name of that column into a pair of braces ({}), for example, {blog_author}.


Output document

Select how the document is written into Elasticsearch.

  • JAVABEAN: if you select this option, tElasticsearchOutput directly uses the input schema to construct the JSON strings to be written.

    For example, if a record with its schema reads as follows

    id name age
    1  user 18

    the document outputted by this JAVABEAN option is {"id":1,"name":"user","age":18}.

  • JSON: with this option, a read-only json_document column is automatically added to the output schema to receive JSON strings (documents in terms of Elasticsearch) from its preceding components. This means you need to use tWriteJSONField in the same Job to construct JSON strings before outputting them to tElasticsearchOutput. The other columns of the schema can be used as metadata of these JSON documents.

    Since tWriteJSONField allows you to construct JSON trees of different complexities, you can thus manage how the JSON strings to be written should look like.

Advanced settings

Document metadata

Complete this table to select the input columns to be used to provide metadata for each document. This table is typically used along with the json_document option from the Output document drop-down list in the Basic settings view.

The Column column is automatically fed with the columns of the input schema. Then in the As metadata column, you need to select the check box(es) that correspond to the column(s) to be used.

In the Metadata type column, select which type of document metadata each column is used to provide.

For further information about the metadata types of an Elasticsearch document, see



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 authentication information.

For further information about tSetKeystore, see tSetKeystore.



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

For example, enter 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

Usage in Spark Streaming Jobs

In a Talend Spark Streaming Job, it is used as an end component and requires an input link. The other components used along with it must be Spark Streaming components, too. They generate native Spark code that can be executed directly in a Spark cluster.

This component should use a tElasticSearchConfiguration component present in the same Job to connect to ElasticSearch. You need to select the Use an existing configuration check box and then select the tElasticSearchConfiguration component to be used.

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.


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

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.