July 30, 2023

tBoundedStreamInput – Docs for ESB 7.x


Provides a data stream for the component to be tested and is suitable for use in a
test case only.

loads data put in its Basic settings tab or from a
given context variable in order to generates a data stream.

is available only in a test case about a given component and is added automatically to
the test case you are using. For further information about test cases, see
Talend Studio User Guide

tBoundedStreamInput properties for Apache Spark Streaming

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

The Spark Streaming
tBoundedStreamInput component belongs to the Technical family.

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

Basic settings

Schema and Edit

A schema is a row description. It defines the number of fields
(columns) to be processed and passed on to the next component. When you create a Spark
Job, avoid the reserved word line when naming the

Click Edit
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


Built-In: You create and store the schema locally for this component


Repository: You have already created the schema and stored it in the
Repository. You can reuse it in various projects and Job designs.


Select the mode that you want to use to generate the data

  • Use Inline Content: enter the
    data that you want to generate.

  • Use context variable: enter
    the name of variable to be used to provide data. This variable
    must have been defined in the Contexts tab of the current Job.

    The syntax to call a variable is context.VariableName.

In either mode, the data you provide must use the separators you have
defined in the Row separator, Field Separator and Micro batch separator fields.


Usage rule

This component is used as a start component and requires an output link.

This component is added automatically to a test case being created to provide input

Spark Connection

In the Spark
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

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

    • When using Altus, specify the S3 bucket or the Azure
      Data Lake Storage for Job deployment in the Spark
    • 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

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

This connection is effective on a per-Job basis.

Related scenarios

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

Document get from Talend https://help.talend.com
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