tFixedFlowInput properties in Spark Batch Jobs - 6.1

Talend Components Reference Guide

EnrichVersion
6.1
EnrichProdName
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 Data Quality
Talend Open Studio for ESB
Talend Open Studio for MDM
Talend Real-Time Big Data Platform
task
Data Governance
Data Quality and Preparation
Design and Development
EnrichPlatform
Talend Studio

Warning

This component will be available in the Palette of Talend Studio on the condition that you have subscribed to one of the Talend solutions with Big Data.

Component family

Misc

 

Basic settings

Schema and Edit Schema

A schema is a row description, it defines the number of fields that will be processed and passed on to the next component. The schema is either built-in or remote in the Repository.

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.

 

 

Built-in: The schema will be created and stored 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, hence can be reused in various projects and job designs. Related topic: see Talend Studio User Guide.

 

Mode

From the three options, select the mode that you want to use.

Use Single Table : Enter the data that you want to generate in the relevant value field.

Use Inline Table : Add the row(s) that you want to generate.

Use Inline Content : Enter the data that you want to generate, separated by the separators that you have already defined in the Row and Field Separator fields.

 

Number of rows

Enter the number of lines to be generated.

 

Values

Between inverted commas, enter the values corresponding to the columns you defined in the schema dialog box via the Edit schema button.

Advanced settings

Set the number of partitions

Select this check box and then enter the number of partitions into which you want to dispatch the input rows.

If you leave this check box clear, each input row forms a partition. For example, with 5 in the Number of rows field, each row is handled as one partition and thus they make 5 partitions in total.

Usage in Spark Batch Jobs

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

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

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.