tCollectAndCheck properties in Spark Streaming 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

Component family

Technical

 

Basic settings

Separator

Enter character, string or regular expression to separate fields for the transferred data.

 

Line separator

Enter the separator used to identify the end of a row.

  Use context variable

If you have already created the context variable representing the reference file to be used, select this check box and enter this variable in the Variable name field that is displayed.

Then syntax to call a variable is context.VariableName.

For further information about variables, see Talend Studio User Guide.

 

Reference data

If you do not want to use context variables to represent the reference data to be used, enter this reference data directly in this field.

 

Keep the order from the reference

If the RDDs to be checked are sorted, select this check box to keep your reference data ordered.

Advanced settings

When the reference is empty, expect no incoming value

By default, this check box is clear, meaning that when an field in the reference data is empty, the test expects an equally empty field in the incoming datasets being verified in order to validate the test result.

If you want the test to expect no value when the reference is empty, select this check box.

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 is added automatically to a test case being created to show the test result in the console of the Run view.

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.

Log4j

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 http://logging.apache.org/log4j/1.2/apidocs/org/apache/log4j/Level.html.