tWindow 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

Warning

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

Processing

 

 Basic settings

Window duration

Enter, without quotation marks, the duration (in milliseconds) that defines the length of the window to be applied.

For example, if the batch size defined in the Spark configuration tab is 2 seconds, a window duration of 6 seconds means that 3 batches are handled each time this window is applied.

 

Define the slide duration

Select the Define the slide duration check box and in the field that is displayed, enter, without quotation marks, the time in milliseconds at the end of which the window is to be applied.

For example, if the batch size defined in the Spark configuration tab is 2 seconds, a slide duration of 4 seconds means the window is applied every 4 seconds; and if the window duration is 6 seconds, after two window applications there will be the overlap of one batch.

If you leave this check box clear, the slide duration is assumed to be the batch size defined in the Spark configuration tab.

Both the window duration and the slide duration must be multiples of the batch size defined in the Spark configuration tab.

Usage in Spark Streaming Jobs

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

This component does not change the data schema but controls the pace of the processing of the micro-batches via the specific window.

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

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.