tJMSInput 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
EnrichPlatform
Talend Studio
task
Data Governance
Data Quality and Preparation
Design and Development

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

Messaging / MOM and JMS

 

Basic settings

Module List

Select the library to be used from the list.

 

Context Provider

Type in the context URL, for example com.tibco.tibjms.naming.TibjmsInitialContextFactory. However, be careful, the syntax can vary according to the JMS server used.

 

Server URL

Type in the server URL, respecting the syntax, for example tibjmsnaming://localhost:7222.

 

Connection Factory JDNI Name

Type in the JDNI name.

 

Use Specified User Identity

If you have to log in, select the check box and type in your login and password.

To enter the password, click the [...] button next to the password field, and then in the pop-up dialog box enter the password between double quotes and click OK to save the settings.

 

Message Type

Select the message type, either: Topic or Queue.

 

Message From

Type in the message source, exactly as expected by the server; this must include the type and name of the source. e.g.: queue/A or topic/testtopic

Note that the field is case-sensitive.

 

Timeout for Next Message (in sec)

Type in the number of seconds before passing to the next message.

 

Maximum Messages

Type in the maximum number of messages to be processed.

 

Message Selector Expression

Set your filter.

 

Processing Mode

Select the processing mode for the messages.

Raw Message or Message Content

 

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.

The schema of this component is read-only. You can click Edit schema to view the schema.

Advanced settings

Use SSL/TLS

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.

 

Properties

Click the plus button underneath the table to add lines that contains username and password required for user authentication.

Usage in Spark Streaming Jobs

In a Talend Spark Streaming Job, it is used as a start component and requires an output 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, 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.

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.

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.