July 30, 2023

tJMSInput – Docs for ESB 7.x

tJMSInput

Creates an interface between a Java application and a Message-Oriented middleware
system.

Using a JMS server, tJMSInput makes it possible to have loosely coupled,
reliable, and asynchronous communication between different components in a distributed
application.

For further information, see the section about messaging brokers supported by Talend messaging components in Talend Data Fabric Studio User Guide.

Depending on the Talend
product you are using, this component can be used in one, some or all of the following
Job frameworks:

tJMSInput Standard properties

These properties are used to configure tJMSInput running in the Standard Job framework.

The Standard
tJMSInput component belongs to the Internet family.

The component in this framework is available in all Talend
products
.

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.

Enable Durable Subscription

Select this check box to enable the durable
subscription.

ClientID

Enter the client ID for the durable subscription.

This field is available only when the Enable Durable Subscription check box is
selected.

Subscriber Name

Enter the subscriber name for the durable
subscription.

This field is available only when the Enable Durable Subscription check box is
selected.

Use JNDI Name Lookup Destination

Select this check box to look up a destination with the JNDI (Java Naming
and Directory Interface) name.

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. When you create a Spark
Job, avoid the reserved word line when naming the
fields.

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

Advanced settings

Properties

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

tStatCatcher Statistics

Select this check box to gather the Job processing metadata at a Job
level as well as at each component level.

Global Variables

Global Variables

ERROR_MESSAGE: the error message generated by the
component when an error occurs. This is an After variable and it returns a string. This
variable functions only if the Die on error check box is
cleared, if the component has this check box.

NB_LINE: the number of rows read by an input component or
transferred to an output component. This is an After variable and it returns an
integer.

A Flow variable functions during the execution of a component while an After variable
functions after the execution of the component.

To fill up a field or expression with a variable, press Ctrl +
Space
to access the variable list and choose the variable to use from it.

For further information about variables, see
Talend Studio

User Guide.

Usage

Usage rule

This component is generally used as an input component. It must be
linked to an output component.

Limitation

Make sure the JMS server is launched.

Due to license incompatibility, one or more JARs required to use
this component are not provided. You can install the missing JARs for this particular
component by clicking the Install button
on the Component tab view. You can also
find out and add all missing JARs easily on the Modules tab in the
Integration
perspective of your studio. You can find more details about how to install external modules in
Talend Help Center (https://help.talend.com)
.

Related scenarios

tJMSInput properties for Apache Spark Streaming

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

The Spark Streaming
tJMSInput component belongs to the Messaging family.

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

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. When you create a Spark
Job, avoid the reserved word line when naming the
fields.

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 encryption information.

Properties

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

Usage

Usage rule

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

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

In the Spark
Configuration
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
      tab.

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

    • When using Altus, specify the S3 bucket or the Azure
      Data Lake Storage for Job deployment in the Spark
      configuration
      tab.
    • 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
    tS3Configuration.

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

This connection is effective on a per-Job basis.

Related scenarios

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


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