August 16, 2023

tJava – Docs for ESB 6.x

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tJava

Extends the functionalities of a Talend Job using custom Java
commands.

tJava enables you to enter personalized
code in order to integrate it in Talend program. You can execute
this code only once.

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

tJava Standard properties

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

The Standard
tJava component belongs to the Custom Code family.

The component in this framework is generally available.

Basic settings

Code

Type in the Java code you want to execute according to the task you
need to perform. For further information about Java functions syntax
specific to
Talend
, see
Talend Studio
 Help Contents (Help >
Developer Guide > API Reference).

For a complete Java reference, check http://docs.oracle.com/javaee/6/api/

Note:

This component offers the advantage of the dynamic schema
feature. This allows you to retrieve unknown columns from source files or
to copy batches of columns from a source with­out mapping each column
individually. For further information about dynamic schemas, see

Talend Studio User Guide.

Advanced settings

Import

Enter the Java code to import, if necessary, external libraries used in the Code field of the Basic settings
view.

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.

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 a one-component subjob.

Limitation

You should know Java language.

Scenario: Printing out a variable content

The following scenario is a simple demo of the extended application of the tJava component. The Job aims at printing out the number of
lines being processed using a Java command and the global variable provided in
Talend Studio
.

Use_Case_tJava1.png

Setting up the Job

  1. Select and drop the following components from the Palette onto the design workspace: tFileInputDelimited, tFileOutputExcel, tJava.
  2. Connect the tFileInputDelimited to the
    tFileOutputExcel using a Row Main connection. The content from a delimited
    txt file will be passed on through the connection to an xls-type of file
    without further transformation.
  3. Then connect the tFileInputDelimited
    component to the tJava component using a
    Trigger > On
    Subjob Ok     link. This link sets a sequence ordering tJava to be executed at the end of the main
    process.

Configuring the input component

  1. Set the Basic settings of the tFileInputDelimited component.

    Use_Case_tJava2.png

  2. Define the path to the input file in the File
    name     field.

    The input file used in this example is a simple text file made of two
    columns: Names and their respective
    Emails.
  3. Click the Edit Schema button, and set the
    two-column schema. Then click OK to close
    the dialog box.

    Use_Case_tJava3.png

  4. When prompted, click OK to accept the
    propagation, so that the tFileOutputExcel
    component gets automatically set with the input schema.

Configuring the output component

Set the output file to receive the input content without changes. If the file does
not exist already, it will get created.

Use_Case_tJava4.png

In this example, the Sheet name is
Email and the Include
Header box is selected.

Configuring the tJava component

  1. Then select the tJava component to set
    the Java command to execute.

    Use_Case_tJava5.png

  2. In the Code area, type in the following
    command:

    In this use case, we use the NB_Line variable. To
    access the global variable list, press Ctrl + Space bar on your keyboard and
    select the relevant global parameter.

Executing the Job

  1. Press Ctrl+S to save
    your Job.
  2. Press F6 to execute
    it.
Use_Case_tJava6.png

The content gets passed on to the Excel file defined and the Number of lines
processed are displayed on the Run
console.

tJava properties for Apache Spark Batch

These properties are used to configure tJava running in the Spark Batch Job framework.

The Spark Batch
tJava component belongs to the Custom Code family.

The component in this framework is available only if you have subscribed to one
of the
Talend
 solutions with Big Data.

Basic settings

Schema et 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.

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.

Note that if the input value of any non-nullable primitive field is
null, the row of data including that field will be rejected.

 

Built-In: You create and store the
schema 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. You can reuse it in various projects and
Job designs. Related topic: see
Talend Studio

User Guide.

Code

Type in the Java code you want to execute to process the incoming RDD
from the input link or even create new RDDs out of this input one.

You need to leverage the schema, the link and the component name to
write the custom code. For example, if this component is labeled
tJava_1 and the connection to it
is labeled row1, then the class of
the input RDD is row1Struct and the
input RDD itself is available with the rdd_tJava_1 variable.

For more detailed instructions, see the default comment provided in
the Code field of this
component.

For further information about Spark’s Java API, see Apache’s Spark
documentation in https://spark.apache.org/docs/latest/api/java/index.html.

Advanced settings

Classes

Define the classes that you need to use in the code written in the Code field in the Basic settings
view.

It is recommended to define new classes in this field, instead of in the Code field, so as to avoid
eventual exceptions in serialization.

Import

Enter the Java code to import, if necessary, external libraries used in the Code field of the Basic settings
view.

Usage

Usage rule

This component is used as an end component and requires an input link.

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, 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: when using Google
    Dataproc, specify a bucket in the Google Storage staging
    bucket     field in the Spark
    configuration     tab; when using other distributions, use a
    tHDFSConfiguration
    component to specify the directory.

  • Standalone mode: you need to choose
    the configuration component depending on the file system you are using, such
    as tHDFSConfiguration
    or tS3Configuration.

This connection is effective on a per-Job basis.

Limitation

Knowledge of Spark and Java language is required.

Related scenarios

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

tJava properties for Apache Spark Streaming

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

The Spark Streaming
tJava component belongs to the Custom Code family.

The component in this framework is available only if you have subscribed to Talend Real-time Big Data Platform or Talend Data
Fabric.

Basic settings

Schema et 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.

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.

Note that if the input value of any non-nullable primitive field is
null, the row of data including that field will be rejected.

 

Built-In: You create and store the
schema 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. You can reuse it in various projects and
Job designs. Related topic: see
Talend Studio

User Guide.

Code

Type in the Java code you want to execute to process the incoming RDD
from the input link or even create new RDDs out of this input one.

You need to leverage the schema, the link and the component name to
write the custom code. For example, if this component is labeled
tJava_1 and the connection to it
is labeled row1, then the class of
the input RDD is row1Struct and the
input RDD itself is available with the rdd_tJava_1 variable.

For more detailed instructions, see the default comment provided in
the Code field of this
component.

For further information about Spark’s Java API, see Apache’s Spark
documentation in https://spark.apache.org/docs/latest/api/java/index.html.

Advanced settings

Classes

Define the classes that you need to use in the code written in the Code field in the Basic settings
view.

It is recommended to define new classes in this field, instead of in the Code field, so as to avoid
eventual exceptions in serialization.

Import

Enter the Java code to import, if necessary, external libraries used in the Code field of the Basic settings
view.

Usage

Usage rule

This component is used as an end component and requires an input 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

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, 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: when using Google
    Dataproc, specify a bucket in the Google Storage staging
    bucket     field in the Spark
    configuration     tab; when using other distributions, use a
    tHDFSConfiguration
    component to specify the directory.

  • Standalone mode: you need to choose
    the configuration component depending on the file system you are using, such
    as tHDFSConfiguration
    or tS3Configuration.

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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Docs 6.x
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