July 30, 2023

tTransliterate – Docs for ESB 7.x

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tTransliterate

Converts strings from many languages of the world to a standard set of characters
(Universal Coded Character Set, UCS).

This is a phonetic operation where the tTransliterate component attempts to create in UCS an equivalent of the
original string based on the sounds the string represents.

tTransliterate encodes text expressed in many of the world’s writing
systems to readable characters based on the repertoire of the Unicode Standard. This
makes it easier for you to recognize and interpret words from different languages than
if the letters are left in the original script. For further information about Unicode
and Unicode Standard, check Unicode and Unicode Standard.

In local mode, Apache Spark 2.0.0, 2.3.0 and 2.4.0 are supported.

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

tTransliterate Standard properties

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

The Standard
tTransliterate component belongs to the Data Quality family.

The component in this framework is available in Talend Data Management Platform, Talend Big Data Platform, Talend Real Time Big Data Platform, Talend Data Services Platform, Talend MDM Platform and in Talend Data Fabric.

Basic settings

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.

 

Built-In: You create and store the schema locally for this component
only.

 

Repository: You have already created the schema and stored it in the
Repository. You can reuse it in various projects and Job designs.

Edit Schema

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.

Transliteration

This table lists the columns defined in the schema of the tTransliterate component.

Select the Transliterate check box
next to the column(s) of which you want to convert the content to
readable standard set of characters.

Advanced settings

tStatCatcher Statistics

Select this check box to collect log data at the 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 an intermediary step. It requires an input and
output flows.

Converting words from different languages to standard set of characters

This scenario applies only to Talend Data Management Platform, Talend Big Data Platform, Talend Real Time Big Data Platform, Talend Data Services Platform, Talend MDM Platform and Talend Data Fabric.

This scenario describes a Job which uses:

  • the tFixedFlowInput component to generate the
    data you want to process,

  • the tTransliterate component to encode initial
    data expressed in different languages to readable characters based on the repertoire
    of the Unicode Standard,

  • the tFileOutputExcel component to output
    converted data in an .xls file.

tTransliterate_1.png

Setting up the Job

  1. Drop the following components from the Palette onto the design workspace: tFixedFlowInput, tTransliterate and
    tFileOutputExcel.
  2. Connect the three components together using the Main links.

Configuring the input component

  1. Double-click tFixedFlowInput to open its
    Basic settings view in the Component tab.

    tTransliterate_2.png

  2. Create the schema through the Edit Schema
    button.

    In the open dialog box, click the [+] button
    and add the columns that will hold input data. For this example, add
    column1, column2,
    column3 and column4. The first two
    columns hold names written in different languages.
  3. Click OK.
  4. In the Number of rows field, enter
    1.
  5. In the Mode area, select the Use Inline Content option.
  6. In the Content table, enter the data you want
    to convert to readable characters based on the Unicode Standard repertoire as
    shown in the above image.

Transliterating data

  1. Double-click tTransliterate to display the
    Basic settings view and define the component
    properties.

    tTransliterate_3.png

  2. If required, click Sync columns to retrieve
    the schema defined in the input component.

    In this example, only the first two columns are processed. You can click the
    Edit schema button to open the schema dialog
    box and see the input and output schemas.
    tTransliterate_4.png

  3. In the Transliteration table of the component
    basic settings view, select the check boxes next to the columns you want to
    convert to standard characters.

Configuring the output component and executing the Job

  1. Double-click the tFileOutputExcel component
    to display the Basic settings view and define
    the component properties.

    tTransliterate_5.png

  2. Set the destination file name as well as the sheet name and then select the
    Define all columns auto size check box.
  3. Save your Job and press F6 to execute
    it.

    The tTransliterate component encodes input
    data to readable characters based on the repertoire of the Unicode
    Standard.
  4. Right-click the output component and select Data
    Viewer     to display the transliterated data.

    tTransliterate_6.png

    All names written in characters from diverse languages have been phonetically
    converted to a standard set of characters based on the Universal Coded Character
    Set, UCS. For example, the names in the first and second rows in the below image
    have been changed to Ragnarr,Lodbrok and to
    Routse,Anna respectively.
    tTransliterate_7.png

    For further information about
    Unicode and Unicode Standards, check Unicode and Unicode
    Standard    .

tTransliterate properties for Apache Spark Batch

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

The Spark Batch
tTransliterate component belongs to the Data Quality family.

The component in this framework is available in all Talend Platform products with Big Data and in Talend Data Fabric.

Basic settings

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.

 

Built-In: You create and store the schema locally for this component
only.

 

Repository: You have already created the schema and stored it in the
Repository. You can reuse it in various projects and Job designs.

Edit Schema

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.

Transliteration

This table lists the columns defined in the schema of the tTransliterate component.

Select the Transliterate check box
next to the column(s) of which you want to convert the content to
readable standard set of characters.

Usage

Usage rule

This component is used as an intermediate step.

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

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 Batch version of this component
yet.

tTransliterate properties for Apache Spark Streaming

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

The Spark Streaming
tTransliterate component belongs to the Data Quality family.

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

Basic settings

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.

 

Built-In: You create and store the schema locally for this component
only.

 

Repository: You have already created the schema and stored it in the
Repository. You can reuse it in various projects and Job designs.

Edit Schema

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.

Transliteration

This table lists the columns defined in the schema of the tTransliterate component.

Select the Transliterate check box
next to the column(s) of which you want to convert the content to
readable standard set of characters.

Usage

Usage rule

This component, along with the Spark Streaming component Palette it belongs to, appears
only when you are creating a Spark Streaming Job.

This component is used as an intermediate step.

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.

This connection is effective on a per-Job basis.

For further information about a
Talend
 Spark Streaming Job, see the sections
describing how to create, convert and configure a
Talend
 Spark Streaming Job of the

Talend Open Studio for Big Data Getting Started Guide
.

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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Docs 7.x
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