tTransliterate properties for Apache Spark Streaming - 7.0

Text standardization

author
Talend Documentation Team
EnrichVersion
7.0
EnrichProdName
Talend Big Data Platform
Talend Data Fabric
Talend Data Management Platform
Talend Data Services Platform
Talend MDM Platform
Talend Real-Time Big Data Platform
task
Data Governance > Third-party systems > Data Quality components > Standardization components > Text standardization components
Data Quality and Preparation > Third-party systems > Data Quality components > Standardization components > Text standardization components
Design and Development > Third-party systems > Data Quality components > Standardization components > Text standardization components
EnrichPlatform
Talend Studio

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 store (technical preview) for Job deployment in the Spark configuration tab.
    • When using other 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.

This connection is effective on a per-Job basis.