tExtractRegexFields MapReduce properties

Data extraction

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Talend Documentation Team
EnrichVersion
6.5
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Talend Big Data Platform
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Talend Open Studio for MDM
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Data Governance > Third-party systems > Data Quality components > Data extraction components
Design and Development > Third-party systems > Data Quality components > Data extraction components
Data Quality and Preparation > Third-party systems > Data Quality components > Data extraction components
EnrichPlatform
Talend Studio

These properties are used to configure tExtractRegexFields running in the MapReduce Job framework.

The MapReduce tExtractRegexFields component belongs to the Processing family.

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

Basic settings

Field to split

Select an incoming field from the Field to split list to split.

Regex

Enter a regular expression according to the programming language you are using.

Property type

Either Built-In or Repository.

 

Built-In: No property data stored centrally.

 

Repository: Select the repository file where the properties are stored.

The properties are stored centrally under the Hadoop Cluster node of the Repository tree.

The fields that come after are pre-filled in using the fetched data.

For further information about the Hadoop Cluster node, see the Getting Started Guide.

Schema and Edit Schema

A schema is a row description. It defines the number of fields (columns) to Repository. When you create a Spark Job, avoid the reserved word line when naming the fields.

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.

Click Sync columns to retrieve the schema from the previous component connected in the Job.

Warning:

Make sure that the output schema does not contain any column with the same name as the input column to be split. Otherwise, the regular expression will not work as expected.

 

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.

Advanced settings

Die on error

Select the check box to stop the execution of the Job when an error occurs.

Clear the check box to skip any rows on error and complete the process for error-free rows. When errors are skipped, you can collect the rows on error using a Row > Reject link.

Encoding

Select the encoding from the list or select Custom and define it manually. This field is compulsory for database data handling. The supported encodings depend on the JVM that you are using. For more information, see https://docs.oracle.com.

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

In a Talend Map/Reduce Job, this component is used as an intermediate step and other components used along with it must be Map/Reduce components, too. They generate native Map/Reduce code that can be executed directly in Hadoop.

You need to use the Hadoop Configuration tab in the Run view to define the connection to a given Hadoop distribution for the whole Job.

This connection is effective on a per-Job basis.

For further information about a Talend Map/Reduce Job, see the sections describing how to create, convert and configure a Talend Map/Reduce 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, and non Map/Reduce Jobs.