tPigCoGroup Standard properties

Pig

author
Talend Documentation Team
EnrichVersion
6.5
EnrichProdName
Talend Big Data
Talend Big Data Platform
Talend Data Fabric
Talend Open Studio for Big Data
Talend Real-Time Big Data Platform
task
Data Governance > Third-party systems > Processing components (Integration) > Pig components
Data Quality and Preparation > Third-party systems > Processing components (Integration) > Pig components
Design and Development > Third-party systems > Processing components (Integration) > Pig components
EnrichPlatform
Talend Studio

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

The Standard tPigCoGroup component belongs to the Big Data and the Processing families.

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

Basic settings

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.

 

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.

Group by

Click the [+] button to add one or more columns of the input flows to this Group by table so as to set these columns as group condition.

Output mapping

This table is automatically filled with the output schema you have defined using the Schema field. Then complete this table to configure how the grouped data is aggregated in the output flow:

Function: select the function you need to use to aggregate a given column.

Source schema: select the input flow from which you aggregate the data.

Expression: select the column to be aggregated and if needed, edit expressions

Advanced settings

Group optimization

Select the Pig algorithm depending on the situation of the input data and the loader you are using to optimize the COGROUP operation.

For further information, see Apache's documentation about Pig.

Use partitioner

Select this check box to call a Hadoop partitioner in order to partition records and return the reduce task or tasks that each record should go to.

Note that this partitioner class must be registered in the Register jar table provided by the tPigLoad component that starts the current Pig process.

Increase parallelism

Select this check box to set the number of reduce tasks for the MapReduce Jobs.

tStatCatcher Statistics

Select this check box to gather the Job processing metadata at the 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 commonly used as intermediate step together with input component and output component.

Prerequisites

The Hadoop distribution must be properly installed, so as to guarantee the interaction with Talend Studio . The following list presents MapR related information for example.

  • Ensure that you have installed the MapR client in the machine where the Studio is, and added the MapR client library to the PATH variable of that machine. According to MapR's documentation, the library or libraries of a MapR client corresponding to each OS version can be found under MAPR_INSTALL\ hadoop\hadoop-VERSION\lib\native. For example, the library for Windows is \lib\native\MapRClient.dll in the MapR client jar file. For further information, see the following link from MapR: http://www.mapr.com/blog/basic-notes-on-configuring-eclipse-as-a-hadoop-development-environment-for-mapr.

    Without adding the specified library or libraries, you may encounter the following error: no MapRClient in java.library.path.

  • Set the -Djava.library.path argument, for example, in the Job Run VM arguments area of the Run/Debug view in the [Preferences] dialog box in the Window menu. This argument provides to the Studio the path to the native library of that MapR client. This allows the subscription-based users to make full use of the Data viewer to view locally in the Studio the data stored in MapR.

For further information about how to install a Hadoop distribution, see the manuals corresponding to the Hadoop distribution you are using.

Limitation

Knowledge of Pig scripts is required.