tPigJoin Standard properties

Pig

author
Talend Documentation Team
EnrichVersion
6.5
EnrichProdName
Talend Real-Time Big Data Platform
Talend Open Studio for Big Data
Talend Big Data Platform
Talend Big Data
Talend Data Fabric
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 tPigJoin running in the Standard Job framework.

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

The component in this framework is available when you are using one of the Talend solutions 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.

Note:

To make this component work, two schemas must be set: the schema of the main flow and the schema of the lookup flow. In the output part of the main schema, the columns of the main input file must be manually concatenated with those of the lookup file.

 

Built-in: The schema will be created and stored locally for this component only. Related topic: see Talend Studio User Guide.

 

Repository: The schema already exists and is stored in the Repository, hence can be reused in various projects and Job designs. Related topic: see Talend Studio User 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.

Note:

To make this component work, two schemas must be set: the schema of the main flow and the schema of the lookup flow. In the output part of the main schema, the columns of the main input file must be manually concatenated with those of the lookup file.

 

Built-in: The schema will be created and stored locally for this component only. Related topic: see Talend Studio User Guide.

 

Repository: The schema already exists and is stored in the Repository, hence can be reused in various projects and Job designs. Related topic: see Talend Studio User Guide.

Filename

Fill in the path of the Lookup file.

Field Separator

Enter character, string or regular expression to separate fields for the transferred data.

Join key

Click the plus button to add lines to set the Join key for Input file and Lookup file.

Join mode

Select a join mode from the list:

inner-join: Select this mode to perform an inner join of two or more relations based on Join keys.

left-outer-join: Select this mode to performs a left outer join of two or more relations based on Join keys.

right-outer-join: Select this mode to performs a right outer join of two or more relations based on Join keys.

full-outer-join: Select this mode to combine the effect of applying both left and right outer joins.

For further information about inner join and outer join, see:

http://en.wikipedia.org/wiki/Join_%28SQL%29

Advanced settings

Optimize the join

Select this check box to optimize the performance of joins using REPLICATED, SKEWED, or MERGE joins. For further information about optimized joins, see:

http://pig.apache.org/docs/r0.8.1/piglatin_ref1.html#Specialized+Joins

Use partitioner

Select this check box to specify the Hadoop Partitioner that controls the partitioning of the keys of the intermediate map-outputs. For further information about the usage of Hadoop Partitioner, see:

http://hadoop.apache.org/docs/r2.2.0/api/org/apache/hadoop/mapred/Partitioner.html

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.