August 17, 2023

tPigFilterRow – Docs for ESB 5.x

  2. Talend for ESB Docs
  3. Docs 5.x
  4. tPigFilterRow – Docs for ESB 5.x

tPigFilterRow

tPigFilterRow_icon32_white.png

Warning

This component will be available in the Palette of the studio on the condition that you have subscribed to
one of the Talend solutions with Big
Data.

tPigFilterRow Properties

Component family

Big Data / Hadoop

  

Function

The tPigFilterRow component
filters or splits the input flow in a Pig process based on
conditions set on given column(s).

Purpose

In a Pig process, this component applies filtering conditions on
one or more specified columns in order to split or filter data from
a relation.

Basic settings

Schema and Edit
Schema

A schema is a row description. It defines the number of fields to be processed and passed on
to the next component. The schema is either Built-In or
stored remotely in the Repository.

Since version 5.6, both the Built-In mode and the Repository mode are
available in any of the Talend solutions.

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.

 

Filter configuration

Click the Add button beneath the
Filter configuration table to
set one or more filter conditions.

Note that when the column to be used by a condition is of the
string type, the text to be
entered in the Value column must be
surrounded by both single and double quotation marks (for example,
“‘California'”), because the
double quotation marks are required by Talend‘s code generator and the single
quotation marks required by Pig’s grammar.

Note

This table disappears if you select Use
advanced filter.

 

Use advanced filter

Select this check box to define advanced filter condition by
entering customized filter expression in the Filter field.

Advanced settings

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

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

This component is commonly used as an intermediate step in a Pig
process.

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
    hadoophadoop-VERSIONlib
    ative    . For example, the library for
    Windows is lib
    ativeMapRClient.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. 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
    set this argument, see the section describing how to view data of Talend Big Data Getting Started Guide.

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

Log4j

The activity of this component can be logged using the log4j feature. For more information on this feature, see Talend Studio User
Guide.

For more information on the log4j logging levels, see the Apache documentation at http://logging.apache.org/log4j/1.2/apidocs/org/apache/log4j/Level.html.

Limitation

Knowledge of Pig scripts is required.

 

Scenario: Filtering rows of data based on a condition and saving the result to a
local file

This scenario describes a four-component Job that filters a list of customers to find
out customers from a particular country, and saves the result list to a local file.
Before the input data is filtered, duplicate entries are first removed from the list.

The input file contains three columns: Name,
Country, and Age, and it has some duplicate entries, as shown below:

Dropping and linking components

  1. Drop the following components from the Palette to the design workspace: tPigLoad, tPigDistinct,
    tPigFilterRow, and tPigStoreResult.

  2. Right-click tPigLoad, select Row > Pig
    Combine     from the contextual menu, and click tPigDistinct to link these two components.

  3. Repeat this operation to link tPigDistinct to tPigFilterRow, and tPigFilterRow to tPigStoreResult using Row >
    Pig Combine connections to form a Pig
    process.

    Use_Case_tPigFilterRow1.png

Configuring the components

Loading the input data and removing duplicates

  1. Double-click tPigLoad to open its
    Basic settings view.

    Use_Case_tPigFilterRow2.png

  2. Click the […] button next to Edit schema to open the [Schema] dialog box.

    Use_Case_tPigFilterRow3.png

  3. Click the [+] button to add three columns
    according to the data structure of the input file: Name
    (string), Country (string) and Age
    (integer), and then click OK to save the
    setting and close the dialog box.

  4. Click Local in the Mode area.

  5. Fill in the Input file URI field with the
    full path to the input file.

  6. Select PigStorage from the Load function list, and leave rest of the
    settings as they are.

  7. Double-click tPigDistinct to open its
    Basic settings view, and click
    Sync columns to make sure that the
    input schema structure is correctly propagated from the preceding
    component.

    This component will remove any duplicates from the data flow.

Configuring the filter

  1. Double-click tPigFilterRow to open its
    Basic settings view.

    Use_Case_tPigFilterRow4.png

  2. Click Sync columns to make sure that the
    input schema structure is correctly propagated from the preceding
    component.

  3. Select Use advanced filter and fill in
    the Filter field with filter
    expression:

    This filter expression selects rows of data that contains “PuertoRico” in
    the Country column.

Configuring the file output

  1. Double-click tPigStoreResult to open its
    Basic settings view.

    Use_Case_tPigFilterRow5.png

  2. Click Sync columns to make sure that the
    input schema structure is correctly propagated from the preceding
    component.

  3. Fill in the Result file field with the
    full path to the result file.

  4. If the target file already exists, select the Remove
    result directory if exists     check box.

  5. Select PigStorage from the Store function list, and leave rest of the
    settings as they are.

Saving and executing the Job

  1. Press Ctrl+S to save your Job.

  2. Press F6 or click the Run button on the Run tab to run the Job.

    The result file contains the information of customers from the specified
    country.

    Use_Case_tPigFilterRow6.png
Document get from Talend https://help.talend.com
Thank you for watching.
Docs 5.x
Subscribe
Notify of
guest
0 Comments
Inline Feedbacks
View all comments
0
Would love your thoughts, please comment.x
()
x