July 31, 2023

tFileOutputDelimited MapReduce properties (deprecated) – Docs for ESB Google Drive 7.x

tFileOutputDelimited MapReduce properties (deprecated)

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

The MapReduce
tFileOutputDelimited component belongs to the MapReduce family.

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

The MapReduce framework is deprecated from Talend 7.3 onwards. Use Talend Jobs for Apache Spark to accomplish your integration tasks.

Basic settings

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
node of the Repository

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

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

tFileOutputDelimited MapReduce properties (deprecated)_1.png

Click this icon to open a database connection wizard and store the
database connection parameters you set in the component Basic

For more information about setting up and storing database
connection parameters, see Talend Studio User Guide.

Schema and Edit 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

Click Edit
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


Built-In: You create and store the schema locally for this component


Repository: You have already created the schema and stored it in the
Repository. You can reuse it in various projects and Job designs.


Browse to, or enter the path pointing to the data to be used in the file system.

This path must point to a folder rather than a file, because a

Map/Reduce Job need to write in its target folder not only the
final result but also multiple part- files generated in
performing Map/Reduce computations.

Note that you need
to ensure you have properly configured the connection to the Hadoop
distribution to be used in the Hadoop
tab in the Run view.


Select an operation for writing data:

Create: Creates a file and write data in

Overwrite: Overwrites the file existing
in the directory specified in the Folder

Row separator

The separator used to identify the end of a row.

Field separator

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

Include Header

Select this check box to include the column header to the

Custom encoding

You may encounter encoding issues when you process the stored data. In that
situation, select this check box to display the Encoding list.

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

Compress the data

Select the Compress the data check box to compress the
output data.

Hadoop provides different compression formats that help reduce the space needed for
storing files and speed up data transfer. When reading a compressed file, the Studio needs
to uncompress it before being able to feed it to the input flow.

Merge result to single file

Select this check box to merge the final part files into a single file and put that file in a
specified directory.

Once selecting it, you need to enter the path to, or browse to the
folder you want to store the merged file in. This directory is
automatically created if it does not exist.

The following check boxes are used to manage the source and the
target files:

  • Remove source dir: select
    this check box to remove the source files after the merge.

  • Override target file:
    select this check box to override the file already existing in the target
    location. This option does not override the folder.

If this component is writing merged files with a Databricks cluster, add the following
parameter to the Spark configuration console of your

parameter prevents the merge file including the log file automatically generated by the
DBIO service of Databricks.

This option is not available for a Sequence file.

Advanced settings

Advanced separator (for number)

Select this check box to change the separator used for numbers. By default, the thousands separator is a comma (,) and the decimal separator is a period (.).

This option is not available for a Sequence file.

CSV options

Select this check box to include CSV specific parameters such as Escape char and Text

Use local timezone for date Select this check box to use the local date of the machine in which your Job is executed. If leaving this check box clear, UTC is automatically used to format the Date-type data.

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 +
to access the variable list and choose the variable to use from it.

For further information about variables, see
Talend Studio

User Guide.


Usage rule

In a
Map/Reduce Job, it is used as an end component and requires
a transformation component as input link. The 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.

Once a Map/Reduce Job is opened in the workspace, tFileOutputDelimited as well as the MapReduce
family appears in the Palette of the

Note that in this documentation, unless otherwise
explicitly stated, a scenario presents only Standard Jobs,
that is to say traditional
data integration Jobs, and non Map/Reduce Jobs.

Hadoop Connection

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.

Document get from Talend https://help.talend.com
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