July 30, 2023

tFileOutputXML – Docs for ESB 7.x

tFileOutputXML

Writes an XML file with separated data values according to a defined
schema.

Depending on the Talend
product you are using, this component can be used in one, some or all of the following
Job frameworks:

tFileOutputXML Standard properties

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

The Standard
tFileOutputXML component belongs to the File and the XML families.

The component in this framework is available in all Talend
products
.

Basic settings

File Name

Name or path to the output file and/or the variable to be used.

Related topic: see Defining variables from the Component view section
in
Talend Studio User Guide

Warning: Use absolute path (instead of relative path) for
this field to avoid possible errors.
Incoming record is a document

Select this check box if the data from the preceding component is in
XML format.

When this check box is selected, a Column
list
appears allowing you to select a Document type column of the schema that holds
the data, and the Row tag field
disappears.

When this check box is selected, in the Advanced
settings
view, only the check boxes Create directory if not exists, Don’t generate empty file, Trim
data
, tStatCatcher
Statistics
and the list Encoding are available.

Row tag

Specify the tag that will wrap data and structure per row.

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
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.

 

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

Sync columns Click to synchronize the output file schema with the input
file schema. The Sync function only displays once the Row connection is
linked with the input component.

Advanced settings

Split output in several files

If the output is big, you can split the output into several files,
each containing the specified number of rows.

Rows in each output file: Specify the
number of rows in each output file.

Create directory if not exists This check box is selected by default. It creates a
directory to hold the output XML files if required.
Root tags

Specify one or more root tags to wrap the whole output file structure and data. The
default root tag is root.

Output format

Define the output format.

  • Column: The columns retrieved
    from the input schema.

  • As attribute: select check box
    for the column(s) you want to use as attribute(s) of the parent
    element in the XML output.

Note:

If the same column is selected in both the Output format table as an attribute
and in the Use dynamic grouping
setting as the criterion for dynamic grouping, only the dynamic
group setting will take effect for that column.

Use schema column name: By
default, this check box is selected for all columns so that the
column labels from the input schema are used as data wrapping tags.
If you want to use a different tag than from the input schema for
any column, clear this check box for that column and specify a tag
label between quotation marks in the Label field.

Use dynamic grouping

Select this check box if you want to dynamically group the output
columns. Click the plus button to add one ore more grouping criteria
in the Group by table.

Column: Select a column you want
to use as a wrapping element for the grouped output rows.

Attribute label: Enter an
attribute label for the group wrapping element, between quotation
marks.

Custom the flush buffer size

Select this check box to define the number of rows to buffer before
the data is written into the target file and the buffer is
emptied.

Row Number: Specify the number of
rows to buffer.

Advanced separator (for numbers)

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 (.).

Thousands separator: define
separators for thousands.

Decimal separator: define separators
for decimals.

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.

Don’t generate empty file Select the check box to avoid the generation of an empty
file.

Trim data

Select this check box to remove the spaces at the beginning and at the
end of the text, and merge multiple consecutive spaces into one within
the text.

tStatCatcher Statistics Select this check box to gather the Job processing metadata
at a 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.

NB_LINE: the number of rows processed. This is an After
variable and it returns an integer.

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

Use this component to write an XML file with data passed on from other
components using a Row link.

tFileOutputXML MapReduce properties (deprecated)

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

The MapReduce
tFileOutputXML 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.

In a
Talend
Map/Reduce Job, tFileOutputXML, as well as the whole Map/Reduce Job using it, generates
native Map/Reduce code. This section presents the specific properties of tFileOutputXML when it is used in that situation. For further
information about a
Talend
Map/Reduce Job, see the
Talend Open Studio for Big Data Getting Started Guide
.

Basic settings

Property type

Either Built-In or Repository.

 

Built-In: No property data stored centrally.

tFileOutputXML_1.png

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

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

 

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.

Row tag

Specify the tag that will wrap data and structure per row.

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
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.

 

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

Folder

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

Talend
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
configuration
tab in the Run view.

Action

Select an operation for writing data:

Create: Creates a file and write data
in it.

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

Advanced settings

Root tags

Specify one or more root tags to wrap the whole output file structure and data. The
default root tag is root.

Output format

Define the output format.

  • Column: The columns retrieved
    from the input schema.

  • As attribute: select check box
    for the column(s) you want to use as attribute(s) of the parent
    element in the XML output.

Note:

If the same column is selected in both the Output format table as an attribute
and in the Use dynamic grouping
setting as the criterion for dynamic grouping, only the dynamic
group setting will take effect for that column.

Use schema column name: By
default, this check box is selected for all columns so that the
column labels from the input schema are used as data wrapping tags.
If you want to use a different tag than from the input schema for
any column, clear this check box for that column and specify a tag
label between quotation marks in the Label field.

Use dynamic grouping

Select this check box if you want to dynamically group the output
columns. Click the plus button to add one ore more grouping criteria
in the Group by table.

Column: Select a column you want
to use as a wrapping element for the grouped output rows.

Attribute label: Enter an
attribute label for the group wrapping element, between quotation
marks.

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.

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 +
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, 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, tFileOutputXML as well as the MapReduce
family appears in the Palette of the
Studio.

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.

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.

Related scenarios

No scenario is available for the Map/Reduce version of this component yet.

tFileOutputXML properties for Apache Spark Batch

These properties are used to configure tFileOutputXML running in the Spark Batch Job framework.

The Spark Batch
tFileOutputXML component belongs to the File and the XML families.

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

Basic settings

Define a storage configuration
component

Select the configuration component to be used to provide the configuration
information for the connection to the target file system such as HDFS.

If you leave this check box clear, the target file system is the local
system.

The configuration component to be used must be present in the same Job.
For example, if you have dropped a tHDFSConfiguration component in the Job, you can select it to write
the result in a given HDFS system.

Property type

Either Built-In or Repository.

 

Built-In: No property data stored centrally.

tFileOutputXML_1.png

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

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

 

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.

Row tag

Specify the tag that will wrap data and structure per row.

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
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.

 

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

Folder

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.

The button for browsing does not work with the Spark
Local mode; if you are
using the other Spark Yarn
modes that the Studio supports with your distribution, ensure that you have properly
configured the connection in a configuration component in the same Job, such as

tHDFSConfiguration
. Use the
configuration component depending on the filesystem to be used.

Action

Select an operation for writing data:

Create: Creates a file and write data
in it.

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

Compress the data

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

Advanced settings

Root tags

Specify one or more root tags to wrap the whole output file structure and data. The
default root tag is root.

Output format

Define the output format.

  • Column: The columns retrieved
    from the input schema.

  • As attribute: select check box
    for the column(s) you want to use as attribute(s) of the parent
    element in the XML output.

Note:

If the same column is selected in both the Output format table as an attribute
and in the Use dynamic grouping
setting as the criterion for dynamic grouping, only the dynamic
group setting will take effect for that column.

Use schema column name: By
default, this check box is selected for all columns so that the
column labels from the input schema are used as data wrapping tags.
If you want to use a different tag than from the input schema for
any column, clear this check box for that column and specify a tag
label between quotation marks in the Label field.

Use dynamic grouping

Select this check box if you want to dynamically group the output
columns. Click the plus button to add one ore more grouping criteria
in the Group by table.

Column: Select a column you want
to use as a wrapping element for the grouped output rows.

Attribute label: Enter an
attribute label for the group wrapping element, between quotation
marks.

Custom 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.

Advanced separator (for numbers)

Select this check box to modify the separators used for
numbers:

Thousands separator: define
separators for thousands.

Decimal separator: define
separators for decimals.

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.

Usage

Usage rule

This component is used as an end component and requires an input link.

This component, along with the Spark Batch component Palette it belongs to,
appears only when you are creating a Spark Batch Job.

Note that in this documentation, unless otherwise explicitly stated, a
scenario presents only Standard Jobs, that is to
say traditional
Talend
data integration Jobs.

Spark Connection

In the Spark
Configuration
tab in the Run
view, define the connection to a given Spark cluster for the whole Job. In
addition, since the Job expects its dependent jar files for execution, you must
specify the directory in the file system to which these jar files are
transferred so that Spark can access these files:

  • Yarn mode (Yarn client or Yarn cluster):

    • When using Google Dataproc, specify a bucket in the
      Google Storage staging bucket
      field in the Spark configuration
      tab.

    • When using HDInsight, specify the blob to be used for Job
      deployment in the Windows Azure Storage
      configuration
      area in the Spark
      configuration
      tab.

    • When using Altus, specify the S3 bucket or the Azure
      Data Lake Storage for Job deployment in the Spark
      configuration
      tab.
    • When using Qubole, add a
      tS3Configuration to your Job to write
      your actual business data in the S3 system with Qubole. Without
      tS3Configuration, this business data is
      written in the Qubole HDFS system and destroyed once you shut
      down your cluster.
    • When using on-premise
      distributions, use the configuration component corresponding
      to the file system your cluster is using. Typically, this
      system is HDFS and so use tHDFSConfiguration.

  • Standalone mode: use the
    configuration component corresponding to the file system your cluster is
    using, such as tHDFSConfiguration or
    tS3Configuration.

    If you are using Databricks without any configuration component present
    in your Job, your business data is written directly in DBFS (Databricks
    Filesystem).

This connection is effective on a per-Job basis.

Related scenarios

No scenario is available for the Spark Batch version of this component
yet.

tFileOutputXML properties for Apache Spark Streaming

These properties are used to configure tFileOutputXML running in the Spark Streaming Job framework.

The Spark Streaming
tFileOutputXML component belongs to the File and the XML families.

This component is available in Talend Real Time Big Data Platform and Talend Data Fabric.

Basic settings

Define a storage configuration
component

Select the configuration component to be used to provide the configuration
information for the connection to the target file system such as HDFS.

If you leave this check box clear, the target file system is the local
system.

The configuration component to be used must be present in the same Job.
For example, if you have dropped a tHDFSConfiguration component in the Job, you can select it to write
the result in a given HDFS system.

Property type

Either Built-In or Repository.

 

Built-In: No property data stored centrally.

tFileOutputXML_1.png

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

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

 

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.

Row tag

Specify the tag that will wrap data and structure per row.

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
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.

 

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

Folder

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.

The button for browsing does not work with the Spark
Local mode; if you are
using the other Spark Yarn
modes that the Studio supports with your distribution, ensure that you have properly
configured the connection in a configuration component in the same Job, such as

tHDFSConfiguration
. Use the
configuration component depending on the filesystem to be used.

Action

Select an operation for writing data:

Create: Creates a file and write data
in it.

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

Compress the data

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

Advanced settings

Root tags

Specify one or more root tags to wrap the whole output file structure and data. The
default root tag is root.

Output format

Define the output format.

  • Column: The columns retrieved
    from the input schema.

  • As attribute: select check box
    for the column(s) you want to use as attribute(s) of the parent
    element in the XML output.

Note:

If the same column is selected in both the Output format table as an attribute
and in the Use dynamic grouping
setting as the criterion for dynamic grouping, only the dynamic
group setting will take effect for that column.

Use schema column name: By
default, this check box is selected for all columns so that the
column labels from the input schema are used as data wrapping tags.
If you want to use a different tag than from the input schema for
any column, clear this check box for that column and specify a tag
label between quotation marks in the Label field.

Use dynamic grouping

Select this check box if you want to dynamically group the output
columns. Click the plus button to add one ore more grouping criteria
in the Group by table.

Column: Select a column you want
to use as a wrapping element for the grouped output rows.

Attribute label: Enter an
attribute label for the group wrapping element, between quotation
marks.

Custom 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.

Advanced separator (for numbers)

Select this check box to modify the separators used for
numbers:

Thousands separator: define
separators for thousands.

Decimal separator: define
separators for decimals.

Write empty batches Select this check box to allow your Spark Job to create an empty batch when the
incoming batch is empty.

For further information about when this is desirable
behavior, see this discussion.

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.

Usage

Usage rule

This component is used as an end component and requires an input link.

This component, along with the Spark Streaming component Palette it belongs to, appears
only when you are creating a Spark Streaming Job.

Note that in this documentation, unless otherwise explicitly stated, a scenario presents
only Standard Jobs, that is to say traditional
Talend
data
integration Jobs.

Spark Connection

In the Spark
Configuration
tab in the Run
view, define the connection to a given Spark cluster for the whole Job. In
addition, since the Job expects its dependent jar files for execution, you must
specify the directory in the file system to which these jar files are
transferred so that Spark can access these files:

  • Yarn mode (Yarn client or Yarn cluster):

    • When using Google Dataproc, specify a bucket in the
      Google Storage staging bucket
      field in the Spark configuration
      tab.

    • When using HDInsight, specify the blob to be used for Job
      deployment in the Windows Azure Storage
      configuration
      area in the Spark
      configuration
      tab.

    • When using Altus, specify the S3 bucket or the Azure
      Data Lake Storage for Job deployment in the Spark
      configuration
      tab.
    • When using Qubole, add a
      tS3Configuration to your Job to write
      your actual business data in the S3 system with Qubole. Without
      tS3Configuration, this business data is
      written in the Qubole HDFS system and destroyed once you shut
      down your cluster.
    • When using on-premise
      distributions, use the configuration component corresponding
      to the file system your cluster is using. Typically, this
      system is HDFS and so use tHDFSConfiguration.

  • Standalone mode: use the
    configuration component corresponding to the file system your cluster is
    using, such as tHDFSConfiguration or
    tS3Configuration.

    If you are using Databricks without any configuration component present
    in your Job, your business data is written directly in DBFS (Databricks
    Filesystem).

This connection is effective on a per-Job basis.

Related scenarios

No scenario is available for the Spark Streaming version of this component
yet.


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