Field

Select an incoming field from the Field list to extract.

Ignore NULL as the source data

Select this check box to ignore the Null value in the
source data.

Clear this check box to generate the Null records that
correspond to the Null value in the source data.

Customize

Select this check box to customize the data format of the
positional file and define the table columns:

Column: Select the column you
want to customize.

Size: Enter the column size.

Padding char: Type in between
inverted commas the padding character used, in order for it to be
removed from the field. A space by default.

Alignment: Select the appropriate
alignment parameter.

Pattern

Enter the pattern to use as basis for the extraction.

A pattern is length values separated by commas,
interpreted as a string between quotes. Make sure the values entered in
this fields are consistent with the schema defined.

Die on error

Clear the check box to skip any rows on error and complete the process for
error-free rows. When errors are skipped, you can collect the rows on error using a Row > Reject link.

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.

Click Sync
columns to retrieve the schema from the previous component connected in the
Job.

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.

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 (.).

Trim Column

Select this check box to remove leading and trailing
whitespace from all columns.

Check each row structure against
schema

Select this check box to check whether the total number of columns
in each row is consistent with the schema. If not consistent, an
error message will be displayed on the console.

tStatCatcher Statistics

Select this check box to gather the 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.

NB_LINE: the number of rows read by an input component or
transferred to an output component. This is an After variable and it returns an
integer.

The NB_LINE
variable is not available to the Map/Reduce version.

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 rule

This component handles flow of data therefore it requires
input and output components. It allows you to extract data from a
delimited field, using a Row >
Main link, and enables you to
create a reject flow filtering data which type does not match the
defined type.

Prev.Comp.Column
list

Select an incoming field from the Field list to extract.

Customize

Select this check box to customize the data format of the
positional file and define the table columns:

Column: Select the column you want
to customize.

Size: Enter the column size.

Padding char: Type in between
inverted commas the padding character used, in order for it to be
removed from the field. A space by default.

Alignment: Select the appropriate
alignment parameter.

Pattern

Enter the pattern to use as basis for the extraction.

A pattern is length values separated by commas, interpreted as a
string between quotes. Make sure the values entered in this fields
are consistent with the schema defined.

Die on error

Clear the check box to skip any rows on error and complete the process for
error-free rows. When errors are skipped, you can collect the rows on error using a Row > Reject link.

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.

Click Sync
columns to retrieve the schema from the previous component connected in the
Job.

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.

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
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.

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 (.).

Trim Column

Select this check box to remove leading and trailing whitespace
from all columns.

Check each row structure against
schema

Select this check box to check whether the total number of columns
in each row is consistent with the schema. If not consistent, an
error message will be displayed on the console.

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 rule

This component handles flow of data therefore it requires input
and output components. It allows you to extract data from a
delimited field, using a Row >
Main link, and enables you to
create a reject flow filtering data which type does not match the
defined type.

In a
Talend
Map/Reduce Job, this component is used as an intermediate
step and 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.

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.

For further information about a
Talend
Map/Reduce Job, see the sections
describing how to create, convert and configure a
Talend
Map/Reduce Job of the

Talend Open Studio for Big Data Getting Started Guide
.

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.

Prev.Comp.Column list

Select an incoming field from the Field list to extract.

Customize

Select this check box to customize the data format of the positional
file and define the table columns:

Column: Select the column you want to
customize.

Size: Enter the column size.

Padding char: Type in between inverted
commas the padding character used, in order for it to be removed from
the field. A space by default.

Alignment: Select the appropriate
alignment parameter.

Pattern

Enter the pattern to use as basis for the extraction.

A pattern is length values separated by commas, interpreted as a
string between quotes. Make sure the values entered in this fields are
consistent with the schema defined.

Die on error

Select the check box to stop the execution of the Job when an error
occurs.

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.

Click Sync
columns to retrieve the schema from the previous component connected in the
Job.

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.

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 (.).

Trim Column

Select this check box to remove leading and trailing whitespace from
all columns.

Check each row structure against
schema

Select this check box to check whether the total number of columns
in each row is consistent with the schema. If not consistent, an
error message will be displayed on the console.

Usage rule

This component is used as an intermediate step.

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

This connection is effective on a per-Job basis.

Prev.Comp.Column list

Select an incoming field from the Field list to extract.

Customize

Select this check box to customize the data format of the positional
file and define the table columns:

Column: Select the column you want to
customize.

Size: Enter the column size.

Padding char: Type in between inverted
commas the padding character used, in order for it to be removed from
the field. A space by default.

Alignment: Select the appropriate
alignment parameter.

Pattern

Enter the pattern to use as basis for the extraction.

A pattern is length values separated by commas, interpreted as a
string between quotes. Make sure the values entered in this fields are
consistent with the schema defined.

Die on error

Clear the check box to skip any rows on error and complete the process for
error-free rows. When errors are skipped, you can collect the rows on error using a Row > Reject link.

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.

Click Sync
columns to retrieve the schema from the previous component connected in the
Job.

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.

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 (.).

Trim Column

Select this check box to remove leading and trailing whitespace from
all columns.

Check each row structure against
schema

Select this check box to check whether the total number of columns
in each row is consistent with the schema. If not consistent, an
error message will be displayed on the console.

Usage rule

This component is used as an intermediate step.

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

This connection is effective on a per-Job basis.