Property type

Either Built-In or Repository.

Built-In: No property data stored centrally.

Repository: Select the repository file where the
properties are stored.

File Name/Stream

File name: Name and path of the file to
be processed.

Stream: The data flow to be processed.
The data must be added to the flow in order for tFileInputDelimited to fetch these data via the corresponding
representative variable.

This variable could be already pre-defined in your Studio or
provided by the context or the components you are using along with this
component; otherwise, you could define it manually and use it according to the
design of your Job, for example, using tJava or tJavaFlex.

In order to avoid the inconvenience of hand writing, you could
select the variable of interest from the auto-completion list (Ctrl+Space) to fill the current field on
condition that this variable has been properly defined.

Related topic to the available variables: see
Talend Studio User Guide

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
data.

CSV options

Select this check box to specify the following CSV parameters:

• Escape char: enter the escape character between double
  quotation marks. For example, you need to type in "\" if the
  backslash character () is used as the escape character.

• Text enclosure: enter the enclosure character (only one
  character) between double quotation marks. For example, """
  needs to be entered when double quotation marks (“) are used as the enclosure
  character.

Header

Enter the number of rows to be skipped in the beginning of file.

Note that when dynamic schema is used, the first row of the input
data is always treated as the header row no matter whether the Header field value is set or not. For more information about dynamic
schema, see
Talend Studio

User Guide.

Footer

Number of rows to be skipped at the end of the file.

Limit

Maximum number of rows to be processed. If Limit = 0, no row is
read or processed.

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. The schema is either Built-In or stored remotely in the Repository.

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 that if the input value of any non-nullable primitive
field is null, the row of data including that field will be rejected.

This component offers the
advantage of the dynamic schema feature. This allows you to retrieve unknown columns
from source files or to copy batches of columns from a source without mapping each
column individually. For further information about dynamic schemas, see
Talend Studio

User Guide.

This dynamic schema
feature is designed for the purpose of retrieving unknown columns of a table and is
recommended to be used for this purpose only; it is not recommended for the use of
creating tables.

When using
the dynamic schema feature, the dynamic column does not contain the actual
column names of the input file. If you want your output flow to include the
actual column names, make sure that your input file has a header row and the
Header value is set properly.

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.

Skip empty rows

Select this check box to skip the empty rows.

Uncompress as zip file

Select this check box to uncompress the input file.

Die on error

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

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.

To catch the FileNotFoundException, you also need to select this check box.

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 (.).

Extract lines at random

Select this check box to set the number of lines to be extracted
randomly.

Encoding

Select the encoding from the list or select Custom and define it manually. This field is compulsory for database
data handling.

Trim all column

Select this check box to remove the leading and trailing whitespaces from all
columns. When this check box is cleared, the Check column to
trim table is displayed, which lets you select particular columns to
trim.

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.

Check date

Select this check box to check the date format strictly against the input schema.

Check columns to trim

This table is filled automatically with the schema being used. Select the check
box(es) corresponding to the column(s) to be trimmed.

Split row before field

Select this check box to split rows before splitting fields.

Permit hexadecimal (0xNNN) or octal (0NNNN) for numeric
types

Select this check box if any of your numeric types (long, integer, short, or byte type), will
be parsed from a hexadecimal or octal string.

In the table that displays, select the check box next to the column or
columns of interest to transform the input string of each selected
column to the type defined in the schema.

Select the Permit hexadecimal or
octal check box to select all the columns.

This table appears only when the Permit
hexadecimal (0xNNN) or octal (0NNNN) for numeric types
check box is selected.

tStatCatcher Statistics

Select this check box to gather the processing metadata at the Job
level as well as at each component level.

Global Variables

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

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

Use this component to read a file and separate fields contained in
this file using a defined separator. It allows you to create a data flow
using a Row > Main link or via a
Row > Reject link in which case
the data is filtered by data that does not correspond to the type
defined. For further information, please see Procedure.

Due to license incompatibility, one or more JARs required to use this component are not
provided. You can install the missing JARs for this particular component by clicking the
Install button on the Component tab view. You can also find out and add all missing JARs easily on the
Modules tab in the
Integration
perspective of your
studio. You can find more details about how to install external modules in Talend Help Center (https://help.talend.com).

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.

For further information about the Hadoop
Cluster node, see the Getting Started 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. The schema is either Built-In or stored remotely in the Repository.

Click Edit schema to make changes to the
schema. Note that if you make changes, the schema automatically becomes built-in.

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.

Folder/File

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

If the path you set points to a folder, this component will read all of the files stored in that folder, for example,/user/talend/in; if sub-folders exist, the sub-folders are automatically ignored unless you define the property mapreduce.input.fileinputformat.input.dir.recursive to be true in the Hadoop properties table in the Hadoop configuration tab.

If you want to specify more than one files or directories in this
field, separate each path using a comma (,).

If the file to be read is a compressed one, enter the file name with
its extension; then this component automatically decompresses it at
runtime. The supported compression formats and their corresponding
extensions are:

• DEFLATE: *.deflate

• gzip: *.gz

• bzip2: *.bz2

• LZO: *.lzo

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.

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.

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
data.

Header

Enter the number of rows to be skipped in the beginning of file.

CSV options

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

Skip empty rows

Select this check box to skip the empty rows.

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.

Then select the encoding to be used from the list or select Custom and define it manually.

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 all columns

Select this check box to remove the leading and trailing whitespaces from all
columns. When this check box is cleared, the Check column to
trim table is displayed, which lets you select particular columns to
trim.

Check column to trim

This table is filled automatically with the schema being used. Select the check
box(es) corresponding to the column(s) to be trimmed.

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.

Check date

Select this check box to check the date format strictly against the input schema.

Decode String for long, int, short, byte
Types

Select this check box if any of your numeric types (long, integer, short, or byte type), will
be parsed from a hexadecimal or octal string.

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

In a
Talend
Map/Reduce Job, it is used as a start component and requires
a transformation component as output 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, tFileInputDelimited 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.

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.

Repository: Select the repository file where the
properties are stored.

The properties are stored centrally under the Hadoop
Cluster node of the Repository
tree.

For further information about the Hadoop
Cluster node, see the Getting Started 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. The schema is either Built-In or stored remotely in the Repository.

Click Edit schema to make changes to the
schema. Note that if you make changes, the schema automatically becomes built-in.

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.

Folder/File

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

If the path you set points to a folder, this component will read all of the files stored in that folder, for example, /user/talend/in; if sub-folders exist, the sub-folders are automatically ignored unless you define the property
spark.hadoop.mapreduce.input.fileinputformat.input.dir.recursive to be true in the Advanced properties table in the Spark configuration tab.

If you want to specify more than one files or directories in this
field, separate each path using a comma (,).

If the file to be read is a compressed one, enter the file name with
its extension; then this component automatically decompresses it at
runtime. The supported compression formats and their corresponding
extensions are:

• DEFLATE: *.deflate

• gzip: *.gz

• bzip2: *.bz2

• LZO: *.lzo

The button for browsing does not work with the Spark Local mode; if you are using the Spark Yarn or the Spark Standalone mode,
ensure that you have properly configured the connection in a configuration component in
the same Job, such as tHDFSConfiguration.

Die on error

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

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
data.

Header

Enter the number of rows to be skipped in the beginning of file.

CSV options

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

Skip empty rows

Select this check box to skip the empty rows.

Set minimum partitions

Select this check box to control the number of partitions to be created from the input
data over the default partitioning behavior of Spark.

In the displayed field, enter, without quotation marks, the minimum number of partitions
you want to obtain.

When you want to control the partition number, you can generally set at least as many partitions as
the number of executors for parallelism, while bearing in mind the available memory and the
data transfer pressure on your network.

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.

Then select the encoding to be used from the list or select Custom and define it manually.

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 all columns

Select this check box to remove the leading and trailing whitespaces from all
columns. When this check box is cleared, the Check column to
trim table is displayed, which lets you select particular columns to
trim.

Check column to trim

This table is filled automatically with the schema being used. Select the check
box(es) corresponding to the column(s) to be trimmed.

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.

Check date

Select this check box to check the date format strictly against the input schema.

Decode String for long, int, short, byte
Types

Select this check box if any of your numeric types (long, integer, short, or byte type), will
be parsed from a hexadecimal or octal string.

Usage rule

This component is used as a start component and requires an output 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

This connection is effective on a per-Job basis.

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.

Repository: Select the repository file where the
properties are stored.

The properties are stored centrally under the Hadoop
Cluster node of the Repository
tree.

For further information about the Hadoop
Cluster node, see the Getting Started 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. The schema is either Built-In or stored remotely in the Repository.

Click Edit schema to make changes to the
schema. Note that if you make changes, the schema automatically becomes built-in.

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.

Folder/File

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

If the path you set points to a folder, this component will read all of the files stored in that folder, for example, /user/talend/in; if sub-folders exist, the sub-folders are automatically ignored unless you define the property
spark.hadoop.mapreduce.input.fileinputformat.input.dir.recursive to be true in the Advanced properties table in the Spark configuration tab.

If you want to specify more than one files or directories in this
field, separate each path using a comma (,).

If the file to be read is a compressed one, enter the file name with
its extension; then this component automatically decompresses it at
runtime. The supported compression formats and their corresponding
extensions are:

• DEFLATE: *.deflate

• gzip: *.gz

• bzip2: *.bz2

• LZO: *.lzo

The button for browsing does not work with the Spark Local mode; if you are using the Spark Yarn or the Spark Standalone mode,
ensure that you have properly configured the connection in a configuration component in
the same Job, such as tHDFSConfiguration.

Die on error

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

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
data.

Header

Enter the number of rows to be skipped in the beginning of file.

CSV options

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

Skip empty rows

Select this check box to skip the empty rows.

Set minimum partitions

Select this check box to control the number of partitions to be created from the input
data over the default partitioning behavior of Spark.

In the displayed field, enter, without quotation marks, the minimum number of partitions
you want to obtain.

When you want to control the partition number, you can generally set at least as many partitions as
the number of executors for parallelism, while bearing in mind the available memory and the
data transfer pressure on your network.

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.

Then select the encoding to be used from the list or select Custom and define it manually.

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 all columns

Select this check box to remove the leading and trailing whitespaces from all
columns. When this check box is cleared, the Check column to
trim table is displayed, which lets you select particular columns to
trim.

Check column to trim

This table is filled automatically with the schema being used. Select the check
box(es) corresponding to the column(s) to be trimmed.

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.

Check date

Select this check box to check the date format strictly against the input schema.

Decode String for long, int, short, byte
Types

Select this check box if any of your numeric types (long, integer, short, or byte type), will
be parsed from a hexadecimal or octal string.

Usage rule

This component is used as a start component and requires an output link.

This component is only used to provide the lookup flow (the right side of a join
operation) to the main flow of a tMap component. In this
situation, the lookup model used by this tMap must be
Load once.

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.