August 15, 2023

tFileInputParquet – Docs for ESB 6.x

tFileInputParquet

Extracts records from a given Parquet format file in a distributed file system and
sends the data to the next component for further processing.

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

tFileInputParquet MapReduce properties

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

The MapReduce
tFileInputParquet component belongs to the MapReduce family.

The component in this framework is available only if you have subscribed to one
of the
Talend
solutions with Big Data.

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
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.

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.

 

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 (,).

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.

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 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, tFileInputParquet 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 scenario

This component is used in the similar way as the tAvroInput
component. For a scenario using tAvroInput, see Scenario: Filtering Avro format employee data.

tFileInputParquet properties for Apache Spark Batch

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

The Spark Batch
tFileInputParquet component belongs to the File family.

The component in this framework is available only if you have subscribed to one
of the
Talend
solutions with Big Data.

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.

 

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.

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.

This component does not support the Object type and the
List type.

 

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 (,).

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.

Usage

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

You need to use the Spark Configuration tab in
the Run view to 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: when using Google
    Dataproc, specify a bucket in the Google Storage staging
    bucket
    field in the Spark
    configuration
    tab; when using other distributions, use a
    tHDFSConfiguration
    component to specify the directory.

  • Standalone mode: you need to choose
    the configuration component depending on the file system you are using, such
    as tHDFSConfiguration
    or tS3Configuration.

This connection is effective on a per-Job basis.

Related scenarios

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

tFileInputParquet properties for Apache Spark Streaming

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

The Spark Streaming
tFileInputParquet component belongs to the File family.

The component in this framework is available only if you have subscribed to Talend Real-time Big Data Platform or 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.

 

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.

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.

This component does not support the Object type and the
List type.

 

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 (,).

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.

Usage

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

You need to use the Spark Configuration tab in
the Run view to 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: when using Google
    Dataproc, specify a bucket in the Google Storage staging
    bucket
    field in the Spark
    configuration
    tab; when using other distributions, use a
    tHDFSConfiguration
    component to specify the directory.

  • Standalone mode: you need to choose
    the configuration component depending on the file system you are using, such
    as tHDFSConfiguration
    or tS3Configuration.

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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