August 16, 2023

tTopBy – Docs for ESB 6.x

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tTopBy

Groups and sorts data and outputs several rows from the first one of the data in
each group.

tTopBy groups the
input data by applying user-defined keys, sorts records in each group and sends to its
following component a given number of first rows of the sorted records.

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

tTopBy properties for Apache Spark Batch

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

The Spark Batch
tTopBy component belongs to the Processing family.

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

Basic settings

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.

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. 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.

Number of line selected

Enter the number of rows to be outputted. The current component selects this number of
rows down from the first rows of the sorted data.

Key

Select the column(s) from which the records are used as keys to group the input
data.

You need to click [+] to add as many lines as required to use as keys for the grouping to be
completed

Criteria

Click [+] to add as many lines as required for the sort
to be completed.

In the Schema column column, select the column from your
schema, which the sort will be based on. Note that the order is essential as it determines
the sorting priority.

In the other columns, select how you need the data to be sorted. For example, if you need
to sort the data in ascending alphabetical order (from A to Z), select alpha and asc in the corresponding
columns.

Usage

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

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.

tTopBy properties for Apache Spark Streaming

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

The Spark Streaming
tTopBy component belongs to the Processing 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

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.

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. 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.

Number of line selected

Enter the number of rows to be outputted. The current component selects this number of
rows down from the first rows of the sorted data.

Key

Select the column(s) from which the records are used as keys to group the input
data.

You need to click [+] to add as many lines as required to use as keys for the grouping to be
completed

Criteria

Click [+] to add as many lines as required for the sort
to be completed.

In the Schema column column, select the column from your
schema, which the sort will be based on. Note that the order is essential as it determines
the sorting priority.

In the other columns, select how you need the data to be sorted. For example, if you need
to sort the data in ascending alphabetical order (from A to Z), select alpha and asc in the corresponding
columns.

Usage

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

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.

Document get from Talend https://help.talend.com
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Docs 6.x
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