August 16, 2023

tPubSubOutput – Docs for ESB 6.x

tPubSubOutput

Receives messages serialized into byte arrays by its preceding component and issues
these messages into a given PubSub service.

tPubSubOutput properties for Apache Spark Streaming

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

The Spark Streaming
tPubSubOutput component belongs to the Messaging 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.

Note that the schema of this component is read-only. It stores the
messages to be published.

Define a Goolge Cloud configuration component

If you are using Dataproc as your Spark cluster, clear this check box.

Otherwise, select this check box to allow the Pub/Sub component to use the Google Cloud
configuration information provided by a
tGoogleCloudConfiguration component.

Topic name

Enter the name of the topic you want to publish messages to. This topic must already
exist.

Topic operation

Select the operation to be performed on the specified topic:

  • None: select this option if the topic to be used already exists.

  • Create if not exists: select this option if the topic to be used does not exist.

Advanced settings

Connection pool

In this area, you configure, for each Spark executor, the connection pool used to control
the number of connections that stay open simultaneously. The default values given to the
following connection pool parameters are good enough for most use cases.

  • Max total number of connections: enter the maximum number
    of connections (idle or active) that are allowed to stay open simultaneously.

    The default number is 8. If you enter -1, you allow unlimited number of open connections at the same
    time.

  • Max waiting time (ms): enter the maximum amount of time
    at the end of which the response to a demand for using a connection should be returned by
    the connection pool. By default, it is -1, that is to say, infinite.

  • Min number of idle connections: enter the minimum number
    of idle connections (connections not used) maintained in the connection pool.

  • Max number of idle connections: enter the maximum number
    of idle connections (connections not used) maintained in the connection pool.

Evict connections

Select this check box to define criteria to destroy connections in the connection pool. The
following fields are displayed once you have selected it.

  • Time between two eviction runs: enter the time interval
    (in milliseconds) at the end of which the component checks the status of the connections and
    destroys the idle ones.

  • Min idle time for a connection to be eligible to
    eviction
    : enter the time interval (in milliseconds) at the end of which the idle
    connections are destroyed.

  • Soft min idle time for a connection to be eligible to
    eviction
    : this parameter works the same way as Min idle
    time for a connection to be eligible to eviction
    but it keeps the minimum number
    of idle connections, the number you define in the Min number of idle
    connections
    field.

Usage

Usage rule

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

This component needs a Write component such as tWriteJSONField to define a serializedValue column in the input schema to send serialized data.

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.

PubSub access permissions

When you use Pub/Sub with a Dataproc cluster, ensure that this cluster
has the appropriate permissions to access the Pub/Sub service.

To do this, you can create the Dataproc cluster by checking
Allow API access to all Google Cloud services in
the same project in the advanced options on Google Cloud Platform, or
via the command line, assigning the scopes explicitly (the following
example is for a low-resource test cluster):


Document get from Talend https://help.talend.com
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