July 30, 2023

tPubSubInputAvro – Docs for ESB 7.x

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tPubSubInputAvro

Connects to Google Cloud Pub/Sub to receive messages in the Avro format for the
components that run transformations over these messages.

tPubSubInputAvro properties for Apache Spark Streaming

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

The Spark Streaming
tPubSubInputAvro component belongs to the Messaging family.

This component is available in Talend Real Time Big Data Platform and Talend Data Fabric.

Basic settings

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.

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.

Note that the schema defined here must correspond exactly to the binary Avro schema of the messages received on Pub/Sub. To guarantee this, you can create another Spark Streaming Job to define a given schema using tWriteAvroFields and write the messages with this schema using tPubSubOutput.

Topic name

Enter the name of topic from which you want to consume the messages.

Subscription name

Enter the name of the subscription that needs to consume the specified topic.

If the subscription exists, it must be connected to the given topic; if
the subscription does not exist, it is created and connected to the
given topic at runtime.

Advanced settings

Storage level

From the Storage level drop-down list that is displayed, select how the cached RDDs are
stored, such as in memory only or in memory and on disk.

For further information about each of the storage level, see https://spark.apache.org/docs/latest/programming-guide.html#rdd-persistence.

Use hierarchical mode

Select this check box to map the binary (including hierarchical) Avro schema to the
flat schema defined in the schema editor of the current component. If the Avro
message to be processed is flat, leave this check box clear.

Once selecting it, you need set the following parameter(s):

  • Local path to the avro
    schema    : browse to the file which defines the
    schema of the Avro data to be processed.

  • Mapping: create the map
    between the schema columns of the current component and the data stored
    in the hierarchical Avro message to be handled. In the
    Node column, you need to
    enter the JSON path pointing to the data to be read from the
    Avro message.

Usage

Usage rule

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

Spark Connection

In the Spark
Configuration tab in the Run
view, 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 (Yarn client or Yarn cluster):

    • When using Google Dataproc, specify a bucket in the
      Google Storage staging bucket
      field in the Spark configuration
      tab.

    • When using HDInsight, specify the blob to be used for Job
      deployment in the Windows Azure Storage
      configuration       area in the Spark
      configuration       tab.

    • When using Altus, specify the S3 bucket or the Azure
      Data Lake Storage for Job deployment in the Spark
      configuration       tab.
    • When using Qubole, add a
      tS3Configuration to your Job to write
      your actual business data in the S3 system with Qubole. Without
      tS3Configuration, this business data is
      written in the Qubole HDFS system and destroyed once you shut
      down your cluster.

    • When using on-premise
      distributions, use the configuration component corresponding
      to the file system your cluster is using. Typically, this
      system is HDFS and so use tHDFSConfiguration.

  • Standalone mode: use the
    configuration component corresponding to the file system your cluster is
    using, such as tHDFSConfiguration or
    tS3Configuration.

    If you are using Databricks without any configuration component present
    in your Job, your business data is written directly in DBFS (Databricks
    Filesystem).

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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Docs 7.x
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