August 15, 2023

tAvroStreamInput – Docs for ESB 6.x

tAvroStreamInput

Listens on a given directory, reads data from Avro files once they are created
and sends this data to the component that follows.

tAvroStreamInput properties for Apache Spark Streaming

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

The Spark Streaming
tAvroStreamInput component belongs to the File family.

The streaming version of this component is available in the Palette of the Studio 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.

 

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.

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.

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.


Document get from Talend https://help.talend.com
Thank you for watching.
Subscribe
Notify of
guest
0 Comments
Inline Feedbacks
View all comments
0
Would love your thoughts, please comment.x
()
x