August 16, 2023

tSetKeystore properties for Apache Spark Streaming – Docs for ESB 6.x

tSetKeystore properties for Apache Spark Streaming

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

The Spark Streaming
tSetKeystore component belongs to the Authentication 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

Basic settings

TrustStore type

Select the type of the TrustStore to be used. It may be PKCS 12 or JKS.

TrustStore file

Type in the path, or browse to the certificate TrustStore file
(including filename) that contains the list of certificates that the
client trusts.

TrustStore password

Type in the password used to check the integrity of the TrustStore

Need Client authentication

Select this check box to validate the keystore data. Once doing so,
you need complete three fields:

KeyStore type: select the type of
the keystore to be used. It may be PKCS
or JKS.

KeyStore file: type in the path,
or browse to the file (including filename) containing the keystore

KeyStore password: type in the
password for this keystore.

Check server identity

Select this check box to make the Job verify the match between the hostname
of the URL and the hostname of the server. If they mismatch, the verification
mechanism asks whether this connection should be allowed.


Usage rule

This component is used with no need to be connected to other components.

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
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
    field in the Spark
    tab; when using other distributions, use a
    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.

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