August 16, 2023

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

tHDFSConfiguration properties for Apache Spark Streaming

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

The Spark Streaming
tHDFSConfiguration component belongs to the Storage family.

The component in this framework is available only if you have subscribed to Talend Real-time Big Data Platform or Talend Data

Basic settings

Property type

Either Built-In or Repository.

Built-In: No property data stored centrally.

Repository: Select the repository file where the
properties are stored.


Select the cluster you are using from the drop-down list. The options in the
list vary depending on the component you are using. Among these options, the following
ones requires specific configuration:

  • If available in this Distribution drop-down list, the Microsoft HD Insight option allows you to
    use a Microsoft HD Insight cluster. For this purpose, you need to configure
    the connections to the WebHCat service, the HD Insight service and the
    Windows Azure Storage service of that cluster in the areas that are
    displayed. A demonstration video about how to configure this connection is
    available in the following link:

  • If you select Amazon
    , you can find more details about how
    to configure an Amazon EMR cluster in Talend Help Center (

  • The Custom option
    allows you to connect to a cluster different from any of the distributions
    given in this list, that is to say, to connect to a cluster not officially
    supported by

  1. Select Import from existing
    to import an officially supported distribution as base
    and then add other required jar files which the base distribution does not

  2. Select Import from zip to
    import the configuration zip for the custom distribution to be used. This zip
    file should contain the libraries of the different Hadoop elements and the index
    file of these libraries.


    Exchange, members of
    community have shared some ready-for-use configuration zip files
    which you can download from this Hadoop configuration
    list and directly use them in your connection accordingly. However, because of
    the ongoing evolution of the different Hadoop-related projects, you might not be
    able to find the configuration zip corresponding to your distribution from this
    list; then it is recommended to use the Import from
    existing version
    option to take an existing distribution as base
    to add the jars required by your distribution.

    Note that custom versions are not officially supported by

    and its community provide you with the opportunity to connect to
    custom versions from the Studio but cannot guarantee that the configuration of
    whichever version you choose will be easy, due to the wide range of different
    Hadoop distributions and versions that are available. As such, you should only
    attempt to set up such a connection if you have sufficient Hadoop experience to
    handle any issues on your own.


    In this dialog box, the active check box must be kept
    selected so as to import the jar files pertinent to the connection to be
    created between the custom distribution and this component.

    For a step-by-step example about how to connect to a custom
    distribution and share this connection, see Connecting to a custom Hadoop distribution.

Hadoop version

Select the version of the Hadoop distribution you are using. The available
options vary depending on the component you are using. Along with the evolution of
Hadoop, please note the following changes:

  • If you use Hortonworks Data
    Platform V2.2
    , the configuration files of your cluster might
    be using environment variables such as ${hdp.version}. If this is your situation, you need to set the mapreduce.application.framework.path property in
    the Hadoop properties table of this
    component with the path value explicitly pointing to the MapReduce framework
    archive of your cluster. For
  • If you use Hortonworks Data
    Platform V2.0.0
    , the type of the operating system for
    running the distribution and a
    Job must be the same, such as Windows or Linux. Otherwise, you
    have to use
    Jobserver to execute the Job in the same type of operating
    system in which the Hortonworks Data Platform
    distribution you are using is run.

Use kerberos authentication

If you are accessing the Hadoop cluster running
with Kerberos security, select this check box, then, enter the Kerberos
principal name for the NameNode in the field displayed. This enables you to use
your user name to authenticate against the credentials stored in Kerberos.

  • If this cluster is a MapR cluster of the version 4.0.1 or later, you can set the MapR
    ticket authentication configuration in addition or as an alternative by following the
    explanation in Connecting to a security-enabled MapR.

    Keep in mind that this configuration generates a new MapR security ticket for the username
    defined in the Job in each execution. If you need to reuse an existing ticket issued for the
    same username, leave both the Force MapR ticket
    check box and the Use Kerberos
    check box clear, and then MapR should be able to automatically
    find that ticket on the fly.

This check box is available depending on the Hadoop distribution you are
connecting to.

Use a keytab to

Select the Use a keytab to authenticate
check box to log into a Kerberos-enabled system using a given keytab file. A keytab
file contains pairs of Kerberos principals and encrypted keys. You need to enter the
principal to be used in the Principal field and
the access path to the keytab file itself in the Keytab field. This keytab file must be stored in the machine in
which your Job actually runs, for example, on a Talend Jobserver.

Note that the user that executes a keytab-enabled Job is not necessarily
the one a principal designates but must have the right to read the keytab file being
used. For example, the user name you are using to execute a Job is user1 and the principal to be used is guest; in this
situation, ensure that user1 has the right to read the keytab
file to be used.

NameNode URI

Type in the URI of the Hadoop NameNode, the master node of a Hadoop system. For
example, we assume that you have chosen a machine called masternode as the NameNode, then the location is hdfs://masternode:portnumber. If you are using WebHDFS, the location should be
webhdfs://masternode:portnumber; if this WebHDFS is secured
with SSL, the scheme should be swebhdfs and you need to use
a tLibraryLoad in the Job to load the library required by
the secured WebHDFS.

User name

The User name field is available when you are not using
Kerberos to authenticate. In the User name field, enter the
login user name for your distribution. If you leave it empty, the user name of the machine
hosting the Studio will be used.


Enter the membership including the authentication user under which the HDFS instances were
started. This field is available depending on the distribution you are using.

Use datanode hostname

Select the Use datanode
check box to allow the Job to access datanodes via
their hostnames. This actually sets the dfs.client.use.datanode.hostname property to true. When connecting to a S3N filesystem, you must select this check

Hadoop properties

Talend Studio
uses a default configuration for its engine to perform
operations in a Hadoop distribution. If you need to use a custom configuration in a specific
situation, complete this table with the property or properties to be customized. Then at
runtime, the customized property or properties will override those default ones.

  • Note that if you are using the centrally stored metadata from the Repository, this table automatically inherits the
    properties defined in that metadata and becomes uneditable unless you change the
    Property type from Repository to Built-in.

For further information about the properties required by Hadoop and its related systems such
as HDFS and Hive, see the documentation of the Hadoop distribution you
are using or see Apache’s Hadoop documentation on and then select the version of the documentation you want. For demonstration purposes, the links to some properties are listed below:

Setup HDFS encryption configurations

If the HDFS transparent encryption has been enabled in your cluster, select
the Setup HDFS encryption configurations check
box and in the HDFS encryption key provider field
that is displayed, enter the location of the KMS proxy.

For further information about the HDFS transparent encryption and its KMS proxy, see Transparent Encryption in HDFS.


Usage rule

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

You need to drop tHDFSConfiguration along with the file
system related Subjob to be run in the same Job so that the configuration is used by the
whole Job at runtime.

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.


The Hadoop distribution must be properly installed, so as to guarantee the interaction
Talend Studio
. The following list presents MapR related information for

  • Ensure that you have installed the MapR client in the machine where the Studio is,
    and added the MapR client library to the PATH variable of that machine. According
    to MapR’s documentation, the library or libraries of a MapR client corresponding to
    each OS version can be found under MAPR_INSTALL
    . For example, the library for
    Windows is lib
    in the MapR
    client jar file. For further information, see the following link from MapR:

    Without adding the specified library or libraries, you may encounter the following
    error: no MapRClient in java.library.path.

  • Set the -Djava.library.path argument, for example, in the Job Run VM arguments area
    of the Run/Debug view in the [Preferences] dialog box in the Window menu. This argument provides to the Studio the path to the
    native library of that MapR client. This allows the subscription-based users to make
    full use of the Data viewer to view locally in the
    Studio the data stored in MapR.

For further information about how to install a Hadoop distribution, see the manuals
corresponding to the Hadoop distribution you are using.

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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