August 15, 2023

tHiveConnection – Docs for ESB 6.x

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tHiveConnection

Establishes a Hive connection to be reused by other Hive components in your
Job.

tHiveConnection opens a
connection to a Hive database.

tHiveConnection Standard properties

These properties are used to configure tHiveConnection running in the Standard Job framework.

The Standard
tHiveConnection component belongs to the Big Data, the Databases and the ELT families.

The component in this framework is generally available.

Basic settings

Connection configuration:

  • When you use this component with Google Dataproc:

    Project identifier

    Enter the ID of your Google Cloud Platform project.

    If you are not certain about your project ID, check it in the Manage
    Resources page of your Google Cloud Platform services.

    Cluster identifier

    Enter the ID of your Dataproc cluster to be used.
    Region

    Enter the geographic zones in which the computing resources are used and your
    data is stored and processed. If you do not need to specify a particular
    region, leave the default value global.

    For further information about the available regions and the zones each region
    groups, see Regions and Zones.
    Google Storage staging bucket

    As a Talend Job expects its
    dependent jar files for execution, specify the Google Storage directory to
    which these jar files are transferred so that your Job can access these
    files at execution.

    The directory to be entered must end with a slash (/). If not existing, the
    directory is created on the fly but the bucket to be used must already
    exist.

    Database

    Fill this field with the name of the database.

    Provide Google Credentials in file

    Leave this check box clear, when you
    launch your Job from a given machine in which Google Cloud SDK has been
    installed and authorized to use your user account credentials to access
    Google Cloud Platform. In this situation, this machine is often your
    local machine.

    When you launch your Job from a remote
    machine, such as a Jobserver, select this check box and in the
    Path to Google Credentials file field that is
    displayed, enter the directory in which this JSON file is stored in the
    Jobserver machine.

    For further information about this Google
    Credentials file, see the administrator of your Google Cloud Platform or
    visit Google Cloud Platform Auth
    Guide    .

  • When you use this component with HDInsight:

    WebHCat configuration

    Enter the address and the authentication information of the WebHCat service
    of the Microsoft HD Insight cluster to be used. The Studio uses this service to
    submit the Job to the HD Insight cluster.

    In the Job result folder field, enter
    the location in which you want to store the execution result of a Job in the Azure
    Storage to be used.

    HDInsight
    configuration

    Enter the authentication information of the HD Insight cluster to be
    used.

    Windows Azure Storage
    configuration

    Enter the address and the authentication information of the Azure Storage
    account to be used.

    In the Container field, enter the name
    of the container to be used.

    In the Deployment Blob field, enter the
    location in which you want to store the current Job and its dependent libraries in
    this Azure Storage account.

    Database

    Fill this field with the name of the database.

  • When you use the other distributions:

    Connection mode

    Select a connection mode from the list. The
    options vary depending on the distribution you are
    using.

    Hive server

    Select the Hive server through which you want the Job using this component to
    execute queries on Hive.

    This Hive server list is available only
    when the Hadoop distribution to be used such as HortonWorks Data
    Platform V1.2.0 (Bimota)     supports HiveServer2. It allows you to select
    HiveServer2 (Hive 2), the server that better support
    concurrent connections of multiple clients than HiveServer (Hive
    1    ).

    For further information about HiveServer2, see https://cwiki.apache.org/confluence/display/Hive/Setting+Up+HiveServer2.

    Host

    Database server IP address.

    Port

    Listening port number of DB server.

    Database

    Fill this field with the name of the
    database.

    Note:

    This field is not available when you
    select Embedded
    from the Connection
    mode     list.

    Username and
    Password

    DB user authentication data.

    To enter the password, click the […] button next to the
    password field, and then in the pop-up dialog box enter the password between double quotes
    and click OK to save the settings.

    Use kerberos authentication

    If you are accessing a Hive Metastore running with Kerberos security,
    select this check box and then enter the relevant parameters in the fields that
    appear.

    • 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
      authentication       check box and the Use Kerberos
      authentication       check box clear, and then MapR should be able to automatically
      find that ticket on the fly.

    The values of the following parameters can be found in the hive-site.xml file of the Hive system to be used.

    1. Hive principal uses the value
      of hive.metastore.kerberos.principal. This is
      the service principal of the Hive Metastore.

    2. HiveServer2 local user
      principal       uses the value of hive.server2.authentication.kerberos.principal.

    3. HiveServer2 local user keytab
      uses the value of hive.server2.authentication.kerberos.keytab

    4. Metastore URL uses the value of
      javax.jdo.option.ConnectionURL. This is the
      JDBC connection string to the Hive Metastore.

    5. Driver class uses the value of
      javax.jdo.option.ConnectionDriverName. This
      is the name of the driver for the JDBC connection.

    6. Username uses the value of javax.jdo.option.ConnectionUserName. This, as
      well as the Password parameter, is the user credential for connecting to
      the Hive Metastore.

    7. Password uses the value of javax.jdo.option.ConnectionPassword.

    For the other parameters that are displayed, please consult the Hadoop
    configuration files they belong to. For example, the Namenode
    principal     can be found in the hdfs-site.xml file
    or the hdfs-default.xml file of the distribution you are
    using.

    This check box is available depending on the Hadoop distribution you are
    connecting to.
    Use a keytab to authenticate

    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.

    Use SSL encryption

    Select this check box to enable the SSL or TLS encrypted connection.

    Then in the fields that are displayed, provide the authentication
    information:

    • In the Trust store
      path       field, enter the path, or browse to the TrustStore
      file to be used. By default, the supported TrustStore types are JKS and PKCS 12.

    • To enter the password, click the […] button next to the
      password field, and then in the pop-up dialog box enter the password between double quotes
      and click OK to save the settings.

    This feature is available only to the HiveServer2 in the Standalone mode of the following distributions:

    • Hortonworks Data Platform 2.0 +

    • Cloudera CDH4 +

    • Pivotal HD 2.0 +

    • Amazon EMR 4.0.0 +

    Set Resource Manager

    Select this check box and in the displayed field, enter the location of the
    ResourceManager of your distribution. For example, tal-qa114.talend.lan:8050.

    Then you can continue to set the following parameters depending on the
    configuration of the Hadoop cluster to be used (if you leave the check box of a
    parameter clear, then at runtime, the configuration about this parameter in the
    Hadoop cluster to be used will be ignored ):

    1. Select the Set resourcemanager
      scheduler address       check box and enter the Scheduler address in
      the field that appears.

    2. Select the Set jobhistory
      address       check box and enter the location of the JobHistory
      server of the Hadoop cluster to be used. This allows the metrics information of
      the current Job to be stored in that JobHistory server.

    3. Select the Set staging
      directory       check box and enter this directory defined in your
      Hadoop cluster for temporary files created by running programs. Typically, this
      directory can be found under the yarn.app.mapreduce.am.staging-dir property in the configuration files
      such as yarn-site.xml or mapred-site.xml of your distribution.

    4. Allocate proper memory volumes to the Map and the Reduce
      computations and the ApplicationMaster
      of YARN by selecting the Set memory
      check box in the Advanced settings
      view.

    5. Select the Set Hadoop
      user       check box and enter the user name under which you
      want to execute the Job. Since a file or a directory in Hadoop has its
      specific owner with appropriate read or write rights, this field allows
      you to execute the Job directly under the user name that has the
      appropriate rights to access the file or directory to be processed.

    6. Select the Use datanode
      hostname       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
      box.

    For further information about these parameters, see the documentation or
    contact the administrator of the Hadoop cluster to be used.

    For further information about the Hadoop Map/Reduce framework, see the
    Map/Reduce tutorial in Apache’s Hadoop documentation on http://hadoop.apache.org.

    Set NameNode URI

    Select this check box and in the displayed field, enter the URI of the Hadoop
    NameNode, the master node of a Hadoop system. For example, assuming 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.

    For further information about the Hadoop Map/Reduce framework, see the
    Map/Reduce tutorial in Apache’s Hadoop documentation on http://hadoop.apache.org.

The other properties:

Property type

Either Built-In or Repository.

Built-In: No property data stored centrally.

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

Distribution

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: https://www.youtube.com/watch?v=A3QTT6VsNoM.

  • If you select Amazon
    EMR    , you can find more details about how
    to configure an Amazon EMR cluster in Talend Help Center (https://help.talend.com)    .

  • 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
    Talend
    .

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

  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.

    In
    Talend

    Exchange, members of
    Talend
     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

    Talend
    .
    Talend
     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.

    Note:

    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.

Hive 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
    example:

  • If you use Hortonworks Data
    Platform V2.0.0    , the type of the operating system for
    running the distribution and a
    Talend
     Job must be the same, such as Windows or Linux. Otherwise, you
    have to use
    Talend
     Jobserver to execute the Job in the same type of operating
    system in which the Hortonworks Data Platform
    V2.0.0     distribution you are using is run.

Inspect the classpath for
configurations

Select this check box to allow the component to check the configuration
files in the directory you have set with the $HADOOP_CONF_DIR
variable and directly read parameters from these files in this directory. This
feature allows you to easily change the Hadoop configuration for the component to
switch between different environments, for example, from a test environment to a
production environment.

In this situation, the fields or options used to configure Hadoop
connection and/or Kerberos security are hidden.

If you want to use certain parameters such as the Kerberos parameters but
these parameters are not included in these Hadoop configuration files, you need to
create a file called talend-site.xml and put this file into the
same directory defined with $HADOOP_CONF_DIR. This talend-site.xml file should read as follows:

The parameters read from these configuration files override the default
ones used by the Studio. When a parameter does not exist in these configuration
files, the default one is used.

Note that this option is available only in Hive
Standalone mode with
Hive 2.

Use or register a shared DB Connection

Select this check box to share your
database connection or fetch a database connection shared by a parent or child Job,
and in the Shared DB Connection Name field displayed, enter the
name for the shared database connection. This allows you to share one single database
connection (except the database schema setting) among several database connection
components from different Job levels that can be either parent or child.

This option is
incompatible with the Use dynamic job and Use an
independent process to run subjob options of the
tRunJob component. Using a shared connection together with a
tRunJob component with either of these two options enabled
will cause your Job to fail.

Execution engine

Select this check box and from the drop-down list, select the framework you need to use to
run the Job.

This list is available only when you are using the Embedded mode for the Hive connection and the distribution you are working with
is among the following ones:

  • Hortonworks: V2.1 and V2.2.

  • MapR: V4.0.1.

  • Custom: this option allows you connect to a distribution supporting Tez but not
    officially supported by
    Talend
    .

Before using Tez, ensure that the Hadoop cluster you are using supports Tez. You will need to configure the access to the relevant Tez libraries via the Advanced settings view of this component.

For further information about Hive on Tez, see Apache’s related documentation in https://cwiki.apache.org/confluence/display/Hive/Hive+on+Tez. Some examples are presented there to show how Tez can be used to gain performance over MapReduce.

Store by HBase

Select this check box to display the parameters to be set to allow the Hive components to
access HBase tables:

  • Once this access is configured, you will be able to use, in tHiveRow and tHiveInput, the Hive QL statements to read and write data in
    HBase.

  • If you are using the Kerberos authentication, you need to define the HBase
    related principals in the corresponding fields that are displayed.

For further information about this access involving Hive and HBase, see Apache’s Hive
documentation about Hive/HBase integration.

Zookeeper quorum

Type in the name or the URL of the Zookeeper service you use to coordinate the transaction
between your Studio and your database. Note that when you configure the Zookeeper, you might
need to explicitly set the zookeeper.znode.parent
property to define the path to the root znode that contains all the znodes created and used
by your database; then select the Set Zookeeper znode
parent check box to define this property.

Zookeeper client port

Type in the number of the client listening port of the Zookeeper service you are
using.

Define the jars to register for
HBase

Select this check box to display the Register jar for
HBase table, in which you can register any missing jar file required by
HBase, for example, the Hive Storage Handler, by default, registered along with your Hive
installation.
Register jar for HBase

Click the [+] button to add rows to this table, then, in the Jar name column, select the jar file(s) to be registered and in the
Jar path column, enter the path(s) pointing to that or
those jar file(s).

Advanced settings

Tez lib

Select how the Tez libraries are accessed:

  • Auto install: at runtime, the Job uploads and deploys the Tez
    libraries provided by the Studio into the directory you specified in the Install folder in HDFS field, for example, /tmp/usr/tez.

    If you have set the tez.lib.uris property in the properties
    table, this directory overrides the value of that property at runtime. But the other
    properties set in the properties table are still effective.

  • Use exist: the Job accesses the Tez libraries already
    deployed in the Hadoop cluster to be used. You need to enter the path pointing to
    those libraries in the Lib path (folder or file)
    field.

  • Lib jar: this table appears when you have selected Auto install from the Tez
    lib     list and the distribution you are using is Custom. In this table, you need to add the Tez libraries to be
    uploaded.

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 http://hadoop.apache.org/docs and then select the version of the documentation you want. For demonstration purposes, the links to some properties are listed below:

Hive properties

Talend Studio uses a default configuration for its engine to perform
operations in a Hive database. 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. For further information for Hive dedicated properties, see https://cwiki.apache.org/confluence/display/Hive/AdminManual+Configuration.

  • If you need to use Tez to run your Hive Job, add
    hive.execution.engine to the
    Properties column and Tez to the
    Value column, enclosing both of these strings in
    double quotation marks.

  • 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.

Mapred job map memory mb and
Mapred job reduce memory
mb

If the Hadoop distribution to be used is Hortonworks Data Platform V1.2 or Hortonworks
Data Platform V1.3, you need to set proper memory allocations for the map and reduce
computations to be performed by the Hadoop system.

In that situation, you need to enter the values you need in the Mapred
job map memory mb and the Mapred job reduce memory
mb fields, respectively. By default, the values are both 1000 which are normally appropriate for running the
computations.

Path separator in server

Leave the default value of the Path separator in
server as it is, unless you have changed the separator used by your
Hadoop distribution’s host machine for its PATH variable or in other words, that
separator is not a colon (:). In that situation, you must change this value to the
one you are using in that host.

tStatCatcher Statistics

Select this check box to collect the log data at a component
level.

Global Variables

Global Variables

ERROR_MESSAGE: the error message generated by the
component when an error occurs. This is an After variable and it returns a string. This
variable functions only if the Die on error check box is
cleared, if the component has this check box.

A Flow variable functions during the execution of a component while an After variable
functions after the execution of the component.

To fill up a field or expression with a variable, press Ctrl +
Space to access the variable list and choose the variable to use from it.

For further information about variables, see
Talend Studio

User Guide.

Usage

Usage rule

This component is generally used with other Hive components,
particularly tHiveClose.

If the Studio used to connect to a Hive database is operated on Windows, you
must manually create a folder called tmp in the root of the disk
where this Studio is installed.

Prerequisites

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

  • 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
    hadoophadoop-VERSIONlib
    ative    . For example, the library for
    Windows is lib
    ativeMapRClient.dll     in the MapR
    client jar file. For further information, see the following link from MapR: http://www.mapr.com/blog/basic-notes-on-configuring-eclipse-as-a-hadoop-development-environment-for-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.

Connecting to a custom Hadoop distribution

As explained in the properties table, when you select the Custom option from the Distribution
drop-down list, you are connecting to a Hadoop distribution different from any of the
Hadoop distributions provided on that Distribution list
in the Studio.

After selecting this Custom option, click the

dotbutton.png

button to display the [Import custom
definition] dialog box and proceed as follows:

  1. Depending on your situation, select Import from existing
    version     or Import from zip to
    configure the custom Hadoop distribution to be connected to.

    • If you have the zip file of the custom Hadoop distribution you need to
      connect to, select Import from zip.

      Talend
       community provides this kind of zip
      files that you can download from http://www.talendforge.org/exchange/index.php.

    • Otherwise, select Import from existing
      version       to import an officially supported Hadoop
      distribution as base so as to customize it by following the wizard.

    import_custom_definition.png

    Note that the check boxes in the wizard allow you to select the Hadoop
    element(s) you need to import. All the check boxes are not always displayed in
    your wizard depending on the context in which you are creating the connection.
    For example, if you are creating this connection for a Hive component, then only
    the Hive check box appears.
  2. Whether you have selected Import from existing
    version     or Import from zip,
    verify that each check box next to the Hadoop element you need to import has
    been selected..
  3. Click OK and then in the pop-up warning, click Yes to accept overwriting any custom setup of jar
    files previously implemented.

    Once done, the [Custom Hadoop version
    definition]     dialog box becomes active.
    export_custom_hadoop_setup.png

    This dialog box lists the Hadoop elements and their jar files you are
    importing.
  4. If you have selected Import from zip, click
    OK to validate the imported
    configuration.

    If you have selected Import from existing
    version     as base, you should still need to add more jar files to
    customize that version. Then from the tab of the Hadoop element you need to
    customize, for example, the HDFS/HCatalog/Oozie
    tab, click the [+] button to open the [Select libraries] dialog box.
  5. Select the External libraries option to open
    its view.
  6. Browse to and select any jar file you need to import.
  7. Click OK to validate the changes and to close
    the [Select libraries] dialog box.

    Once done, the selected jar file appears on the list in the tab of the Hadoop
    element being configured.
    Note that if you need to share the custom Hadoop setup with another Studio,
    you can export this custom connection from the [Custom
    Hadoop version definition]     window using the

    export.png

    button.

  8. In the [Custom Hadoop version definition]
    dialog box, click OK to validate the customized
    configuration. This brings you back to the Distribution list in the Basic
    settings     view of the component.

Now that the configuration of the custom Hadoop version has been set up and you are
back to the Distribution list, you are able to continue
to enter other parameters required by the connection.

If the custom Hadoop version you need to connect to contains YARN and you want to use
it, select the Use YARN check box next to the Distribution list.

A video is available in the following link to demonstrate, by taking HDFS as example, how
to set up the connection to a custom Hadoop cluster, also referred to as an unsupported
Hadoop distribution: How to add an unsupported Hadoop
distribution to the Studio.

Scenario: creating a partitioned Hive table

This scenario illustrates how to use tHiveConnection,
tHiveCreateTable and tHiveLoad to create a partitioned Hive table and write data in
it.

Note that tHiveCreateTable and tHiveLoad are available only when you are using one of the
Talend

solutions with Big Data.

components-use_case-thiveload1.png
The sample data to be used in this scenario is employee information of a company,
reading as follows:

The information contains some employees’ names and the dates when they are registered
in a HR system. Since these employees work for the US subsidiary of the company, you
will create a US partition for this sample data.

Before starting to replicate this scenario, ensure that you have appropriate rights
and permissions to access the Hive database to be used.

Note that if you are using the Windows operating system, you have to create a
tmp folder at the root of the disk where the
Studio is installed.

Then proceed as follows:

Linking the components

  1. In the
    Integration
     perspective
    of the Studio, create an empty Job from the Job
    Designs     node in the Repository tree view.

    For further information about how to create a Job, see the chapter
    describing how to designing a Job in
    Talend Studio
    User Guide    .
  2. Drop tHiveConnection, tHiveCreateTable and tHiveLoad onto the workspace.
  3. Connect them using the Trigger > On Subjob
    OK     link.

Configuring the connection to Hive

Configuring tHiveConnection
  1. Double-click tHiveConnection to open its
    Component view.

    components-use_case-thiveload2.png

  2. From the Property type list, select
    Built-in. If you have created the
    connection to be used in Repository, then
    select Repository, click the

    dotbutton.png

    button to open the [Repository
    content]     dialog box and select that connection. This way, the
    Studio will reuse that set of connection information for this Job.

    For further information about how to create a Hadoop connection in
    Repository, see the chapter describing the Hadoop
    cluster     node of the
    Talend Open Studio for Big Data Getting Started
    Guide
    .
  3. In the Version area, select the Hadoop
    distribution to be used and its version. If you cannot find from the list
    the distribution corresponding to yours, select Custom so as to connect to a Hadoop distribution not
    officially supported in the Studio.

    For a step-by-step example about how to use this Custom option, see Connecting to a custom Hadoop distribution.
  4. In the Connection area, enter the
    connection parameters to the Hive database to be used.
  5. In the Name node field,
    enter the location of the master node, the NameNode, of the distribution to be
    used. For example, talend-hdp-all:50300. 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.
  6. In the Job tracker field, enter the
    location of the JobTracker of your distribution. For example, hdfs://talend-hdp-all:8020.

    Note that the notion Job in this term JobTracker designates the MR or the
    MapReduce jobs described in Apache’s documentation on http://hadoop.apache.org/.

Configuring tHiveConnection

  1. Double-click tHiveConnection to open its
    Component view.

    components-use_case-thiveload2.png

  2. From the Property type list, select
    Built-in. If you have created the
    connection to be used in Repository, then
    select Repository, click the

    dotbutton.png

    button to open the [Repository
    content]     dialog box and select that connection. This way, the
    Studio will reuse that set of connection information for this Job.

    For further information about how to create a Hadoop connection in
    Repository, see the chapter describing the Hadoop
    cluster     node of the
    Talend Open Studio for Big Data Getting Started
    Guide
    .
  3. In the Version area, select the Hadoop
    distribution to be used and its version. If you cannot find from the list
    the distribution corresponding to yours, select Custom so as to connect to a Hadoop distribution not
    officially supported in the Studio.

    For a step-by-step example about how to use this Custom option, see Connecting to a custom Hadoop distribution.
  4. In the Connection area, enter the
    connection parameters to the Hive database to be used.
  5. In the Name node field, enter
    the location of the master node, the NameNode, of the distribution to be used. For
    example, talend-hdp-all:50300. 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.
  6. In the Job tracker field, enter the
    location of the JobTracker of your distribution. For example, hdfs://talend-hdp-all:8020.

    Note that the notion Job in this term JobTracker designates the MR or the
    MapReduce jobs described in Apache’s documentation on http://hadoop.apache.org/.

Creating the Hive table

Defining the schema

  1. Double-click tHiveCreateTable to open its
    Component view.

    components-use_case-thiveload3.png

  2. Select the Use an existing connection
    check box and from Component list, select
    the connection configured in the tHiveConnection component you are using for this Job.
  3. Click the

    dotbutton.png

    button next to Edit
    schema     to open the schema editor.

  4. Click the

    plus_button.png

    button four times to add four rows and in the Column column, rename them to Id, FirstName, LastName and
    Reg_date, respectively.

    components-use_case-thiveload4.png

    Note that you cannot use the Hive reserved keywords to name the columns,
    such as location or date.
  5. In the Type column, select the type of
    the data in each column. In this scenario, Id is of the Integer type,
    Reg_date is of the Date type and the others are of the String type.
  6. In the DB type column, select the Hive
    type of each column corresponding to their data types you have defined. For
    example, Id is of INT and Reg_date is of
    TIMESTAMP.
  7. In the Data pattern column, define the
    pattern corresponding to that of the raw data. In this example, use the
    default one.
  8. Click OK to validate these
    changes.

Defining the table settings

  1. In Table name field, enter the name of
    the Hive table to be created. In this scenario, it is employees.
  2. From the Action on table list, select
    Create table if not exists.
  3. From the Format list, select the data
    format that this Hive table in question is created for. In this scenario, it
    is TEXTFILE.
  4. Select the Set partitions check box to
    add the US partition as explained at the
    beginning of this scenario. To define this partition, click the

    dotbutton.png

    button next to Edit
    schema     that appears.

  5. Leave the Set file location check box
    clear to use the default path for Hive table.
  6. Select the Set Delimited row format check
    box to display the available options of row format.
  7. Select the Field check box and enter a
    semicolon (;) as field separator in the
    field that appears.
  8. Select the Line check box and leave the
    default value as line separator.

Writing data to the table

Configuring tHiveLoad
  1. Double-click tHiveLoad to open its
    Component view.

    components-use_case-thiveload5.png

  2. Select the Use an existing connection
    check box and from Component list, select
    the connection configured in the tHiveConnection component you are using for this Job.
  3. From the Load action field, select
    LOAD to write data from the file
    holding the sample data that is presented at the beginning of this
    scenario.
  4. In the File path field, enter the
    directory where the sample data is stored. In this example, the data is
    stored in the HDFS system to be used.

    In the real-world practice, you can
    use tHDFSOutput to write data into the HDFS
    system and you need to ensure that the Hive application has the appropriate
    rights and permissions to read or even move the data.

    For further information about tHDFSOutput, see tHDFSOutput.

    for further
    information about the related rights and permissions, see the documentation
    or contact the administrator of the Hadoop cluster to be used.

    Note if you need to read data from a local file system other than the HDFS
    system, ensure that the data to be read is stored in the local file system
    of the machine in which the Job is run and then select the Local check box in this Basic settings view. For example, when the connection mode
    to Hive is Standalone, the Job is run in
    the machine where the Hive application is installed and thus the data should
    be stored in that machine.
  5. In the Table name field, enter the name
    of the target table you need to load data in. In this scenario, it is
    employees.
  6. From the Action on file list, select
    APPEND.
  7. Select the Set partitions check box and
    in the field that appears, enter the partition you need to add data to. In
    this scenario, this partition is country=’US’.

Configuring tHiveLoad

  1. Double-click tHiveLoad to open its
    Component view.

    components-use_case-thiveload5.png

  2. Select the Use an existing connection
    check box and from Component list, select
    the connection configured in the tHiveConnection component you are using for this Job.
  3. From the Load action field, select
    LOAD to write data from the file
    holding the sample data that is presented at the beginning of this
    scenario.
  4. In the File path field, enter
    the directory where the sample data is stored. In this example, the data is
    stored in the HDFS system to be used. In the real-world
    practice, you can use tHDFSOutput to write
    data into the HDFS system and you need to ensure that the Hive application has
    the appropriate rights and permissions to read or even move the data.

    For further information about the related rights and permissions,
    see the documentation or contact the administrator of the Hadoop cluster to be
    used.

    Note if you need to read data from a local file system other than the HDFS
    system, ensure that the data to be read is stored in the local file system
    of the machine in which the Job is run and then select the Local check box in this Basic settings view. For example, when the connection mode
    to Hive is Standalone, the Job is run in
    the machine where the Hive application is installed and thus the data should
    be stored in that machine.

  5. In the Table name field, enter the name
    of the target table you need to load data in. In this scenario, it is
    employees.
  6. From the Action on file list, select
    APPEND.
  7. Select the Set partitions check box and
    in the field that appears, enter the partition you need to add data to. In
    this scenario, this partition is country=’US’.

Executing the Job

Then you can press F6 to run this Job.

Once done, the Run view is opened automatically,
where you can check the execution process.

You can as well verify the results in the web console of the Hadoop distribution
used.

components-use_case-thiveload6.png

If you need to obtain more details about the Job, it is recommended to use the web
console of the Jobtracker provided by the Hadoop distribution you are using.

Document get from Talend https://help.talend.com
Thank you for watching.
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