July 30, 2023

tHiveConnection – Docs for ESB 7.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 available in all Talend
products.

Basic settings

Connection configuration:

  • When you use this component with Qubole on AWS:
    API Token

    Click the … button next to the
    API Token field to enter the
    authentication token generated for the Qubole user account
    to be used. For further information about how to obtain this
    token, see Manage Qubole
    account     from the Qubole documentation.

    This
    token allows you to specify the user account you want to
    use to access Qubole. Your Job automatically uses
    the rights and permissions granted to this user account
    in Qubole.

    Cluster label

    Select the Cluster label check
    box and enter the name of the Qubole cluster to be used. If
    leaving this check box clear, the default cluster is
    used.

    If you need details about your default cluster,
    ask the administrator of your Qubole service. You can
    also read this article
    from the Qubole documentaiton to find more information
    about configuring a default Qubole cluster.

    Change API endpoint

    Select the Change API endpoint
    check box and select the region to be used. If leaving this
    check box clear, the default region is used.

    For further
    information about the Qubole Endpoints supported on
    QDS-on-AWS, see Supported Qubole
    Endpoints on Different Cloud
    Providers    .

  • 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

    From this drop-down list, select the Google Cloud region to
    be used.
    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 Microsoft HD
    Insight cluster to be used. For example, the address could be
    your_hdinsight_cluster_name.azurehdinsight.net and the
    authentication information is your Azure account name: ychen.
    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

    • The Username is the one defined when
      creating your cluster. You can find it in the SSH
      + Cluster login       blade of your cluster.
    • The Password is defined when creating your HDInsight
      cluster for authentication to this cluster.

    Windows Azure Storage
    configuration

    Enter the address and the authentication information of the Azure Storage
    account to be used. In this configuration, you do not define where to read or write
    your business data but define where to deploy your Job only. Therefore always use
    the Azure
    Storage
    system for this configuration.

    In the Container field, enter the name
    of the container to be
    used. You can
    find the available containers in the Blob blade of the Azure
    Storage account 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.

    In the Hostname field, enter the
    Primary Blob Service Endpoint of your Azure Storage account without the https:// part. You can find this endpoint in the Properties blade of this storage account.

    In the Username field, enter the name of the Azure Storage account to be used.

    In the Password field, enter the access key of the Azure Storage account to be used. This key can be found in the Access keys blade of this 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 5.0.0 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; WebHDFS with SSL is not
    supported yet.

    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 HD
    Insightcluster and the Windows Azure Storage service of that cluster in the
    areas that are displayed. For
    detailed explanation about these parameters, search for configuring the
    connection manually on Talend Help Center (https://help.talend.com).

  • If you select Amazon EMR, find more details about Amazon EMR getting started 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 Hortonworks.

Hive version

Select the version of the Hadoop distribution you are using. The available
options vary depending on the component you are using.

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:

  • 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

You can tune the map and reduce computations by
selecting the Set memory check box to set proper memory allocations
for the 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

tHiveConnection_1.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.

    tHiveConnection_2.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.
    tHiveConnection_3.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 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

    tHiveConnection_3.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.

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.

tHiveConnection_5.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.

    tHiveConnection_6.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

    tHiveConnection_7.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; WebHDFS with SSL is not
    supported yet.
  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.

    tHiveConnection_6.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

    tHiveConnection_7.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; WebHDFS with SSL is not
    supported yet.
  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.

    tHiveConnection_10.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

    tHiveConnection_7.png

    button next to Edit
    schema     to open the schema editor.

  4. Click the

    tHiveConnection_12.png

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

    tHiveConnection_13.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

    tHiveConnection_7.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.

    tHiveConnection_15.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.

    tHiveConnection_15.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.

tHiveConnection_17.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.

Creating a JDBC Connection to Azure HDInsight Hive

This scenario illustrates how to use tHiveConnection, tHiveInput and
tHiveClose to create a JDBC Connection to
HDInsight Hive.

tHiveConnection_18.png

Prerequisites

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

Configuring a DataBase Connection to Hive

This example uses version 3.6 of Azure
HDInsight.
  1. In the Repository view,
    extend the Metadata drop-down menu.
  2. Click Db Connections, and then right-click Create Connection
    .
  3. Give a name to your connection.

    tHiveConnection_19.png

  4. Click Next.

  5. Set up the connection configuration similarly to the following table:

    tHiveConnection_20.png

    DB Type

    Select Hive.

    Hadoop Cluster

    Select None.

    Distribution

    Select Horton Works.

    HDInsight is leveraging Horton Works distribution on the backend. This
    will allow you to use Horton Works libraries to connect to
    HDInsighs.

    DB Type

    Select Hive.

    Version

    Select Hortonworks Data Platform V2.6.0.3-8
    [Built in]    .

    Hive Model

    Select Standalone.

    Login

    Password

    Server

    Fill in the fields as required.

    Port

    Input 443.

    You will be able to communicate through the proxy port since the
    HDInsight cluster sits behind a proxy by default.

    DataBase

    Leave default.

    Additional JDBC Setting
    Input transportMode=http;ssl=true;httpPath=/hive2, where:

    • transportMode=http sets the transport mode to HTTP instead of the default Hive JDBC transport mode.
    • SSL=true enables SSL.
    • httpPath=/hive2 sets the HTTP endpoint.
  6. Click Test Connection to
    ensure the Talend Studio connects
    successfully to the cluster.

Building the Job

  1. From the Repository view of the Talend Studio, right-click Job Designs, and then click Create Standard Job.
  2. Give a name to your Job.
  3. Click Finish.

    tHiveConnection_21.png

  4. Add a tPreJob component
    to your workspace.
  5. Add a tHiveConnection
    component to your workspace.
  6. Double click the tHiveConnection component and choose Repository as the Property Type and the Database Connection created above.

    tHiveConnection_22.jpeg

  7. Right-click the tPreJob
    component.
  8. Select Trigger > On Component Ok and connect the tPreJob to the tHiveConnection.

    tHiveConnection_23.png
  9. Add a tHiveInput
    component to your workspace.
  10. Select it and check the box Use an
    existing connection    , then select the tHiveConnection component in the Component List drop-down menu.
  11. In the Query field,
    input show tables to run a query
    displaying the available tables in the database.

    tHiveConnection_24.jpeg

  12. Add a tLogRow component
    to your workspace.
  13. Right-click the tHiveInput component and select Row > Main.
  14. Click the tLogRow
    component to connect both components. They will display the information from the
    query above.
  15. From the Component tab of the tLogRow, select Table (print values in celles of a table).

    tHiveConnection_25.png
  16. Add a tPostJob component
    to your workspace.
  17. Add a tHiveClose
    component to your workspace.
  18. Connect the tPostJob
    component to the tHiveClose component
    using an On Component Ok connection to
    close the connection opened.

    tHiveConnection_26.png

  19. From the Run tab,
    click Run to run the Job and ensure of a
    successful connection to Hive on HDInsight and of the readability of the table
    data.

    tHiveConnection_27.jpeg

Document get from Talend https://help.talend.com
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