tHiveConnection

tHiveConnection properties

Component Family

Big Data / Hive

Function

tHiveConnection opens a
connection to a Hive database.

Purpose

This component allows you to establish a Hive connection to be
reused by other Hive components in your Job.

Basic settings

Property type

Either Built-in or Repository.

Built-in: No property data stored
centrally.

Repository: Select the repository
file in which the properties are stored. The fields that follow are
completed automatically using the data retrieved.

Version

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
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.

In order to connect to a custom distribution, once selecting Custom, click the button to display the dialog box in which you can
alternatively:

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.
Select Import from zip to import a custom
distribution zip that, for example, you can download from http://www.talendforge.org/exchange/index.php.

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 an 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:

mapreduce.application.framework.path=/hdp/apps/2.2.0.0-2041/mapreduce/mapreduce.tar.gz#mr-framework

1

mapreduce.application.framework.path=/hdp/apps/2.2.0.0-2041/mapreduce/mapreduce.tar.gz#mr-framework
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. For further information about Talend Jobserver, see
Talend Installation
and Upgrade Guide.

Connection

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

DB server listening port.

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.

Authentication

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.

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

Hive principal uses the value of hive.metastore.kerberos.principal. This is the
service principal of the Hive Metastore.
Metastore URL uses the value of javax.jdo.option.ConnectionURL. This is the JDBC
connection string to the Hive Metastore.
Driver class uses the value of javax.jdo.option.ConnectionDriverName. This is the
name of the driver for the JDBC connection.
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.
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 Hadoop 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.

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 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 +

Hadoop properties

Set Jobtracker URI

Select this check box to indicate the location of the Jobtracker service within the Hadoop
cluster to be used. For example, we assume that you have chosen a machine called machine1 as the JobTracker, then set its location as machine1:portnumber. A Jobtracker is the service that assigns
Map/Reduce tasks to specific nodes in a Hadoop cluster. Note that the notion job in this
term JobTracker does not designate a Talend Job, but rather a Hadoop job
described as MR or MapReduce job in Apache’s Hadoop documentation on http://hadoop.apache.org.

This property is required when the query you want to use is executed in Windows and it is
a Select query. For example, SELECT your_column_name FROM your_table_name

If you use YARN in your Hadoop cluster such as Hortonworks Data
Platform V2.0.0 or Cloudera CDH4.3 + (YARN
mode), you need to specify the location of the Resource
Manager instead of the Jobtracker. 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 ):

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

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 to indicate the location of the NameNode of the Hadoop cluster to be
used. The NameNode is the master node of a Hadoop cluster. For example, we assume that you
have chosen a machine called masternode as the NameNode
of an Apache Hadoop distribution, then the location is hdfs://masternode:portnumber.

This property is required when the query you want to use is executed in Windows and it is
a Select query. For example, SELECT your_column_name FROM your_table_name

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

Microsoft HD Insight properties

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.

Use or register a shared DB Connection

Select this check box to share your connection or fetch a
connection shared by a parent or child Job. This allows you to share
one single DB connection among several DB connection components from
different Job levels that can be either parent or child.

Warning

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.

Shared DB Connection Name: set or
type in the shared connection name.

HBase Configuration

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 Talend and HBase. Note that when you configure the Zookeeper, you
might need to set the zookeeper.znode.parent property to
define the root of the relative path of an HBase’s Zookeeper file; 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

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:

Typically, the HDFS-related properties can be found in the hdfs-default.xml file of your distribution, such as

http://hadoop.apache.org/docs/r2.6.0/hadoop-project-dist/hadoop-hdfs/hdfs-default.xml.
Apache also provides a page to list the Hive-related properties: https://cwiki.apache.org/confluence/display/Hive/Configuration+Properties.

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.

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

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

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. 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
set this argument, see the section describing how to view data of Talend Big Data Getting Started Guide.

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

Log4j

The activity of this component can be logged using the log4j feature. For more information on this feature, see Talend Studio User
Guide.

For more information on the log4j logging levels, see the Apache documentation at http://logging.apache.org/log4j/1.2/apidocs/org/apache/log4j/Level.html.

Limitation

n/a

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

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.
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.
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..
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.

This dialog box lists the Hadoop elements and their jar files you are
importing.
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.
Select the External libraries option to open
its view.
Browse to and select any jar file you need to import.
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 button.
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.

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.

The sample data to be used in this scenario is employee information of a company,
reading as follows:

1;Lyndon;Fillmore;21-05-2008;US

2;Ronald;McKinley;15-08-2008

3;Ulysses;Roosevelt;05-10-2008

4;Harry;Harrison;23-11-2007

5;Lyndon;Garfield;19-07-2007

6;James;Quincy;15-07-2008

7;Chester;Jackson;26-02-2008

8;Dwight;McKinley;16-07-2008

9;Jimmy;Johnson;23-12-2007

10;Herbert;Fillmore;03-04-2008

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

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.
Drop tHiveConnection, tHiveCreateTable and tHiveLoad onto the workspace.
Connect them using the Trigger > On Subjob
OK link.

Configuring the connection to Hive

Configuring tHiveConnection

Double-click tHiveConnection to open its
Component view.
From the Property type list, select
Built-in. If you have created the
connection to be used in Repository, then
select Repository, click the 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 an Hadoop connection in
Repository, see the chapter describing the Hadoop
cluster node of the Talend Big Data Getting Started Guide.
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.
In the Connection area, enter the
connection parameters to the Hive database to be used.
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.
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

Double-click tHiveCreateTable to open its
Component view.
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.
Click the button next to Edit
schema to open the schema editor.
Click the button four times to add four rows and in the Column column, rename them to Id, FirstName, LastName and
Reg_date, respectively.

Note that you cannot use the Hive reserved keywords to name the columns,
such as location or date.
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.
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.
In the Data pattern column, define the
pattern corresponding to that of the raw data. In this example, use the
default one.
Click OK to validate these
changes.

Defining the table settings

In Table name field, enter the name of
the Hive table to be created. In this scenario, it is employees.
From the Action on table list, select
Create table if not exists.
From the Format list, select the data
format that this Hive table in question is created for. In this scenario, it
is TEXTFILE.
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 button next to Edit
schema that appears.
Leave the Set file location check box
clear to use the default path for Hive table.
Select the Set Delimited row format check
box to display the available options of row format.
Select the Field check box and enter a
semicolon (;) as field separator in the
field that appears.
Select the Line check box and leave the
default value as line separator.

Writing data to the table

Configuring tHiveLoad

Double-click tHiveLoad to open its
Component view.
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.
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.
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.
In the Table name field, enter the name
of the target table you need to load data in. In this scenario, it is
employees.
From the Action on file list, select
APPEND.
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.

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.

Docs 5.x

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