tHiveLoad – Docs for ESB 5.x

Component family

Big Data / Hive

Function

This component connects to a given Hive database and copies or
moves data into an existing Hive table or a directory you
specify.

Purpose

This component is used to write data of different formats into a
given Hive table or to export data from a Hive table to a
directory.

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.

Use an existing connection

Select this check box and in the Component List click the
relevant connection component to reuse the connection details you already defined.

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:

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:

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.

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.

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.

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:

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

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.

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 ):

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.

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

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.

Load action

Select the action you need to carry for writing data into the
specified destination.

Target type

This drop-down list appears only when you have selected INSERT from the Load action list.

Select from this list the type of the location you need to write
data in.

Table name

Enter the name of the Hive table you need to write data in.

Note that with the INSERT action,
this field is available only when you have selected Table from the Target type list.

File path

Enter the directory you need to read data from or write data in,
depending on the action you have selected from the Load action list.

The target table uses the Parquet
format

If the table in which you need to write data is a Parquet table, select this check box.

Note that when the file format to be used is PARQUET, you
might be prompted to find the specific Parquet jar file and install it into the Studio.

This jar file can be downloaded from Apache’s site. For further information
about how to install an external jar file, see https://help.talend.com/display/KB/How+to+install+external+modules+in+the+Talend+products.

Then from the Compression list that appears, select the
compression mode you need to use to handle the Parquet file. The default mode is Uncompressed.

Action on file

Select the action to be carried out for writing data.

This list is available only when the target is a Hive table; if
the target is a directory, the action to be used is automatically
OVERWRITE.

Query

This field appears when you have selected INSERT from the Load
action list.

Enter the appropriate query for selecting the data to be exported
to the specified Hive table or directory.

Local

Select this check box to use the Hive LOCAL statement
for accessing a local directory. Note that this local directory is
actually in the machine in which the Job is run. Therefore, when the
connection mode to Hive is Standalone, the Job is run in the machine where the
Hive application is installed and thus this local directory is in
that machine.

This statement is used along with the directory you have defined
in the File path field. Therefore,
this Local check box is available
only when the File path field is
available.

For further information about this LOCAL statement,
see Apache’s documentation about Hive’s Language.

Select this check box to use the Hive Partition
clause in loading or inserting data in a Hive table. You need to
enter the partition keys and their values to be used in the field
that appears.

For example, enter contry=’US’,
state=’CA’. This makes a partition clause reading
Partition (contry='US', state='CA'), that is to
say, a US and CA
partition.

Also, it is recommended to select the Create
partition if not exist check box that appears to
ensure that you will not create a duplicate partition.

Die on error

Select this check box to kill the Job when an error occurs.

Advanced settings

Temporary path

If you do not want to set the Jobtracker and the NameNode when you execute the query
select * from your_table_name, you need to set this temporary path. For
example, /C:/select_all in Windows.

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.

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.

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.

If the distribution is YARN, then the memory parameters to be set become Map (in Mb), Reduce (in Mb) and
ApplicationMaster (in Mb), accordingly. These fields
allow you to dynamically allocate memory to the map and the reduce computations and the
ApplicationMaster of YARN.

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 log data at the component
level.

Dynamic settings

Click the [+] button to add a row in the table and fill
the Code field with a context variable to choose your
database connection dynamically from multiple connections planned in your Job. This feature
is useful when you need to access database tables having the same data structure but in
different databases, especially when you are working in an environment where you cannot
change your Job settings, for example, when your Job has to be deployed and executed
independent of Talend Studio.

The Dynamic settings table is available only when the
Use an existing connection check box is selected in the
Basic settings view. Once a dynamic parameter is
defined, the Component List box in the Basic settings view becomes unusable.

For more information on Dynamic settings and context
variables, see Talend Studio User Guide.

Global Variables

QUERY: the SQL query statement being processed. This is a
Flow variable and it returns a string.

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 works standalone and supports writing a wide range
of data formats such as RC, ORC or AVRO.

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.

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.