Component family
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Big Data / Hive
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Function
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tHiveRow is the dedicated
component for this database. It executes the HiveQL query stated in
the specified database. The row suffix means the component
implements a flow in the Job design although it does not provide
output.
This component can also perform queries in a HBase database once
you activate its Store by HBase
function.
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Purpose
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Depending on the nature of the query and the database, tHiveRow acts on the actual DB structure
or on the data (although without handling data). The SQLBuilder tool
helps you write your HiveQL statements easily.
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Basic settings
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Property type
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Either Built-in or Repository.
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Built-in: No property data stored
centrally.
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Repository : Select the
repository file in which the properties are stored. The fields that
follow are completed automatically using the data retrieved. |
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Use an existing connection
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Select this check box and in the Component List click the
relevant connection component to reuse the connection details you already defined.
Note
When a Job contains the parent Job and the child Job, if you need to share an existing
connection between the two levels, for example, to share the connection created by the
parent Job with the child Job, you have to:
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In the parent level, register the database connection to be shared in the
Basic settings view of the connection
component which creates that very database connection.
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In the child level, use a dedicated connection component to read that
registered database connection.
For an example about how to share a database connection across Job levels, see
Talend Studio User
Guide.
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Version
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Distribution
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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:
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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
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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:
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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.
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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.
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Hive version
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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:
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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:
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mapreduce.application.framework.path=/hdp/apps/2.2.0.0-2041/mapreduce/mapreduce.tar.gz#mr-framework |
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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.
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Connection
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Connection mode
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Select a connection mode from the list. The options vary depending
on the distribution you are using.
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Hive server
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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.
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Host
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Database server IP address.
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Port
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Listening port number of DB server.
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Database
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Fill this field with the name of the database.
Note
This field is not available when you select Embedded from the Connection mode list.
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Username and
Password
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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.
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Authentication
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Use kerberos authentication
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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.
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Hive principal uses the value of hive.metastore.kerberos.principal. This is the
service principal of the Hive Metastore.
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Metastore URL uses the value of javax.jdo.option.ConnectionURL. This is the JDBC
connection string to the Hive Metastore.
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Driver class uses the value of javax.jdo.option.ConnectionDriverName. This is the
name of the driver for the JDBC connection.
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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.
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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.
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Use a keytab to authenticate
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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.
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Use SSL encryption
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Select this check box to enable the SSL encrypted connection.
Then in the fields that are displayed, provide the authentication information:
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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.
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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:
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Hadoop properties
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Set Jobtracker URI
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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 ):
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Select the Set resourcemanager scheduler
address check box and enter the Scheduler address in the field
that appears.
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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.
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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.
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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.
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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.
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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.
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Set NameNode URI
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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.
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Microsoft HD Insight
properties |
WebHCat configuration
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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.
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HDInsight configuration
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Enter the authentication information of the HD Insight cluster to be used.
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Windows Azure Storage
configuration
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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.
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Schema and Edit
Schema
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A schema is a row description. It defines the number of fields to be processed and passed on
to the next component. The schema is either Built-In or
stored remotely in the Repository.
Click Edit schema to make changes to the schema. If the
current schema is of the Repository type, three options are
available:
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View schema: choose this option to view the
schema only.
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Change to built-in property: choose this option
to change the schema to Built-in for local
changes.
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Update repository connection: choose this option to change
the schema stored in the repository and decide whether to propagate the changes to
all the Jobs upon completion. If you just want to propagate the changes to the
current Job, you can select No upon completion and
choose this schema metadata again in the [Repository
Content] window.
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Built-in: The schema is created
and stored locally for this component only. Related topic: see
Talend Studio User
Guide.
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Repository: The schema already
exists and is stored in the Repository, hence can be reused. Related
topic: see Talend Studio User
Guide.
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Table Name
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Name of the table to be processed.
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Query type
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Either Built-in or Repository.
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Built-in: Fill in manually the
query statement or build it graphically using SQLBuilder
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Repository: Select the relevant
query stored in the Repository. The Query field gets accordingly
filled in.
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Guess Query
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Click the Guess Query button to
generate the query which corresponds to your table schema in the
Query field.
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This query uses Parquet objects
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When available, select this check box to indicate that the table to be handled uses the
Parquet format and thus make the component to call the required jar file.
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.
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When the connection mode to Hive is Embedded,
the Job is run in your local machine and calls this jar installed in the
Studio.
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When the connection mode to Hive is Standalone, the Job is run in the server hosting Hive and this
jar file is sent to the HDFS system of the cluster you are connecting to.
Therefore, ensure that you have properly defined the NameNode URI in the
corresponding field of the Basic settings
view.
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.
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Query
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Enter your DB query paying particularly attention to properly
sequence the fields in order to match the schema definition.
For further information about the Hive query language, see https://cwiki.apache.org/confluence/display/Hive/LanguageManual.
Note
Compressed data in the form of Gzip or Bzip2 can be processed through the query
statements. For details, see https://cwiki.apache.org/confluence/display/Hive/CompressedStorage.
Hadoop provides different compression formats that help reduce the space needed for
storing files and speed up data transfer. When reading a compressed file, the Studio
needs to uncompress it before being able to feed it to the input flow.
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Die on error
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This check box is selected by default. Clear the check box to skip
the row on error and complete the process for error-free rows. If
needed, you can retrieve the rows on error via a Row > Rejects link.
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HBase Configuration
Note
Available only when the Use an existing
connection check box is clear
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Store by HBase
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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.
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Zookeeper quorum
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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.
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Zookeeper client port
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Type in the number of the client listening port of the Zookeeper service you are
using.
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Define the jars to register for
HBase
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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.
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Register jar for HBase
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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).
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Advanced settings
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Temporary path
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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.
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Propagate QUERY’s recordset
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Select this check box to insert the result of the query into a
COLUMN of the current flow. Select this column from the use column list.
Note
This option allows the component to have a different schema
from that of the preceding component. Moreover, the column that
holds the QUERY’s recordset should be set to the type of
Object and this component
is usually followed by tParseRecordSet.
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Hadoop properties
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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:
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Hive properties
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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.
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Mapred job map memory mb and
Mapred job reduce memory
mb
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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.
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Path separator in server
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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.
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tStatCatcher Statistics
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Select this check box to collect log data at the component
level.
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Dynamic settings
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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.
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Global Variables
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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.
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Usage
|
This component offers the benefit of flexible DB queries and
covers all possible Hive QL queries.
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.
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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.
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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.
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