# tMapRDBOutput MapReduce properties (deprecated) Availability-note[Deprecated](https://help.talend.com/r/en-US/Cloud/labels-on-talend-help-center/availability-deprecated) This content is deprecated. These properties are used to configure tMapRDBOutput running in the MapReduce Job framework. The MapReduce tMapRDBOutput component belongs to the MapReduce and the Databases families. The component in this framework is available in all Talend products with Big Data and Talend Data Fabric. Availability-note[Deprecated](https://help.talend.com/r/en-US/Cloud/labels-on-talend-help-center/availability-deprecated) This content is deprecated. The MapReduce framework is deprecated from Talend 7.3 onwards. Use Talend Jobs for Apache Spark to accomplish your integration tasks. ## Basic settings | Property type | Either Built-In or Repository.

Built-In: No property data stored centrally.

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

The properties are stored centrally under the Hadoop
Cluster node of the Repository
tree. | | --- | --- | | Distribution and
Version | Select the MapR distribution to be used. Only MapR V5.2 onwards is supported
by the MapRDB components.

If the distribution you need to use with your MapRDB database is not
officially supported by this MapRBD component, that is to say, this distribution is MapR
but is not listed in the Version drop-down list of
this components or this distribution is not MapR at all, select Custom.

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 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.

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.

Information noteNote:
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.

| | 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. | | Use kerberos authentication | If the database to be used is running with Kerberos security, select this
check box, then, enter the principal names in the displayed fields. You should be
able to find the information in the *hbase-site.xml* file of the
cluster to be used.

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.

If you need to use a Kerberos keytab file to log in, select Use a keytab to authenticate. 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 username 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. | | Schema et Edit
schema | A schema is a row description. It defines the number of fields
(columns) to be processed and passed on to the next component. When you create a Spark
Job, avoid the reserved word line when naming the
fields.

Click Edit
schema to make changes to the schema. If the current schema is of the Repository type, three options are available:

View schema: choose this option to view the schema only.
Change to built-in property: choose this option to change the schema to Built-in for local changes.
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.

| | | Built-In: You create and store the schema locally for this component
only. | | | Repository: You have already created the schema and stored it in the
Repository. You can reuse it in various projects and Job designs. | | Table name | Type in the name of the table in which you need to write data. This table must already
exist. | | Table Namespace mappings | Enter the string to be used to construct the mapping between an Apache HBase table and a
MapR table.

For the valid syntax you can use, see http://doc.mapr.com/display/MapR40x/Mapping+Table+Namespace+Between+Apache+HBase+Tables+and+MapR+Tables. | | Row key column | Select the column used as the row key column of the table.

Then if needs be, select the Store row key column to HBase
column check box to make the row key column a column
belonging to a specific column family. | | Families | Complete this table to map the columns of the table to be used with the schema columns you
have defined for the data flow to be processed.

The Column column of this table is automatically filled
once you have defined the schema; in the Family name
column, enter the column families you want to create or use to group the columns in the
Column column. For further information about a column
family, see Apache documentation at [Column families](http://hbase.apache.org/0.94/book/columnfamily.html). | ## Advanced settings | Properties | If you need to use custom configuration for your database, complete this table with the
property or properties to be customized. Then at runtime, the customized property or
properties will override the corresponding ones used by the Studio.

For example, you need to define the value of the *dfs.replication* property as *1* for the
database configuration. Then you need to add one row to this table using the plus button and
type in the name and the value of this property in this row. | | --- | --- | ## 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** | In a
Talend
Map/Reduce Job, it is used as an end component and requires
a transformation component as input link. The other components used along with it must be
Map/Reduce components, too. They generate native Map/Reduce code that can be executed
directly in Hadoop.

The Hadoop configuration you use for the whole Job and the Hadoop distribution you use for
this component must be the same. Actually, this component requires that its Hadoop
distribution parameter be defined separately so as to launch its database driver only when
that component is used. | | --- | --- | | Hadoop Connection | You need to use the Hadoop Configuration tab in the
Run view to define the connection to a given Hadoop
distribution for the whole Job.

This connection is effective on a per-Job basis. | | Prerequisites | Before starting, ensure that you have met the Loopback IP prerequisites expected by your
database.

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\ hadoop\hadoop-VERSION\lib\native. For example, the library for Windows is \lib\native\MapRClient.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. |