tMapRDBInput MapReduce properties (deprecated)

These properties are used to configure tMapRDBInput running in the MapReduce Job framework.

The MapReduce tMapRDBInput 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.

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.
	Click this icon to open a database connection wizard and store the database connection parameters you set in the component Basic settings view. For more information about setting up and storing database connection parameters, see Talend Studio User Guide.
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 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.
Table name	Type in the name of the table from which you need to extract columns.
Mapping	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.
Die on error	Select the check box to stop the execution of the Job when an error occurs. Clear the check box to skip any rows on error and complete the process for error-free rows. When errors are skipped, you can collect the rows on error using a Row > Reject link.

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.
Is by filter	Select this check box to use filters to perform fine-grained data selection from your database, such as selection of keys, or values, based on regular expressions. Once selecting it, the Filter table that is used to define filtering conditions becomes available. This feature leverages filters provided by HBase and subject to constraints explained in Apache HBase documentation. Therefore, advanced knowledge of HBase is required to make full use of these filters.
Logical operation	Select the operator you need to use to define the logical relation between filters. This available operators are: And: every defined filtering conditions must be satisfied. It represents the relationship FilterList.Operator.MUST_PASS_ALL Or: at least one of the defined filtering conditions must be satisfied. It represents the relationship: FilterList.Operator.MUST_PASS_ONE
Filter	Click the button under this table to add as many rows as required, each row representing a filter. The parameters you may need to set for a filter are: Filter type: the drop-down list presents pre-existing filter types that are already defined by HBase. Select the type of the filter you need to use. Filter column: enter the column qualifier on which you need to apply the active filter. This parameter becomes mandatory depending on the type of the filter and of the comparator you are using. For example, it is not used by the Row Filter type but is required by the Single Column Value Filter type. Filter family: enter the column family on which you need to apply the active filter. This parameter becomes mandatory depending on the type of the filter and of the comparator you are using. For example, it is not used by the Row Filter type but is required by the Single Column Value Filter type. Filter operation: select from the drop-down list the operation to be used for the active filter. Filter Value: enter the value on which you want to use the operator selected from the Filter operation drop-down list. Filter comparator type: select the type of the comparator to be combined with the filter you are using. Depending on the Filter type you are using, some or each of the parameters become mandatory. For further information, see HBase filters

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.

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 a start component and requires a transformation component as output 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. 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. 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.
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.
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.

Usage rule

In a Talend Map/Reduce Job, it is used as a start component and requires a transformation component as output 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.

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.

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.

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.

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.

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