Schema and 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.

Note that the schema of this component is read-only. It stores the
messages to be published.

Use an existing connection

Select this check box and from the list displayed select the
relevant connection component to reuse the connection details you have already defined.

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.

1. 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.

2. 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.

   In
   Talend
   
   Exchange, members of
   Talend
   community have shared some ready-for-use configuration zip files
   which you can download from this Hadoop configuration
   list and directly use them in your connection accordingly. However, because of
   the ongoing evolution of the different Hadoop-related projects, you might not be
   able to find the configuration zip corresponding to your distribution from this
   list; then it is recommended to use the Import from
   existing version option to take an existing distribution as base
   to add the jars required by your distribution.

   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.

   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 a step-by-step example about how to connect to a custom
   distribution and share this connection, see Hortonworks.

Enter the name of the topic you want to publish messages to. This topic must already
exist. You must enter the name of the stream to which this topic belongs. The syntax is
path_to_the_stream:topic_name.

Compress the data

Select the Compress the data check box to compress the
output data.

Producer properties

Add the MapR Streams producer properties you need to customize to this table.

For further information about the producer configuration you can define in this table, see
the section describing the important producer configuration properties for MapR Streams in
MapR documentation at MapR Streams Overview.

tStatCatcher Statistics

Select this check box to gather the processing metadata at the Job
level as well as at each 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 rule

This component is an end component. It requires a tJavaRow or tJava component to transform the incoming data into
serialized byte arrays.

The following sample shows how to construct a statement to perform
this transformation:

In this code, the output_row
variable represents the schema of the data to be output to tMapRStreamsOutput and output_row.serializedValue the single read-only column of
that schema; the input_row variable
represents the schema of the incoming data and input_row.users the input column called users to be transformed to byte arrays by the
getBytes() method.

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 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.

Schema and 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.

Note that the schema of this component is read-only. It stores the
messages to be published.

Enter the name of the topic you want to publish messages to. This topic must already
exist. You must enter the name of the stream to which this topic belongs. The syntax is
path_to_the_stream:topic_name.

Compress the data

Select the Compress the data check box to compress the
output data.

Producer properties

Add the MapR Streams producer properties you need to customize to this table.

For further information about the producer configuration you can define in this table, see
the section describing the important producer configuration properties for MapR Streams in
MapR documentation at MapR Streams Overview.

Connection pool

In this area, you configure, for each Spark executor, the connection pool used to control
the number of connections that stay open simultaneously. The default values given to the
following connection pool parameters are good enough for most use cases.

• Max total number of connections: enter the maximum number
  of connections (idle or active) that are allowed to stay open simultaneously.

  The default number is 8. If you enter -1, you allow unlimited number of open connections at the same
  time.

• Max waiting time (ms): enter the maximum amount of time
  at the end of which the response to a demand for using a connection should be returned by
  the connection pool. By default, it is -1, that is to say, infinite.

• Min number of idle connections: enter the minimum number
  of idle connections (connections not used) maintained in the connection pool.

• Max number of idle connections: enter the maximum number
  of idle connections (connections not used) maintained in the connection pool.

Evict connections

Select this check box to define criteria to destroy connections in the connection pool. The
following fields are displayed once you have selected it.

• Time between two eviction runs: enter the time interval
  (in milliseconds) at the end of which the component checks the status of the connections and
  destroys the idle ones.

• Min idle time for a connection to be eligible to
  eviction: enter the time interval (in milliseconds) at the end of which the idle
  connections are destroyed.

• Soft min idle time for a connection to be eligible to
  eviction: this parameter works the same way as Min idle
  time for a connection to be eligible to eviction but it keeps the minimum number
  of idle connections, the number you define in the Min number of idle
  connections field.

Usage rule

This component is used as an end component and requires an input link.

This component needs a Write component such as tWriteJSONField to define a serializedValue column in the input schema to send serialized data.

Spark Connection

This connection is effective on a per-Job basis.

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 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.