tKafkaOutput - 6.1

Talend Components Reference Guide

EnrichVersion
6.1
EnrichProdName
Talend Big Data
Talend Big Data Platform
Talend Data Fabric
Talend Data Integration
Talend Data Management Platform
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Talend ESB
Talend MDM Platform
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Talend Real-Time Big Data Platform
task
Data Governance
Data Quality and Preparation
Design and Development
EnrichPlatform
Talend Studio

Function

This component receives messages serialized into byte arrays by its preceding component and issues these messages into a given Kafka system.

Purpose

The tKafkaOutput component publishes messages into a Kafka system.

If you have subscribed to one of the Talend solutions with Big Data, this component is available in the following types of Jobs:

tKafkaOutput properties

Component family

Internet/Kafka

 

Basic settings

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. The schema is either Built-In or stored remotely in the Repository.

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 in the Component List click the relevant connection component to reuse the connection details you already defined.

 

Version

Select the version of the Kafka cluster to be used.

 

Broker list

Enter the addresses of the broker nodes of the Kafka cluster to be used.

The form of this address should be hostname:port. This information is the name and the port of the hosting node in this Kafka cluster.

If you need to specify several addresses, separate them using a comma (,).

 Topic name

Enter the name of the topic you want to publish messages to. This topic must already exist.

 

Compress the data

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

Advanced settings

Kafka properties

Add the Kafka new producer properties you need to customize to this table.

For further information about the new producer properties you can define in this table, see the section describing the new producer configuration in Kafka's documentation in http://kafka.apache.org/documentation.html#newproducerconfigs.

 

tStatCatcher Statistics

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

Usage

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:

output_row.serializedValue = input_row.users.getBytes();

In this code, the output_row variable represents the schema of the data to be output to tKafkaOutput 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.

Related scenarios

No scenario is available for this component yet.

tKafkaOutput properties in Spark Streaming Jobs

Component family

Messaging/Kafka

 

Basic settings

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. The schema is either Built-In or stored remotely in the Repository.

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

 

Broker list

Enter the addresses of the broker nodes of the Kafka cluster to be used.

The form of this address should be hostname:port. This information is the name and the port of the hosting node in this Kafka cluster.

If you need to specify several addresses, separate them using a comma (,).

 Topic name

Enter the name of the topic you want to publish messages to. This topic must already exist.

 

Compress the data

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

Advanced settings

Kafka properties

Add the Kafka new producer properties you need to customize to this table.

For further information about the new producer properties you can define in this table, see the section describing the new producer configuration in Kafka's documentation in http://kafka.apache.org/documentation.html#newproducerconfigs.

 

Connection pool

In this area, you configure the connection pool used to control the number of connections that stay open simultaneously. Generally speaking, 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) allowed in the connection pool.

  • Max number of idle connections: enter the maximum number of idle connections (connections not used) allowed 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 in Spark Streaming Jobs

In a Talend Spark Streaming Job, it is used as an end component and requires an input link. The other components used along with it must be Spark Streaming components, too. They generate native Spark code that can be executed directly in a Spark cluster.

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

This component, along with the Spark Streaming component Palette it belongs to, appears only when you are creating a Spark Streaming Job.

Note that in this documentation, unless otherwise explicitly stated, a scenario presents only Standard Jobs, that is to say traditional Talend data integration Jobs.

Log4j

If you are using a subscription-based version of the Studio, 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.

Spark Connection

You need to use the Spark Configuration tab in the Run view to define the connection to a given Spark cluster for the whole Job. In addition, since the Job expects its dependent jar files for execution, one and only one file system related component from the Storage family is required in the same Job so that Spark can use this component to connect to the file system to which the jar files dependent on the Job are transferred:

This connection is effective on a per-Job basis.

Related scenarios

No scenario is available for the Spark Streaming version of this component yet.