tWriteAvroFields - 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
Talend Data Services Platform
Talend ESB
Talend MDM Platform
Talend Open Studio for Big Data
Talend Open Studio for Data Integration
Talend Open Studio for Data Quality
Talend Open Studio for ESB
Talend Open Studio for MDM
Talend Real-Time Big Data Platform
task
Data Governance
Data Quality and Preparation
Design and Development
EnrichPlatform
Talend Studio

Warning

The streaming version of this component is available in the Palette of the studio on the condition that you have subscribed to Talend Real-time Big Data Platform or Talend Data Fabric.

Function

tWriteAvroFields transforms the incoming data into Avro files.

Purpose

tWriteAvroFields generates Avro binaries to be used by the components requiring serialized data as input such as tKafkaOutput.

tWriteAvroFields properties in Spark Streaming Jobs

Warning

The streaming version of this component is available in the Palette of the studio on the condition that you have subscribed to Talend Real-time Big Data Platform or Talend Data Fabric.

Component family

Processing/Fields

 

 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.

The schema of this component is read-only. You can click Edit schema to view the schema.

This read-only schema of tWriteAvroFields receives data as an entire object from the schema of its input component without caring about what this input schema should look like and serializes the incoming object into Avro binaries.

That is to say, it does not require the input flow to have the identical schema. For example, an input schema composed of a user column and an age column can be directly serialized. Note that the supported data types by this component are listed in its Basic settings view.

Usage in Spark Streaming Jobs

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

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.

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.

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.

Related scenarios

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