tWriteXMLFields - 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
EnrichPlatform
Talend Studio
task
Data Governance
Data Quality and Preparation
Design and Development

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

tWriteXMLFields embeds the incoming data into a single XML column.

Purpose

tWriteXMLFields generates strings or byte arrays to be used by the output components, such as tKafkaOutput requiring serialized data while tJMSOutput requiring strings.

tWriteXMLFields 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

Output type

Select the type of the data to be outputted into the target file. The data is byte arrays if you select byte[].

 

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.

When the output type is String, the read-only single column is messageContent. This column is used to provide strings to the output components such as tJMSOutput.

When the output type is byte[], the read-only single column is serializedValue. This column is used to provide byte arrays to the output components such as tKafkaOutput.

The output schema and its read-only column can be seen by clicking the Row > Output link to the component that follows in the same Job. The schema is displayed in the Basic settings tab of the Component view

 

Row tag

Specify the tag that will wrap data and structure per row.

 

Custom encoding

You may encounter encoding issues when you process the stored data. In that situation, select this check box to display the Encoding list.

Select the encoding from the list or select Custom and define it manually. This field is compulsory for database data handling.

Advanced settings

Root tags

Select this check box to change the separator used for numbers. By default, the thousands separator is a comma (,) and the decimal separator is a period (.).

 Output format

Define the output format.

  • Column: The columns retrieved from the input schema.

  • As attribute: select check box for the column(s) you want to use as attribute(s) of the parent element in the XML output.

Note

If the same column is selected in both the Output format table as an attribute and in the Use dynamic grouping setting as the criterion for dynamic grouping, only the dynamic group setting will take effect for that column.

Use schema column name: By default, this check box is selected for all columns so that the column labels from the input schema are used as data wrapping tags. If you want to use a different tag than from the input schema for any column, clear this check box for that column and specify a tag label between quotation marks in the Label field.

 

Use dynamic grouping

Select this check box if you want to dynamically group the output columns. Click the plus button to add one ore more grouping criteria in the Group by table.

Column: Select a column you want to use as a wrapping element for the grouped output rows.

Attribute label: Enter an attribute label for the group wrapping element, between quotation marks.

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.