tLogRow properties in Spark Batch Jobs - 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

Component family

Misc

 

Basic settings

Define a storage configuration component

Select the configuration component to be used to provide the configuration information for the connection to the target file system such as HDFS or S3.

If you leave this check box clear, the target file system is the local system.

Note that the configuration component to be used must be present in the same Job. For example, if you have dropped a tHDFSConfiguration component in the Job, you can select it to write the result in a given HDFS system.

 

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.

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. Related topic: see Talend Studio User Guide.

  

Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. Related topic: see Talend Studio User Guide.

  Sync columns Click to synchronize the output file schema with the input file schema. The Sync function is available only when the component is linked with the preceding component using a Row connection.
  Basic Displays the output flow in basic mode.
  Table Displays the output flow in table cells.
  Vertical

Displays each row of the output flow as a key-value list.

With this mode selected, you can choose to show either the unique name or the label of component, or both of them, for each output row.

 

Separator

(For Basic mode only)

Enter the separator which will delimit data on the Log display.

 

Print header

(For Basic mode only)

Select this check box to include the header of the input flow in the output display.

 

Print component unique name in front of each output row

(For Basic mode only)

Select this check box to show the unique name the component in front of each output row to differentiate outputs in case several tLogRow components are used.

 

Print schema column name in front of each value

(For Basic mode only)

Select this check box to retrieve column labels from output schema.

 

Use fixed length for values

(For Basic mode only)

Select this check box to set a fixed width for the value display.

Usage in Spark Batch Jobs

In a Talend Spark Batch Job, this component is used as an intermediate or an end step. It generates native Spark code that can be executed directly in a Spark cluster.

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