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tS3Input MapReduce properties (deprecated)

Availability-noteDeprecated

These properties are used to configure tS3Input running in the MapReduce Job framework.

The MapReduce tS3Input component belongs to the MapReduce family.

The information in this section is only for users who have subscribed to Talend Data Fabric or to any Talend product with Big Data.

Availability-noteDeprecated
The MapReduce framework is deprecated from Talend 7.3 onwards. Use Talend Jobs for Apache Spark to accomplish your integration tasks.

Basic settings

Property type

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.

 

Built-In: You create and store the schema locally for this component only.

 

Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs.

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.

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.

 

Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs.

Bucket and Folder

Enter the bucket name and its folder you need to use. You need to separate the bucket name and the folder name using a slash (/).

Access key and Secret key

Enter the authentication information required to connect to the Amazon S3 bucket to be used.

To enter the password, click the [...] button next to the password field, and then in the pop-up dialog box enter the password between double quotes and click OK to save the settings.

Type

Select the type of the file to be processed. The type of the file may be:
  • Text file.

  • Sequence file: a Hadoop sequence file consists of binary key/value pairs and is suitable for the Map/Reduce framework. For further information, see http://wiki.apache.org/hadoop/SequenceFile.

    Once you select the Sequence file format, the Key column list and the Value column list appear to allow you to select the keys and the values of that Sequence file to be processed.

Row separator

The separator used to identify the end of a row.

Field separator

Enter a character, a string, or a regular expression to separate fields for the transferred data.

Header

Enter the number of rows to be skipped in the beginning of file.

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. The supported encodings depend on the JVM that you are using. For more information, see https://docs.oracle.com.

This option is not available for a Sequence file.

Advanced settings

Advanced separator (for number)

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 (.).

This option is not available for a Sequence file.

Trim all column

Select this check box to remove the leading and trailing whitespaces from all columns. When this check box is cleared, the Check column to trim table is displayed, which lets you select particular columns to trim.

This option is not available for a Sequence file.

Check column to trim

This table is filled automatically with the schema being used. Select the check box(es) corresponding to the column(s) to be trimmed.

This option is not available for a Sequence file.

Enable parallel execution

Select this check box to perform high-speed data processing, by treating multiple data flows simultaneously. Note that this feature depends on the database or the application ability to handle multiple inserts in parallel as well as the number of CPU affected. In the Number of parallel executions field, either:
  • Enter the number of parallel executions desired.
  • Press Ctrl + Space and select the appropriate context variable from the list. For further information, see Talend Studio User Guide.

Global Variables

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

Usage rule

In a Talend Map/Reduce Job, it is used as a start component and requires a transformation component as output link. The other components used along with it must be Map/Reduce components, too. They generate native Map/Reduce code that can be executed directly in Hadoop.

Once a Map/Reduce Job is opened in the workspace, tS3Input as well as the MapReduce family appears in the Palette of the Studio.

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

Hadoop Connection

You need to use the Hadoop Configuration tab in the Run view to define the connection to a given Hadoop distribution for the whole Job.

This connection is effective on a per-Job basis.

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