tReplace properties for Apache Spark Streaming

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.

Simple Mode Search / Replace

Click the button to add as many conditions as needed. The conditions are performed one after the other for each row.

Input column: Select the column of the schema the search & replace is to be operated on

Search: Type in the value to search in the input column

Replace with: Type in the substitution value.

Whole word: Select this check box if the searched value is to be considered as whole.

Case sensitive: Select this check box to care about the case.

Note that you cannot use regular expression in these columns.

Advanced mode

Select this check box when the operation you want to perform cannot be carried out through the simple mode. In the text field, type in the regular expression as required.

Usage rule

This component is used as an intermediate step.

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

This connection is effective on a per-Job basis.