tFilterColumns properties for Apache Spark Structured Streaming | Talend Components for Jobs Help
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tFilterColumns properties for Apache Spark Structured Streaming

Last updated: 9/30/2026

Use these properties to configure tFilterColumns running in the Spark Structured Streaming Job framework.

The Spark Structured Streaming tFilterColumns component belongs to the Processing family. tFilterColumns excludes specific columns from a streaming dataset by keeping only the columns defined in the output schema. Any columns present in the input but missing in the output schema are automatically removed.

The streaming version of this component is available in Talend Real-Time Big Data Platform and in Talend Data Fabric.

Basic settings

Properties Description
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.

  • 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.

Click Edit schema to make changes to the schema. If you make changes, the schema automatically becomes built-in.

  • 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.

Usage

Usage guidance Description
Usage rule

This component is used as an intermediate step.

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

Spark Connection

You need to use the Structured Streaming Configuration tab in the Run view to define the connection to a Spark cluster for the whole Job.

This connection is effective on a per-Job basis.

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