tAvroStreamInput properties for Apache Spark Structured Streaming | Talend Components for Jobs Help
Skip to main content Skip to complementary content

tAvroStreamInput properties for Apache Spark Structured Streaming

Last updated: 9/30/2026

These properties are used to configure tAvroStreamInput running in the Spark Structured Streaming Job framework.

The Spark Structured Streaming tAvroStreamInput component belongs to the File family.

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

Basic settings

Properties Description
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.

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

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.

Property Type

Select the way the file path and the schema will be set.

  • Built-In: The file path and the schema will be set locally for this component.

  • Repository: The file details stored centrally in Repository > Metadata will be reused by this component.

    You need to click the [...] button next to it and in the pop-up Repository Content dialog box, select the file to be reused, and all related properties will be automatically filled in.

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.

Folder Browse to or enter the path to the directory with data to read. If the path points to a folder, the component reads all Avro files in that folder. To read from cloud storage, add the corresponding configuration component to the Job. For example, use tS3Configuration for Amazon S3, tGSConfiguration for Google Cloud Storage, or tAzureFSConfiguration for Azure Data Lake Storage.
Enable watermarking Select this check box to activate watermarking and select the time mode to be used:
  • Event time: Select to use a timestamp column representing when each event occurred, then select the column in the Watermark column (timestamp) drop-down list.
  • Processing time: Select to use the time when Spark reads each record.

In the Watermark delay field, specify how long Spark waits for late data before finalizing each window.

Usage

Usage guidance Description
Usage rule

This component is used as a start component and requires an output link.

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.

Did this page help you?

If you find any issues with this page or its content – a typo, a missing step, or a technical error – please let us know!