tReservoirSampling properties for Apache Spark Batch

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 Sync columns to retrieve the schema from the previous component in the Job.

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.

Sample Size

Set how many rows to sample from the input flow.

Seed for random generator

Set a random number if you want to extract the same sample in different executions of the Job.

Repeating the execution with a different value for the seed will result in a different data samples being extracted.

Keep this field empty if you want to extract a different data sample each time you execute the Job.

Usage rule

This component is used as an intermediate step.

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

This connection is effective on a per-Job basis.