tDataShuffling 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 connected in the Job.

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.

Shuffling columns

Define the groups of columns to be shuffled:

• Column: Select the columns to be shuffled.

• Group ID: Select the group identifier to group columns. The columns having the same group identifier are shuffled together.

  This field is set to 0 by default. This means that the column is not part of the shuffling process.

Seed for random generator

Set a random number if you want to shuffle the data in the same order in each execution of the Job. The seed is not set by default.

If you do not set the seed, the component creates a new random seed for each Job execution. Repeating the execution with a different value for this field will shuffle the data in a different order.

Partitioning columns

Add the columns used for partitioning the data.

The selected columns separate the shuffling process into small partitions. Only the rows within a partition can be shuffled together.

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.