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Tonic Structural User Guide
About Tonic Structural
Logging into Structural for the first time
Getting started with the Structural free trial
Managing your user account
Frequently Asked Questions
Tutorial videos
Creating and managing workspaces
Configuring data generation
Running data generation
Installing and Administering Structural
Connecting to your data
Using the Structural API

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Connecting to your data

Spark SDK

Last updated 5 months ago

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In addition to its native integration with Databricks and Amazon EMR, Tonic Structural also supports Spark through an SDK.

The Spark SDK allows you to incorporate Structural directly into existing Spark programs and workflows.

The Structural Spark SDK is written in Java. It can be used in existing Java, PySpark, and Scala Spark programs.

Structural process for Spark SDK

How Structural data generation works with the Spark SDK.

Structural differences and limitations

Features that are unavailable or work differently in Spark SDK workspaces.

Configure workspace data connections

Data connection settings for Spark SDK workspaces.

Run data generation from Spark

Use the Structural SDK to run data generation on Spark SDK workspaces.