Run large-scale Spark jobs from any Python, R, Scala, or Java application.It allows you to write jobs using Spark APIs and run them remotely on an Azure Databricks cluster instead of in the local Spark session.įor example, when you run the DataFrame command (.).load(.).groupBy(.).agg(.).show() using Databricks Connect, the logical representation of the command is sent to the Spark server running in Azure Databricks for execution on the remote cluster. Overviewĭatabricks Connect is a client library for the Databricks Runtime. This article explains how Databricks Connect works, walks you through the steps to get started with Databricks Connect, explains how to troubleshoot issues that may arise when using Databricks Connect, and differences between running using Databricks Connect versus running in an Azure Databricks notebook. Databricks Connect recommends that you use Databricks Connect for Databricks Runtime 13.0 and above instead.ĭatabricks plans no new feature work for Databricks Connect for Databricks Runtime 12.2 LTS and below.ĭatabricks Connect allows you to connect popular IDEs such as Visual Studio Code and P圜harm, notebook servers, and other custom applications to Azure Databricks clusters.
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