Anywhere you can import pyspark, import, or require(SparkR), you can now run Spark jobs directly from your application, without needing to install any IDE plugins or use Spark submission scripts. Run large-scale Spark jobs from any Python, Java, Scala, or R application. Then, the logical representation of the job is sent to the Spark server running in Databricks for execution in the cluster. It allows you to write jobs using Spark APIs and run them remotely on a Databricks cluster instead of in the local Spark session.įor example, when you run the DataFrame command ("parquet").load(.).groupBy(.).agg(.).show() using Databricks Connect, the parsing and planning of the job runs on your local machine. Tutorial: Databricks Terraform Providerĭatabricks Connect is a client library for Databricks Runtime.
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