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Limitations with Databricks Connect for Scala

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Note

This article covers Databricks Connect for Databricks Runtime 13.3 LTS and above.

This article lists limitations with Databricks Connect for Scala. Databricks Connect enables you to connect popular IDEs, notebook servers, and custom applications to Azure Databricks clusters. See What is Databricks Connect?. For the Python version of this article, see Limitations with Databricks Connect for Python.

Not available on Databricks Connect for Databricks Runtime 13.3 LTS and below:

  • Streaming foreachBatch
  • Creating DataFrames larger than 128 MB
  • Long queries over 3600 seconds
  • Scalar UDFs on clusters that use Single user cluster access mode

Not available:

  • Databricks Utilities: credentials, library, notebook workflow, widgets
  • SparkContext
  • RDDs
  • MLflow model inference: pyfunc.spark_udf() API
  • Mosaic geospatial
  • CREATE TABLE <table-name> AS SELECT (instead, use spark.sql("SELECT ...").write.saveAsTable("table"))
  • Changing the log4j log level through SparkContext
  • Distributed ML training
  • Synchronizing the local development environment with the remote cluster