RumbleDB 1.14.0 "Acacia" beta

• Rumble now outputs error messages displaying the faulty line of code and pointing to the place of error.
• Machine Learning estimators and models can now run at scale (in parallel) on very large amounts of data. This is automatically detected.
• Many stability improvements in the Machine Learning library
• Machine Learning Pipelines are now supported with stages given as function items
• Static typing is now always done and used to optimize even more
• Initial (experimental) support for user-defined types with the JSound Compact syntax. Types can be used everywhere builtin types can be used (instance of, treat as, type annotations for variables...).
• New validate type expression to validate against user-defined types and (if the type is DF-compatible) to create object* instances as optimized dataframes.
• Features must be assembled with the VectorAssembler transformer prior to being used with an estimator or transformer (for example, at the start of a pipeline). featuresCol and InputCol must specify the name (as a string) of the assembled feature vector field. This is now fully consistent with the Spark ML framework.

Note that Spark 2.4.x is no longer maintained. We provide rumbledb-1.14.0-for-spark-2.jar only for legacy purposes for a smooth transition, and recommend instead using Spark 3.0.x or 3.1.x with the rumbledb-1.14.0.jar package.