Bulk Operation

SPARK-42471 Add vector assembler feature transformer

SPARK-42471 Add doc entry for `pyspark.ml.connect` module

SPARK-42471 Avoid Spark connect ML model to change input pandas dataframe

SPARK-42471 Add pyspark "ml-connect" extras dependencies

SPARK-42471 Add example code

SPARK-42471 Implement classification evaluator

SPARK-42471 Move namespace from `pyspark.mlv2` to `pyspark.ml.connect`

SPARK-42471 Implement cross validator estimator

SPARK-42471 Implement pipeline estimator

SPARK-42471 Basic saving / loading implementation

SPARK-42471 Add API `copyLocalFileToHadoopFS`

SPARK-42471 Add spark DataFrame binary file format writer

SPARK-42471 Basic estimator / transformer / model / evaluator interfaces and basic transformer / evaluator implementation

SPARK-42471 Implement pyspark ML logistic regression estimator on top of torch distributor

SPARK-42471 Add torch distributor data loader that loads data from spark partition data

SPARK-42471 Torch Distributor support Local Mode

SPARK-42471 Make Torch Distributor compatible with Spark Connect

SPARK-42471 Move `toCatalystValue` to connect-common

SPARK-42471 Implement ml function {array_to_vector, vector_to_array}

SPARK-42471 Helper function to convert proto literal to value in Python Client

SPARK-42471 Factor literal value conversion out to connect-common

SPARK-42471 Make LiteralExpression support array

SPARK-42471 Extract the common .ml classes to `mllib-common`

SPARK-42471 High level design doc for Distributed ML <> spark connect

SPARK-42471 Make spark connect supporting canceling job group

SPARK-42471 Initial prototype implementation for PySparkML