[ML] Instrumenting C++ Data Frame Analytics

[valeriy42]

We want to provide users with rich information using _stats API. To this end, we need to instrument C++ code to return additional information to the Java backend as new result types.

There are several kinds of instrumentation data we require:

• peak memory usage
• job runtime parameters/hyperparameters
• intermediate quality of results (e.g. for the current iteration)
• intermediate computation time (e.g. for the current iteration)

The kind of returned information and the schema for the return type may vary depending on the ML job type.

Sub-Tasks

• Define json schemas for the return types
• Update memory usage output to conform with the new schema