[FEA] JSON reader parses types compatible with Spark

[GaryShen2008]

The current CUDF code parses types how they want to, and not how Spark wants them to be parsed.
We might be able to ask CUDF to read all of the types as Strings and then parse them ourselves.
This will not fix everything because looking at cast there are a number of types
that we do not fully support when casting from a string still.
But it will be a step in the right direction and should let us avoid most of the enable this type for JSON configs.
We could at a minimum reused the cast from string configs that already exist.

This will not work 100% because Spark parses it line by line and then casts it to the desired result.
So with {"a": "100.0"} and {"a": 100.0}. If we asked for a double to be returned,
Spark would parse the first one as a String and then cast it to a double,
but for the second one it would parse it directly as a double and do no casting at the end.
In most cases this should not make a difference, but there can be very subtile differences,
between Sparks casting and what the JSON parser does to read the data.

• [FEA] Improve support for reading JSON boolean types #4763
• [FEA] Improve support for reading JSON integer types #4762
• Improve support for reading CSV and JSON floating-point values #4637
• Initial support for reading decimal types from JSON and CSV #4825
• Improve date support in JSON and CSV readers #4853
• [FEA] Improve timestamp support in JSON and CSV readers #4863
• [FEA] Support reading JSON numeric values as timestamps and dates #4940
• [FEA] Optimize JSON reading of floating-point values #4837
• [FEA] JSON number normalization when returned as a string rapidsai/cudf#15318

[sameerz]

Removing from 22.08 until the cudf dependencies are satisfied.