[spark] Make xgboost spark support large model size

[WeichenXu123]

Spark RDD can't support one line with very long content.

To make large size model training / saving / loading works,
I split model json string to chunks when collecting model in training, and modify saving / loading code too.

[wbo4958]

LGTM for the functionality except the CI issue.

[wbo4958]

Could you run python tests/ci_build/lint_python.py --format=1 --type-check=1 --pylint=1 to check the python format

[WeichenXu123]

I can't fully understand the linter error:

xgboost/spark/core.py:1162: error: Incompatible types in assignment (expression has type "str", variable has type "Booster")  [assignment]
xgboost/spark/core.py:1164: error: Argument 1 to "len" has incompatible type "Booster"; expected "Sized"  [arg-type]
Found 2 errors in 1 file (checked 41 source files)

@wbo4958 any ideas ?

[trivialfis]

@WeichenXu123 XGBoost's Python package uses Python typehint. In the following line:

booster = booster.save_raw("json").decode("utf-8")

The booster was a xgboost.Booster object, the decode("utf-8") however, returns a string. Assigning a string to a Booster type violates static typing.

[wbo4958]

LGTM if the CI can pass

[WeichenXu123]

@trivialfis Can we make a patch release to include this fix ? We have several customers facing the issue. thanks!

[trivialfis]

@WeichenXu123 #10992 .