Support nested types as groupby keys in libcudf

[PointKernel]

Related to #8039

This PR replaces old row operators in list groupby with new ones thus nested types like lists and structs can be used as groupby keys in libcudf. It partially fixes the issue and comprehensive python refactoring requires non-trivial future work. It is a breaking change since libcudf will no longer throw an error when nulls are excluded and groupby keys are of nested types. Comprehensive tests for complex nested types like structs of lists of lists of structs depend on #11222.

Closes #10181

Description

Checklist

• I am familiar with the Contributing Guidelines.
• New or existing tests cover these changes.
• The documentation is up to date with these changes.

[codecov]

Codecov Report

Base: 87.47% // Head: 88.10% // Increases project coverage by +0.62% 🎉

Coverage data is based on head (270593f) compared to base (f817d96).
Patch has no changes to coverable lines.

❗ Current head 270593f differs from pull request most recent head d94e452. Consider uploading reports for the commit d94e452 to get more accurate results

Additional details and impacted files

@@               Coverage Diff                @@
##           branch-22.12   #11792      +/-   ##
================================================
+ Coverage         87.47%   88.10%   +0.62%     
================================================
  Files               133      135       +2     
  Lines             21826    22133     +307     
================================================
+ Hits              19093    19500     +407     
+ Misses             2733     2633     -100     

Impacted Files	Coverage Δ
python/cudf/cudf/core/column/interval.py	85.45% <0.00%> (-9.10%)	⬇️
python/cudf/cudf/io/text.py	91.66% <0.00%> (-8.34%)	⬇️
python/strings_udf/strings_udf/__init__.py	76.47% <0.00%> (-7.85%)	⬇️
python/cudf/cudf/core/_base_index.py	81.28% <0.00%> (-4.27%)	⬇️
python/cudf/cudf/io/json.py	92.06% <0.00%> (-2.68%)	⬇️
python/cudf/cudf/utils/utils.py	89.91% <0.00%> (-0.69%)	⬇️
python/cudf/cudf/core/column/timedelta.py	90.17% <0.00%> (-0.58%)	⬇️
python/cudf/cudf/core/column/datetime.py	89.21% <0.00%> (-0.51%)	⬇️
python/cudf/cudf/core/column/column.py	87.96% <0.00%> (-0.46%)	⬇️
python/dask_cudf/dask_cudf/core.py	73.72% <0.00%> (-0.41%)	⬇️
... and 43 more

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[shwina]

@PointKernel as we saw yesterday, when attempting to do a groupby-agg with a list column as keys, we see the following error:

RuntimeError: cuDF failure at: cudf/cpp/src/groupby/hash/groupby.cu:661: Null keys of nested type cannot be excluded.

This is because the default option in Python is dropna=True which asks libcudf to exclude null keys. Now, should the above error be raised in libcudf only when there are actually nulls in the list column, or should it be the caller's (i.e., Cython's) responsibility to check for nulls before passing the exclude policy to libcudf?

[PointKernel]

@PointKernel as we saw yesterday, when attempting to do a groupby-agg with a list column as keys, we see the following error:

RuntimeError: cuDF failure at: cudf/cpp/src/groupby/hash/groupby.cu:661: Null keys of nested type cannot be excluded.

This is because the default option in Python is dropna=True which asks libcudf to exclude null keys. Now, should the above error be raised in libcudf only when there are actually nulls in the list column, or should it be the caller's (i.e., Cython's) responsibility to check for nulls before passing the exclude policy to libcudf?

IIRC, The error message was added to align with Spark's behavior thus we don't have to throw the error in libcudf. I will just remove it and see if anyone complains.

[vyasr]

I would like to see my comment regarding ordering of outputs in the test addressed. However, given the tight time constraints (code freeze starts tomorrow) I don't want to block this PR on that. If you have time to make that change in this PR that's great, but if not please file it away for future work. Thanks!

[PointKernel]

@gpucibot merge