Add strings 'like' function

[davidwendt]

Description

Adds new strings like function to cudf. This is a wildcard-based string matching function based on SQL's LIKE statement.
https://www.sqltutorial.org/sql-like/
Though some SQL implementations provide regex-like capabilities in the like statement pattern, the implementation here is strictly limited to the % (multi-character placeholder) and the _ (single character placeholder) behavior. It also accepts an optional escape character that can be used when trying to match strings that contain % or _ in them.

This is an easier (and faster) alternative to using the regex based contains function.
Example usage:

s = cudf.Series(["David", "Daniel", "Darcy"])
s.str.like('Da%')   ==> [True, True, True]    # starts with 'Da'
s.str.like('_a_i%') ==> [True, True, False]   # 2nd character is 'a' and 4th character is 'i'
s.str.like('_____') ==> [True, False, True]   # match any 5 characters
s.str.like('%y')    ==> [False, False, True]  # ends with 'y'

This PR includes gtests, pytest, and an nvbench-mark.

Reference #10797

Checklist

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

[davidwendt]

This was benchmarked against cudf::strings::contains_re with equivalent patterns over the same dataset. The benchmark was setup to so both functions required reading the entire matching string to resolve to true. This provided the fairest comparison between implementations. The results are pictured here varying 4K to 16M rows with 1-100% hit-rates (matches).

The speedup is an x-factor which ranged between 2x to ~12x.
These were compared by temporarily implementing contains_re with nvbench. A follow-on PR will migrate and consolidate the contains gbenchmarks with the new like nvbench-mark.

[codecov]

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[bdice]

Looks great. I have a couple small issues with naming, otherwise approved.

[bdice]

Thanks @davidwendt!

[bdice]

@gpucibot merge