PERF: Indexing with pyarrow timestamp & duration dtypes

[lukemanley]

• Tests added and passed if fixing a bug or adding a new feature
• All code checks passed.
• Added type annotations to new arguments/methods/functions.
• Added an entry in the latest doc/source/whatsnew/v2.1.0.rst file if fixing a bug or adding a new feature.

pyarrow timestamps:

import pandas as pd

N = 100_000

idx = pd.Index(range(N), dtype="timestamp[s][pyarrow]")
idx2 = idx[::2]

%timeit idx.get_indexer_for(idx2)

# 264 ms ± 13 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)      -> main
# 1.1 ms ± 168 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)  -> PR

pyarrow durations:

import pandas as pd

N = 100_000

idx = pd.Index(range(N), dtype="duration[s][pyarrow]")
idx2 = idx[::2]

%timeit idx.get_indexer_for(idx2)

# 705 ms ± 21.5 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)        -> main
# 1.35 ms ± 83.9 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)  -> PR

[phofl]

lgtm

[mroeschke]

Thanks @lukemanley