perf: Improve unique performance by adding RangedUniqueKernel for primitive arrays

[coastalwhite]

This PR adds a unique value kernel that is selected based on the metadata for PrimitiveArray. When the difference between the metadata min and max value is small enough a different kernel is used that does not require sorting the data first.

This is mostly to show how the new metadata can be used to select a different kernel.

For a microbenchmark on release mode, we see the following results:

import polars as pl
import numpy as np
from timeit import timeit

xs = list(np.random.randint(5, 100, size = 500000))
df = pl.DataFrame({ "x": xs, }, schema = { "x": pl.Int32 })

def rand_unique():
    df.select(pl.col.x.unique())

t = timeit(rand_unique, number = 10000)
print(f'Before Time = {t}')
df.select(xmin = pl.col.x.min(), xmax = pl.col.x.max())
t = timeit(rand_unique, number = 10000)
print(f'After Time = {t}')

Before Time = 22.795969667999998
After Time = 4.657802337999783

This is a ~4.9x improvement. I feel like this can also be further improved if needed.

[codecov]

Codecov Report

Attention: Patch coverage is 34.52915% with 146 lines in your changes missing coverage. Please review.

Project coverage is 80.78%. Comparing base (4731834) to head (54e83dc).
Report is 5 commits behind head on main.

Files	Patch %	Lines
crates/polars-compute/src/unique/primitive.rs	0.00%	112 Missing ⚠️
...es/polars-core/src/chunked_array/ops/unique/mod.rs	40.00%	21 Missing ⚠️
crates/polars-compute/src/unique/boolean.rs	82.66%	13 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main   #17166      +/-   ##
==========================================
- Coverage   80.94%   80.78%   -0.16%     
==========================================
  Files        1464     1465       +1     
  Lines      191928   192093     +165     
  Branches     2742     2743       +1     
==========================================
- Hits       155349   155183     -166     
- Misses      36070    36399     +329     
- Partials      509      511       +2     

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