perf: Use List's TotalEqKernel

[coastalwhite]

This utilizes List's variant of TotalEqKernel and implements broadcasting for that kernel. This gives a nice speed-up, reduces code-bloat and reduces chance of bugs.

For a measure on how much faster this is, I did a microbenchmark:

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

lists = [None] + [list(range(i)) for i in range(11)]
a = [lists[length] for length in np.random.randint(0, 11, 1_000_000)]
b = [lists[length] for length in np.random.randint(0, 11, 1_000_000)]

a = pl.Series('a', a)
b = pl.Series('b', b)

t = timeit(lambda: a == b, number=100)
print(f"Time: {t:.2}s")

• Before: Time: 16s
• After: Time: 1.9s

I feel like there is more that can be done to make this a lot faster, but I feel like this is good enough for now.

[codecov]

Codecov Report

Attention: Patch coverage is 89.72973% with 19 lines in your changes missing coverage. Please review.

Project coverage is 79.86%. Comparing base (3904774) to head (bfa1d64).
Report is 14 commits behind head on main.

Files with missing lines	Patch %	Lines
...es/polars-core/src/chunked_array/comparison/mod.rs	83.18%	19 Missing ⚠️

Additional details and impacted files

@@           Coverage Diff            @@
##             main   #18984    +/-   ##
========================================
  Coverage   79.86%   79.86%            
========================================
  Files        1523     1523            
  Lines      207504   207618   +114     
  Branches     2904     2904            
========================================
+ Hits       165720   165821   +101     
- Misses      41237    41250    +13     
  Partials      547      547            

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