Use highest available pickle protocol when serializing

[rbetz]

Pickle protocol 5 allows for zero-copy pickling of numpy arrays, but protocol version 4 remains the default for Python 3.8 onwards. When loading datasets with large numpy arrays and reader_pool_type="process", using protocol 5 significantly improves serialization time and overall performance.

Protocol 5 is only available in Python 3.8 and onwards, so for backwards and forwards compatibility with future pickle protocol improvements we specify pickle.HIGHEST_PROTOCOL.

Small test case

import time
import numpy as np
from petastorm.reader_impl.pickle_serializer import PickleSerializer

s = PickleSerializer()
data = [np.random.random((1000, 1000)) for _ in range(10)]
t = time.time()
for x in range(100):
  _ = s.deserialize(s.serialize(data))
print(time.time() - t)

master:
11.40 sec

This PR:
8.78 sec

[CLAassistant]

All committers have signed the CLA.

[selitvin]

The change looks good to me. Can you please update docs/release-notes.rst and accept the CLA? Once we land it, I can cut a new release.

[codecov]

Codecov Report

Merging #737 (5a73d49) into master (76a36fe) will not change coverage.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master     #737   +/-   ##
=======================================
  Coverage   86.27%   86.27%           
=======================================
  Files          85       85           
  Lines        5084     5084           
  Branches      787      787           
=======================================
  Hits         4386     4386           
  Misses        559      559           
  Partials      139      139           

Impacted Files	Coverage Δ
petastorm/reader_impl/pickle_serializer.py	100.00% <100.00%> (ø)

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[rbetz]

bump... Is there something I need to do to get the unit tests to run?

[selitvin]

bump... Is there something I need to do to get the unit tests to run?

Sorry. Did not notice you were blocked on the tests. I had to approve the run for a user's first time. Should be ok going forward. Also, note there is a flaky test (some test that has to do with reading from a partitioned dataset). Feel free to rerunning the build if you bump into it.

[rbetz]

@selitvin I think I need permission to run the tests again. They did all pass, except for the ones you mentioned were flaky.

[selitvin]

That's weird. I thought it I am expected to approve running tests only for the first time. Will see if I can reconfigure this.

[rbetz]

Thanks for your help. Looks like the tests passed this time, so it's ready to merge :)

[selitvin]

Beautiful! Thank you for the PR.