Optimize memory usage during materialization

[judahrand]

What this PR does / why we need it:
I have run memory usage into issues on initial materialization of a large FeatureView with approaching 10 million rows and 30 columns. Acquiring the Arrow table succeeds but the conversion to Protobuf seems to require duplicating the whole dataset in memory which is not practical.

This initial improvement batches the table returned by to_arrow into RecordBatches which improves the situation. Looking forward I think that there should be the option (or requirement?) for RetrievalJobs to yield these RecordBatches directly to further reduce memory requirements.

This PR improves the situation from #2071 but I do not believe is enough to close it.

Which issue(s) this PR fixes:

Fixes #

Does this PR introduce a user-facing change?:

None

[feast-ci-bot]

Hi @judahrand. Thanks for your PR.

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[judahrand]

/ok-to-test

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/ok-to-test

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[adchia]

/ok-to-test

[adchia]

/lgtm

[feast-ci-bot]

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: adchia, judahrand

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[judahrand]

Failures don't look related to PR

[adchia]

FYI @tsotnet looks like an issue with feature server docker images

[codecov-commenter]

Codecov Report

Merging #2073 (1d31495) into master (91b37e7) will increase coverage by 25.12%.
The diff coverage is 100.00%.

@@             Coverage Diff             @@
##           master    #2073       +/-   ##
===========================================
+ Coverage   58.19%   83.31%   +25.12%     
===========================================
  Files         100      100               
  Lines        8082     8084        +2     
===========================================
+ Hits         4703     6735     +2032     
+ Misses       3379     1349     -2030     

Flag	Coverage Δ
integrationtests	73.74% <100.00%> (?)
unittests	58.20% <100.00%> (+0.01%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
sdk/python/feast/infra/passthrough_provider.py	100.00% <100.00%> (+11.11%)	⬆️
sdk/python/feast/infra/provider.py	91.73% <100.00%> (+4.95%)	⬆️
sdk/python/feast/data_source.py	61.29% <0.00%> (+0.40%)	⬆️
sdk/python/feast/online_response.py	87.71% <0.00%> (+1.75%)	⬆️
sdk/python/feast/infra/online_stores/sqlite.py	96.77% <0.00%> (+2.15%)	⬆️
sdk/python/feast/feature.py	72.72% <0.00%> (+3.03%)	⬆️
sdk/python/feast/errors.py	70.00% <0.00%> (+5.00%)	⬆️
sdk/python/feast/infra/offline_stores/file.py	96.80% <0.00%> (+8.00%)	⬆️
sdk/python/feast/registry.py	80.41% <0.00%> (+10.13%)	⬆️
... and 51 more

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