[Gh-539][Encoding] Add ALPpd encoding to parquet

[prtkgaur]

Co-authored-by: [email protected]

Rationale for this change

ALP significantly improves on the compression ratio and decompression speed over of float/double columns over other encoding/compression techniques.

What changes are included in this PR?

This PR
Introduces ALP (pseudo-decimal) encoding into c++ arrow code.
We also provide benchmarks and dataset to prove the effectiveness of the above algorithm.

Adding above needed us to add following classes.

• Alp h/cc : Houses core logic for encoding and decoding.
• Sampler h/cc : Houses logic to sample and select parameters for encoding.
• AlpWrapper h/cc : Binds together Alp and Sampler classes.

Integration of the above code was done in

• Encoder/Decoder cc which exposes wrapper to encode buffer of data.

Unit tests were added to

• alp_test.cc

And Benchmarks are added to

• encoding_benchmark.cc and encoding_alp_benchmark.cc

Are these changes tested?

• We have added unit tests to test the code.
• Also the benchmarks have been added that cover wide variety of floating point values from low precision to high precision.

Are there any user-facing changes?

• It's a new encoding so the only impact is query performance which we claim will only get better.

[github-actions]

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See also:

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• Contribution Guidelines - Contributing Overview

[alamb]

I think the more standard place to put test data is in either arrow-testing or parquet-testing so it can be used across implementations

In this case I would recommend https://github.com/apache/parquet-testing

[prtkgaur]

Makes sense. Thanks.
apache/parquet-testing#100

[alamb]

🎉

[alamb]

Thanks @prtkgaur -- it is super exciting to see this movement.

Unfortunately, I am not familiar with the C/C++ codebase to give this a realistic review.

I started the CI checks on this PR and had some comments about the testing.

[prtkgaur]

Makes sense. Thanks.
apache/parquet-testing#100

[prtkgaur]

@Reviewer the data sits in the parquet-testing submodule
apache/parquet-testing#100

[prtkgaur]

Using this over resize gave us around 2-3% performance improvement