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This PR adds parquet as an output format for analyze. It uses PyArrow to handle all of the parquet reading and writing.
Currently, it creates a separate "table" for each timestamp, which might result in nonoptimal compression when there are few results per timestamp. There are a few options to improve this:
Combining the results into a single file (with
--combine_results) does make the output much smaller, but it would be ideal to have good compression without having to do this extra step.Either way, I have found that parquet's columnar compression works particularly well on classifier outputs due to the repetitive nature of their outputs (e.g. filenames are repeated for many rows). For large datasets, parquet should provide a significant improvement in file size.
This is somewhat related to #230 as well.