Benjamin Mako Hill
172e66865c
sort_and_write() now takes num_partitions (default from config or 200) and passes it explicitly to repartition() instead of relying on spark.sql.shuffle.partitions. comments_part2 defaults to 800 partitions (~1GB/file matching the existing dataset density) and submissions_part2 to 300. Also cache the preprocessed DataFrame so the input is not re-read and reshuffled twice when writing the by_subreddit and by_author outputs. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
24 lines
963 B
Python
Executable File
24 lines
963 B
Python
Executable File
#!/usr/bin/env python3
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"""Part 2 for submissions: Spark sort + repartition into the final datasets.
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Must be launched from a login node via the Hyak-provided wrapper:
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start_spark_and_run.sh 1 submissions_part2.py
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start_spark_and_run.sh 1 submissions_part2.py --indir=/path/to/parquets --mode=append
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--indir defaults to the temp submissions dir in dumps_helper.py.
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--out_by_subreddit and --out_by_author default to the live dataset paths;
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override them to write to staging directories first (see add_months.sh).
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"""
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import fire
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from dumps_helper import SUBMISSIONS, sort_and_write
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if __name__ == "__main__":
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fire.Fire(lambda indir=None, out_by_subreddit=None, out_by_author=None,
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num_partitions=300:
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sort_and_write(SUBMISSIONS, indir=indir,
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out_by_subreddit=out_by_subreddit,
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out_by_author=out_by_author,
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num_partitions=num_partitions))
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