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  1. Apache Arrow
  2. ARROW-9458

[Python] Dataset Scanner is single-threaded only

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      I'm not sure this is a misunderstanding, or a compilation issue (flags?) or an issue in the C++ layer.

      I have 1000 parquet files with a total of 1 billion rows (1 million rows each file, ~20 columns). I wanted to see if I could go through all rows 1 of 2 columns efficiently (vaex use case).

       

      import pyarrow.parquet
      import pyarrow as pa
      import pyarrow.dataset as ds
      import glob
      ds = pa.dataset.dataset(glob.glob('/data/taxi_parquet/data_*.parquet'))
      scanned = 0
      for scan_task in ds.scan(batch_size=1_000_000, columns=['passenger_count'], use_threads=True):
          for record_batch in scan_task.execute():
              scanned += record_batch.num_rows
      scanned
      

      This only seems to use 1 cpu.

      Using a threadpool from Python:

      # %%timeit
      import concurrent.futures
      pool = concurrent.futures.ThreadPoolExecutor()
      ds = pa.dataset.dataset(glob.glob('/data/taxi_parquet/data_*.parquet'))
      def process(scan_task):
          scan_count = 0
          for record_batch in scan_task.execute():
              scan_count += len(record_batch)
          return scan_count
      sum(pool.map(process, ds.scan(batch_size=1_000_000, columns=['passenger_count'], use_threads=False)))
      

      Gives me a similar performance, again, only 100% cpu usage (=1 core/cpu).

      py-spy (profiler for Python) shows no GIL, so this might be something at the C++ layer.

      Am I 'holding it wrong' or could this be a bug? Note that IO speed is not a problem on this system (it actually all comes from OS cache, no disk read observed)

       

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          Maarten Breddels
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          Maarten Breddels

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              • Assignee:
                maartenbreddels Maarten Breddels
                Reporter:
                maartenbreddels Maarten Breddels
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