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  1. Apache Arrow
  2. ARROW-7059

[Python] Reading parquet file with many columns is much slower in 0.15.x versus 0.14.x

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    Details

    • Type: Bug
    • Status: Resolved
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: 0.15.1
    • Fix Version/s: 0.16.0
    • Component/s: Python
    • Environment:

      Description

      Reading Parquet files with large number of columns still seems to be very slow in 0.15.1 compared to 0.14.1. I using the same test used inĀ ARROW-6876 except I set use_threads=False to make for an apples-to-apples comparison with respect to # of CPUs.

      import numpy as np
      import pyarrow as pa
      import pyarrow.parquet as pq
      table = pa.table(\{'c' + str(i): np.random.randn(10) for i in range(10000)})
      pq.write_table(table, "test_wide.parquet")
      res = pq.read_table("test_wide.parquet")
      print(pa.__version__)
      %time res = pq.read_table("test_wide.parquet", use_threads=False)
      

      In 0.14.1 with use_threads=False:

      0.14.1
      CPU times: user 515 ms, sys: 9.3 ms, total: 524 ms
      Wall time: 525 ms
      **

      In 0.15.1 with use_threads=False:

      0.15.1
      CPU times: user 9.89 s, sys: 37.8 ms, total: 9.93 s
      Wall time: 9.93 s

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              • Assignee:
                wesm Wes McKinney
                Reporter:
                ekisslinger Eric Kisslinger
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