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Joris Van den Bossche commented on ARROW-6876: ---------------------------------------------- Small reproducer: {code} 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") {code} > Reading parquet file becomes really slow for 0.15.0 > --------------------------------------------------- > > Key: ARROW-6876 > URL: https://issues.apache.org/jira/browse/ARROW-6876 > Project: Apache Arrow > Issue Type: Bug > Components: Python > Affects Versions: 0.15.0 > Environment: python3.7 > Reporter: Bob > Priority: Major > Attachments: image-2019-10-14-18-10-42-850.png, > image-2019-10-14-18-12-07-652.png > > > Hi, > > I just noticed that reading a parquet file becomes really slow after I > upgraded to 0.15.0 when using pandas. > > Example: > *With 0.14.1* > In [4]: %timeit df = pd.read_parquet(path) > 2.02 s ± 47.5 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) > *With 0.15.0* > In [5]: %timeit df = pd.read_parquet(path) > 22.9 s ± 478 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) > > The file is about 15MB in size. I am testing on the same machine using the > same version of python and pandas. > > Have you received similar complain? What could be the issue here? > > Thanks a lot. > > > Edit1: > Some profiling I did: > 0.14.1: > !image-2019-10-14-18-12-07-652.png! > > 0.15.0: > !image-2019-10-14-18-10-42-850.png! > -- This message was sent by Atlassian Jira (v8.3.4#803005)