pyarrow版本1.0错误在使用ParquetDataset读取大量文件时抛出了内存不足异常与版本0.13兼容

如何解决pyarrow版本1.0错误在使用ParquetDataset读取大量文件时抛出了内存不足异常与版本0.13兼容

我将一个数据帧拆分并存储在5000多个文件中。我使用ParquetDataset（fnames）.read（）加载所有文件。我将pyarrow从0.13.0更新到了最新版本1.0.1，它开始抛出“ OSError：内存不足：大小为131072的malloc失败”。同一台计算机上的相同代码仍适用于旧版本。我的机器具有256Gb内存，足以装载需要

    # create a big dataframe
    import pandas as pd
    import numpy as np

    df = pd.DataFrame({'A': np.arange(50000000)})
    df['F1'] = np.random.randn(50000000) * 100
    df['F2'] = np.random.randn(50000000) * 100
    df['F3'] = np.random.randn(50000000) * 100
    df['F4'] = np.random.randn(50000000) * 100
    df['F5'] = np.random.randn(50000000) * 100
    df['F6'] = np.random.randn(50000000) * 100
    df['F7'] = np.random.randn(50000000) * 100
    df['F8'] = np.random.randn(50000000) * 100
    df['F9'] = 'ABCDEFGH'
    df['F10'] = 'ABCDEFGH'
    df['F11'] = 'ABCDEFGH'
    df['F12'] = 'ABCDEFGH01234'
    df['F13'] = 'ABCDEFGH01234'
    df['F14'] = 'ABCDEFGH01234'
    df['F15'] = 'ABCDEFGH01234567'
    df['F16'] = 'ABCDEFGH01234567'
    df['F17'] = 'ABCDEFGH01234567'

    # split and save data to 5000 files
    for i in range(5000):
        df.iloc[i*10000:(i+1)*10000].to_parquet(f'{i}.parquet',index=False)

    # use a fresh session to read data

    # below code works to read
    import pandas as pd
    df = []
    for i in range(5000):
        df.append(pd.read_parquet(f'{i}.parquet'))

    df = pd.concat(df)


    # below code crashes with memory error in pyarrow 1.0/1.0.1 (works fine with version 0.13.0)
    # tried use_legacy_dataset=False,same issue
    import pyarrow.parquet as pq

    fnames = []
    for i in range(5000):
        fnames.append(f'{i}.parquet')

    len(fnames)

    df = pq.ParquetDataset(fnames).read(use_threads=False)