python似乎已经安装-- Dask返回一个ValueError。
朱庇特和工人的舵手:
env:
- name: EXTRA_CONDA_PACKAGES
value: numba xarray s3fs python-snappy pyarrow ruamel.yaml -c conda-forge
- name: EXTRA_PIP_PACKAGES
value: dask-ml --upgrade容器显示python-snappy (通过conda列表)
dataframe是从Apache钻机生成的多部分拼花文件中加载的:
files = ['s3://{}'.format(f) for f in fs.glob(path='{}/*.parquet'.format(filename))]
df = dd.read_parquet(files)在dataframe上运行len(df)返回:
distributed.utils - ERROR - Data is compressed as snappy but we don't have this installed
Traceback (most recent call last):
File "/opt/conda/lib/python3.6/site-packages/distributed/utils.py", line 622, in log_errors
yield
File "/opt/conda/lib/python3.6/site-packages/distributed/client.py", line 921, in _handle_report
six.reraise(*clean_exception(**msg))
File "/opt/conda/lib/python3.6/site-packages/six.py", line 692, in reraise
raise value.with_traceback(tb)
File "/opt/conda/lib/python3.6/site-packages/distributed/comm/tcp.py", line 203, in read
msg = yield from_frames(frames, deserialize=self.deserialize)
File "/opt/conda/lib/python3.6/site-packages/tornado/gen.py", line 1099, in run
return
File "/opt/conda/lib/python3.6/site-packages/tornado/gen.py", line 315, in wrapper
future.set_result(_value_from_stopiteration(e))
File "/opt/conda/lib/python3.6/site-packages/distributed/comm/utils.py", line 75, in from_frames
res = _from_frames()
File "/opt/conda/lib/python3.6/site-packages/distributed/comm/utils.py", line 61, in _from_frames
return protocol.loads(frames, deserialize=deserialize)
File "/opt/conda/lib/python3.6/site-packages/distributed/protocol/core.py", line 96, in loads
msg = loads_msgpack(small_header, small_payload)
File "/opt/conda/lib/python3.6/site-packages/distributed/protocol/core.py", line 171, in loads_msgpack
" installed" % str(header['compression']))
ValueError: Data is compressed as snappy but we don't have this installed有人可以建议正确的配置或补救步骤吗?
发布于 2018-05-15 01:30:45
这个错误实际上不是来自读取您的拼花文件,而是来自于Dask如何在机器之间压缩数据。您可能可以通过在所有客户端/调度程序/工作舱上一致安装python-snappy来解决这一问题。
您应该执行以下任一操作:
jupyter和worker荚的conda包列表中删除python。如果您使用的是pyarrow,那么这是不必要的,我相信Arrow在C++级别包含了snappy。python-snappy添加到scheduler吊舱中FWIW我个人推荐lz4用于snappy上的机器间压缩.
https://stackoverflow.com/questions/50340721
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