jupyter和工人的头盔配置:
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)
数据框是从Apache Drill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)
在数据框上运行len(df)
会返回:
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
有人可以在这里建议正确的配置或补救步骤吗?
答案 0 :(得分:1)
这个错误实际上不是来自阅读你的镶木地板文件,而是来自Dask如何压缩机器之间的数据。您可以通过在所有客户端/调度程序/工作器窗格上安装或不安装python-snappy
来解决此问题。
您应该执行以下任一操作:
jupyter
和worker
广告连播的conda包列表中删除python-snappy。如果您正在使用pyarrow
,那么这是不必要的,我相信Arrow在C ++级别包含了snappy。python-snappy
添加到您的scheduler
广告 FWIW我个人建议lz4
进行snappy
之间的机器间压缩。