docker - 在 Docker 中运行 Kedro 管道时找不到 PartitionedDataSet

Question

我在我阅读和处理的 S3 存储桶中有多个文本文件。因此，我在 Kedro 数据目录中定义了 PartitionedDataSet，如下所示:

raw_data:
  type: PartitionedDataSet
  path: s3://reads/raw
  dataset: pandas.CSVDataSet
  load_args:
    sep: "\t"
    comment: "#"

另外，我实现了这个 solution通过环境变量(包括 AWS key )从凭证文件中获取所有 secret 。
当我使用 kedro run 在本地运行时一切正常，但是当我构建 Docker 镜像(使用 kedro-docker )并使用 kedro docker run 在 Docker 环境中运行管道时并使用 --docker-args 提供所有环境变量选项我收到以下错误:

Traceback (most recent call last):
  File "/usr/local/bin/kedro", line 8, in <module>
    sys.exit(main())
  File "/usr/local/lib/python3.7/site-packages/kedro/framework/cli/cli.py", line 724, in main
    cli_collection()
  File "/usr/local/lib/python3.7/site-packages/click/core.py", line 829, in __call__
    return self.main(*args, **kwargs)
  File "/usr/local/lib/python3.7/site-packages/click/core.py", line 782, in main
    rv = self.invoke(ctx)
  File "/usr/local/lib/python3.7/site-packages/click/core.py", line 1259, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/usr/local/lib/python3.7/site-packages/click/core.py", line 1066, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/usr/local/lib/python3.7/site-packages/click/core.py", line 610, in invoke
    return callback(*args, **kwargs)
  File "/home/kedro/kedro_cli.py", line 230, in run
    pipeline_name=pipeline,
  File "/usr/local/lib/python3.7/site-packages/kedro/framework/context/context.py", line 767, in run
    raise exc
  File "/usr/local/lib/python3.7/site-packages/kedro/framework/context/context.py", line 759, in run
    run_result = runner.run(filtered_pipeline, catalog, run_id)
  File "/usr/local/lib/python3.7/site-packages/kedro/runner/runner.py", line 101, in run
    self._run(pipeline, catalog, run_id)
  File "/usr/local/lib/python3.7/site-packages/kedro/runner/sequential_runner.py", line 90, in _run
    run_node(node, catalog, self._is_async, run_id)
  File "/usr/local/lib/python3.7/site-packages/kedro/runner/runner.py", line 213, in run_node
    node = _run_node_sequential(node, catalog, run_id)
  File "/usr/local/lib/python3.7/site-packages/kedro/runner/runner.py", line 221, in _run_node_sequential
    inputs = {name: catalog.load(name) for name in node.inputs}
  File "/usr/local/lib/python3.7/site-packages/kedro/runner/runner.py", line 221, in <dictcomp>
    inputs = {name: catalog.load(name) for name in node.inputs}
  File "/usr/local/lib/python3.7/site-packages/kedro/io/data_catalog.py", line 392, in load
    result = func()
  File "/usr/local/lib/python3.7/site-packages/kedro/io/core.py", line 213, in load
    return self._load()
  File "/usr/local/lib/python3.7/site-packages/kedro/io/partitioned_data_set.py", line 240, in _load
    raise DataSetError("No partitions found in `{}`".format(self._path))
kedro.io.core.DataSetError: No partitions found in `s3://reads/raw`

注意:Pipeline 在 Docker 环境中工作得很好，如果我将文件移动到某个本地目录，定义 PartitionedDataSet 并构建 Docker 镜像并通过 --docker-args 提供环境变量

Answer 1

解决方案(至少在我的情况下)是提供 AWS_DEFAULT_REGION kedro docker run 中的 env 变量命令。