我在读取和处理的 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: "#"
此外,我实施了这个解决方案,通过环境变量(包括 AWS 密钥)从凭证文件中获取所有秘密。
当我使用一切在本地运行时kedro run
一切正常,但是当我构建 Docker 映像(使用kedro-docker)并在 Docker 环境中运行管道时,kedro docker run
使用选项并通过提供所有环境变量,--docker-args
我得到以下错误:
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:管道在 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 映像并通过提供环境变量--docker-args