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https://issues.apache.org/jira/browse/BEAM-2573?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16081160#comment-16081160
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Ahmet Altay commented on BEAM-2573:
-----------------------------------
[~demeshchuk], I belive you are mixing two SDK versions. The SDK version
installed in your virtual environment should exactly match the sdk version you
use with --sdk_location flag.
You have two options:
1. Use the released version. pip install the latest version and do not set the
--sdk_location flag. You will not have the new features that will be available
in the next version.
2. Use the head version. Build and sdk from head. Install that in your new
virtual environment and also use --sdk_location flag to point to that sdk. You
will have all the new features available at head.
> Better filesystem discovery mechanism in Python SDK
> ---------------------------------------------------
>
> Key: BEAM-2573
> URL: https://issues.apache.org/jira/browse/BEAM-2573
> Project: Beam
> Issue Type: Task
> Components: runner-dataflow, sdk-py
> Affects Versions: 2.0.0
> Reporter: Dmitry Demeshchuk
> Priority: Minor
>
> It looks like right now custom filesystem classes have to be imported
> explicitly:
> https://github.com/apache/beam/blob/master/sdks/python/apache_beam/io/filesystems.py#L30
> Seems like the current implementation doesn't allow discovering filesystems
> that come from side packages, not from apache_beam itself. Even if I put a
> custom FileSystem-inheriting class into a package and explicitly import it in
> the root __init__.py of that package, it still doesn't make the class
> discoverable.
> The problems I'm experiencing happen on Dataflow runner, while Direct runner
> works just fine. Here's an example of Dataflow output:
> {code}
> (320418708fe777d7): Traceback (most recent call last):
> File
> "/usr/local/lib/python2.7/dist-packages/dataflow_worker/batchworker.py", line
> 581, in do_work
> work_executor.execute()
> File "/usr/local/lib/python2.7/dist-packages/dataflow_worker/executor.py",
> line 166, in execute
> op.start()
> File
> "/usr/local/lib/python2.7/dist-packages/dataflow_worker/native_operations.py",
> line 54, in start
> self.output(windowed_value)
> File "dataflow_worker/operations.py", line 138, in
> dataflow_worker.operations.Operation.output
> (dataflow_worker/operations.c:5768)
> def output(self, windowed_value, output_index=0):
> File "dataflow_worker/operations.py", line 139, in
> dataflow_worker.operations.Operation.output
> (dataflow_worker/operations.c:5654)
> cython.cast(Receiver,
> self.receivers[output_index]).receive(windowed_value)
> File "dataflow_worker/operations.py", line 72, in
> dataflow_worker.operations.ConsumerSet.receive
> (dataflow_worker/operations.c:3506)
> cython.cast(Operation, consumer).process(windowed_value)
> File "dataflow_worker/operations.py", line 328, in
> dataflow_worker.operations.DoOperation.process
> (dataflow_worker/operations.c:11162)
> with self.scoped_process_state:
> File "dataflow_worker/operations.py", line 329, in
> dataflow_worker.operations.DoOperation.process
> (dataflow_worker/operations.c:11116)
> self.dofn_receiver.receive(o)
> File "apache_beam/runners/common.py", line 382, in
> apache_beam.runners.common.DoFnRunner.receive
> (apache_beam/runners/common.c:10156)
> self.process(windowed_value)
> File "apache_beam/runners/common.py", line 390, in
> apache_beam.runners.common.DoFnRunner.process
> (apache_beam/runners/common.c:10458)
> self._reraise_augmented(exn)
> File "apache_beam/runners/common.py", line 431, in
> apache_beam.runners.common.DoFnRunner._reraise_augmented
> (apache_beam/runners/common.c:11673)
> raise new_exn, None, original_traceback
> File "apache_beam/runners/common.py", line 388, in
> apache_beam.runners.common.DoFnRunner.process
> (apache_beam/runners/common.c:10371)
> self.do_fn_invoker.invoke_process(windowed_value)
> File "apache_beam/runners/common.py", line 281, in
> apache_beam.runners.common.PerWindowInvoker.invoke_process
> (apache_beam/runners/common.c:8626)
> self._invoke_per_window(windowed_value)
> File "apache_beam/runners/common.py", line 307, in
> apache_beam.runners.common.PerWindowInvoker._invoke_per_window
> (apache_beam/runners/common.c:9302)
> windowed_value, self.process_method(*args_for_process))
> File
> "/Users/dmitrydemeshchuk/miniconda2/lib/python2.7/site-packages/apache_beam/transforms/core.py",
> line 749, in <lambda>
> File
> "/Users/dmitrydemeshchuk/miniconda2/lib/python2.7/site-packages/apache_beam/io/iobase.py",
> line 891, in <lambda>
> File
> "/usr/local/lib/python2.7/dist-packages/apache_beam/options/value_provider.py",
> line 109, in _f
> return fnc(self, *args, **kwargs)
> File
> "/usr/local/lib/python2.7/dist-packages/apache_beam/io/filebasedsink.py",
> line 146, in initialize_write
> tmp_dir = self._create_temp_dir(file_path_prefix)
> File
> "/usr/local/lib/python2.7/dist-packages/apache_beam/io/filebasedsink.py",
> line 151, in _create_temp_dir
> base_path, last_component = FileSystems.split(file_path_prefix)
> File
> "/usr/local/lib/python2.7/dist-packages/apache_beam/io/filesystems.py", line
> 99, in split
> filesystem = FileSystems.get_filesystem(path)
> File
> "/usr/local/lib/python2.7/dist-packages/apache_beam/io/filesystems.py", line
> 61, in get_filesystem
> raise ValueError('Unable to get the Filesystem for path %s' % path)
> ValueError: Unable to get the Filesystem for path
> s3://my-test-bucket/test_output [while running
> 'write/Write/WriteImpl/InitializeWrite']
> {code}
> I apologize for not providing full context or codebase, because a lot of the
> code we are running is internal, and some of it is tightly coupled to our
> infrastructure. If I run out of experimenting options, I'll try to narrow my
> use case down to the simplest case possible (like, override a gcs filesystem
> with a different path prefix or something).
> I think there are several possibilities here:
> 1. I'm doing something wrong, and it should be trivial to achieve something
> like that. This probably implies figuring out the right approach and writing
> some guideline for the sources/sinks page in the docs.
> 2. The current order of imports is not optimal, and we could possibly import
> the side packages before initializing the filesystem classes. I currently
> possess too little knowledge about the way things get executed in Dataflow,
> so it's hard for me to tell how much it's worth diving that rabbithole.
> 3. There just needs to be a better way of referring to additional filesystem
> classes. One way of doing that is to just specify a class name explicitly
> inside the ReadFromText and WriteToText functions (or something along these
> lines). PipelineOptions seems like an overkill for this, but may still be an
> option. Finally, maybe there could be just a function that gets called in the
> main script that somehow tells Beam to discover a specific class?
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