Dmitry Demeshchuk created BEAM-2573: ---------------------------------------
Summary: 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 Reporter: Dmitry Demeshchuk Assignee: Thomas Groh 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? -- This message was sent by Atlassian JIRA (v6.4.14#64029)