Hi Dian,
Thanks! Adding -pyfs definitely helps.
However, I am curious. If I define my udf this way:
```python
@udf(input_types=[DataTypes.STRING()], result_type=DataTypes.STRING())
def decrypt(s):
import pandas as pd
d = pd.read_csv('resources.zip/resources/crypt.csv', header=None, index_col=
0, squeeze=True).to_dict()
return d.get(s, "unknown")
```
I can `flink run` without having to specify -pyfs option. The code can also
be found in the commit
https://github.com/YikSanChan/pyflink-quickstart/commit/cd003ca7d36583999dbb5ffd45958762e4323607.
I wonder why?
Best,
Yik San
On Tue, Apr 27, 2021 at 8:13 PM Dian Fu <[email protected]> wrote:
> Hi Yik San,
>
> From the exception message, it’s clear that it could not find module
> `decrypt_fun` during execution.
>
> You need to specify file `decrypt_fun.py` as a dependency during
> submitting the job, e.g. via -pyfs command line arguments. Otherwise, this
> file will not be available during execution.
>
> Regards,
> Dian
>
> 2021年4月27日 下午8:01，Yik San Chan <[email protected]> 写道：
>
> Hi,
>
> Here's the reproducible code sample:
> https://github.com/YikSanChan/pyflink-quickstart/tree/83526abca832f9ed5b8ce20be52fd506c45044d3
>
> I implement my Python UDF by extending the ScalarFunction base class in a
> separate file named decrypt_fun.py, and try to import the udf into my main
> python file named udf_use_resource.py.
>
> However, after I `flink run`, I find the error log in TaskManager log:
>
> ```
> Caused by: java.lang.RuntimeException: Error received from SDK harness for
> instruction 1: Traceback (most recent call last):
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/sdk_worker.py",
> line 376, in get
> processor = self.cached_bundle_processors[bundle_descriptor_id].pop()
> IndexError: pop from empty list
>
> During handling of the above exception, another exception occurred:
>
> Traceback (most recent call last):
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/sdk_worker.py",
> line 253, in _execute
> response = task()
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/sdk_worker.py",
> line 310, in <lambda>
> lambda: self.create_worker().do_instruction(request), request)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/sdk_worker.py",
> line 480, in do_instruction
> getattr(request, request_type), request.instruction_id)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/sdk_worker.py",
> line 509, in process_bundle
> instruction_id, request.process_bundle_descriptor_id)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/sdk_worker.py",
> line 382, in get
> self.data_channel_factory)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/bundle_processor.py",
> line 847, in __init__
> self.ops = self.create_execution_tree(self.process_bundle_descriptor)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/bundle_processor.py",
> line 902, in create_execution_tree
> descriptor.transforms, key=topological_height, reverse=True)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/bundle_processor.py",
> line 901, in <listcomp>
> (transform_id, get_operation(transform_id)) for transform_id in sorted(
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/bundle_processor.py",
> line 791, in wrapper
> result = cache[args] = func(*args)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/bundle_processor.py",
> line 885, in get_operation
> pcoll_id in descriptor.transforms[transform_id].outputs.items()
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/bundle_processor.py",
> line 885, in <dictcomp>
> pcoll_id in descriptor.transforms[transform_id].outputs.items()
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/bundle_processor.py",
> line 883, in <listcomp>
> tag: [get_operation(op) for op in pcoll_consumers[pcoll_id]]
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/bundle_processor.py",
> line 791, in wrapper
> result = cache[args] = func(*args)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/bundle_processor.py",
> line 888, in get_operation
> transform_id, transform_consumers)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/apache_beam/runners/worker/bundle_processor.py",
> line 1174, in create_operation
> return creator(self, transform_id, transform_proto, payload, consumers)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/pyflink/fn_execution/beam/beam_operations.py",
> line 39, in create_scalar_function
> operations.ScalarFunctionOperation)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/pyflink/fn_execution/beam/beam_operations.py",
> line 166, in _create_user_defined_function_operation
> internal_operation_cls)
> File "pyflink/fn_execution/beam/beam_operations_fast.pyx", line 110, in
> pyflink.fn_execution.beam.beam_operations_fast.StatelessFunctionOperation.__init__
> File "pyflink/fn_execution/beam/beam_operations_fast.pyx", line 49, in
> pyflink.fn_execution.beam.beam_operations_fast.FunctionOperation.__init__
> File "pyflink/fn_execution/beam/beam_operations_fast.pyx", line 114, in
> pyflink.fn_execution.beam.beam_operations_fast.StatelessFunctionOperation.generate_operation
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/pyflink/fn_execution/operations.py",
> line 91, in __init__
> super(ScalarFunctionOperation, self).__init__(spec)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/pyflink/fn_execution/operations.py",
> line 56, in __init__
> self.func, self.user_defined_funcs =
> self.generate_func(self.spec.serialized_fn)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/pyflink/fn_execution/operations.py",
> line 105, in generate_func
> [operation_utils.extract_user_defined_function(udf) for udf in
> serialized_fn.udfs])
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/pyflink/fn_execution/operations.py",
> line 105, in <listcomp>
> [operation_utils.extract_user_defined_function(udf) for udf in
> serialized_fn.udfs])
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/pyflink/fn_execution/operation_utils.py",
> line 86, in extract_user_defined_function
> user_defined_func = pickle.loads(user_defined_function_proto.payload)
> File
> "/usr/local/anaconda3/envs/featflow-ml-env/lib/python3.7/site-packages/pyflink/fn_execution/pickle.py",
> line 29, in loads
> return cloudpickle.loads(payload)
> ModuleNotFoundError: No module named 'decrypt_fun'
>
> at
> org.apache.beam.runners.fnexecution.control.FnApiControlClient$ResponseStreamObserver.onNext(FnApiControlClient.java:177)
> ~[blob_p-c18fee26bdebc8cb6523e7161974631be9f3b3d0-8f27cc9e92a718bc9d3d138d1d2d49ca:1.12.0]
> at
> org.apache.beam.runners.fnexecution.control.FnApiControlClient$ResponseStreamObserver.onNext(FnApiControlClient.java:157)
> ~[blob_p-c18fee26bdebc8cb6523e7161974631be9f3b3d0-8f27cc9e92a718bc9d3d138d1d2d49ca:1.12.0]
> at
> org.apache.beam.vendor.grpc.v1p26p0.io.grpc.stub.ServerCalls$StreamingServerCallHandler$StreamingServerCallListener.onMessage(ServerCalls.java:251)
> ~[blob_p-c18fee26bdebc8cb6523e7161974631be9f3b3d0-8f27cc9e92a718bc9d3d138d1d2d49ca:1.12.0]
> at
> org.apache.beam.vendor.grpc.v1p26p0.io.grpc.ForwardingServerCallListener.onMessage(ForwardingServerCallListener.java:33)
> ~[blob_p-c18fee26bdebc8cb6523e7161974631be9f3b3d0-8f27cc9e92a718bc9d3d138d1d2d49ca:1.12.0]
> at
> org.apache.beam.vendor.grpc.v1p26p0.io.grpc.Contexts$ContextualizedServerCallListener.onMessage(Contexts.java:76)
> ~[blob_p-c18fee26bdebc8cb6523e7161974631be9f3b3d0-8f27cc9e92a718bc9d3d138d1d2d49ca:1.12.0]
> at
> org.apache.beam.vendor.grpc.v1p26p0.io.grpc.internal.ServerCallImpl$ServerStreamListenerImpl.messagesAvailableInternal(ServerCallImpl.java:309)
> ~[blob_p-c18fee26bdebc8cb6523e7161974631be9f3b3d0-8f27cc9e92a718bc9d3d138d1d2d49ca:1.12.0]
> at
> org.apache.beam.vendor.grpc.v1p26p0.io.grpc.internal.ServerCallImpl$ServerStreamListenerImpl.messagesAvailable(ServerCallImpl.java:292)
> ~[blob_p-c18fee26bdebc8cb6523e7161974631be9f3b3d0-8f27cc9e92a718bc9d3d138d1d2d49ca:1.12.0]
> at
> org.apache.beam.vendor.grpc.v1p26p0.io.grpc.internal.ServerImpl$JumpToApplicationThreadServerStreamListener$1MessagesAvailable.runInContext(ServerImpl.java:782)
> ~[blob_p-c18fee26bdebc8cb6523e7161974631be9f3b3d0-8f27cc9e92a718bc9d3d138d1d2d49ca:1.12.0]
> at
> org.apache.beam.vendor.grpc.v1p26p0.io.grpc.internal.ContextRunnable.run(ContextRunnable.java:37)
> ~[blob_p-c18fee26bdebc8cb6523e7161974631be9f3b3d0-8f27cc9e92a718bc9d3d138d1d2d49ca:1.12.0]
> at
> org.apache.beam.vendor.grpc.v1p26p0.io.grpc.internal.SerializingExecutor.run(SerializingExecutor.java:123)
> ~[blob_p-c18fee26bdebc8cb6523e7161974631be9f3b3d0-8f27cc9e92a718bc9d3d138d1d2d49ca:1.12.0]
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> ~[?:1.8.0_282]
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> ~[?:1.8.0_282]
> ... 1 more
> ```
>
> I wonder why? If I move the Decrypt class into udf_use_resource.py,
> everything works just fine.
>
> Thank you!
>
> Best,
> Yik San
>
>
>
