Google数据流是否支持使用pythonsdk开发的有状态管道？

Question

根据capability matrix和{a2}，googledataflow似乎在某种程度上支持有状态的管道

但是，虽然我有一个状态管道可以很好地与DirectRunner一起运行，但是我在DataflowRunner中遇到了以下错误：

...
 File "pipelines/StatefulPipeline.py", line 197, in process
    states = list(location_state.read())
  File "/usr/local/lib/python2.7/dist-packages/apache_beam/runners/worker/bundle_processor.py", line 318, in __iter__
    for elem in self.first:
  File "/usr/local/lib/python2.7/dist-packages/apache_beam/runners/worker/bundle_processor.py", line 187, in __iter__
    data, continuation_token = self._state_handler.blocking_get(self._state_key)
  File "/usr/local/lib/python2.7/dist-packages/apache_beam/runners/worker/sdk_worker.py", line 489, in blocking_get
    continuation_token=continuation_token)))
  File "/usr/local/lib/python2.7/dist-packages/apache_beam/runners/worker/sdk_worker.py", line 518, in _blocking_request
    raise RuntimeError(response.error)
RuntimeError: java.lang.IllegalStateException: Tried to access state for stateless step: NameContext{stageName=s02, originalName=s12, systemName=s12, userName=AlertEngine}
    at org.apache.beam.vendor.guava.v20_0.com.google.common.base.Preconditions.checkState(Preconditions.java:444)
    at org.apache.beam.runners.dataflow.worker.StreamingModeExecutionContext$StepContext.stateInternals(StreamingModeExecutionContext.java:685)
    at org.apache.beam.runners.dataflow.worker.StreamingModeExecutionContext$UserStepContext.stateInternals(StreamingModeExecutionContext.java:737)
    at org.apache.beam.runners.dataflow.worker.fn.control.RegisterAndProcessBundleOperation.lambda$handleBagUserState$5(RegisterAndProcessBundleOperation.java:509)
    at java.util.concurrent.ConcurrentHashMap.computeIfAbsent(ConcurrentHashMap.java:1660)
    at org.apache.beam.runners.dataflow.worker.fn.control.RegisterAndProcessBundleOperation.handleBagUserState(RegisterAndProcessBundleOperation.java:505)
    at org.apache.beam.runners.dataflow.worker.fn.control.RegisterAndProcessBundleOperation.delegateByStateKeyType(RegisterAndProcessBundleOperation.java:384)
    at org.apache.beam.runners.fnexecution.state.GrpcStateService$Inbound.onNext(GrpcStateService.java:130)
    at org.apache.beam.runners.fnexecution.state.GrpcStateService$Inbound.onNext(GrpcStateService.java:118)
    at org.apache.beam.vendor.grpc.v1p13p1.io.grpc.stub.ServerCalls$StreamingServerCallHandler$StreamingServerCallListener.onMessage(ServerCalls.java:248)
    at org.apache.beam.vendor.grpc.v1p13p1.io.grpc.ForwardingServerCallListener.onMessage(ForwardingServerCallListener.java:33)
    at org.apache.beam.vendor.grpc.v1p13p1.io.grpc.Contexts$ContextualizedServerCallListener.onMessage(Contexts.java:76)
    at org.apache.beam.vendor.grpc.v1p13p1.io.grpc.internal.ServerCallImpl$ServerStreamListenerImpl.messagesAvailable(ServerCallImpl.java:263)
    at org.apache.beam.vendor.grpc.v1p13p1.io.grpc.internal.ServerImpl$JumpToApplicationThreadServerStreamListener$1MessagesAvailable.runInContext(ServerImpl.java:683)
    at org.apache.beam.vendor.grpc.v1p13p1.io.grpc.internal.ContextRunnable.run(ContextRunnable.java:37)
    at org.apache.beam.vendor.grpc.v1p13p1.io.grpc.internal.SerializingExecutor.run(SerializingExecutor.java:123)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
 [while running 'generatedPtransform-327']
...

我的代码看起来有点像：

^{pr2}$

因此，我开始不确定带有pythonsdk的有状态管道是否只是不受数据流的支持。我在pythonsdk发行说明中发现了很少的信息。在