To clarify, is the error resolved with the cross-language transform as well ? If not please file a Jira.
On Mon, Jun 1, 2020 at 8:24 AM Kyle Weaver <kcwea...@google.com> wrote: > > It would be useful to print out such errors with Error level log, I > think. > > I agree, using environment_type=PROCESS is difficult enough without hiding > the logs by default. I re-opened the issue. > > On Mon, Jun 1, 2020 at 11:01 AM Alexey Romanenko <aromanenko....@gmail.com> > wrote: > >> Thanks! It was an issue with a setting *virtualenv* for a worker console >> where it should be running. >> >> It would be useful to print out such errors with Error level log, I think. >> >> On 29 May 2020, at 18:55, Kyle Weaver <kcwea...@google.com> wrote: >> >> That's probably a problem with your worker. You'll need to get additional >> logs to debug (see https://jira.apache.org/jira/browse/BEAM-8278) >> >> On Fri, May 29, 2020 at 12:48 PM Alexey Romanenko < >> aromanenko....@gmail.com> wrote: >> >>> Many thanks! It helped to avoid the error. I saw this option in the >>> xlang tests before but I didn’t add it since I was confused because of the >>> name =) >>> Also, I think we need to added “*—**sdk_location=container*” for >>> Expansion Service >>> >>> Finally, I've managed to only Java and xlang pipeline (with Python >>> external) and it works for Docker Harness (though, I observe some new >>> exceptions in the runtime). >>> >>> On the other hand, with Process Harness it still fails with an error: >>> >>> 20/05/29 18:33:30 INFO >>> org.apache.beam.runners.fnexecution.environment.ProcessEnvironmentFactory: >>> Still waiting for startup of >>> environment >>> '/dev/github/beam2/sdks/python/container/build/target/launcher/darwin_amd64/boot' >>> for worker id 1-10 >>> 20/05/29 18:33:30 ERROR org.apache.spark.executor.Executor: Exception in >>> task 1.0 in stage 0.0 (TID 1) >>> org.apache.beam.vendor.guava.v26_0_jre.com.google.common.util.concurrent.UncheckedExecutionException: >>> java.lang.IllegalStateException: Process died with exit code 1 >>> >>> If it’s unknown issue, I’ll create a Jira for that. >>> >>> On 29 May 2020, at 16:46, Kyle Weaver <kcwea...@google.com> wrote: >>> >>> Alexey, can you try adding --experiments=beam_fn_api to your pipeline >>> options? We add the option automatically in Python [1] but we don't in Java. >>> >>> I filed BEAM-10151 [2] to document this workflow. Alexey, perhaps you >>> can help with that. >>> >>> [1] >>> https://github.com/apache/beam/blob/a5b2046b10bebc59c5bde41d4cb6498058fdada2/sdks/python/apache_beam/pipeline.py#L209 >>> [2] https://jira.apache.org/jira/browse/BEAM-10151 >>> >>> On Fri, May 29, 2020 at 10:05 AM Alexey Romanenko < >>> aromanenko....@gmail.com> wrote: >>> >>>> Yes, I did run only Java pipeline with Portable Runner and there is the >>>> same error. >>>> >>>> Also, I did the same (without cross-language component) against Beam >>>> 2.19 and 2.20. >>>> It works fine against Beam 2.19 (as expected, since I tested it already >>>> before) and fails with kind the same error against Beam 2.20: >>>> >>>> 20/05/29 15:59:23 ERROR >>>> org.apache.beam.runners.fnexecution.jobsubmission.JobInvocation: Error >>>> during job invocation >>>> classificationpipeline-aromanenko-0529135917-9d94008d_25acfc79-abdb-4d04-be01-ad053334f6d1. >>>> java.lang.IllegalArgumentException: GreedyPipelineFuser requires all >>>> root nodes to be runner-implemented beam:transform:impulse:v1 or >>>> beam:transform:read:v1 primitives, but >>>> transform Create.Values/Read(CreateSource) executes in environment >>>> Optional[urn: "beam:env:docker:v1" >>>> payload: "\n\033apache/beam_java_sdk:2.20.0" >>>> >>>> Do you think it’s a bug or I miss something in configuration? >>>> >>>> On 28 May 2020, at 22:25, Kyle Weaver <kcwea...@google.com> wrote: >>>> >>>> Can you try removing the cross-language component(s) from the >>>> pipeline and see if it still has the same error? >>>> >>>> On Thu, May 28, 2020 at 4:15 PM Alexey Romanenko < >>>> aromanenko....@gmail.com> wrote: >>>> >>>>> For testing purposes, it’s just “Create.of(“Name1”, “Name2”, ...)" >>>>> >>>>> On 28 May 2020, at 19:29, Kyle Weaver <kcwea...@google.com> wrote: >>>>> >>>>> What source are you using? >>>>> >>>>> On Thu, May 28, 2020 at 1:24 PM Alexey Romanenko < >>>>> aromanenko....@gmail.com> wrote: >>>>> >>>>>> Hello, >>>>>> >>>>>> I’m trying to run a Cross-Language pipeline (Beam 2.21, Java pipeline >>>>>> with an external Python transform) with a PROCESS SDK Harness and Spark >>>>>> Portable Runner but it fails. >>>>>> To do that I have a running Spark Runner Job Server (Spark local) and >>>>>> standalone Expansion Service (Python) which contains a code of my Python >>>>>> transform that should be called from main Java pipeline. >>>>>> >>>>>> Once job has been submitted on Job Server and started running, it >>>>>> fails with this error: >>>>>> >>>>>> 20/05/28 18:55:12 INFO org.apache.beam.runners.spark.SparkJobInvoker: >>>>>> Invoking job >>>>>> classificationpipeline-aromanenko-0528165508-5a8f57b9_63b11806-bed9-48e5-a9d9-314dbc93e719 >>>>>> 20/05/28 18:55:12 INFO >>>>>> org.apache.beam.runners.fnexecution.jobsubmission.JobInvocation: Starting >>>>>> job invocation >>>>>> classificationpipeline-aromanenko-0528165508-5a8f57b9_63b11806-bed9-48e5-a9d9-314dbc93e719 >>>>>> 20/05/28 18:55:12 ERROR >>>>>> org.apache.beam.runners.fnexecution.jobsubmission.JobInvocation: Error >>>>>> during job invocation >>>>>> classificationpipeline-aromanenko-0528165508-5a8f57b9_63b11806-bed9-48e5-a9d9-314dbc93e719. >>>>>> >>>>>> *java.lang.IllegalArgumentException: GreedyPipelineFuser requires all >>>>>> root nodes to be runner-implemented beam:transform:impulse:v1 or >>>>>> beam:transform:read:v1 primitives, but >>>>>> transform Create.Values/Read(CreateSource) executes in environment >>>>>> Optional[urn: "beam:env:docker:v1"*payload: >>>>>> "\n\033apache/beam_java_sdk:2.21.0" >>>>>> capabilities: "beam:coder:bytes:v1” >>>>>> …. >>>>>> >>>>>> >>>>>> Some code snippets of my pipeline that can be helpful. >>>>>> >>>>>> *Java transform:* >>>>>> >>>>>> private static final String URN = "ml:genreclassifier:python:v1"; >>>>>> >>>>>> @Override >>>>>> public PCollection<KV<String, String>> expand(PCollection<String> input) >>>>>> { >>>>>> PCollection<KV<String, String>> output = >>>>>> input.apply( >>>>>> "ExternalGenreClassifier", >>>>>> External.of(URN, new byte[] {}, >>>>>> options.getExpansionServiceURL()) >>>>>> .<KV<String, String>>withOutputType()); >>>>>> return output; >>>>>> } >>>>>> >>>>>> >>>>>> *expansion_service.py* >>>>>> >>>>>> @ptransform.PTransform.register_urn('ml:genreclassifier:python:v1', None) >>>>>> class GenreClassifier(ptransform.PTransform): >>>>>> def __init__(self): >>>>>> super(GenreClassifier, self).__init__() >>>>>> >>>>>> def expand(self, pcoll): >>>>>> return pcoll | "GenreClassifier" >> >>>>>> beam.ParDo(_GenreClassifierFn()) >>>>>> >>>>>> def to_runner_api_parameter(self, unused_context): >>>>>> return 'ml:genreclassifier:python:v1', None >>>>>> >>>>>> @staticmethod >>>>>> def from_runner_api_parameter(unused_ptransform, unused_parameter, >>>>>> unused_context): >>>>>> return GenreClassifier() >>>>>> >>>>>> >>>>>> def main(unused_argv): >>>>>> ... >>>>>> server = grpc.server(UnboundedThreadPoolExecutor()) >>>>>> beam_expansion_api_pb2_grpc.add_ExpansionServiceServicer_to_server( >>>>>> expansion_service.ExpansionServiceServicer( >>>>>> PipelineOptions.from_dictionary({ >>>>>> 'environment_type': 'PROCESS', >>>>>> 'environment_config': *'{"command": >>>>>> **“/dev**/beam/sdks/python/container/build/target/launcher/darwin_amd64/boot"}'*, >>>>>> 'sdk_location': 'container', >>>>>> }) >>>>>> ), server >>>>>> ) >>>>>> server.add_insecure_port('localhost:{}'.format(options.port)) >>>>>> server.start() >>>>>> >>>>>> Does anyone have an idea what’s wrong with my setup/pipeline and how >>>>>> to fix it? >>>>>> >>>>>> >>>>>> >>>>> >>>> >>> >>
