Hi Lydian, and thanks for answering.
If you have a working minimal example, could you share it?
I’ve tried your suggestion, which required me to bump apache-beam to 2.41. I
get a different error when I do that (I tried extracting the relevant stack
trace bits):
2023-01-06 10:38:04,885 WARN org.apache.flink.runtime.taskmanager.Task
[] - Source:
ReadFromKafka(beam:transform:org.apache.beam:kafka_read_without_metadata:v1)/KafkaIO.Read/KafkaIO.Read.ReadFromKafkaViaUnbounded/Read(KafkaUnboundedSource)
-> Flat Map -> Map ->
[1]ReadFromKafka(beam:transform:org.apache.beam:kafka_read_without_metadata:v1)/Remove
Kafka Metadata -> [2]{WindowInto(WindowIntoFn), Map(print)} (1/1)#0
(d15bfc4aeee2cc9143ec7796cab67a09) switched from INITIALIZING to FAILED with
failure cause:
org.apache.beam.vendor.guava.v26_0_jre.com.google.common.util.concurrent.UncheckedExecutionException:
org.apache.beam.vendor.grpc.v1p43p2.io.grpc.StatusRuntimeException:
UNAVAILABLE: io exception
…
Caused by: org.apache.beam.vendor.grpc.v1p43p2.io.grpc.StatusRuntimeException:
UNAVAILABLE: io exception
…
Caused by:
org.apache.beam.vendor.grpc.v1p43p2.io.netty.channel.AbstractChannel$AnnotatedConnectException:
finishConnect(..) failed: Connection refused: localhost/127.0.0.1:50747
Caused by: java.net.ConnectException: finishConnect(..) failed: Connection
refused
…
Caused by: java.lang.ClassNotFoundException:
org.apache.beam.vendor.grpc.v1p43p2.io.grpc.internal.InternalSubchannel$4
…
2023-01-06 10:38:44,627 ERROR
org.apache.flink.runtime.util.ClusterUncaughtExceptionHandler [] - WARNING:
Thread 'grpc-default-executor-0' produced an uncaught exception. If you want to
fail on uncaught exceptions, then configure cluster.uncaught-exception-handling
accordingly
java.lang.NoClassDefFoundError:
org/apache/beam/vendor/grpc/v1p43p2/io/grpc/internal/LogExceptionRunnable
What could this be?
Thanks,
Florentin
> On 6 Jan 2023, at 09:52, Lydian <lydia...@gmail.com> wrote:
>
> Hi,
> I had the same issue before, and I *think* the 8097 is only work if you're
> using the flink runner, i.e., --runner=FlinkRunner, but it's not working for
> PortableRunner.
>
> So far, what seems work for me is to do things like this:
>
> from apache_beam.io.kafka import default_io_expansion_service
> ReadFromKafka(
> consumer_config=consumer_config,
> topics=[topic],
> with_metadata=False,
> expansion_service=default_io_expansion_service(
> append_args=[
> '--defaultEnvironmentType=PROCESS',
>
> '--defaultEnvironmentConfig={"command":"/opt/apache/beam/boot"}',
> '--experiments=use_deprecated_read',
> ]
> )
>
> this would ensure it will start an expansion service for you automatically
> use that expansion service.
> Also I have to provide extra --defaultEnvironmentType as well, otherwise it
> will start another docker container, but i don't have docker available inside
> my job manager, and thus have to force it to use PROCESS instead.
> The /opt/apache/beam/boot can be get via adding this line to my Dockerfile
>
> COPY --from=apache/beam_java8_sdk:2.41.0 /opt/apache/beam/
> /opt/apache/beam_java/
>
> Finally it is really important to add '--experiments=use_deprecated_read'.
> Turned out beam python doesn't support the Splitable DoFn very well, and when
> I test, the newer version will crash in about a day, but it would be totally
> working well if I add this use_deprecated_read.
>
> Sincerely,
> Lydian Lee
>
>
>
> On Thu, Jan 5, 2023 at 2:37 AM Florentin Hennecker <fhennec...@scortex.io
> <mailto:fhennec...@scortex.io>> wrote:
> Hello,
>
> I’ve been trying to write a pipeline in Python with apache-beam==2.38.0,
> which starts with a ReadFromKafka step.
> I have a flink cluster running in docker-compose, as well as the Flink job
> service image, which should serve the expansion service on port 8097,
> according to the docs:
> https://beam.apache.org/releases/pydoc/2.38.0/apache_beam.io.kafka.html
> <https://beam.apache.org/releases/pydoc/2.38.0/apache_beam.io.kafka.html>
>
> However, when trying to launch the pipeline, the ReadFromKafka step fails
> with:
> failed to connect to all addresses; last error: UNAVAILABLE:
> ipv4:127.0.0.1:8097 <http://127.0.0.1:8097/>: Socket closed
>
> I have tried a range of possible values for the expansion service passed to
> the ReadFromKafka step: internal docker compose DNS, my LAN IP address, and
> they all fail with various reasons. I have tried using different runners,
> changing everything that I could change, but no luck.
>
> What am I doing wrong?
>
> Here are the minimal beam pipeline and docker-compose to reproduce:
>
> pipeline.py
>
> import apache_beam as beam
> from apache_beam import window
> from apache_beam.transforms.trigger import (
> AccumulationMode,
> Repeatedly,
> AfterCount,
> )
> from apache_beam.options.pipeline_options import PipelineOptions
> from apache_beam.options.pipeline_options import StandardOptions
> from apache_beam.io.kafka import ReadFromKafka
>
>
> pipeline_options = PipelineOptions(
> [
> "--runner=PortableRunner",
> "--job_endpoint=localhost:8099",
> "--environment_type=LOOPBACK",
> ]
> )
> pipeline_options.view_as(StandardOptions).streaming = True
> with beam.Pipeline(options=pipeline_options) as pipeline:
> _ = (
> pipeline
> | ReadFromKafka(
> consumer_config={"bootstrap.servers": "redpanda:9092"},
> topics=["my-topic"],
> expansion_service="localhost:8097",
> )
> | beam.WindowInto(
> window.GlobalWindows(),
> trigger=Repeatedly(AfterCount(1)),
> accumulation_mode=AccumulationMode.DISCARDING,
> )
> | beam.Map(print)
> )
>
>
> docker-compose.yml
>
> version: '3.7'
> services:
>
> flink-jobmanager:
> image: flink:1.14
> ports:
> - "8081:8081"
> command: jobmanager
> environment:
> - |
> FLINK_PROPERTIES=
> jobmanager.rpc.address: jobmanager
>
> flink-taskmanager:
> image: flink:1.14
> depends_on:
> - flink-jobmanager
> command: taskmanager
> scale: 1
> environment:
> - |
> FLINK_PROPERTIES=
> jobmanager.rpc.address: jobmanager
> taskmanager.numberOfTaskSlots: 2
>
> beam-flink-jobserver:
> image: apache/beam_flink1.14_job_server:latest
> ports:
> - "8097:8097"
> - "8098:8098"
> - "8099:8099"
>
> Thanks in advance for your help!
>
> Best,
> Florentin
