Running env:
OS: ubuntu 20.04
kafka version: 2.12-2.0.1
apach-beam library version: apache-beam==2.32.0
Procedure:
shell 1: Run below code
import apache_beam as beam
from apache_beam.options.pipeline_options import PipelineOptions
from apache_beam.io.external.kafka import ReadFromKafka
pipeline_options = PipelineOptions(["--runner=DirectRunner"])
def run():
with beam.Pipeline(options=pipeline_options) as p:
_ = (
p
| 'ReadData' >> ReadFromKafka(
consumer_config={"bootstrap.servers": "localhost:9092"},
topics=["my-first-topic"],
)
| 'PrintData' >> beam.Map(print)
)
if __name__ == "__main__":
run()
output of shell1:
WARNING:apache_beam.runners.interactive.interactive_environment:You have limited Interactive Beam features since your ipython kernel is not connected to any notebook frontend.
WARNING:root:Make sure that locally built Python SDK docker image has Python 3.8 interpreter.
2.32.0: Pulling from apache/beam_java11_sdk
Digest: sha256:a45f89584071950d371966abf910869c456179ab54c7b5213e3f4e2a54bd2753
Status: Image is up to date for apache/beam_java11_sdk:2.32.0
docker.io/apache/beam_java11_sdk:2.32.0
shell 2:
$ cd kafka_2.12-2.0.1/bin && ./kafka-console-producer.sh --topic "my-first-topic" --broker-list localhost:9092
>2
>3
>4
output of shell 1:
WARNING:root:Make sure that locally built Python SDK docker image has Python 3.8 interpreter.
2.32.0: Pulling from apache/beam_java11_sdk
Digest: sha256:a45f89584071950d371966abf910869c456179ab54c7b5213e3f4e2a54bd2753
Status: Image is up to date for apache/beam_java11_sdk:2.32.0
docker.io/apache/beam_java11_sdk:2.32.0
ERROR:root:severity: ERROR
timestamp {
seconds: 1630485467
nanos: 764000000
}
message: "Client failed to deque and process the value"
trace: "org.apache.beam.sdk.util.UserCodeException: java.lang.IllegalArgumentException: Unable to encode element \'org.apache.beam.sdk.io.kafka.KafkaRecord#4c9edf30\' with coder \'KafkaRecordCoder(ByteArrayCoder,ByteArrayCoder)\'.\n\tat org.apache.beam.sdk.util.UserCodeException.wrap(UserCodeException.java:39)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.outputTo(FnApiDoFnRunner.java:1683)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.access$2500(FnApiDoFnRunner.java:139)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner$NonWindowObservingProcessBundleContext.outputWithTimestamp(FnApiDoFnRunner.java:2205)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner$ProcessBundleContextBase.output(FnApiDoFnRunner.java:2374)\n\tat org.apache.beam.sdk.transforms.DoFnOutputReceivers$WindowedContextOutputReceiver.output(DoFnOutputReceivers.java:78)\n\tat org.apache.beam.sdk.transforms.MapElements$1.processElement(MapElements.java:142)\n\tat org.apache.beam.sdk.transforms.MapElements$1$DoFnInvoker.invokeProcessElement(Unknown Source)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.processElementForParDo(FnApiDoFnRunner.java:750)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:266)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:218)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.outputTo(FnApiDoFnRunner.java:1680)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.access$2500(FnApiDoFnRunner.java:139)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner$WindowObservingProcessBundleContext.outputWithTimestamp(FnApiDoFnRunner.java:2092)\n\tat org.apache.beam.sdk.transforms.DoFnOutputReceivers$WindowedContextOutputReceiver.outputWithTimestamp(DoFnOutputReceivers.java:87)\n\tat org.apache.beam.sdk.io.kafka.ReadFromKafkaDoFn.processElement(ReadFromKafkaDoFn.java:378)\n\tat org.apache.beam.sdk.io.kafka.ReadFromKafkaDoFn$DoFnInvoker.invokeProcessElement(Unknown Source)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.processElementForWindowObservingSizedElementAndRestriction(FnApiDoFnRunner.java:1048)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.access$1000(FnApiDoFnRunner.java:139)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner$4.accept(FnApiDoFnRunner.java:637)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner$4.accept(FnApiDoFnRunner.java:632)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:266)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:218)\n\tat org.apache.beam.fn.harness.BeamFnDataReadRunner.forwardElementToConsumer(BeamFnDataReadRunner.java:221)\n\tat org.apache.beam.sdk.fn.data.DecodingFnDataReceiver.accept(DecodingFnDataReceiver.java:43)\n\tat org.apache.beam.sdk.fn.data.DecodingFnDataReceiver.accept(DecodingFnDataReceiver.java:25)\n\tat org.apache.beam.fn.harness.data.QueueingBeamFnDataClient$ConsumerAndData.accept(QueueingBeamFnDataClient.java:316)\n\tat org.apache.beam.fn.harness.data.QueueingBeamFnDataClient.drainAndBlock(QueueingBeamFnDataClient.java:219)\n\tat org.apache.beam.fn.harness.control.ProcessBundleHandler.processBundle(ProcessBundleHandler.java:329)\n\tat org.apache.beam.fn.harness.control.BeamFnControlClient.delegateOnInstructionRequestType(BeamFnControlClient.java:140)\n\tat org.apache.beam.fn.harness.control.BeamFnControlClient$InboundObserver.lambda$onNext$0(BeamFnControlClient.java:110)\n\tat java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)\n\tat java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)\n\tat java.base/java.lang.Thread.run(Thread.java:829)\nCaused by: java.lang.IllegalArgumentException: Unable to encode element \'org.apache.beam.sdk.io.kafka.KafkaRecord#4c9edf30\' with coder \'KafkaRecordCoder(ByteArrayCoder,ByteArrayCoder)\'.\n\tat org.apache.beam.sdk.coders.Coder.getEncodedElementByteSize(Coder.java:300)\n\tat org.apache.beam.sdk.coders.Coder.registerByteSizeObserver(Coder.java:291)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$SampleByteSizeDistribution.tryUpdate(PCollectionConsumerRegistry.java:385)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:259)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:218)\nCaused by: org.apache.beam.sdk.coders.CoderException: cannot encode a null byte[]\n\tat org.apache.beam.sdk.coders.ByteArrayCoder.encode(ByteArrayCoder.java:63)\n\tat org.apache.beam.sdk.coders.ByteArrayCoder.encode(ByteArrayCoder.java:56)\n\tat org.apache.beam.sdk.coders.ByteArrayCoder.encode(ByteArrayCoder.java:41)\n\tat org.apache.beam.sdk.coders.KvCoder.encode(KvCoder.java:72)\n\tat org.apache.beam.sdk.coders.KvCoder.encode(KvCoder.java:63)\n\tat org.apache.beam.sdk.io.kafka.KafkaRecordCoder.encode(KafkaRecordCoder.java:70)\n\tat org.apache.beam.sdk.io.kafka.KafkaRecordCoder.encode(KafkaRecordCoder.java:40)\n\tat org.apache.beam.sdk.coders.Coder.getEncodedElementByteSize(Coder.java:297)\n\tat org.apache.beam.sdk.coders.Coder.registerByteSizeObserver(Coder.java:291)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$SampleByteSizeDistribution.tryUpdate(PCollectionConsumerRegistry.java:385)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:259)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:218)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.outputTo(FnApiDoFnRunner.java:1680)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.access$2500(FnApiDoFnRunner.java:139)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner$NonWindowObservingProcessBundleContext.outputWithTimestamp(FnApiDoFnRunner.java:2205)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner$ProcessBundleContextBase.output(FnApiDoFnRunner.java:2374)\n\tat org.apache.beam.sdk.transforms.DoFnOutputReceivers$WindowedContextOutputReceiver.output(DoFnOutputReceivers.java:78)\n\tat org.apache.beam.sdk.transforms.MapElements$1.processElement(MapElements.java:142)\n\tat org.apache.beam.sdk.transforms.MapElements$1$DoFnInvoker.invokeProcessElement(Unknown Source)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.processElementForParDo(FnApiDoFnRunner.java:750)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:266)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:218)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.outputTo(FnApiDoFnRunner.java:1680)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.access$2500(FnApiDoFnRunner.java:139)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner$WindowObservingProcessBundleContext.outputWithTimestamp(FnApiDoFnRunner.java:2092)\n\tat org.apache.beam.sdk.transforms.DoFnOutputReceivers$WindowedContextOutputReceiver.outputWithTimestamp(DoFnOutputReceivers.java:87)\n\tat org.apache.beam.sdk.io.kafka.ReadFromKafkaDoFn.processElement(ReadFromKafkaDoFn.java:378)\n\tat org.apache.beam.sdk.io.kafka.ReadFromKafkaDoFn$DoFnInvoker.invokeProcessElement(Unknown Source)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.processElementForWindowObservingSizedElementAndRestriction(FnApiDoFnRunner.java:1048)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner.access$1000(FnApiDoFnRunner.java:139)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner$4.accept(FnApiDoFnRunner.java:637)\n\tat org.apache.beam.fn.harness.FnApiDoFnRunner$4.accept(FnApiDoFnRunner.java:632)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:266)\n\tat org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:218)\n\tat org.apache.beam.fn.harness.BeamFnDataReadRunner.forwardElementToConsumer(BeamFnDataReadRunner.java:221)\n\tat org.apache.beam.sdk.fn.data.DecodingFnDataReceiver.accept(DecodingFnDataReceiver.java:43)\n\tat org.apache.beam.sdk.fn.data.DecodingFnDataReceiver.accept(DecodingFnDataReceiver.java:25)\n\tat org.apache.beam.fn.harness.data.QueueingBeamFnDataClient$ConsumerAndData.accept(QueueingBeamFnDataClient.java:316)\n\tat org.apache.beam.fn.harness.data.QueueingBeamFnDataClient.drainAndBlock(QueueingBeamFnDataClient.java:219)\n\tat org.apache.beam.fn.harness.control.ProcessBundleHandler.processBundle(ProcessBundleHandler.java:329)\n\tat org.apache.beam.fn.harness.control.BeamFnControlClient.delegateOnInstructionRequestType(BeamFnControlClient.java:140)\n\tat org.apache.beam.fn.harness.control.BeamFnControlClient$InboundObserver.lambda$onNext$0(BeamFnControlClient.java:110)\n\tat java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)\n\tat java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)\n\tat java.base/java.lang.Thread.run(Thread.java:829)\n"
instruction_id: "bundle_116"
log_location: "org.apache.beam.fn.harness.data.QueueingBeamFnDataClient"
thread: "31"
ERROR:root:severity: ERROR
timestamp {
seconds: 1630485467
nanos: 770000000
}
message: "Exception while trying to handle InstructionRequest bundle_116"
trace: "org.apache.beam.sdk.util.UserCodeException: java.lang.IllegalArgumentException: Unable to encode element \'org.apache.beam.sdk.io.kafka.KafkaRecord#4c9edf30\' with coder \'KafkaRecordCoder(ByteArrayCoder,ByteArrayCoder)\'.
...
/home/newdisk/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py in _run_bundle(self, runner_execution_context, bundle_context_manager, data_input, data_output, input_timers, expected_timer_output, bundle_manager)
767 expected_timer_output)
768
--> 769 result, splits = bundle_manager.process_bundle(
770 data_input, data_output, input_timers, expected_timer_output)
771 # Now we collect all the deferred inputs remaining from bundle execution.
/home/newdisk/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py in process_bundle(self, inputs, expected_outputs, fired_timers, expected_output_timers, dry_run)
1118
1119 if result.error:
-> 1120 raise RuntimeError(result.error)
1121
1122 if result.process_bundle.requires_finalization:
RuntimeError: org.apache.beam.sdk.util.UserCodeException: java.lang.IllegalArgumentException: Unable to encode element 'org.apache.beam.sdk.io.kafka.KafkaRecord#4c9edf30' with coder 'KafkaRecordCoder(ByteArrayCoder,ByteArrayCoder)'.
at org.apache.beam.sdk.util.UserCodeException.wrap(UserCodeException.java:39)
at org.apache.beam.fn.harness.FnApiDoFnRunner.outputTo(FnApiDoFnRunner.java:1683)
at org.apache.beam.fn.harness.FnApiDoFnRunner.access$2500(FnApiDoFnRunner.java:139)
at org.apache.beam.fn.harness.FnApiDoFnRunner$NonWindowObservingProcessBundleContext.outputWithTimestamp(FnApiDoFnRunner.java:2205)
at org.apache.beam.fn.harness.FnApiDoFnRunner$ProcessBundleContextBase.output(FnApiDoFnRunner.java:2374)
at org.apache.beam.sdk.transforms.DoFnOutputReceivers$WindowedContextOutputReceiver.output(DoFnOutputReceivers.java:78)
at org.apache.beam.sdk.transforms.MapElements$1.processElement(MapElements.java:142)
at org.apache.beam.sdk.transforms.MapElements$1$DoFnInvoker.invokeProcessElement(Unknown Source)
at org.apache.beam.fn.harness.FnApiDoFnRunner.processElementForParDo(FnApiDoFnRunner.java:750)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:266)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:218)
at org.apache.beam.fn.harness.FnApiDoFnRunner.outputTo(FnApiDoFnRunner.java:1680)
at org.apache.beam.fn.harness.FnApiDoFnRunner.access$2500(FnApiDoFnRunner.java:139)
at org.apache.beam.fn.harness.FnApiDoFnRunner$WindowObservingProcessBundleContext.outputWithTimestamp(FnApiDoFnRunner.java:2092)
at org.apache.beam.sdk.transforms.DoFnOutputReceivers$WindowedContextOutputReceiver.outputWithTimestamp(DoFnOutputReceivers.java:87)
at org.apache.beam.sdk.io.kafka.ReadFromKafkaDoFn.processElement(ReadFromKafkaDoFn.java:378)
at org.apache.beam.sdk.io.kafka.ReadFromKafkaDoFn$DoFnInvoker.invokeProcessElement(Unknown Source)
at org.apache.beam.fn.harness.FnApiDoFnRunner.processElementForWindowObservingSizedElementAndRestriction(FnApiDoFnRunner.java:1048)
at org.apache.beam.fn.harness.FnApiDoFnRunner.access$1000(FnApiDoFnRunner.java:139)
at org.apache.beam.fn.harness.FnApiDoFnRunner$4.accept(FnApiDoFnRunner.java:637)
at org.apache.beam.fn.harness.FnApiDoFnRunner$4.accept(FnApiDoFnRunner.java:632)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:266)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:218)
at org.apache.beam.fn.harness.BeamFnDataReadRunner.forwardElementToConsumer(BeamFnDataReadRunner.java:221)
at org.apache.beam.sdk.fn.data.DecodingFnDataReceiver.accept(DecodingFnDataReceiver.java:43)
at org.apache.beam.sdk.fn.data.DecodingFnDataReceiver.accept(DecodingFnDataReceiver.java:25)
at org.apache.beam.fn.harness.data.QueueingBeamFnDataClient$ConsumerAndData.accept(QueueingBeamFnDataClient.java:316)
at org.apache.beam.fn.harness.data.QueueingBeamFnDataClient.drainAndBlock(QueueingBeamFnDataClient.java:219)
at org.apache.beam.fn.harness.control.ProcessBundleHandler.processBundle(ProcessBundleHandler.java:329)
at org.apache.beam.fn.harness.control.BeamFnControlClient.delegateOnInstructionRequestType(BeamFnControlClient.java:140)
at org.apache.beam.fn.harness.control.BeamFnControlClient$InboundObserver.lambda$onNext$0(BeamFnControlClient.java:110)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:829)
Caused by: java.lang.IllegalArgumentException: Unable to encode element 'org.apache.beam.sdk.io.kafka.KafkaRecord#4c9edf30' with coder 'KafkaRecordCoder(ByteArrayCoder,ByteArrayCoder)'.
at org.apache.beam.sdk.coders.Coder.getEncodedElementByteSize(Coder.java:300)
at org.apache.beam.sdk.coders.Coder.registerByteSizeObserver(Coder.java:291)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$SampleByteSizeDistribution.tryUpdate(PCollectionConsumerRegistry.java:385)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:259)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:218)
Caused by: org.apache.beam.sdk.coders.CoderException: cannot encode a null byte[]
at org.apache.beam.sdk.coders.ByteArrayCoder.encode(ByteArrayCoder.java:63)
at org.apache.beam.sdk.coders.ByteArrayCoder.encode(ByteArrayCoder.java:56)
at org.apache.beam.sdk.coders.ByteArrayCoder.encode(ByteArrayCoder.java:41)
at org.apache.beam.sdk.coders.KvCoder.encode(KvCoder.java:72)
at org.apache.beam.sdk.coders.KvCoder.encode(KvCoder.java:63)
at org.apache.beam.sdk.io.kafka.KafkaRecordCoder.encode(KafkaRecordCoder.java:70)
at org.apache.beam.sdk.io.kafka.KafkaRecordCoder.encode(KafkaRecordCoder.java:40)
at org.apache.beam.sdk.coders.Coder.getEncodedElementByteSize(Coder.java:297)
at org.apache.beam.sdk.coders.Coder.registerByteSizeObserver(Coder.java:291)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$SampleByteSizeDistribution.tryUpdate(PCollectionConsumerRegistry.java:385)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:259)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:218)
at org.apache.beam.fn.harness.FnApiDoFnRunner.outputTo(FnApiDoFnRunner.java:1680)
at org.apache.beam.fn.harness.FnApiDoFnRunner.access$2500(FnApiDoFnRunner.java:139)
at org.apache.beam.fn.harness.FnApiDoFnRunner$NonWindowObservingProcessBundleContext.outputWithTimestamp(FnApiDoFnRunner.java:2205)
at org.apache.beam.fn.harness.FnApiDoFnRunner$ProcessBundleContextBase.output(FnApiDoFnRunner.java:2374)
at org.apache.beam.sdk.transforms.DoFnOutputReceivers$WindowedContextOutputReceiver.output(DoFnOutputReceivers.java:78)
at org.apache.beam.sdk.transforms.MapElements$1.processElement(MapElements.java:142)
at org.apache.beam.sdk.transforms.MapElements$1$DoFnInvoker.invokeProcessElement(Unknown Source)
at org.apache.beam.fn.harness.FnApiDoFnRunner.processElementForParDo(FnApiDoFnRunner.java:750)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:266)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:218)
at org.apache.beam.fn.harness.FnApiDoFnRunner.outputTo(FnApiDoFnRunner.java:1680)
at org.apache.beam.fn.harness.FnApiDoFnRunner.access$2500(FnApiDoFnRunner.java:139)
at org.apache.beam.fn.harness.FnApiDoFnRunner$WindowObservingProcessBundleContext.outputWithTimestamp(FnApiDoFnRunner.java:2092)
at org.apache.beam.sdk.transforms.DoFnOutputReceivers$WindowedContextOutputReceiver.outputWithTimestamp(DoFnOutputReceivers.java:87)
at org.apache.beam.sdk.io.kafka.ReadFromKafkaDoFn.processElement(ReadFromKafkaDoFn.java:378)
at org.apache.beam.sdk.io.kafka.ReadFromKafkaDoFn$DoFnInvoker.invokeProcessElement(Unknown Source)
at org.apache.beam.fn.harness.FnApiDoFnRunner.processElementForWindowObservingSizedElementAndRestriction(FnApiDoFnRunner.java:1048)
at org.apache.beam.fn.harness.FnApiDoFnRunner.access$1000(FnApiDoFnRunner.java:139)
at org.apache.beam.fn.harness.FnApiDoFnRunner$4.accept(FnApiDoFnRunner.java:637)
at org.apache.beam.fn.harness.FnApiDoFnRunner$4.accept(FnApiDoFnRunner.java:632)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:266)
at org.apache.beam.fn.harness.data.PCollectionConsumerRegistry$MetricTrackingFnDataReceiver.accept(PCollectionConsumerRegistry.java:218)
at org.apache.beam.fn.harness.BeamFnDataReadRunner.forwardElementToConsumer(BeamFnDataReadRunner.java:221)
at org.apache.beam.sdk.fn.data.DecodingFnDataReceiver.accept(DecodingFnDataReceiver.java:43)
at org.apache.beam.sdk.fn.data.DecodingFnDataReceiver.accept(DecodingFnDataReceiver.java:25)
at org.apache.beam.fn.harness.data.QueueingBeamFnDataClient$ConsumerAndData.accept(QueueingBeamFnDataClient.java:316)
at org.apache.beam.fn.harness.data.QueueingBeamFnDataClient.drainAndBlock(QueueingBeamFnDataClient.java:219)
at org.apache.beam.fn.harness.control.ProcessBundleHandler.processBundle(ProcessBundleHandler.java:329)
at org.apache.beam.fn.harness.control.BeamFnControlClient.delegateOnInstructionRequestType(BeamFnControlClient.java:140)
at org.apache.beam.fn.harness.control.BeamFnControlClient$InboundObserver.lambda$onNext$0(BeamFnControlClient.java:110)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:829)
Looks like it is related with key_deserializer and value_deserializer args of ReadFromKafka, So I tried to change them:
# key_deserializer="org.apache.kafka.common.serialization.StringSerializer",
# value_deserializer="org.apache.kafka.common.serialization.StringSerializer",
But it raised an another error:
RuntimeError: java.lang.RuntimeException: Failed to build transform beam:external:java:kafkaio:typedwithoutmetadata:v1 from spec urn: "beam:external:java:kafkaio:typedwithoutmetadata:v1"
payload: "\n\213\002\n\035\n\017consumer_config\032\n*\b\n\002\020\a\022\002\020\a\n\020\n\006topics\032\006\032\004\n\002\020\a\n\026\n\020key_deserializer\032\002\020\a\n\030\n\022value_deserializer\032\002\020\a\n\027\n\017start_read_time\032\004\b\001\020\004\n\027\n\017max_num_records\032\004\b\001\020\004\n\025\n\rmax_read_time\032\004\b\001\020\004\n\037\n\031commit_offset_in_finalize\032\002\020\b\n\026\n\020timestamp_policy\032\002\020\a\022$6a700b0b-2839-492d-8629-9b3268d90919\022\272\001\t\002p\000\000\000\000\001\021bootstrap.servers\016localhost:9092\000\000\000\001\016my-first-topic6org.apache.kafka.common.serialization.StringSerializer6org.apache.kafka.common.serialization.StringSerializer\000\016ProcessingTime"
What's wrong with them? Anything that I'm missing?
I had this issue as well. It turned out the smoking gun was this line in the traceback:
Caused by: org.apache.beam.sdk.coders.CoderException: cannot encode a null byte[]
What it's saying is that there's a null value value somewhere and it can't encode it. For me, it turned out I was sending key=None in my kafka-python producer.send function and changing the key value to a string fixed the issue. For example:
with open("../data/sample_data.json") as fp:
for line in fp.readlines():
producer.send(KAFKA_TOPIC, key=str.encode("foo"), value=str.encode(line))
You can also set the key_serializer and value_serializer in the KafkaProducer object.
A heads up: even after fixing the null read there are still problems with reading from Kafka in Python outside of the Dataflow Runner. See: https://issues.apache.org/jira/browse/BEAM-11998
I had the same problem. As i figured out, ReadFromKafka wants to read the Data in a key:value format. My solution was to start the kafka-console-producer.sh with the option:
--property "parse.key=true" --property "key.separator=:"
and add data in the format key:value (f.e. name:peter instead of peter)
Related
・Python3.8
・JDK 11
I've started learning pyflink and write a code instructed by official web which is https://nightlies.apache.org/flink/flink-docs-master/docs/dev/python/datastream/intro_to_datastream_api/
And here is my code
from pyflink.common.serialization import JsonRowDeserializationSchema,JsonRowSerializationSchema
from pyflink.common import WatermarkStrategy, Row
from pyflink.common.serialization import Encoder
from pyflink.common.typeinfo import Types
from pyflink.datastream import StreamExecutionEnvironment
from pyflink.datastream.connectors import FlinkKafkaConsumer,FlinkKafkaProducer
def streaming():
env = StreamExecutionEnvironment.get_execution_environment()
deserialization_schema =JsonRowDeserializationSchema.builder().type_info(
type_info=Types.ROW([Types.INT(), Types.STRING()])).build()
kafka_consumer = FlinkKafkaConsumer(
topics='test',
deserialization_schema=deserialization_schema,
properties={'bootstrap.servers': 'localhost:9092','group.id': 'test_group'})
ds = env.add_source(kafka_consumer)
ds = ds.map(lambda a: Row(a % 4, 1),
output_type=Types.ROW([Types.LONG(), Types.LONG()])) \
.key_by(lambda a: a[0]) \
.reduce(lambda a, b: Row(a[0], a[1] + b[1]))
serialization_schema = JsonRowSerializationSchema.builder().with_type_info(
type_info=Types.ROW([Types.LONG(), Types.LONG()])).build()
kafka_sink = FlinkKafkaProducer(
topic='test_sink_topic',
serialization_schema=serialization_schema,
producer_config={'bootstrap.servers': 'localhost:9092',
'group.id': 'test_group'})
ds.add_sink(kafka_sink)
env.execute('datastream_api_demo')
if __name__ == '__main__':
streaming()
Firstly it said to me to specify jarfile. So I downloaded flink-connector-kafka and kafka-clients jarfile for each from https://mvnrepository.com/artifact/org.apache.flink and put them into pyflink/lib directory.
And now I'm at next step getting this error;
(pyflink_demo) C:\work\pyflink_demo>python Kafka_stream_Kafka.py
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.flink.api.java.ClosureCleaner (file:/C:/work/pyflink_demo/Lib/site-packages/pyflink/lib/flink-dist_2.11-1.14.4.jar) to field java.util.P
roperties.serialVersionUID
WARNING: Please consider reporting this to the maintainers of org.apache.flink.api.java.ClosureCleaner
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
Traceback (most recent call last):
File "Kafka_stream_Kafka.py", line 38, in <module>
streaming()
File "Kafka_stream_Kafka.py", line 33, in streaming
env.execute('datastream_api_demo')
File "C:\work\pyflink_demo\lib\site-packages\pyflink\datastream\stream_execution_environment.py", line 691, in execute
return JobExecutionResult(self._j_stream_execution_environment.execute(j_stream_graph))
File "C:\work\pyflink_demo\lib\site-packages\py4j\java_gateway.py", line 1285, in __call__
return_value = get_return_value(
File "C:\work\pyflink_demo\lib\site-packages\pyflink\util\exceptions.py", line 146, in deco
return f(*a, **kw)
File "C:\work\pyflink_demo\lib\site-packages\py4j\protocol.py", line 326, in get_return_value
raise Py4JJavaError(
py4j.protocol.Py4JJavaError: An error occurred while calling o0.execute.
: org.apache.flink.runtime.client.JobExecutionException: Job execution failed.
at org.apache.flink.runtime.jobmaster.JobResult.toJobExecutionResult(JobResult.java:144)
at org.apache.flink.runtime.minicluster.MiniClusterJobClient.lambda$getJobExecutionResult$3(MiniClusterJobClient.java:137)
at java.base/java.util.concurrent.CompletableFuture$UniApply.tryFire(CompletableFuture.java:642)
at java.base/java.util.concurrent.CompletableFuture.postComplete(CompletableFuture.java:506)
at java.base/java.util.concurrent.CompletableFuture.complete(CompletableFuture.java:2073)
at org.apache.flink.runtime.rpc.akka.AkkaInvocationHandler.lambda$invokeRpc$1(AkkaInvocationHandler.java:258)
at java.base/java.util.concurrent.CompletableFuture.uniWhenComplete(CompletableFuture.java:859)
at java.base/java.util.concurrent.CompletableFuture$UniWhenComplete.tryFire(CompletableFuture.java:837)
at java.base/java.util.concurrent.CompletableFuture.postComplete(CompletableFuture.java:506)
at java.base/java.util.concurrent.CompletableFuture.complete(CompletableFuture.java:2073)
at org.apache.flink.util.concurrent.FutureUtils.doForward(FutureUtils.java:1389)
at org.apache.flink.runtime.concurrent.akka.ClassLoadingUtils.lambda$null$1(ClassLoadingUtils.java:93)
at org.apache.flink.runtime.concurrent.akka.ClassLoadingUtils.runWithContextClassLoader(ClassLoadingUtils.java:68)
at org.apache.flink.runtime.concurrent.akka.ClassLoadingUtils.lambda$guardCompletionWithContextClassLoader$2(ClassLoadingUtils.java:92)
at java.base/java.util.concurrent.CompletableFuture.uniWhenComplete(CompletableFuture.java:859)
at java.base/java.util.concurrent.CompletableFuture$UniWhenComplete.tryFire(CompletableFuture.java:837)
at java.base/java.util.concurrent.CompletableFuture.postComplete(CompletableFuture.java:506)
at java.base/java.util.concurrent.CompletableFuture.complete(CompletableFuture.java:2073)
at org.apache.flink.runtime.concurrent.akka.AkkaFutureUtils$1.onComplete(AkkaFutureUtils.java:47)
at akka.dispatch.OnComplete.internal(Future.scala:300)
at akka.dispatch.OnComplete.internal(Future.scala:297)
at akka.dispatch.japi$CallbackBridge.apply(Future.scala:224)
at akka.dispatch.japi$CallbackBridge.apply(Future.scala:221)
at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:60)
at org.apache.flink.runtime.concurrent.akka.AkkaFutureUtils$DirectExecutionContext.execute(AkkaFutureUtils.java:65)
at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:68)
at scala.concurrent.impl.Promise$DefaultPromise.$anonfun$tryComplete$1(Promise.scala:284)
at scala.concurrent.impl.Promise$DefaultPromise.$anonfun$tryComplete$1$adapted(Promise.scala:284)
at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:284)
at akka.pattern.PromiseActorRef.$bang(AskSupport.scala:621)
at akka.pattern.PipeToSupport$PipeableFuture$$anonfun$pipeTo$1.applyOrElse(PipeToSupport.scala:24)
at akka.pattern.PipeToSupport$PipeableFuture$$anonfun$pipeTo$1.applyOrElse(PipeToSupport.scala:23)
at scala.concurrent.Future.$anonfun$andThen$1(Future.scala:532)
at scala.concurrent.impl.Promise.liftedTree1$1(Promise.scala:29)
at scala.concurrent.impl.Promise.$anonfun$transform$1(Promise.scala:29)
at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:60)
at akka.dispatch.BatchingExecutor$AbstractBatch.processBatch(BatchingExecutor.scala:63)
at akka.dispatch.BatchingExecutor$BlockableBatch.$anonfun$run$1(BatchingExecutor.scala:100)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:12)
at scala.concurrent.BlockContext$.withBlockContext(BlockContext.scala:81)
at akka.dispatch.BatchingExecutor$BlockableBatch.run(BatchingExecutor.scala:100)
at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:49)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(ForkJoinExecutorConfigurator.scala:48)
at java.base/java.util.concurrent.ForkJoinTask.doExec(ForkJoinTask.java:290)
at java.base/java.util.concurrent.ForkJoinPool$WorkQueue.topLevelExec(ForkJoinPool.java:1020)
at java.base/java.util.concurrent.ForkJoinPool.scan(ForkJoinPool.java:1656)
at java.base/java.util.concurrent.ForkJoinPool.runWorker(ForkJoinPool.java:1594)
at java.base/java.util.concurrent.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:183)
Caused by: org.apache.flink.runtime.JobException: Recovery is suppressed by NoRestartBackoffTimeStrategy
at org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.handleFailure(ExecutionFailureHandler.java:138)
at org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.getFailureHandlingResult(ExecutionFailureHandler.java:82)
at org.apache.flink.runtime.scheduler.DefaultScheduler.handleTaskFailure(DefaultScheduler.java:252)
at org.apache.flink.runtime.scheduler.DefaultScheduler.maybeHandleTaskFailure(DefaultScheduler.java:242)
at org.apache.flink.runtime.scheduler.DefaultScheduler.updateTaskExecutionStateInternal(DefaultScheduler.java:233)
at org.apache.flink.runtime.scheduler.SchedulerBase.updateTaskExecutionState(SchedulerBase.java:684)
at org.apache.flink.runtime.scheduler.SchedulerNG.updateTaskExecutionState(SchedulerNG.java:79)
at org.apache.flink.runtime.jobmaster.JobMaster.updateTaskExecutionState(JobMaster.java:444)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
at org.apache.flink.runtime.rpc.akka.AkkaRpcActor.lambda$handleRpcInvocation$1(AkkaRpcActor.java:316)
at org.apache.flink.runtime.concurrent.akka.ClassLoadingUtils.runWithContextClassLoader(ClassLoadingUtils.java:83)
at org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleRpcInvocation(AkkaRpcActor.java:314)
at org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleRpcMessage(AkkaRpcActor.java:217)
at org.apache.flink.runtime.rpc.akka.FencedAkkaRpcActor.handleRpcMessage(FencedAkkaRpcActor.java:78)
at org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleMessage(AkkaRpcActor.java:163)
at akka.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:24)
at akka.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:20)
at scala.PartialFunction.applyOrElse(PartialFunction.scala:123)
at scala.PartialFunction.applyOrElse$(PartialFunction.scala:122)
at akka.japi.pf.UnitCaseStatement.applyOrElse(CaseStatements.scala:20)
at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:171)
at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:172)
at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:172)
at akka.actor.Actor.aroundReceive(Actor.scala:537)
at akka.actor.Actor.aroundReceive$(Actor.scala:535)
at akka.actor.AbstractActor.aroundReceive(AbstractActor.scala:220)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:580)
at akka.actor.ActorCell.invoke(ActorCell.scala:548)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:270)
at akka.dispatch.Mailbox.run(Mailbox.scala:231)
at akka.dispatch.Mailbox.exec(Mailbox.scala:243)
... 5 more
Caused by: java.lang.RuntimeException: Failed to create stage bundle factory! INFO:root:Initializing Python harness: C:\work\pyflink_demo\lib\site-packages\pyflink\fn_execution\beam\bea
m_boot.py --id=4-1 --provision_endpoint=localhost:51794
INFO:root:Starting up Python harness in loopback mode.
at org.apache.flink.streaming.api.runners.python.beam.BeamPythonFunctionRunner.createStageBundleFactory(BeamPythonFunctionRunner.java:566)
at org.apache.flink.streaming.api.runners.python.beam.BeamPythonFunctionRunner.open(BeamPythonFunctionRunner.java:255)
at org.apache.flink.streaming.api.operators.python.AbstractPythonFunctionOperator.open(AbstractPythonFunctionOperator.java:131)
at org.apache.flink.streaming.api.operators.python.AbstractOneInputPythonFunctionOperator.open(AbstractOneInputPythonFunctionOperator.java:116)
at org.apache.flink.streaming.api.operators.python.PythonProcessOperator.open(PythonProcessOperator.java:59)
at org.apache.flink.streaming.runtime.tasks.RegularOperatorChain.initializeStateAndOpenOperators(RegularOperatorChain.java:110)
at org.apache.flink.streaming.runtime.tasks.StreamTask.restoreGates(StreamTask.java:711)
at org.apache.flink.streaming.runtime.tasks.StreamTaskActionExecutor$SynchronizedStreamTaskActionExecutor.call(StreamTaskActionExecutor.java:100)
at org.apache.flink.streaming.runtime.tasks.StreamTask.restoreInternal(StreamTask.java:687)
at org.apache.flink.streaming.runtime.tasks.StreamTask.restore(StreamTask.java:654)
at org.apache.flink.runtime.taskmanager.Task.runWithSystemExitMonitoring(Task.java:958)
at org.apache.flink.runtime.taskmanager.Task.restoreAndInvoke(Task.java:927)
at org.apache.flink.runtime.taskmanager.Task.doRun(Task.java:766)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:575)
at java.base/java.lang.Thread.run(Thread.java:834)
Caused by: org.apache.beam.vendor.guava.v26_0_jre.com.google.common.util.concurrent.UncheckedExecutionException: java.lang.IllegalStateException: Process died with exit code 0
at org.apache.beam.vendor.guava.v26_0_jre.com.google.common.cache.LocalCache$Segment.get(LocalCache.java:2050)
at org.apache.beam.vendor.guava.v26_0_jre.com.google.common.cache.LocalCache.get(LocalCache.java:3952)
at org.apache.beam.vendor.guava.v26_0_jre.com.google.common.cache.LocalCache.getOrLoad(LocalCache.java:3974)
at org.apache.beam.vendor.guava.v26_0_jre.com.google.common.cache.LocalCache$LocalLoadingCache.get(LocalCache.java:4958)
at org.apache.beam.vendor.guava.v26_0_jre.com.google.common.cache.LocalCache$LocalLoadingCache.getUnchecked(LocalCache.java:4964)
at org.apache.beam.runners.fnexecution.control.DefaultJobBundleFactory$SimpleStageBundleFactory.<init>(DefaultJobBundleFactory.java:451)
at org.apache.beam.runners.fnexecution.control.DefaultJobBundleFactory$SimpleStageBundleFactory.<init>(DefaultJobBundleFactory.java:436)
at org.apache.beam.runners.fnexecution.control.DefaultJobBundleFactory.forStage(DefaultJobBundleFactory.java:303)
at org.apache.flink.streaming.api.runners.python.beam.BeamPythonFunctionRunner.createStageBundleFactory(BeamPythonFunctionRunner.java:564)
... 14 more
Caused by: java.lang.IllegalStateException: Process died with exit code 0
at org.apache.beam.runners.fnexecution.environment.ProcessManager$RunningProcess.isAliveOrThrow(ProcessManager.java:75)
at org.apache.beam.runners.fnexecution.environment.ProcessEnvironmentFactory.createEnvironment(ProcessEnvironmentFactory.java:112)
at org.apache.beam.runners.fnexecution.control.DefaultJobBundleFactory$1.load(DefaultJobBundleFactory.java:252)
at org.apache.beam.runners.fnexecution.control.DefaultJobBundleFactory$1.load(DefaultJobBundleFactory.java:231)
at org.apache.beam.vendor.guava.v26_0_jre.com.google.common.cache.LocalCache$LoadingValueReference.loadFuture(LocalCache.java:3528)
at org.apache.beam.vendor.guava.v26_0_jre.com.google.common.cache.LocalCache$Segment.loadSync(LocalCache.java:2277)
at org.apache.beam.vendor.guava.v26_0_jre.com.google.common.cache.LocalCache$Segment.lockedGetOrLoad(LocalCache.java:2154)
at org.apache.beam.vendor.guava.v26_0_jre.com.google.common.cache.LocalCache$Segment.get(LocalCache.java:2044)
... 22 more
I tried to figure out what's going on and found very similar question What's wrong with my Pyflink setup that Python UDFs throw py4j exceptions?
It says that was caused by network proxy problem. JVM and python uses local socket communication. So set local communication with no proxy.
I set environment valuable "no_proxy" but it doesn't work.
enter image description here
Could anyone provide solution for this?
There is no useful information in the exception stack to help to identify the problem. This should be caused by a known issue(FLINK-26543, already solved, however still not released). This issue only occurs in loopback mode which is enabled by default when executing the job locally.
For now, you could try to force the job run in process mode instead of loopback mode by setting environment variable _python_worker_execution_mode to process. After doing this, you should see the root cause of the failure.
Besides, there is also a small issue in your code. I guess you meant ds.map(lambda a: Row(a[0] % 4, 1), output_type=Types.ROW([Types.LONG(), Types.LONG()])) instead of ds.map(lambda a: Row(a % 4, 1), output_type=Types.ROW([Types.LONG(), Types.LONG()])) as it doesn't support % operation in Row object.
I have tried the script. I am not quite sure what caused the error. Try to start kafka first and create the topics, before running the script. Or start kafka and run the script a second time after first failure.
I have a pyspark application that will transform csv to parquet and before this happen I'm copying some S3 object from a bucket to another.
pyspark with spark 2.4, emr 5.27, maximizeResourceAllocation set to true
I have various csv files size, from 80kb to 500mb.
Nonetheless, my EMR cluster (it doesn't fail on local with spark-submit) fails at 70% completion on a file that is 166mb (a previous at 480mb succeeded).
The job is simple:
def organise_adwords_csv():
s3 = boto3.resource('s3')
bucket = s3.Bucket(S3_ORIGIN_RAW_BUCKET)
for obj in bucket.objects.filter(Prefix=S3_ORIGIN_ADWORDS_RAW + "/"):
key = obj.key
copy_source = {
'Bucket': S3_ORIGIN_RAW_BUCKET,
'Key': key
}
key_tab = obj.key.split("/")
if len(key_tab) < 5:
print("continuing from length", obj)
continue
file_name = ''.join(key_tab[len(key_tab)-1:len(key_tab)])
if file_name == '':
print("continuing", obj)
continue
table = file_name.split("_")[1].replace("-", "_")
new_path = "{0}/{1}/{2}".format(S3_DESTINATION_ORDERED_ADWORDS_RAW_PATH, table, file_name)
print("new_path", new_path) <- the last print will end here
try:
s3.meta.client.copy(copy_source, S3_DESTINATION_RAW_BUCKET, new_path)
print("copy done")
except Exception as e:
print(e)
print("an exception occured while copying")
if __name__=='__main__':
organise_adwords_csv()
print("copy Final done") <- never printed
spark = SparkSession.builder.appName("adwords_transform") \
...
but, in the stdout, no errors / exception are showing.
In stderr logs:
19/10/09 16:16:57 INFO ApplicationMaster: Waiting for spark context initialization...
19/10/09 16:18:37 ERROR ApplicationMaster: Uncaught exception:
java.util.concurrent.TimeoutException: Futures timed out after [100000 milliseconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:223)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:227)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
at org.apache.spark.deploy.yarn.ApplicationMaster.runDriver(ApplicationMaster.scala:468)
at org.apache.spark.deploy.yarn.ApplicationMaster.org$apache$spark$deploy$yarn$ApplicationMaster$$runImpl(ApplicationMaster.scala:305)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply$mcV$sp(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:779)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1844)
at org.apache.spark.deploy.yarn.ApplicationMaster.doAsUser(ApplicationMaster.scala:778)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:244)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:803)
at org.apache.spark.deploy.yarn.ApplicationMaster.main(ApplicationMaster.scala)
19/10/09 16:18:37 INFO ApplicationMaster: Final app status: FAILED, exitCode: 13, (reason: Uncaught exception: java.util.concurrent.TimeoutException: Futures timed out after [100000 milliseconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:223)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:227)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
at org.apache.spark.deploy.yarn.ApplicationMaster.runDriver(ApplicationMaster.scala:468)
at org.apache.spark.deploy.yarn.ApplicationMaster.org$apache$spark$deploy$yarn$ApplicationMaster$$runImpl(ApplicationMaster.scala:305)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply$mcV$sp(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:779)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1844)
at org.apache.spark.deploy.yarn.ApplicationMaster.doAsUser(ApplicationMaster.scala:778)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:244)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:803)
at org.apache.spark.deploy.yarn.ApplicationMaster.main(ApplicationMaster.scala)
)
19/10/09 16:18:37 INFO ShutdownHookManager: Shutdown hook called
I'm completely blind, I don't understand what is failing / why.
How can I figure that out? On local it works like a charm (but super slow of course)
Edit:
After many tries I can confirm that the function:
s3.meta.client.copy(copy_source, S3_DESTINATION_RAW_BUCKET, new_path)
make the EMR cluster timeout, even tho it processed 80% of the files already.
Does anyone have a recommendation about this?
s3.meta.client.copy(copy_source, S3_DESTINATION_RAW_BUCKET, new_path)
This will fail for any source object larger than 5 GB. please use multipart upload in AWS. See https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html#multipartupload
I'm trying to develop a K-means model in Flink (Scala), using Zeppelin.
This is part of my simple code:
//Reading data
val mapped : DataSet[Vector] = data.map {x => DenseVector (x._1,x._2) }
//Create algorithm
val knn = KNN()
.setK(3)
.setBlocks(10)
.setDistanceMetric(SquaredEuclideanDistanceMetric())
.setUseQuadTree(false)
.setSizeHint(CrossHint.SECOND_IS_SMALL)
...
//Just to learn I use the same data predicting the model
val result = knn.predict(mapped).collect()
When I print the data or to use predict method, i got this ERROR:
org.apache.flink.client.program.ProgramInvocationException: The program execution failed: Job execution failed.
at org.apache.flink.client.program.ClusterClient.run(ClusterClient.java:409)
at org.apache.flink.client.program.StandaloneClusterClient.submitJob(StandaloneClusterClient.java:95)
at org.apache.flink.client.program.ClusterClient.run(ClusterClient.java:382)
at org.apache.flink.client.program.ClusterClient.run(ClusterClient.java:369)
at org.apache.flink.client.program.ClusterClient.run(ClusterClient.java:344)
at org.apache.flink.client.RemoteExecutor.executePlanWithJars(RemoteExecutor.java:211)
at org.apache.flink.client.RemoteExecutor.executePlan(RemoteExecutor.java:188)
at org.apache.flink.api.java.RemoteEnvironment.execute(RemoteEnvironment.java:172)
at org.apache.flink.api.java.ExecutionEnvironment.execute(ExecutionEnvironment.java:896)
at org.apache.flink.api.scala.ExecutionEnvironment.execute(ExecutionEnvironment.scala:637)
at org.apache.flink.api.scala.DataSet.collect(DataSet.scala:547)
... 36 elided
Caused by: org.apache.flink.runtime.client.JobExecutionException: Job execution failed.
at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$handleMessage$1$$anonfun$applyOrElse$7.apply$mcV$sp(JobManager.scala:822)
at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$handleMessage$1$$anonfun$applyOrElse$7.apply(JobManager.scala:768)
at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$handleMessage$1$$anonfun$applyOrElse$7.apply(JobManager.scala:768)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:41)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:401)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.pollAndExecAll(ForkJoinPool.java:1253)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1346)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
Caused by: org.apache.flink.api.common.io.ParseException: Line could not be parsed: '-6.59 -44.68'
ParserError NUMERIC_VALUE_FORMAT_ERROR
Expect field types: class java.lang.Double, class java.lang.Double
in file: /home/borja/flink/kmeans/points
at org.apache.flink.api.common.io.GenericCsvInputFormat.parseRecord(GenericCsvInputFormat.java:407)
at org.apache.flink.api.java.io.CsvInputFormat.readRecord(CsvInputFormat.java:110)
at org.apache.flink.api.common.io.DelimitedInputFormat.nextRecord(DelimitedInputFormat.java:470)
at org.apache.flink.api.java.io.CsvInputFormat.nextRecord(CsvInputFormat.java:78)
at org.apache.flink.runtime.operators.DataSourceTask.invoke(DataSourceTask.java:162)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:585)
at java.lang.Thread.run(Thread.java:748)
I do not know if it's my fault loading the data or it has related with something like that.
Thanks for any help! :)
You haven't shown us the code you are using to read and parse the data, which is where the error is occurring. But given the error message, I'll hazard a guess that you are using readCSVFile with data that is delimited by spaces or tabs, and didn't specify the fieldDelimiter (which defaults to comma). If that's the case, see the docs for how to configure the CSV parser.
I am using storm 1.0.1 and Kafka 0.10.0.0 with storm-kafka-client 1.0.3.
please find the code config I have below.
kafkaConsumerProps.put(KafkaSpoutConfig.Consumer.KEY_DESERIALIZER, "org.apache.kafka.common.serialization.ByteArrayDeserializer");
kafkaConsumerProps.put(KafkaSpoutConfig.Consumer.VALUE_DESERIALIZER, "org.apache.kafka.common.serialization.ByteArrayDeserializer");
KafkaSpoutStreams kafkaSpoutStreams = new KafkaSpoutStreamsNamedTopics.Builder(new Fields(fieldNames), topics)
.build();
KafkaSpoutRetryService retryService = new KafkaSpoutRetryExponentialBackoff(TimeInterval.microSeconds(500),
TimeInterval.milliSeconds(2), Integer.MAX_VALUE, TimeInterval.seconds(10));
KafkaSpoutTuplesBuilder tuplesBuilder = new KafkaSpoutTuplesBuilderNamedTopics.Builder(new TestTupleBuilder(topics))
.build();
KafkaSpoutConfig kafkaSpoutConfig = new KafkaSpoutConfig.Builder<String, String>(kafkaConsumerProps, kafkaSpoutStreams, tuplesBuilder, retryService)
.setOffsetCommitPeriodMs(10_000)
.setFirstPollOffsetStrategy(LATEST)
.setMaxRetries(5)
.setMaxUncommittedOffsets(250)
.build();
When I fail the tuple its not getting replayed. Spout throws below error.
Please let me know why it's throwing nullpointer exception.
53501 [Thread-359-test-spout-executor[295 295]] ERROR o.a.s.util - Async loop died!
java.lang.NullPointerException
at org.apache.storm.kafka.spout.KafkaSpout.doSeekRetriableTopicPartitions(KafkaSpout.java:260) ~[storm-kafka-client-1.0.3.jar:1.0.3]
at org.apache.storm.kafka.spout.KafkaSpout.pollKafkaBroker(KafkaSpout.java:248) ~[storm-kafka-client-1.0.3.jar:1.0.3]
at org.apache.storm.kafka.spout.KafkaSpout.nextTuple(KafkaSpout.java:203) ~[storm-kafka-client-1.0.3.jar:1.0.3]
at org.apache.storm.daemon.executor$fn__7885$fn__7900$fn__7931.invoke(executor.clj:645) ~[storm-core-1.0.1.jar:1.0.1]
at org.apache.storm.util$async_loop$fn__625.invoke(util.clj:484) [storm-core-1.0.1.jar:1.0.1]
at clojure.lang.AFn.run(AFn.java:22) [clojure-1.8.0.jar:?]
at java.lang.Thread.run(Thread.java:745) [?:1.8.0_102]
53501 [Thread-359-test-spout-executor[295 295]] ERROR o.a.s.d.executor -
java.lang.NullPointerException
at org.apache.storm.kafka.spout.KafkaSpout.doSeekRetriableTopicPartitions(KafkaSpout.java:260) ~[storm-kafka-client-1.0.3.jar:1.0.3]
at org.apache.storm.kafka.spout.KafkaSpout.pollKafkaBroker(KafkaSpout.java:248) ~[storm-kafka-client-1.0.3.jar:1.0.3]
at org.apache.storm.kafka.spout.KafkaSpout.nextTuple(KafkaSpout.java:203) ~[storm-kafka-client-1.0.3.jar:1.0.3]
at org.apache.storm.daemon.executor$fn__7885$fn__7900$fn__7931.invoke(executor.clj:645) ~[storm-core-1.0.1.jar:1.0.1]
at org.apache.storm.util$async_loop$fn__625.invoke(util.clj:484) [storm-core-1.0.1.jar:1.0.1]
at clojure.lang.AFn.run(AFn.java:22) [clojure-1.8.0.jar:?]
at java.lang.Thread.run(Thread.java:745) [?:1.8.0_102]
53527 [Thread-359-test-spout-executor[295 295]] ERROR o.a.s.util - Halting process: ("Worker died")
java.lang.RuntimeException: ("Worker died")
at org.apache.storm.util$exit_process_BANG_.doInvoke(util.clj:341) [storm-core-1.0.1.jar:1.0.1]
at clojure.lang.RestFn.invoke(RestFn.java:423) [clojure-1.8.0.jar:?]
at org.apache.storm.daemon.worker$fn__8554$fn__8555.invoke(worker.clj:761) [storm-core-1.0.1.jar:1.0.1]
at org.apache.storm.daemon.executor$mk_executor_data$fn__7773$fn__7774.invoke(executor.clj:271) [storm-core-1.0.1.jar:1.0.1]
at org.apache.storm.util$async_loop$fn__625.invoke(util.clj:494) [storm-core-1.0.1.jar:1.0.1]
at clojure.lang.AFn.run(AFn.java:22) [clojure-1.8.0.jar:?]
at java.lang.Thread.run(Thread.java:745) [?:1.8.0_102]
Please find the complete spout configs below
{key.deserializer=org.apache.kafka.common.serialization.ByteArrayDeserializer, value.deserializer=org.apache.kafka.common.serialization.ByteArrayDeserializer, group.id=test-group, ssl.keystore.location=C:/test.jks, bootstrap.servers=localhost:1000, auto.commit.interval.ms=1000, security.protocol=SSL, enable.auto.commit=true, ssl.truststore.location=C:/test1.jks, ssl.keystore.password=pass123, ssl.key.password=pass123, ssl.truststore.password=pass123, session.timeout.ms=30000, auto.offset.reset=latest}
Storm 1.0.1 consists of storm-kafka-client in beta quality. We have fixed few issues and more stable version is available in Storm 1.1 release and can be used against Kafka 0.10 onwards.
In your topology you can make dependency against storm-kafka-client version 1.1 and kafka-clients dependency with appropriate version. You don't need to upgrade storm cluster itself.
I had enable.auto.commit=true making the value as false resolved the issue for me.
I'm trying to read in some json, infer a schema, and write it out again as parquet to s3 (s3a). For some reason, about a third of the way through the writing portion of the run, spark always errors out with the error included below. I can't find any obvious reasons for the issue: it isn't out of memory; there are no long GC pauses. There don't seem to be any additional error messages in the logs of the individual executors.
The script runs fine on another set of data that I have, which is of a very similar structure, but several orders of magnitude smaller.
I am running spark 2.0.1-hadoop-2.7 and am using the FileOutputCommitter. The algorithm version doesn't seem to matter.
Edit:
This does not appear to be a problem in badly formed json or corrupted files. I have unzipped and read in each file individually with no error.
Here's a simplified version of the script:
object Foo {
def parseJson(json: String): Option[Map[String, Any]] = {
if (json == null)
Some(Map())
else
parseOpt(json).map((j: JValue) => j.values.asInstanceOf[Map[String, Any]])
}
}
}
// read in as text and parse json using json4s
val jsonRDD: RDD[String] = sc.textFile(inputPath)
.map(row -> Foo.parseJson(row))
// infer a schema that will encapsulate the most rows in a sample of size sampleRowNum
val schema: StructType = Infer.getMostCommonSchema(sc, jsonRDD, sampleRowNum)
// get documents compatibility with schema
val jsonWithCompatibilityRDD: RDD[(String, Boolean)] = jsonRDD
.map(js => (js, Infer.getSchemaCompatibility(schema, Infer.inferSchema(js)).toBoolean))
.repartition(partitions)
val jsonCompatibleRDD: RDD[String] = jsonWithCompatibilityRDD
.filter { case (js: String, compatible: Boolean) => compatible }
.map { case (js: String, _: Boolean) => js }
// create a dataframe from documents with compatible schema
val dataFrame: DataFrame = spark.read.schema(schema).json(jsonCompatibleRDD)
It completes the earlier schema inferring steps successfully. The error itself occurs on the last line, but I suppose that could encompass at least the immediately preceding statemnt, if not earlier:
org.apache.spark.SparkException: Task failed while writing rows
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:261)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(InsertIntoHadoopFsRelationCommand.scala:143)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(InsertIntoHadoopFsRelationCommand.scala:143)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.RuntimeException: Failed to commit task
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.org$apache$spark$sql$execution$datasources$DefaultWriterContainer$$commitTask$1(WriterContainer.scala:275)
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer$$anonfun$writeRows$1.apply$mcV$sp(WriterContainer.scala:257)
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer$$anonfun$writeRows$1.apply(WriterContainer.scala:252)
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer$$anonfun$writeRows$1.apply(WriterContainer.scala:252)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1345)
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:258)
... 8 more
Suppressed: java.lang.NullPointerException
at org.apache.parquet.hadoop.InternalParquetRecordWriter.flushRowGroupToStore(InternalParquetRecordWriter.java:147)
at org.apache.parquet.hadoop.InternalParquetRecordWriter.close(InternalParquetRecordWriter.java:113)
at org.apache.parquet.hadoop.ParquetRecordWriter.close(ParquetRecordWriter.java:112)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.close(ParquetFileFormat.scala:569)
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.org$apache$spark$sql$execution$datasources$DefaultWriterContainer$$abortTask$1(WriterContainer.scala:282)
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer$$anonfun$writeRows$2.apply$mcV$sp(WriterContainer.scala:258)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1354)
... 9 more
Caused by: com.amazonaws.AmazonClientException: Unable to unmarshall response (Failed to parse XML document with handler class com.amazonaws.services.s3.model.transform.XmlResponsesSaxParser$ListBucketHandler). Response Code: 200, Response Text: OK
at com.amazonaws.http.AmazonHttpClient.handleResponse(AmazonHttpClient.java:738)
at com.amazonaws.http.AmazonHttpClient.executeHelper(AmazonHttpClient.java:399)
at com.amazonaws.http.AmazonHttpClient.execute(AmazonHttpClient.java:232)
at com.amazonaws.services.s3.AmazonS3Client.invoke(AmazonS3Client.java:3528)
at com.amazonaws.services.s3.AmazonS3Client.invoke(AmazonS3Client.java:3480)
at com.amazonaws.services.s3.AmazonS3Client.listObjects(AmazonS3Client.java:604)
at org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:962)
at org.apache.hadoop.fs.s3a.S3AFileSystem.deleteUnnecessaryFakeDirectories(S3AFileSystem.java:1147)
at org.apache.hadoop.fs.s3a.S3AFileSystem.finishedWrite(S3AFileSystem.java:1136)
at org.apache.hadoop.fs.s3a.S3AOutputStream.close(S3AOutputStream.java:142)
at org.apache.hadoop.fs.FSDataOutputStream$PositionCache.close(FSDataOutputStream.java:72)
at org.apache.hadoop.fs.FSDataOutputStream.close(FSDataOutputStream.java:106)
at org.apache.parquet.hadoop.ParquetFileWriter.end(ParquetFileWriter.java:400)
at org.apache.parquet.hadoop.InternalParquetRecordWriter.close(InternalParquetRecordWriter.java:117)
at org.apache.parquet.hadoop.ParquetRecordWriter.close(ParquetRecordWriter.java:112)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.close(ParquetFileFormat.scala:569)
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.org$apache$spark$sql$execution$datasources$DefaultWriterContainer$$commitTask$1(WriterContainer.scala:267)
... 13 more
Caused by: com.amazonaws.AmazonClientException: Failed to parse XML document with handler class com.amazonaws.services.s3.model.transform.XmlResponsesSaxParser$ListBucketHandler
at com.amazonaws.services.s3.model.transform.XmlResponsesSaxParser.parseXmlInputStream(XmlResponsesSaxParser.java:150)
at com.amazonaws.services.s3.model.transform.XmlResponsesSaxParser.parseListBucketObjectsResponse(XmlResponsesSaxParser.java:279)
at com.amazonaws.services.s3.model.transform.Unmarshallers$ListObjectsUnmarshaller.unmarshall(Unmarshallers.java:75)
at com.amazonaws.services.s3.model.transform.Unmarshallers$ListObjectsUnmarshaller.unmarshall(Unmarshallers.java:72)
at com.amazonaws.services.s3.internal.S3XmlResponseHandler.handle(S3XmlResponseHandler.java:62)
at com.amazonaws.services.s3.internal.S3XmlResponseHandler.handle(S3XmlResponseHandler.java:31)
at com.amazonaws.http.AmazonHttpClient.handleResponse(AmazonHttpClient.java:712)
... 29 more
Caused by: org.xml.sax.SAXParseException; lineNumber: 1; columnNumber: 2; XML document structures must start and end within the same entity.
at org.apache.xerces.util.ErrorHandlerWrapper.createSAXParseException(Unknown Source)
at org.apache.xerces.util.ErrorHandlerWrapper.fatalError(Unknown Source)
at org.apache.xerces.impl.XMLErrorReporter.reportError(Unknown Source)
at org.apache.xerces.impl.XMLErrorReporter.reportError(Unknown Source)
at org.apache.xerces.impl.XMLErrorReporter.reportError(Unknown Source)
at org.apache.xerces.impl.XMLScanner.reportFatalError(Unknown Source)
at org.apache.xerces.impl.XMLDocumentFragmentScannerImpl.endEntity(Unknown Source)
at org.apache.xerces.impl.XMLDocumentScannerImpl.endEntity(Unknown Source)
at org.apache.xerces.impl.XMLEntityManager.endEntity(Unknown Source)
at org.apache.xerces.impl.XMLEntityScanner.load(Unknown Source)
at org.apache.xerces.impl.XMLEntityScanner.skipChar(Unknown Source)
at org.apache.xerces.impl.XMLDocumentScannerImpl$PrologDispatcher.dispatch(Unknown Source)
at org.apache.xerces.impl.XMLDocumentFragmentScannerImpl.scanDocument(Unknown Source)
at org.apache.xerces.parsers.XML11Configuration.parse(Unknown Source)
at org.apache.xerces.parsers.XML11Configuration.parse(Unknown Source)
at org.apache.xerces.parsers.XMLParser.parse(Unknown Source)
at org.apache.xerces.parsers.AbstractSAXParser.parse(Unknown Source)
at com.amazonaws.services.s3.model.transform.XmlResponsesSaxParser.parseXmlInputStream(XmlResponsesSaxParser.java:141)
... 35 more
Here's my conf:
spark.executor.extraJavaOptions -XX:+UseG1GC -XX:MaxPermSize=1G -XX:+HeapDumpOnOutOfMemoryError
spark.executor.memory 16G
spark.executor.uri https://s3.amazonaws.com/foo/spark-2.0.1-bin-hadoop2.7.tgz
spark.hadoop.fs.s3a.impl org.apache.hadoop.fs.s3a.S3AFileSystem
spark.hadoop.fs.s3a.buffer.dir /raid0/spark
spark.hadoop.fs.s3n.buffer.dir /raid0/spark
spark.hadoop.fs.s3a.connection.timeout 500000
spark.hadoop.fs.s3n.multipart.uploads.enabled true
spark.hadoop.parquet.block.size 2147483648
spark.hadoop.parquet.enable.summary-metadata false
spark.jars.packages com.databricks:spark-avro_2.11:3.0.1
spark.local.dir /raid0/spark
spark.mesos.coarse false
spark.mesos.constraints priority:1
spark.network.timeout 600
spark.rpc.message.maxSize 500
spark.speculation false
spark.sql.parquet.mergeSchema false
spark.sql.planner.externalSort true
spark.submit.deployMode client
spark.task.cpus 1
I can think for three possible reasons for this problem.
JVM version. AWS SDK checks for the following ones. "1.6.0_06",
"1.6.0_13", "1.6.0_17", "1.6.0_65", "1.7.0_45". If you are using one
of them, try upgrading.
Old AWS SDK. Refer to
https://github.com/aws/aws-sdk-java/issues/460 for a workaround.
If you lots of files in the directory where you are writing these files, you might be hitting https://issues.apache.org/jira/browse/HADOOP-13164. Consider increasing the timeout to larger values.
A SAXParseException may indicate a badly formatted XML file. Since the job fails roughly a third of the way through consistently, this means it's probably failing in the same place every time (a file whose partition is roughly a third of the way through the partition list).
Can you paste your script? It may be possible to wrap the Spark step in a try/catch loop that will print out the file if this error occurs, which will let you easily zoom in on the problem.
From the logs:
Caused by: org.xml.sax.SAXParseException; lineNumber: 1; columnNumber: 2; XML document structures must start and end within the same entity.
and
Caused by: com.amazonaws.AmazonClientException: Failed to parse XML document with handler class com.amazonaws.services.s3.model.transform.XmlResponsesSaxParser$ListBucketHandler
It looks like you have a corrupted/incorrectly formatted file, and your error is actually occurring during the read portion of the task. You could confirm this by trying another operation that will force the read such as count().
If confirmed, the goal would then be to find the corrupted file. You could do this by listing the s3 files, sc.parallelize() that list, and then trying to read the files in a custom function using map().
import boto3
from pyspark.sql import Row
def scanKeys(startKey, endKey):
bucket = boto3.resource('s3').Bucket('bucketName')
for obj in bucket.objects.filter(Prefix='prefix', Marker=startKey):
if obj.key < endKey:
yield obj.key
else:
return
def testFile(s3Path):
s3obj = boto3.resource('s3').Object(bucket_name='bucketName', key=key)
body = s3obj.get()['Body']
...
logic to test file format, or use a try/except and attempt to parse it
...
if fileFormatedCorrectly == True:
return Row(status='Good', key = s3Path)
else:
return Row(status='Fail', key = s3Path)
keys = list(scanKeys(startKey, endKey))
keyListRdd = sc.parallelize(keys, 1000)
keyListRdd.map(testFile).filter(lambda x: x.asDict.get('status') == 'Fail').collect()
This will return the s3 paths for the incorrectly formatted files
For Googlers:
If you:
have a versioned bucket
use s3a://
see ListBucketHandler and listObjects in your error message
Quick solution:
use s3:// instead of s3a://, which will use S3 driver provided by EMR
You may see this error because s3a:// in older versions uses S3::ListObjects (v1) API instead of S3::ListObjectsV2. The former would return extra info like owner, and is not robust against large number of deletion markers. Newer versions of the s3a:// driver solved this problem, but you could always use the s3:// driver instead.
Quote:
the V1 list API experience always returns 5000 entries (as set in fs.s3a.paging.maximum
except for the final entry
if you have versioning turned on in your bucket, deleted entries retain tombstone markers with references to their versions
which will surface in the S3-side of list calls, but get stripped out from the response
so...for a very large tree, you may end up S3 having to keep a channel open while is skips of thousands to millions of deleted
objects before it can find actual ones to return.
which can time out connections.
Quote:
Introducing a new version of the ListObjects (ListObjectsV2) API that allows listing objects with a large number of delete markers.
Quote:
If there are thousands of delete markers, the list operation might timeout。