Vivek Agarwal created BEAM-4803:
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Summary: Beam spark runner not working properly with kafka
Key: BEAM-4803
URL: https://issues.apache.org/jira/browse/BEAM-4803
Project: Beam
Issue Type: Bug
Components: io-java-kafka, runner-spark
Affects Versions: 2.4.0
Reporter: Vivek Agarwal
Assignee: Raghu Angadi
We are running a beam stream processing job on a spark runner, which reads from
a kafka topic using kerberos authentication. We are using java-io-kafka v2.4.0
to read from kafka topic in the pipeline. The issue is that the kafkaIO client
is continuously creating a new kafka consumer with specified config, doing
kerberos login every time. Also, there are spark streaming jobs which get
spawned for the unbounded source, every second or so even when there is no data
in the kafka topic. Log has these jobs-
INFO SparkContext: Starting job: [email protected]:172
We can see in the logs
INFO MicrobatchSource: No cache reader found for split:
[org.apache.beam.sdk.io.kafka.KafkaUnboundedSource@2919a728]. Creating new
reader at checkpoint mark...
And then it creates new consumer doing fresh kerberos login, which is creating
issues.
We are unsure of what should be correct behavior here and why so many spark
streaming jobs are getting created. We tried the beam code with flink runner
and did not find this issue there. Can someone point to the correct settings
for using unbounded kafka source with spark runner using beam?
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