Michal Walenia created BEAM-8207:
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Summary: KafkaIOITs generate different hashes each run, sometimes
dropping records
Key: BEAM-8207
URL: https://issues.apache.org/jira/browse/BEAM-8207
Project: Beam
Issue Type: Bug
Components: io-java-kafka, testing
Reporter: Michal Walenia
While working to adapt Java's KafkaIOIT to work with a large dataset generated
by a SyntheticSource I encountered a problem. I want to push 100M records
through a Kafka topic, verify data correctness and at the same time check the
performance of KafkaIO.Write and KafkaIO.Read.
To perform the tests I'm using a Kafka cluster on Kubernetes from the Beam repo
([here|https://github.com/apache/beam/tree/master/.test-infra/kubernetes/kafka-cluster]).
The expected result would be that first the records are generated in a
deterministic way (using hashes of list positions as Random seeds), next they
are written to Kafka - this concludes the write pipeline.
As for reading and correctness checking - first, the data is read from the
topic and after being decoded into String representations, a hashcode of the
whole PCollection is calculated (For details, check KafkaIOIT.java).
During the testing I ran into several problems:
1. When all the records are read from the Kafka topic, the hash is different
each time.
2. Sometimes not all the records are read and the Dataflow task waits for the
input indefinitely, occasionally throwing exceptions.
I believe there are two possible causes of this behavior:
either there is something wrong with the Kafka cluster configuration
or KafkaIO behaves erratically on high data volumes, duplicating and/or
dropping records.
Second option seems troubling and I would be grateful for help with the first.
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