anandchangediya edited a comment on issue #21038: [SPARK-22968][DStream] Throw an exception on partition revoking issue URL: https://github.com/apache/spark/pull/21038#issuecomment-541604823 @koeninger According to Kafka documentation `If all the consumer instances have the same consumer group, then the records will effectively be load-balanced over the consumer instances` This means I can have multiple consumers with the same groupId which can help me to load balance my application and scale accordingly. I don't know why it is said "fundamentally wrong" to have multiple consumers with the same groupId in spark. So how can I achieve scalability to listen to a single partition and increase consumption rate with multiple spark consumers? Is this the spark design fault or any other way to achieve scaling which I am unaware of? @SehanRathnayake Any thoughts?
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