Hi all, I’m currently trying to understand Flink’s Kafka Connector and how parallelism affects it. So, I am running the flink playground click count job and the parallelism is set to 2 by default.
However, I don’t see the 2nd subtask of the Kafka Connector sending any records: https://imgur.com/cA5ucSg. Do I need to rebalance after reading from kafka? ``` clicks = clicks .keyBy(ClickEvent::getPage) .map(new BackpressureMap()) .name("Backpressure"); ``` `clicks` is the kafka click stream. From my reading in the operator docs, it seems counterintuitive to do a `rebalance()` when I am already doing a `keyBy()`. So, my questions: 1. How do I make use of the 2nd subtask? 2. Does the number of partitions have some sort of correspondence with the parallelism of the source operator? If so, is there a general statement to be made about parallelism across all source operators? Thanks, Mason
