A civic portal must feed both Spark jobs and a hot counter store from the same page events. Which ingestion pattern fits the web analyzer?
Select an answer to reveal the explanation.
Short Explanation
One topic, many listeners—that is the Kafka idea for city page hits. Spark can crunch history while a hot store ticks live counters from the same stream. Publish once, consume many times, and stop forking brittle copy pipelines.
Full Explanation
Integrating Kafka-style ingestion into a Cap. 10 web analyzer lets page events fan out to multiple processors. Spark can handle deeper analytics while a hot counter store serves live popularity, both reading the same topic. That pattern reuses Cap. 8 ingestion concepts inside the civic portal analytics stack.