A city operations center streams 311 and AVL events through messaging topics that Spark jobs continuously consume. What typical pairing does this illustrate?
Select an answer to reveal the explanation.
Short Explanation
Kafka is the city's radio channel; Spark is the dispatch board listening in. Events hop on the topic, and Spark jobs tune in to process them as they arrive.
Full Explanation
In many Big Data architectures, Kafka or similar logs handle durable, scalable ingestion while Spark Streaming or Structured Streaming consumes those topics for analytics. Municipal event streams such as 311 and AVL commonly follow this pairing. Understanding the bridge prepares learners for the data-ingestion domain that focuses on Kafka itself.