Transit analysts need to join massive fare-tap logs to daily weather observations by date using Hadoop-era batch processing. Which statement best frames the MapReduce role?

Distributed join patterns—map-side or reduce-side—are a core MapReduce use-case class when datasets are too large for single-node processing. Joining fare taps to weather by date overnight fits that batch profile. Kafka excels at ingestion and streaming; it is not the only path for historical batch joins.