Spark can be used to perform maintenance operations on Cassandra data. There are three basic patterns for interacting with Cassandra using Spark: read-transform-write (1:1), read-transform-write (1:m), and read-filter-delete (m:1). Deletes are tricky in Cassandra and require either selecting records to delete and issuing deletes or selecting records to keep and rewriting/deleting partitions. The document provides examples of using Spark for cache maintenance, trimming user history, publishing data, and multitenant backup and recovery.