Explain the concept of Spark’s block manager.

Spark’s block manager is a component responsible for managing data blocks in memory and on disk across the cluster. It plays a vital role in caching and efficient data storage for RDDs (Resilient Distributed Datasets) and data frames. The block manager stores the data blocks in a serialized form and keeps track of their location and status. It manages the movement of data blocks between memory and disk, as well as data replication for fault tolerance. The block manager also facilitates data sharing among tasks within the same executor, promoting data locality and reducing network overhead.