How is RDD in Apache Spark different from Distributed Storage Management?

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- September 20, 2018 at 4:46 pm #5929
  
  DataFlair Team
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  Differentiate Apache Spark different from Distributed Storage Management.
  Compare Apache Spark different from Distributed Storage Management.
- September 20, 2018 at 4:46 pm #5931
  
  DataFlair Team
  Spectator
  
  Some of the differences between an RDD and Distributed Storage are as follows:
  
  Resilient Distributed Dataset (RDD) is the primary abstraction of data for Apache Sparkframework.
  Distributed Storage is simply a file system which works on multiple nodes.
  
  RDDs store data in-memory (unless explicitly cached).
  Distributed Storage stores data in persistent storage.
  
  RDDs can re-compute itself in the case of failure or data loss.
  If data is lost from the Distributed Storage system it is gone forever (unless there is an internal replication system).
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