Spark has the following benefits over MapReduce :
* Due to the availability of in-memory processing, Spark implements the processing around 10 to 100 times faster than Hadoop MapReduce whereas MapReduce makes use of persistence storage for any of the data processing tasks.
* Unlike Hadoop, Spark provides inbuilt libraries to perform multiple tasks from the same core like batch processing, Steaming, Machine learning, Interactive SQL queries. However, Hadoop only supports batch processing.
* Hadoop is highly disk-dependent whereas Spark promotes caching and in-memory data storage.
* Spark is capable of performing computations multiple times on the same dataset. This is called iterative computation while there is no iterative computing implemented by Hadoop.
