Following are the benefits of Spark over MapReduce:
- With in-memory processing available, Spark accomplishes 10–100 times more data processing than Hadoop MapReduce. For each data processing task, MapReduce takes to use, however, of persistent storage.
- In contrast to Hadoop, Spark provides built-in libraries for several tasks like batch processing, streaming, machine learning, and interactive SQL queries. But only batch processing is supported by Hadoop.
- Sparc encourages innovative caching and data storage, whereas Hadoop is mainly disc reliant.
- Spark can run calculations on the same dataset, named iterative calculation, several times. Instead, Hadoop does not utilize iterative computing