What are the benefits of Spark over MapReduce?

1.	What are the benefits of Spark over MapReduce?
Answer» Here are some of the ADVANTAGES of using Spark rather than Hadoop’s MapReduce: Spark is relatively easier to program and requires a lot less of actual coding than MapReduce Spark has an in-built interactive mode, whereas MapReduce is, by DEFAULT, has only batch processing and does not have an in-built interactive mode. Spark uses a data abstraction, RDD, to make the features more productive, whereas MapReduce does not have any concept Spark executes batch processing jobs almost 10X to 100X times FASTER than MapReduce. Spark is considered as a general-purpose cluster computing engine due to its various methods for data processing such as steaming, batch processing, and machine learning, whereas MapReduce only has a Batch Engine. Spark consumes lower latency VIA PARTIAL or complete caching of results across various nodes whereas, MapReduce is disk-based and consumes a far higher latency.

Answer»

Here are some of the ADVANTAGES of using Spark rather than Hadoop’s MapReduce:

Spark is relatively easier to program and requires a lot less of actual coding than MapReduce
Spark has an in-built interactive mode, whereas MapReduce is, by DEFAULT, has only batch processing and does not have an in-built interactive mode.
Spark uses a data abstraction, RDD, to make the features more productive, whereas MapReduce does not have any concept
Spark executes batch processing jobs almost 10X to 100X times FASTER than MapReduce.
Spark is considered as a general-purpose cluster computing engine due to its various methods for data processing such as steaming, batch processing, and machine learning, whereas MapReduce only has a Batch Engine.
Spark consumes lower latency VIA PARTIAL or complete caching of results across various nodes whereas, MapReduce is disk-based and consumes a far higher latency.

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