parallel processing - Apache Spark vs Akka -


could please tell me difference between apache spark , akka, know both frameworks meant programme distributed , parallel computations, yet don't see link or difference between them.

moreover, use cases suitable each of them.

apache spark built on akka.

akka general purpose framework create reactive, distributed, parallel , resilient concurrent applications in scala or java. akka uses actor model hide thread-related code , gives simple , helpful interfaces implement scalable , fault-tolerant system easily. example akka real-time application consumes , process data coming mobile phones , sends them kind of storage.

apache spark (not spark streaming) framework process batch data using generalized version of map-reduce algorithm. example apache spark calculation of metrics of stored data better insight of data. data gets loaded , processed on demand.

apache spark streaming able perform similar actions , functions on near real-time small batches of data same way if data stored.

update april 2016

from apache spark 1.6.0, apache spark no longer relying on akka communication between nodes. @eugenemi comment.


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