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Storm Assignment Help


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What is Apache Storm?


  1. Distributed real time and big data processing system
  2. Fault tolerant and horizontal scalable
  3. Data manipulations on real time
  4. Easy to setup, operate and message guarantee 
  5. Task Parallel computations
  6. Stream processing engine which can undergo micro batching
  7. Fault tolerant method for multiple computations on an event with each event dealt with individually
  8. Record at a time processing model
  9. Latency is sub second
  10. A better option is case of no data loss wanted
  11. Implemented in clojure
  12. Comes with a Java API 
  13. Storm runs on Mesos
  14. Operates on data in motion i.e. continuous streaming of data


Difference between Apache storm and apache spark:


Features
Apache storm
Apache spark
Programming language
Java, scala, clojure
Java, scala
Processing models
True stream processing   model through system layer
Apache spark streaming   is wrapper over batch processing
Reliability
Support exactly once   processing mode. Can also be used in at least once and at most once   processing modes
Support exactly once   processing mode
Latency
Apache storm provides better latency
Apache spark provides less latency
Resource management
Can run on YARN and Mesos
Can run on YARK and Mesos


Finding the Features of Storm online service to Storm Assignment Help:


  1. Faster Speed and easy to operate
  2. Scalability and Reliability
  3. Fault Tolerance
  4. Operational Ease
  5. Dynamic in nature, real time stream processing
  6. In memory computing
  7. Advance analytics
  8. Its processing mode is micro batching
  9. Its state access is full state scan for each micro-batch


Comparison between Storm and Hadoop:


STORM
HADOOP
Real time stream processing
Batch processing
Mater/slave architecture with ZooKeeper based coordination. The master node is called as   nimbus and slaves are supervisors.
Master slave architecture with or without ZooKeeper based coordination master node is job   tracker and slave node is task traker.
Stateless
Stateful
Storm topology runs until shutdown by the user or an unexpected unrecoverable unsuccess
Mapreduce jobs are   executed in a sequential order and completed eventually 
A storm streaming process can access tens of thousands messages per second on cluster
Hadoop Distributed file   system uses Mapreduce framework to process the vast amount of data that takes minutes or hours.


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