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You're reading from  Mastering Apache Storm

Product typeBook
Published inAug 2017
Reading LevelExpert
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ISBN-139781787125636
Edition1st Edition
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Author (1)
Ankit Jain
Ankit Jain
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Ankit Jain

Ankit Jain holds a bachelor's degree in computer science and engineering. He has 6 years, experience in designing and architecting solutions for the big data domain and has been involved with several complex engagements. His technical strengths include Hadoop, Storm, S4, HBase, Hive, Sqoop, Flume, Elasticsearch, machine learning, Kafka, Spring, Java, and J2EE. He also shares his thoughts on his personal blog. You can follow him on Twitter at @mynameisanky. He spends most of his time reading books and playing with different technologies. When not at work, he spends time with his family and friends watching movies and playing games.
Read more about Ankit Jain

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Features of Storm


The following are some of the features of Storm that make it a perfect solution to process streams of data in real time:

  • Fast: Storm has been reported to process up to 1 million tuples/records per second per node.
  • Horizontally scalable: Being fast is a necessary feature to build a high volume/velocity data processing platform, but a single node will have an upper limit on the number of events that it can process per second. A node represents a single machine in your setup that executes Storm applications. Storm, being a distributed platform, allows you to add more nodes to your Storm cluster and increase the processing capacity of your application. Also, it is linearly scalable, which means that you can double the processing capacity by doubling the nodes.
  • Fault tolerant: Units of work are executed by worker processes in a Storm cluster. When a worker dies, Storm will restart that worker, and if the node on which the worker is running dies, Storm will restart that worker on some other node in the cluster. This feature will be covered in more detail in Chapter 3, Storm Parallelism and Data Partitioning.
  • Guaranteed data processing: Storm provides strong guarantees that each message entering a Storm process will be processed at least once. In the event of failures, Storm will replay the lost tuples/records. Also, it can be configured so that each message will be processed only once.
  • Easy to operate: Storm is simple to deploy and manage. Once the cluster is deployed, it requires little maintenance.
  • Programming language agnostic: Even though the Storm platform runs on Java virtual machine (JVM), the applications that run over it can be written in any programming language that can read and write to standard input and output streams.
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Author (1)

author image
Ankit Jain

Ankit Jain holds a bachelor's degree in computer science and engineering. He has 6 years, experience in designing and architecting solutions for the big data domain and has been involved with several complex engagements. His technical strengths include Hadoop, Storm, S4, HBase, Hive, Sqoop, Flume, Elasticsearch, machine learning, Kafka, Spring, Java, and J2EE. He also shares his thoughts on his personal blog. You can follow him on Twitter at @mynameisanky. He spends most of his time reading books and playing with different technologies. When not at work, he spends time with his family and friends watching movies and playing games.
Read more about Ankit Jain