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Building Python Real time Applications with Storm

You're reading from   Building Python Real time Applications with Storm Learn to process massive real-time data streams using Storm and Python—no Java required!

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Product type Paperback
Published in Dec 2015
Publisher
ISBN-13 9781784392857
Length 122 pages
Edition 1st Edition
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Toc

A physical view of a Storm cluster

The next figure explains the physical position of each process. There can be only one Nimbus. However, more than one Zookeeper is there to support failover, and per machine, there is one supervisor.

A physical view of a Storm cluster

Stream grouping

A stream grouping controls the flow of tuples between from spout to bolt or bolt to bolt. In Storm, we have four types of groupings. Shuffle and field grouping are most commonly used:

  • Shuffle grouping: Tuple flow between two random tasks in this grouping
  • Field grouping: A tuple with a particular field key is always delivered to the same task of the downstream bolt
  • All grouping: Sends the same tuple to all tasks of the downstream bolt
  • Global grouping: Tuples from all tasks reach one task

The subsequent figure gives a diagrammatic explanation of all the four types of groupings:

Stream grouping

Fault tolerance in Storm

Supervisor runs a synchronization thread to get assignment information (what part of topology I am supposed to run) from Zookeeper and write to the local...

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