December 2015
Beginner to intermediate
122 pages
2h 23m
English
Content preview from Building Python Real time Applications with Storm
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Tuning parallelism in Storm – scaling a distributed computation
To explain parallelism of Storm, we will configure three parameters:
- The number of workers
- The number of executors
- The number of tasks
The following figure gives a diagrammatic explanation of an example where we have a topology with just one spout and one bolt. In this case, we will set different values for the numbers of workers, executors, and tasks at the spout and bolt levels, and see how parallelism works in each case:
// assume we have two workers in total for topology. topology.workers: 2 // just one executor of spout. builder.setSpout("spout-sentence", TwitterStreamSpout(),1)
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