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Storm framework terminology

Storm is free associate degree open supply, big-data process system that differs from alternative systems therein it's supposed for distributed real-time operation. Storm works on streaming further as static knowledge.Unlike Hadoop, that solely works on execution.

Storm has several use cases: realtime analytics, on-line machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over 1,000,000 tuples processed per second per node. 


storm cluster


Storm Cluster

A storm cluster contains 2 forms of nodes. One is Master node and other is worker node and uses Zookeeper node to co-ordinate to every alternative.

Master node runs a dameon referred to as "Nimbus" and worker node runs a daemon referred to as "supervisor". Master (Nimbus) assign the work for worker node and distribute the code round the cluster and additionally observance for failure.

Worker (supervisor) hear nimbus for work assigned thereto and run worker method to execute the set of a topology.

Each supervisor will run one or additional worker method acoording to configuration outline in storm.yaml. employee method on supervisor hear a specific port. every employee method uses one port to concentrate work assined by the nimbus to supervisor.

Zookeeper node act as a communication bridge between nimbus and supervisor node. All communication between nimbus and supervisor done through zookeeper cluster. nimbus and supervisor area unit homeless and quick fail, all state is kept on  zookeeper on native disk.This means you'll be able to stop Nimbus or the Supervisors and they will begin copy like nothing happened. This style results in Storm clusters being implausibly stable.

Topology: 

 

storm topology

Toplogy is sort of a connected graph of computation. every node in toplogy contains process logic and links between the node outline however proceessed knowledge passed to next node in topolgy.

There area unit 2 element of storm toplogy one is 'spout' and another is 'bolt'.

Spout:

It is the supply of stream that recieves the strems from outside world and pass those stream to bolt for a few process. for instance a spout will receive knowledge kind a computer address that contains files to translate from one indian language to a different indian language.

Bolt:

It is the another element of topology that receives tuples(data/stream) from Spout and do some process on this tuple and should emits new tuples for more proceesing. For eample its invoke a system on a knowledge or tuples comes from spout , that translate this tuple from one indian language to a different indian language.

In a storm topology there is also multiple spouts and bolts. And one bolt more pass tuple to a different bolt for more process.

Tuples:

It is the info structure that is provided by storm framework to pass stream from one element to a different element of storm toplogy. Tuple is associate degree orderted list of object.Storm supports all the primitive varieties, strings, and computer memory unit arrays as tuple field values. To use associate degree object of another sort, you simply ought to implement a serializer for the kind.Tuple will store multiple fields.

A sample of tuple
Object1(filename)  Object2(text)

Above illustration shows a tuple that have 2 fields. initial field stores a computer filename as string object and alternative field store the text of the file as a string object.

since storm could be a distributed framework its ought to acumen arrange and deserialize objects.

By default, Storm will arrange primitive varieties, strings, computer memory unit arrays, ArrayList, HashMap, HashSet, and therefore the Clojure assortment varieties. If you would like to use another sort in your tuples, you'll have to register a custom serializer.

Stream:
A strean is infinite sequence of tuple(data).

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