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Storm
Real-Time Stream Processing
Premnath Thimma
Agenda
 What is Storm?
 Architecture
 Components
 Demo
What is Storm?
 Fast, Highly scalable, Fault-tolerance, Real-Time stream
processing system
 Programming language agnostic (Java, Python, Ruby)
 When should I use Storm?
 Stream Processing
 Continuous computation
 Distributed RPC
 Real Time Analytics
Storm Architecture
 Master – Runs daemon called “Nimbus”
 Distributing code, Assigning Tasks and Monitor Failure
 Stateless and Fail-fast
 Worker – Runs daemon called “Supervisor”
 Creates, Stops and Starts worker processes
 Stateless and Fail-fast
 ZooKeeper
 State-full, Manages cluster coordination
 kill -9 Supervisor or Nimbus
 Operating Modes –
 Local Cluster – Development
 Remote Cluster – Production
Storm Cluster
Application Components
 Spouts and Bolts process streams
 Stream is an unbounded sequence of tuples
 Tuple – Key Value Pair
 Topology – abstraction that defines network of computation;
and contains Spouts and Bolts
 Can deploy Topology to Storm Cluster using Storm executable
 storm jar <code.jar> com.fis.YourTopology arg1 arg2
 storm kill “Name of the Topology”
 storm activate “Name of the Topology”
 storm deactivate “Name of the Topology”
 storm rebalance “Name of the Topology” –w wait_time –n
worker_count –e executor_name=executor_count
Components (Cont.)
Spout
 Implements IRichSpout Interface
 Methods
 open(java.util.Map conf, TopologyContext context,
SpoutOutputCollector collector)
 Called just before the bolt starts processing tuples
 declareOutputFields(OutputFieldsDeclarer declarer)
 Declare the output schema
 nextTuple()
 Emit tuples
 ack() or fail()
 Called when a bolt is going to shut down
Bolts
 Implements IRichBolt Interface
 Methods
 declareOutputFields(OutputFieldsDeclarer declarer)
 Declare the output schema for this bolt
 prepare(java.util.Map conf, TopologyContext context,
OutputCollector collector)
 Called just before the bolt starts processing tuples
 execute(Tuple input)
 Process a single tuple of input
 cleanup()
 Called when a bolt is going to shut down
Parallelism – Key Terms
 Node
 Machine that participate in storm cluster
 Executes a portion of storm topology
 Workers (independent JVM process)
 Executors (threads that run within JVM process)
 Tasks (instances of spout or bolt)
Grouping
 Shuffle
 Distributes tuples randomly across target’s bolt tasks
 Fields
 Based on the value of the field tuple routed to same bolt
 All
 replicates the tuple stream across all bolt tasks
 Global
 Routes all tuples in a stream to a single task
 Direct
 Source stream decides which component will receive a given
tuple by calling the emitDirect() method
MongoDB
 Document oriented database
 Has collections
 Collection holds document
 Document
 are stored in JSON style
 can have dynamic schema
 Start Server:
 <mongo install dir>/bin/mongod <db location>
 Start Client
 <mongo install dir>/bin/mongo
In theaters near you…
 Microsoft Azure supports Storm
 SCP.Net (Stream Computing Platform) in Azure and
HDInsight
URL: http://azure.microsoft.com/en-
us/documentation/articles/hdinsight-hadoop-storm-
scpdotnet-csharp-develop-streaming-data-processing-
application/
Demo

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Storm

  • 2. Agenda  What is Storm?  Architecture  Components  Demo
  • 3. What is Storm?  Fast, Highly scalable, Fault-tolerance, Real-Time stream processing system  Programming language agnostic (Java, Python, Ruby)  When should I use Storm?  Stream Processing  Continuous computation  Distributed RPC  Real Time Analytics
  • 4. Storm Architecture  Master – Runs daemon called “Nimbus”  Distributing code, Assigning Tasks and Monitor Failure  Stateless and Fail-fast  Worker – Runs daemon called “Supervisor”  Creates, Stops and Starts worker processes  Stateless and Fail-fast  ZooKeeper  State-full, Manages cluster coordination  kill -9 Supervisor or Nimbus  Operating Modes –  Local Cluster – Development  Remote Cluster – Production
  • 6. Application Components  Spouts and Bolts process streams  Stream is an unbounded sequence of tuples  Tuple – Key Value Pair  Topology – abstraction that defines network of computation; and contains Spouts and Bolts  Can deploy Topology to Storm Cluster using Storm executable  storm jar <code.jar> com.fis.YourTopology arg1 arg2  storm kill “Name of the Topology”  storm activate “Name of the Topology”  storm deactivate “Name of the Topology”  storm rebalance “Name of the Topology” –w wait_time –n worker_count –e executor_name=executor_count
  • 8. Spout  Implements IRichSpout Interface  Methods  open(java.util.Map conf, TopologyContext context, SpoutOutputCollector collector)  Called just before the bolt starts processing tuples  declareOutputFields(OutputFieldsDeclarer declarer)  Declare the output schema  nextTuple()  Emit tuples  ack() or fail()  Called when a bolt is going to shut down
  • 9. Bolts  Implements IRichBolt Interface  Methods  declareOutputFields(OutputFieldsDeclarer declarer)  Declare the output schema for this bolt  prepare(java.util.Map conf, TopologyContext context, OutputCollector collector)  Called just before the bolt starts processing tuples  execute(Tuple input)  Process a single tuple of input  cleanup()  Called when a bolt is going to shut down
  • 10. Parallelism – Key Terms  Node  Machine that participate in storm cluster  Executes a portion of storm topology  Workers (independent JVM process)  Executors (threads that run within JVM process)  Tasks (instances of spout or bolt)
  • 11.
  • 12.
  • 13. Grouping  Shuffle  Distributes tuples randomly across target’s bolt tasks  Fields  Based on the value of the field tuple routed to same bolt  All  replicates the tuple stream across all bolt tasks  Global  Routes all tuples in a stream to a single task  Direct  Source stream decides which component will receive a given tuple by calling the emitDirect() method
  • 14. MongoDB  Document oriented database  Has collections  Collection holds document  Document  are stored in JSON style  can have dynamic schema  Start Server:  <mongo install dir>/bin/mongod <db location>  Start Client  <mongo install dir>/bin/mongo
  • 15. In theaters near you…  Microsoft Azure supports Storm  SCP.Net (Stream Computing Platform) in Azure and HDInsight URL: http://azure.microsoft.com/en- us/documentation/articles/hdinsight-hadoop-storm- scpdotnet-csharp-develop-streaming-data-processing- application/
  • 16. Demo