Storm is to real-time stream processing what Hadoop is to batch processing. Using Storm you can build applications which need you to be highly responsive to the latest data and react within seconds and minutes, such as finding the latest trending topics on twitter, or monitoring spikes in payment gateway failures. From simple data transformations to applying machine learning algorithms on the fly, Storm can do it all. This course has 25 Solved Examples on buildingStorm Applications. What’s covered?1)UnderstandingSpoutsandBoltswhich are the building blocks of every Storm topology.2)Runninga Storm topology in thelocal modeand in theremote mode3)Parallelizingdata processing within a topology using different grouping strategies: Shuffle grouping, fields grouping, Direct grouping, All grouping, Custom Grouping4) Managingreliability and fault-tolerancewithin Spouts and Bolts5)Performingcomplex transformations on the flyusing theTrident topology: Map, Filter, Windowing and Partitioning operations6)Applying ML algorithms on the fly using libraries likeTrident-ML and Storm-R.
