Learn By Example : Apache Storm

About Learn By Example : Apache Storm

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 building Storm Applications.

What's covered?

1) Understanding

Spouts

and

Bolts

which are the building blocks of every Storm topology. 2) Running a Storm topology in the

local mode

and in the

remote mode

3) Parallelizing data processing within a topology using different grouping strategies _: Shuffle grouping, fields grouping, Direct grouping, All grouping, Custom Grouping_ 4) Managing

reliability and fault-tolerance

within Spouts and Bolts 5) Performing complex transformations on the fly using the

Trident topology : Map, Filter, Windowing and Partitioning operations

6) Applying ML algorithms on the fly using libraries like

Trident-ML and Storm-R

.