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.
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.
Using discussion forums
Please use the discussion forums on this course to engage with other students and to help each other out. Unfortunately, much as we would like to, it is not possible for us at Loonycorn to respond to individual questions from students:-(
We're super small and self-funded with only 2 people developing technical video content. Our mission is to make high-quality courses available at super low prices.
The only way to keep our prices this low is to *NOT offer additional technical support over email or in-person*. The truth is, direct support is hugely expensive and just does not scale.
We understand that this is not ideal and that a lot of students might benefit from this additional support. Hiring resources for additional support would make our offering much more expensive, thus defeating our original purpose.
It is a hard trade-off.
Thank you for your patience and understanding!
Understand how stream processing is different from batch processing
Stream processing is great for certain applications, but performance can be an issue at large scale. How do we solve this?
Understand Spouts and Bolts which make up a Storm topology
Understand how a Storm topology allows parellelism across components
A Storm topology runs on a cluster. Understand the different services which run on the cluster
Loonycorn is us, Janani Ravi and Vitthal Srinivasan. Between us, we have studied at Stanford, been admitted to IIM Ahmedabad and have spent years working in tech, in the Bay Area, New York, Singapore and Bangalore.
Janani: 7 years at Google (New York, Singapore); Studied at Stanford; also worked at Flipkart and Microsoft
Vitthal: Also Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too
We think we might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why we are so excited to be here on Udemy!
We hope you will try our offerings, and think you'll like them :-)