Flink is a stream processing technology with added capability to do lots of other things like batch processing, graph algorithms, machine learning etc. Using Flink you can build applications which need you to be highly responsive to the latest data such as monitoring spikes in payment gateway failures or triggering trades based on live stock price movements.
This course has 30 Solved Examples on building Flink Applications for both Streaming and Batch Processing
1) Transformations in the DataStream API : filter, map, flatMap and reduce
2) Operations on multiple streams : union, cogroup, connect, comap, join and iterate
3) Window operations : Tumbling, Sliding, Count and Session windows; the notion of time and how to implement custom Window functions
4) Managing fault-tolerance with State and Checkpointing
5) Transformations in the DataSet API : filter, map, reduce, reduceGroup
6) Applying ML algorithms on the fly using Flink-ML
7) Representing Graph data using Gelly
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!