Just completes the book "Learning Storm". Very nice read, interesting readers can go to the following link to buy:
https://www.packtpub.com/big-data-and-business-intelligence/learning-storm
The book covers quite widely, with quite a number of ways to show how other technologies working with Storm introduced in a easy-to-understand way such as the covering of ZooKeeper, Kafka, Hadoop, YARN, Ganglia, JMX, HBase, Redis, MySQL, etc. I especially likes the way they teach Trident, which makes it much easier to grasp the concept of Trident, and the last chapter on machine is extremely useful.
While the normal readers can read the book chapters by chapters to take a slow and full exposure. For someone like me, who always like to delve directly into practice, the best approach is actually to read the book three times, each time skipping some chapters.
During first time, the reader should go through chapter 1 to chapter 4, skipping the thrift library introduction in chapter 3, and then directly jump to chapter 8, which gives an example of log processing in Storm. With this the reader will build a level of confidence after practicing the simple cases in these chapters.
During the second time, the reader should go through chapter 5 and chapter 9 to get a good ideas of what Trident is and how Trident work, as well as how to do machine learning using Trident.
During the third time, the reader can optionally go through the thrift library in chapter 3, then go to chapter 7 which show rich tools to interact with Storm such JMX and Ganglia. Finally if there is a need for integration with Hadoop, then go to chapter 6 and some other parts in chapter 7.
