In this chapter, we will introduce you to trend analysis techniques using Storm and Trident. Real-time trend analysis involves identifying patterns in data streams, such as recognizing when the occurrence rate or count of certain events reaches a certain threshold. Common examples include trending topics in social media, such as when a specific hashtag becomes popular on Twitter or identifying trending search terms in a search engine. Storm originated as a project to perform real-time analytics on Twitter data, and it provides many of the core primitives required for analytical computation.

In the previous chapters, the spout implementations used were primarily simulations that used static sample data or randomly generated data. In this chapter, we will introduce an open source spout that emits data from a queue (Apache Kafka) and supports all three types of the Trident spout transaction (Non-transaction, Repeat Transaction, and Opaque Transactional). We...