In this chapter, we used the different versions of the collect() method provided by the Stream framework to transform and group the elements of a Stream. This and Chapter 7, Processing Massive Datasets with Parallel Streams – The Map and Reduce Model, teach you how to work with the whole stream API.

Basically, the collect() method needs a collector that processes the data of the stream and generates a data structure returned by the set of aggregate operations that forms the stream. A collector works with three different data structures—the class of the input elements, an intermediate data structure used while processing the input elements, and a final data structure that is returned.

We used the different versions of the collect() method to implement a search tool that must look for a query in a set of files without an inverted index, a recommendation system, and a tool to calculate the common contacts between two users in a social network.

In the next chapter, we will take a deep look at the concurrent data structures and synchronization mechanisms provided by the Java concurrent API.