Collecting data with streams - Java 8 in Action: Lambdas, Streams, and Functional-Style Programming - page 149

Chapter 6. Collecting data with streams

This chapter covers

 Creating and using a collector with the Collectors class

 Reducing streams of data to a single value

 Summarization as a special case of reduction

 Grouping and partitioning data

 Developing your own custom collectors

You learned in the previous chapter that streams help you process collections with database-like
operations. You can view Java 8 streams as fancy lazy iterators of sets of data. They support two
types of operations: intermediate operations such as filter or map and terminal operations such
as count, findFirst, forEach, and reduce. Intermediate operations can be chained to convert a
stream into another stream. These operations don't consume from a stream; their purpose is to
set up a pipeline of streams. By contrast, terminal operations do consume from a stream—to
produce a final result (for example, returning the largest element in a stream). They can often
shorten computations by optimizing the pipeline of a stream.

We already used the collect terminal operation on streams in chapters 4 and 5 , but we employed
it there mainly to combine all the elements of a Stream into a List. In this chapter, you'll
discover that collect is a reduction operation, just like reduce, that takes as argument various
recipes for accumulating the elements of a stream into a summary result. These recipes are
defined by a new Collector interface, so it's important to distinguish Collection, Collector, and
collect!

Here are some example queries of what you'll be able to do using collect and collectors:

 Group a list of transactions by currency to obtain the sum of the values of all transactions with that
currency (returning a Map<Currency, Integer> )

 Partition a list of transactions into two groups: expensive and not expensive (returning a
Map<Boolean, List<Transaction>> )

 Create multilevel groupings such as grouping transactions by cities and then further categorizing by

a Map<String , Map<Boolean ,

whether they're expensive or not (returning

List<Transaction>>> )

Excited? Great, let's start by exploring an example that benefits from collectors. Imagine a
scenario where you have a List of Transactions, and you want to group them based on their