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This chapter covers the foundations of streams, in particular the Stream API, which is a declarative way of processing data using streams and allows programmers to harness the power of multicore architectures for parallel processing of data. This chapter maps to the Java SE 17 Developer Exam Objectives [6.1]-[6.3].

This chapter is from the book

Chapter Topics

  • Understanding the construction of a stream pipeline

  • Understanding various aspects of streams: sequential or parallel, ordered or unordered, finite or infinite, and object or numeric

  • Creating object streams from various sources; for example, assorted collections, arrays, strings, and I/O classes

  • Creating infinite numeric streams using generator functions

  • Understanding the various aspects of intermediate stream operations: stream mapping, lazy execution, short-circuit evaluation, and stateless or stateful operations

  • Understanding the implications of operation order, and non-interfering and stateless behavioral parameters of intermediate stream operations

  • Filtering, skipping, and examining stream elements

  • Selecting distinct elements and truncating a stream

  • Understanding mapping and flattening a stream

  • Sorting stream elements

  • Changing the execution mode of a stream and marking a stream as unordered

  • Understanding interoperability between stream types

  • Understanding the role of the Optional class

  • How to create, query, filter, map, and flatten optionals

  • Using numeric optionals

  • Understanding the implication of invoking a terminal operation on a stream

  • Applying consumer actions to elicit side effects in a stream

  • Using terminal operations to match, find, and count stream elements

  • Understanding functional and mutable reduction, both sequential and parallel

  • Collecting stream results in lists, sets, and arrays

  • Using functional reduction on numeric streams, including statistical operations

  • Understanding the role of a collector in stream execution

  • Collecting to a collection, list, set, map, and concurrent map

  • Using a collector to join strings

  • Using collectors that group and partition stream elements

  • Using downstream collectors for functional reduction: counting, finding min/max, summing, averaging, and summarizing

  • How to implement collectors for customized reduction

  • How to use map-reduce, filtering, flat mapping, and finishing adapters for downstream collectors

  • Understanding how to build and execute a parallel stream

  • Understanding factors that can affect parallel stream execution

  • Understanding the importance of benchmarking parallel stream execution

Java SE 17 Developer Exam Objectives


[6.1]  Use Java object and primitive Streams, including lambda expressions implementing functional interfaces, to supply, filter, map, consume, and sort data

  • round.jpg Streams are covered in this chapter.

  • round.jpg For lambda expressions implementing functional interfaces, see Chapter 13, p. 673.

§16.3, p. 884

§16.4, p. 890

§16.5, p. 905

§16.7, p. 946

[6.2]  Perform decomposition, concatenation and reduction, and grouping and partitioning on sequential and parallel streams

§16.7, p. 946

§16.8, p. 978

§16.9, p. 1009

Java SE 11 Developer Exam Objectives


[6.2]  Use Java Streams to filter, transform and process data

§16.3, p. 884

§16.4, p. 890

§16.5, p. 905

§16.7, p. 946

[6.3]  Perform decomposition and reduction, including grouping and partitioning on sequential and parallel streams

§16.7, p. 946

§16.8, p. 978

§16.9, p. 1009

The Stream API brings a new programming paradigm to Java: a declarative way of processing data using streams—expressing what should be done to the values and not how it should be done. More importantly, the API allows programmers to harness the power of multicore architectures for parallel processing of data.

We strongly suggest reviewing the following topics which we consider essential prerequisites for learning about streams:

  • Functional-style programming (Chapter 13, p. 673); specially, functional interfaces, lambda expressions, method references, and built-in functional interfaces

  • Comparing objects (Chapter 14, p. 741); in particular, the Comparator<E> functional interface (§14.4, p. 761)

16.1 Introduction to Streams

A stream allows aggregate operations to be performed on a sequence of elements. An aggregate operation performs a task on the stream as a whole rather than on an individual element of the stream. In the context of streams, these aggregation operations are called stream operations. Such operations utilize behavior parameterization implemented by functional interfaces for actions performed on the stream elements.

Examples of stream operations accepting implementation of functional interfaces include:

  • Generating elements of the stream using a Supplier

  • Converting the elements in the stream according to a mapping defined by a Function

  • Filtering the elements in the stream according to some criteria defined by a Predicate

  • Sorting the elements in the stream using a Comparator

  • Performing actions for each of the elements in the stream with the help of a Consumer

Streams can be produced from a variety of sources. Collections and arrays are typical examples of sources for streams. The Collection<E> interface and the Arrays utility class both provide a stream() method that builds a stream from the elements of a collection or an array.

In the loop-based solution below, elements from the values list are processed using a for(:) loop to test whether a year is after the year 2000. The strings in the list are parsed to a Year object before being tested in an if statement.

// Loop-based solution:
List<String> values = List.of("2001", "1999", "2021");
for (String s : values) {
  Year y = Year.parse(s);
  if (y.isAfter(Year.of(2000))) {
    System.out.print(s + " ");                      // 2001 2021
// Stream-based solution:
List<String> values2 = List.of("2001", "1999", "2021");
values2.stream()                                    // (1)
       .map(s -> Year.parse(s))                     // (2)
       .filter(y -> y.isAfter(Year.of(2000)))       // (3)
       .forEach(y -> System.out.print(y + " "));    // (4) 2001 2021

A stream-based solution for the same problem is also presented above. The stream() operation at (1) generates a stream based on the elements from the collection. The map() operation at (2) parses the string elements to a Year object, as defined by the lambda expression that implements the Function interface. The filter() operation at (3) performs a filtering of the elements in the stream that are after the year 2000, as defined by a lambda expression that implements the Predicate interface. The forEach() operation at (4) performs an action on each stream element, as defined by a lambda expression that implements the Consumer interface.

The loop-based solution specifies how the operations should be performed. The stream-based solution states what operations should be performed, qualified by the implementation of an appropriate functional interface. Stream-based solutions to many problems can be elegant and concise compared to their iteration-based counterparts.

In this chapter we will cover many stream operations in detail, as well as discover other use cases and benefits of using streams.

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