Streams
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
This chapter is from the book
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 |
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[6.1] Use Java object and primitive Streams, including lambda expressions implementing functional interfaces, to supply, filter, map, consume, and sort data
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§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 |
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[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 |
Streams are covered in this chapter.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.