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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteIn Java 8, a stream pipeline processes data from a source through optional intermediate operations and a terminal operation. Use filter to select elements, map to transform them, and reduce to combine values into a result. The intermediate steps describe the work; the terminal operation starts it.
What a Java 8 stream is—and how its pipeline works
A stream is a sequence of elements that supports sequential or parallel aggregate operations. It is not a collection or a container that stores the results of each step. Instead, it describes a computation over a source, such as a collection.
A pipeline has three parts: a source, zero or more intermediate operations, and a terminal operation. Intermediate operations such as filter and map are lazy: they set up processing but do not, by themselves, traverse the source. Processing begins when a terminal operation is initiated, and elements are consumed as needed.
What filter, map, and reduce do
| Operation | Pipeline role | What it produces | Empty-stream behavior |
|---|---|---|---|
filter(predicate) |
Intermediate | A stream containing only elements for which the predicate is true. | An empty stream remains empty. |
map(function) |
Intermediate | A stream of values produced by applying the function to each input element. | An empty stream remains empty. |
reduce(accumulator) without an identity |
Terminal | An Optional containing the combined result, if one exists. |
Returns an empty Optional. |
reduce(identity, accumulator) |
Terminal | A result formed by combining the identity with the stream elements. | Returns the identity. |
filter: select elements
filter takes a predicate—a function that answers true or false for an element—and retains only elements for which it is true. For example, .filter(n -> n > 0) keeps positive numbers.
map: transform elements
map applies a function to each element and emits the resulting values. It does not select or discard values based on a condition. For example, .map(n -> n * 2) doubles each number that reaches that stage.
reduce: combine elements
reduce combines elements using an associative accumulation function. Associative means that grouping the same values in different ways does not change the result, as with addition: (a + b) + c equals a + (b + c). This property matters for reductions, including when a pipeline may run in parallel.
Rank #2
The overload without an identity returns an Optional because an empty stream has no element to use as a result. The overload with an identity returns a value even when the stream is empty, so its identity must genuinely match the accumulation operation. For addition, zero is the identity; for multiplication, it is one.
Putting the three operations together
This example keeps positive numbers, doubles them, then adds the results:
int total = numbers.stream()
.filter(n -> n > 0)
.map(n -> n * 2)
.reduce(0, Integer::sum);If numbers contains 3, -2, and 4, the filter keeps 3 and 4, the map produces 6 and 8, and the reduction adds them to produce 14. If no positive numbers remain, the reduction returns its identity, 0.
The same selection-then-aggregation pattern can use a primitive stream when the mapped values are numeric:
Rank #4
int totalWeight = widgets.stream()
.filter(widget -> widget.getColor() == RED)
.mapToInt(Widget::getWeight)
.sum();mapToInt produces an IntStream, whose numeric operations include sum. Java 8 also provides LongStream and DoubleStream alongside reference streams such as Stream<T>.
Why a pipeline may appear to do nothing
Building intermediate stages does not execute them. A terminal operation is what initiates the work. In the examples above, reduce and sum are terminal operations. Other terminal operations include count and collect.
Best Value
If you need a collection rather than a single aggregate value, use a collection-producing terminal operation such as collect; a stream itself is not a list. The choice of terminal operation determines the shape of the result: a count is a number, a reduction is an aggregate value, and a collection-producing operation gives you a collection.
Sequential and parallel streams
Java 8 supports both execution modes. For a collection, stream() creates a sequential stream, while parallelStream() creates a parallel stream. Parallel execution is an option, not a guarantee of faster completion: the API defines the modes but does not promise a speedup for every task. A reduction intended for parallel execution must also use an appropriate associative operation and identity.
Further reading
For a longer treatment of Java 8 lambdas and streams, Manning lists Java 8 in Action: Lambdas, streams, and functional-style programming, by Raoul-Gabriel Urma, Mario Fusco, and Alan Mycroft. Its August 2014 edition is 424 pages and is aimed at programmers familiar with Java and basic object-oriented programming. Manning also lists the newer Modern Java in Action; the older book is specifically about Java 8.
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