When using the Java Stream API to process collection data, there are a number of ways to create streams and perform operations. Common steps include: 1. Create a stream from a collection, array or directly generate elements; 2. Use intermediate operations such as filter, map, sorted to build a processing flow; 3. Trigger actual execution through termination operations such as collect, forEach, reduce, etc.; 4. Parallel flow can be enabled in large data scenarios to improve performance, but pay attention to thread safety and task overhead to avoid improper use affecting efficiency.
Java's Stream API is a powerful tool for processing collection data, which is very convenient especially when it is necessary to filter, transform, aggregate data and other operations. If you have used Java collection operations, Stream can make your code more concise and readable.
Here are some common scenarios and practical suggestions for using the Stream API:
Several Ways to Create a Stream
To use Stream, you must first have a data source. Common ways of creating include from collections, arrays, or directly generating:
- Create from a collection:
list.stream() - Create from array:
Arrays.stream(array) - Use
Stream.of()to pass in the element directly, for example:Stream.of("a", "b", "c") - Generate infinite streams through
Stream.iterate()orStream.generate()(need to be used with limit)
These methods are very commonly used, and which one you choose depends mainly on where your data source is.
Common intermediate operations: filter, map, sorted
The intermediate operation will not be executed immediately, but will "prepare" the process. The commonly used ones are as follows:
-
filter : filter elements that meet the criteria
list.stream().filter(s -> s.length() > 3);
map : map each element into another form
list.stream().map(String::toUpperCase);
sorted : sort, default in natural order, you can also customize the comparator
list.stream().sorted(Comparator.reverseOrder());
These operations can be called chained, for example:
List<String> result = list.stream()
.filter(s -> s.length() > 3)
.map(String::toUpperCase)
.sorted()
.toList(); Note: Starting from Java 16, you can quickly convert .toList() to immutable lists, otherwise you need to use Collectors.toList() .
Terminate operation: collect, forEach, reduce
Intermediate operations are just "planning", and what really triggers execution is the termination operation. Common ones include:
collect : Collect results into containers, one of the most common ways, such as collecting List or Map:
Map<String, Integer> map = list.stream() .collect(Collectors.toMap( Function.identity(), String::length ));forEach : traversal processing of each element (commonly used for debugging)
list.stream().forEach(System.out::println);
reduce : merge elements in the stream, such as summing, splicing strings, etc.
Optional<String> result = list.stream().reduce((a, b) -> a "-" b);
Note: The return of reduce is Optional. You must determine whether there is a value before taking it out.
Tips: Parallel Stream and Performance Considerations
Stream is serial by default, but parallel processing can be enabled via .parallelStream() . Suitable for large data calculations, such as:
int sum = numbers.parallelStream().mapToInt(Integer::intValue).sum();
However, it should be noted that not all scenarios are suitable for parallelism. If the data volume is small or the task itself is not time-consuming, it will cause additional overhead due to thread scheduling.
In addition, be careful when processing shared resources in parallel streams to avoid concurrent modification exceptions.
Basically that's it. The Stream API is powerful, but it is more important to not over-neck when using it.
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