Java 8 Streams API Tutorial: Intermediate and Final Operators
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Java 8 introduced a revolutionary new feature called Streams, which revolutionized the way Java developers process data collections. With Streams, Java developers can perform complex operations on collections using a concise and efficient syntax.
This comprehensive guide will cover everything you need to know about Java 8 Streams, including their benefits, usage, and implementation. We will also answer some of the most commonly asked questions about Streams in Java.
What are Java 8 Streams?
Java 8 Streams are a sequence of elements that can be processed in parallel or sequential order. They allow the processing of data collections in a concise, expressive, and parallelized way. It provides a set of functional-style operations that can be applied to streams of elements, such as filtering, mapping, reducing, and sorting.
Streams can be created from various sources, such as collections, arrays, files, generators, and iterators. Once a stream is created, a pipeline of operations can be applied to it, resulting in a final stream that can be consumed or collected.
They are built on top of collections and provide a set of intermediate and terminal operations.
Intermediate operations transform a stream into another stream, while terminal operations return a result or a side effect. Streams can be processed in a sequential or parallel mode. In parallel mode, multiple threads can process the elements of the stream simultaneously, which can lead to significant performance improvements.
Java 8 Streams API
The Java 8 Streams API provides a set of functional interfaces, classes, and methods for creating, processing and manipulating streams. Some of the important classes and interfaces in the Streams API include:
- Stream: Represents a sequence of elements that can be processed sequentially or parallel.
- IntStream, LongStream, DoubleStream: Specialized streams for handling primitive data types.
- Collector: Performs a reduction operation on a stream and returns a result as a collection or a single value.
- Supplier: Provides a new instance of a collection or a stream.
- Predicate: Evaluates a boolean expression for a given input.
- Function: Applies a transformation on the input and returns a new output.
- Comparator: Compares two objects and returns a result.
How to Create a Stream in Java 8
Java 8 provides several ways to create a stream, depending on the data source. Here are some of the most common ways to create a stream in Java 8:
1. Creating an Empty Stream
In Java 8, you can create an empty stream using the Stream.empty() method. This method returns a sequential stream with no elements.
Stream<String> emptyStream = Stream.empty();Creating an empty stream can be useful in cases where you want to handle an empty collection gracefully or as a starting point for building a larger stream through concatenation or flatMap operations.
List<String> list1 = Arrays.asList("apple", "banana", "orange");
List<String> list2 = Collections.emptyList();
Stream<String> stream = Stream.concat(list1.stream(), list2.stream());
stream.forEach(System.out::println); //Output: apple, banana, orange2. Creating a Stream from a Collection
Create a stream from a collection: You can create a stream from any collection, such as List, Set, or Map using the Collections.stream() method. Here’s an example:
List list = Arrays.asList("apple", "banana", "orange", "kiwi");
Stream stream = list.stream();3. Creating a Stream from an Array
Create a stream from an array: You can create a stream from an array using the Arrays.stream() method. Here’s an example:
int() arr = {1, 2, 3, 4, 5};
IntStream stream = Arrays.stream(arr);4. Creating a Stream of Values
Create a stream of values: You can create a stream from a set of values using the Stream.of() method. Here’s an example:
Stream<String> stream = Stream.of("apple", "banana", "orange", "kiwi");5. Creating a Stream from a File
Create a stream from a file: You can create a stream from a file using the Files.lines() method. Here’s an example:
Path path = Paths.get("file.txt");
Stream<String> stream = Files.lines(path);6. Creating a Stream from a Primitive Value Range
It is also possible to create a stream from a range of values. For instance, you can create a stream from a range of values using the IntStream.range(int startInclusive, int endExclusive) or IntStream.rangeClosed() method.
The IntStream.range(int startInclusive, int endExclusive) method is used to create a sequential ordered stream of int values starting from startInclusive and ending at endExclusive - 1.
The IntStream.rangeClosed(int startInclusive, int endInclusive) method is used to create a sequential ordered stream of int values starting from startInclusive and ending at endInclusive.
Here’s an example using IntStream.range() and IntStream.rangeClosed():
IntStream stream = IntStream.range(1, 5); // generates stream of 1, 2, 3, 4
IntStream stream2 = IntStream.rangeClosed(1, 5); // generates stream of 1, 2, 3, 4, 57. Creating a Stream using Stream.generate()
Create a stream from a generator: You can create an infinite stream using the Stream.generate() method.
The Stream.generate(Supplier<T> s) method is used to create a sequential unordered stream where each element is generated by the provided Supplier. The Supplier functional interface generates the next value in the stream each time its get() method is called.
We can use a lambda expression to provide an implementation for the Supplier’s get() method.
Stream.generate(() -> Math.random())
.limit(5)
.forEach(System.out::println);8. Creating a Stream using an iterator
Create a stream from an iterator: You can create a stream from an iterator using the StreamSupport.stream() method. Here’s an example:
Iterator<String> iterator = Arrays.asList("apple", "banana", "orange", "kiwi").iterator();
Stream<String> stream = StreamSupport.stream(Spliterators.spliteratorUnknownSize(iterator, Spliterator.ORDERED), false);9. Creating a Stream using Stream.iterate()
The Stream.iterate(T seed, UnaryOperator<T> f) method is used to create a sequential ordered stream where each element is generated by applying a function f to the previous element, starting with the seed element seed.
Stream<Integer> stream = Stream.iterate(0, n -> n + 2)
.limit(5)
.forEach(System.out::println);In summary, Java 8 provides a wide variety of options for creating streams, making it easy for developers to process data collections using a concise and efficient syntax.
Stream Referencing in Java 8
In Java 8, a stream is a one-time use object, which means you can’t use it again once you’ve used it to perform intermediate and terminal operations. If you try to perform another operation on a stream that has already been closed, you’ll get an IllegalStateException.
To reference a stream in Java 8, you simply create a new stream and assign it to a variable. For example, the following code creates a stream of integers and assigns it to the variable stream:
Stream<Integer> stream = Stream.of(1, 2, 3, 4, 5);Once you have a reference to a stream, you can perform intermediate and terminal operations on it as needed. However, you must be careful not to close the stream before you’re finished with it. If you try to perform another operation on a closed stream, you’ll get an IllegalStateException.
Here’s an example of how to use a stream reference:
Stream<Integer> stream = Stream.of(1, 2, 3, 4, 5);
stream.filter(n -> n % 2 == 0)
.forEach(System.out::println);In the above example, we create a stream of integers and assign it to the variable stream. We then perform an intermediate operation using the filter() method to keep only the even numbers, and finally, we output the result using the forEach() method. Because we haven’t closed the stream, we can use the stream reference to perform other operations if needed.
In summary, to reference a stream in Java 8, you simply create a new stream and assign it to a variable. However, be sure not to close the stream before you’re finished with it, or you’ll get an IllegalStateException if you try to perform another operation on it.
Stream Pipelining in Java 8
Stream pipelining in Java 8 refers to the process of chaining multiple stream operations together to form a pipeline. The output of one operation becomes the input of the next operation, allowing for complex data transformations to be performed on a stream of data.
In Java 8, streams have two types of operations: intermediate and terminal. Intermediate operations are operations that return a new stream, allowing for further operations to be performed. Terminal operations return a non-stream result, such as a primitive value or a collection.
Stream pipelining allows us to combine intermediate operations to form a single pipeline executed by calling a single terminal operation. This allows us to write concise, readable code while performing complex data transformations.
Here is an example of stream pipelining:
List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5);
int sum = numbers.stream()
.filter(n -> n % 2 == 0)
.mapToInt(Integer::intValue)
.sum();In this example, we start with a list of integers and create a stream from it using the stream() method. We then chain together three intermediate operations: filter(), mapToInt(), and sum(). The filter() operation filters out any odd numbers, the mapToInt() operation converts the remaining even numbers to primitive integers, and the sum() operation calculates the sum of the resulting numbers. Finally, the sum() terminal operation returns the result of the entire pipeline, which is the sum of all even numbers in the list.
It’s important to note that the operations in a stream pipeline are executed lazily. This means that the intermediate operations are not actually executed until a terminal operation is called. This allows for efficient processing of large data sets by only processing the data that is actually needed for the final result.
It’s also important to optimize the order of operations in a pipeline. In the example above, the filter() operation is executed before the mapToInt() operation, which is executed before the sum() operation. Changing the order of these operations would result in a different result.
Stream Laziness
Laziness in Java 8 Streams is a key concept allowing streams to optimize and avoid unnecessary computations. In essence, laziness means that intermediate operations on a stream do not execute until a terminal operation is called.
This means that when we create a stream, nothing actually happens until we call a terminal operation like forEach(), reduce(), or collect(). Before that, all intermediate operations just create a pipeline that will be executed when a terminal operation is invoked.
For example, consider the following code:
List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5);
Stream<Integer> stream = numbers.stream()
.filter(n -> n % 2 == 0)
.map(n -> n * n);
stream.forEach(System.out::println);In this code, we create a stream from a list of integers and apply two intermediate operations: filter() and map(). However, nothing happens until we call the terminal operation forEach().
This laziness allows Java 8 Streams to optimize performance by avoiding unnecessary computations. For example, if we have a large data set and we only need the first 10 elements of a stream, we don’t need to process the entire data set before we can access those elements. Instead, we can stop processing the stream as soon as we get the 10 elements we need.
In addition, laziness allows us to chain multiple intermediate operations together, creating a pipeline that can be optimized and executed more efficiently. For example, we can filter a stream before mapping it, reducing the number of elements that need to be mapped.
Overall, laziness is a powerful feature of Java 8 Streams that allows for efficient and optimized stream processing.
The Importance of Operation Order in Streams
To best illustrate the importance of operation and execution order in streams, let’s alter the previous example to the following:
List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5);
numbers.stream().filter(n -> n % 2 == 0)
.map(n -> n * 2)
.forEach(System.out::println); //Output: 4, 8
numbers.stream().map(n -> n * 2)
.filter(n -> (n / 2) % 2 == 0)
.forEach(System.out::println); //Output: 4, 8In the above code example, both statements will print the same output:
However, the second statement is suboptimal because it involves more computation than the first statement.
In the first statement, the filter() operation is applied before the map() operation. This is beneficial because the filter() operation eliminates half of the elements in the stream before the map() operation doubles the remaining elements. Therefore, the map() operation will only have to perform half the number of computations it would have to perform if it was applied to all the elements in the stream.
On the other hand, the second statement applies the map() operation before the filter() operation. This means that the map() operation will be applied to all elements in the stream, even though the subsequent filter() operation will eliminate some of them. This results in unnecessary computation, which can slow down the performance of the code.
Therefore, it is recommended to apply the filter() operation before the map() operation to optimize the performance of the code by reducing the stream’s size.
Intermediate Operations in Java 8 Streams
Intermediate operations in Java 8 Streams transform a stream into another stream. These operations are lazy, meaning they do not execute until a terminal operation is called. Some of the important intermediate operations in Java 8 Streams include:
- filter(): Filters the elements of a stream based on a given predicate.
- map(): Transforms each stream element to another element using a given function.
- flatMap(): Flattens a stream of streams into a single stream.
- distinct(): Removes duplicate elements from a stream.
- sorted(): Sorts the elements of a stream based on a given comparator.
- peek(): Applies a function to each stream element and returns a new stream.
- skip(): Discards the first n elements of a stream.
- limit(): Returns a stream that is no longer than the request size n.
1. Stream filter() operator
Stream<T> filter(Predicate<? super T> predicate)The filter() operation takes a Predicate<T> as input and returns a new stream containing all elements that satisfy the predicate. The resulting stream will have the same type as the original stream.
Here’s an example that filters out all even numbers from a list of integers:
List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);
List<Integer> evenNumbers = numbers.stream()
.filter(n -> n % 2 == 0)
.collect(Collectors.toList());
System.out.println(evenNumbers); // Output: (2, 4, 6, 8, 10)2. Stream map() operator
<R> Stream<R> map(Function<? super T, ? extends R> mapper)The map() operation takes a Function<T, R> as input and returns a new stream containing the result of applying the function to each element in the original stream. The resulting stream will have the type R.
Here’s an example that squares each element in a list of integers:
List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5);
List<Integer> squares = numbers.stream()
.map(n -> n * n)
.collect(Collectors.toList());
System.out.println(squares); // Output: (1, 4, 9, 16, 25)Here is another example where we use the map() method to convert a stream of Employee objects to a stream of integers (their salaries):
public class Employee {
private String name;
private int salary;
public Employee(String name, int salary) {
this.name = name;
this.salary = salary;
}
public int getSalary() {
return salary;
}
}
public class Main {
public static void main(String() args) {
List<Employee> employees = Arrays.asList(
new Employee("John", 50000),
new Employee("Jane", 60000),
new Employee("Bob", 70000)
);
List<Integer> salaries = employees.stream()
.map(Employee::getSalary)
.collect(Collectors.toList());
System.out.println(salaries);
}
}3. Stream flatMap() operator
<R> Stream<R> flatMap(Function<? super T, ? extends Stream<? extends R>> mapper)The Java 8 Streams API operator flatMap() is an intermediate operation that transforms a stream of collections or arrays into a flat stream of individual elements. The flatMap() method is used when we have a stream of elements containing nested collections and want to transform it into a stream of individual elements.
Here’s an example that uses the flatMap() operator to flatten a stream of lists of integers:
List<List<Integer>> numbers = Arrays.asList(Arrays.asList(1, 2), Arrays.asList(3, 4), Arrays.asList(5, 6));
List<Integer> flattened = numbers.stream()
.flatMap(Collection::stream)
.collect(Collectors.toList());
System.out.println(flattened); // Output: (1, 2, 3, 4, 5, 6)In this example, we have a list of lists of integers numbers. We create a stream from this list using the stream() method, and then use the flatMap() method to flatten the stream of lists into a stream of individual integers. We then collect the resulting stream into a new List<Integer> using the collect() method.
As we can see from the output, the flatMap() method allowed us to flatten the stream of lists into a stream of individual integers.
The flatMap() method can also be used with arrays, as shown in the following example:
String()() data = {{"a", "b"}, {"c", "d"}, {"e", "f"}};
Stream<String> stream = Arrays.stream(data)
.flatMap(Arrays::stream);
stream.forEach(System.out::println); //Output: a b c d e f - One letter per lineIn this example, we have a two-dimensional array data of strings. We create a stream from this array using the Arrays.stream() method and then use the flatMap() method to flatten the stream of arrays into a stream of individual strings. We then use the terminal operator forEach() method to print each element of the resulting stream.
In summary, the Java 8 Streams API flatMap() operator is an intermediate operation that transforms a stream of collections or arrays into a flat stream of individual elements. It is useful when we have a stream of elements containing nested collections or arrays and want to transform it into a stream of individual elements.
Here is another example in which we use the flatMap() method to gather the skills of Employees into a single stream:
public class Employee {
private String name;
private List<String> skills;
public Employee(String name, List<String> skills) {
this.name = name;
this.skills = skills;
}
public List<String> getSkills() {
return skills;
}
}
public class Main {
public static void main(String() args) {
List<Employee> employees = Arrays.asList(
new Employee("John", Arrays.asList("Java", "SQL")),
new Employee("Jane", Arrays.asList("Java", "Python", "C++")),
new Employee("Bob", Arrays.asList("Python", "Ruby"))
);
List<String> allSkills = employees.stream()
.flatMap(employee -> employee.getSkills().stream())
.distinct()
.collect(Collectors.toList());
System.out.println(allSkills); //Output: (Java, SQL, Python, Ruby)
}
}In this example, we have a class Employee with a getSkills() method that returns a list of the employee’s skills. We create a list of Employee objects and then use the flatMap() method to flatten the list of skills for each employee into a stream of individual skills. The flatMap() method takes a Function that returns a stream, and in this case, we use a lambda expression to return the stream of skills for each employee using the getSkills() method.
We then use the distinct() method to remove any duplicate skills from the resulting stream, and finally, use the collect() method to collect the stream of skills into a new List<String>. We then print out the list of all skills, which should be (Java, SQL, Python, C++, Ruby).
So, in summary, this example demonstrates how to use the flatMap() method to flatten a stream of lists into a stream of individual elements and how to use it to transform a stream of Employee objects into a stream of their distinct skills.
4. Stream distinct() operator
Stream<T> distinct()The distinct() operation returns a new stream containing the distinct elements from the original stream. The elements must be comparable or implement the hashCode() and equals() methods.
Here’s an example that removes duplicates from a list of integers:
List<Integer> numbers = Arrays.asList(1, 2, 2, 3, 3, 3, 4, 5, 5);
List<Integer> distinctNumbers = numbers.stream()
.distinct()
.collect(Collectors.toList());
System.out.println(distinctNumbers); // Output: (1, 2, 3, 4, 5)5. Stream sorted() operator
Stream<T> sorted()The ordered() method is an intermediate operation in Java 8 Streams API that returns a stream with elements sorted in their natural order. The natural order is either the order in which the elements were added to the stream or, for Comparable objects, the order determined by their compareTo() method implementation. The ordered() method ensures that the resulting stream will be ordered according to this natural order.
Here’s an example that sorts a list of strings in alphabetical order:
List<String> words = Arrays.asList("dog", "cat", "bird", "zebra", "elephant");
List<String> sortedWords = words.stream()
.sorted()
.collect(Collectors.toList());
System.out.println(sortedWords); // Output: (bird, cat, dog, elephant, zebra)We can also use the sorted() operator to sort a list of integers:
List<Integer> numbers = Arrays.asList(4, 2, 1, 5, 3);
List<Integer> sortedNumbers = numbers.stream()
.sorted()
.collect(Collectors.toList());
System.out.println(sortedNumbers); // Output (1, 2, 3, 4, 5)6. Stream peek() operator
Stream<T> peek(Consumer<? super T> action)The peek() operator in Java 8 Streams API is an intermediate operation that allows us to perform some side-effect actions on the elements of a stream without modifying the stream itself. The peek() method can be useful for debugging and troubleshooting, allowing us to inspect the stream elements as they pass through the pipeline.
Here’s an example that uses the peek() operator to print the elements of a stream as they pass through the pipeline:
List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5);
List<Integer> doubledNumbers = numbers.stream()
.peek(n -> System.out.println("Processing number: " + n))
.map(n -> n * 2)
.collect(Collectors.toList());
System.out.println(doubledNumbers);In this example, we have a list of integers numbers. We create a stream from this list using the stream() method and then use the peek() method to print a message for each element as it passes through the pipeline. We then use the map() method to double each element and finally collect the resulting stream into a new List<Integer> using the collect() method.
The output of this example will be:
Processing number: 1
Processing number: 2
Processing number: 3
Processing number: 4
Processing number: 5
(2, 4, 6, 8, 10)As we can see from the output, the peek() method allowed us to print a message for each stream element as it passed through the pipeline without modifying the stream elements or the pipeline itself.
It is important to note that the peek() method should be used only for debugging and troubleshooting purposes, not for modifying the stream elements or pipeline. Any modifications to the stream elements or the pipeline should be done using other intermediate operations, such as map(), filter(), and sorted().
In summary, the peek() operator in the Java 8 Streams API is an intermediate operation that allows us to perform side-effect actions on the elements of a stream without modifying the elements or the stream itself. It can be useful for debugging and troubleshooting purposes but should not be used for modifying the elements or the pipeline.
7. Stream skip() operator
Stream<T> skip(long N)The skip() operator in Java 8 Stream API is an intermediate operation that returns a new Stream with a specified number of initial elements skipped. This operator can be useful when you want to discard a certain number of elements from the beginning of a Stream before processing the remaining elements. It takes a single argument: the number of elements to skip. If the provided number is greater than or equal to the size of the Stream, an empty Stream will be returned.
Here’s an example to demonstrate the usage of the skip() operator:
List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);
// Create a Stream of numbers, skipping the first 5 elements
Stream<Integer> skippedStream = numbers.stream().skip(5);
// Print the remaining elements in the Stream
skippedStream.forEach(System.out::println);8. Stream limit() operator
Stream<T> limit(long N)The limit() operator in Java 8 Stream API is an intermediate operation that returns a new Stream with a specified maximum size. It is useful when truncating a Stream to a certain number of elements, effectively limiting the number of elements processed.
The limit() operator takes a single argument, the maximum number of elements you want the resulting Stream to have. If the provided number is greater than or equal to the size of the Stream, the entire Stream will be returned without truncation.
Here’s an example to demonstrate the usage of the limit() operator:
List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);
// Create a Stream of numbers, limiting it to the first 5 elements
Stream<Integer> limitedStream = numbers.stream().limit(5);
// Print the elements in the limited Stream
limitedStream.forEach(System.out::println);Terminal Operations in Java 8 Streams
Terminal operations in Java 8 Streams return a result or a side-effect. These operations are eager, meaning they execute immediately when called. Some of the important terminal operations in Java 8 Streams include:
forEach()– TheforEach()terminal operation is used to iterate over the elements of a stream and apply a function to each element.toArray()– returns an array containing the elements in the streamcollect()– Thecollect()method in Java 8 Streams is a terminal operation used to accumulate the elements of a stream into a collection or other type of data structure. Thecollect()method takes aCollectorobject as a parameter, which specifies how the elements of the stream should be accumulated.reduce()– Thereduceterminal operation combines the elements of a stream into a single value. It takes a binary operator as its argument, which is used to perform the reduction.count()– Thecount()method in Java 8 Streams is a terminal operation that returns the count of elements in the stream as a long value. This method does not modify the stream but instead returns a new value representing the number of elements in the stream.min()andmax()– Themin()andmax()methods in Java 8 Streams are terminal operations that return the minimum and maximum element in a stream, respectively. These methods require aComparatorobject to compare the elements in the stream, which is used to determine the minimum or maximum value.anyMatch(), allMatch(), noneMatch():- The anyMatch() final operator returns true if any element in the stream matches a given predicate.
- The allMatch() final operator returns true if all elements in the stream match a given predicate.
- The noneMatch() final operator returns true if no elements in the stream match a given predicate.
findFirst()andfindAny()– The findfindFirst()andfindAny()final operators return the first or any element in the stream that matches a given predicate.
1. Stream forEach() Final Operator
The forEach() method performs the given action for each element of the stream. It can perform side-effect operations on each stream element, such as printing the elements to the console.
List<String> names = Arrays.asList("John", "Jane", "Mark");
names.stream().forEach(System.out::println);2. Stream toArray() Final Operator
The toArray() method collects the elements of the stream into an array. It can be used to convert the elements of a stream into an array.
List<String> names = Arrays.asList("John", "Jane", "Mark");
String() namesArray = names.stream().toArray(String()::new);3. Stream reduce() Final Operator
The reduce() method performs a reduction operation on the elements of the stream. It can be used to reduce the elements of the stream to a single value, such as finding the sum of the elements or the maximum element.
List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5);
int sum = numbers.stream().reduce(0, (a, b) -> a + b);
System.out.println("The sum is: " + sum);4. Stream collect() Final Operator
The collect() method collects the elements of the stream into a collection or other data structure. It can be used to convert the elements of a stream into a List, Set, Map, or other collection.
List<String> names = Arrays.asList("John", "Jane", "Mark");
List<String> upperCaseNames = names.stream().map(String::toUpperCase).collect(Collectors.toList());5. Stream min() and max() Final Operators
The min() and max() methods return the minimum and maximum elements of the stream, respectively. They can be used to find the smallest or largest element of the stream, as long the elements implement the Comparator interface.
List<Integer> numbers = Arrays.asList(3, 6, 1, 8, 2, 10);
Optional<Integer> min = numbers.stream().min(Integer::compareTo);
Optional<Integer> max = numbers.stream().max(Integer::compareTo);
System.out.println("Minimum value: " + min.get());
System.out.println("Maximum value: " + max.get());6. Stream count() Final Operator
The count() method returns the count of elements in the stream. It can be used to find the number of elements in the stream.
List<String> names = Arrays.asList("John", "Jane", "Mark");
long count = names.stream().count();7. Stream anyMatch(), allMatch(), and NoneMatch() Final Operators
The anyMatch(), allMatch(), and noneMatch() methods check if any, all, or none of the elements in the stream match a given predicate, respectively. They can be used to check if a condition is true for any, all, or none of the elements in the stream.
List<String> words = Arrays.asList("apple", "banana", "cherry", "date");
// Test if any word starts with "b"
boolean anyStartsWithB = words.stream().anyMatch(s -> s.startsWith("b"));
System.out.println("Any word starts with B? " + anyStartsWithB); //Output: true
// Test if all words have length > 3
boolean allLengthGreaterThan3 = words.stream().allMatch(s -> s.length() > 3);
System.out.println("All words have length > 3? " + allLengthGreaterThan3); //Output: true
// Test if no words contain the letter "q"
boolean noneContainQ = words.stream().noneMatch(s -> s.contains("q"));
System.out.println("No words contain Q? " + noneContainQ); //Output: true8. Stream findFirst() and findAny() Final Operators
The findFirst() and findAny() methods return the first and any element of the stream, respectively. They can be used to find the first or any element of the stream.
findFirst() example
Here is an example using the findFirst() terminal operator to find the first even number in a stream of integers:
List<Integer> numbers = Arrays.asList(1, 3, 7, 2, 8, 4, 6);
Optional<Integer> firstEven = numbers.stream()
.filter(n -> n % 2 == 0)
.findFirst();
if (firstEven.isPresent()) {
System.out.println("The first even number is: " + firstEven.get());
} else {
System.out.println("There are no even numbers in the list.");
}In this example, we start by creating a list of integers. We then call the stream method to create a stream from the list. We use the filter intermediate operation to filter out all the odd numbers in the stream, leaving only the even numbers. Finally, we call the findFirst terminal operation to find the first even number in the stream.
The findFirst operation returns an Optional object which may or may not contain a value. In this example, we check if the Optional contains a value using the isPresent method. If it does, we get the value and print it to the console using the method. If it doesn’t, we print a message indicating no even numbers in the list.
Note that the findFirst operation is short-circuiting, meaning it only processes as many elements in the stream as it needs to find the first matching element. In this example, once the findFirst operation finds the first even number, it stops processing the stream and returns the result. This can be more efficient than processing the entire stream, especially if the stream is very large.
findAny() example
Below you will find an example using the findAny() to check whether a word that starts with the letter “A” appears in the stream.
List<String> words = Arrays.asList("apple", "banana", "apricot", "orange", "avocado");
Optional<String> anyA = words.stream()
.filter(s -> s.startsWith("A"))
.findAny();
if (anyA.isPresent()) {
System.out.println("Found a word starting with A: " + anyA.get());
} else {
System.out.println("No words starting with A found.");
}In this example, we start by creating a list of strings. We then call the stream method to create a stream from the list. We use the filter intermediate operation to filter out all the strings that do not start with the letter “A”. Finally, we call the findAny terminal operation to find any string in the stream that starts with the letter “A”.
Like findFirst, the findAny operation returns an Optional object, which may or may not contain a value. In this example, we check if the Optional object contains a value using the isPresent method. If it does, we get the value and print it to the console using the Optional.get() method. If it doesn’t, we print a message indicating that no words starting with “A” were found.
It’s worth noting that the findAny operation is non-deterministic and may return different results when called on the same stream. This is because the operation does not guarantee to return the first matching element in the stream, but rather any matching element. However, in practice, the findAny operation usually returns the same result each time it is called on the same stream unless the stream is modified between calls.
Parallel Streams: Concurrent Stream Processing
Parallel streams in Java 8 are a feature of the Stream API that enables parallel processing of elements in a Stream. Parallel streams divide the data into multiple chunks and process these chunks concurrently, leveraging multi-core processors to achieve better performance for compute-bound tasks. They can be particularly useful for large data sets and operations that require significant computational effort.
To create a parallel stream, you can either call the parallelStream() method on a collection or call the parallel() method on an existing sequential stream. Keep in mind that parallel streams can introduce potential issues, such as thread-safety concerns and unpredictable ordering, so it’s essential to ensure that the operations performed on the parallel stream are thread-safe and don’t rely on the order of elements.
Here’s an example of using a parallel stream to calculate the sum of squares of even numbers from a list:
import java.util.Arrays;
import java.util.List;
public class Main {
public static void main(String() args) {
List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);
// Create a parallel stream from the list
int sumOfSquares = numbers.parallelStream()
// Filter even numbers
.filter(n -> n % 2 == 0)
// Calculate square of each even number
.mapToInt(n -> n * n)
// Calculate the sum of squares
.sum();
System.out.println("Sum of squares of even numbers: " + sumOfSquares);
}
}In this example, we have a List of integers from 1 to 10. We create a parallel stream from the list using the parallelStream() method. Then, we apply the filter() operation to keep only even numbers, followed by the mapToInt() operation to calculate the square of each even number. Finally, we use the sum() operation to calculate the sum of squares. The parallel stream processes these operations concurrently, potentially improving performance compared to a sequential stream.
Note that this example assumes that the input list is large enough to benefit from parallel processing. Keep in mind that the overhead of creating and synchronizing parallel tasks might outweigh the performance benefits for small lists.
Conclusion
In conclusion, the Java 8 Stream API has introduced a powerful and expressive way to perform complex data manipulations and transformations on collections. The Stream API enables developers to write concise and efficient code for processing large data sets by leveraging functional programming principles and providing a rich set of built-in operations.
This tutorial covered the fundamentals of Java 8 streams, including the distinction between intermediate and terminal operations. It demonstrated how to create and manipulate streams using various operations such as filter(), map(), limit(), skip(), and parallel streams.
As you continue exploring the Stream API, you will discover even more capabilities to help you write clean, maintainable, and high-performance code. We encourage you to experiment with these concepts and integrate them into your projects to harness the full potential of Java 8 streams.
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