


Is Java 8\'s Streams API faster than traditional Collections in performance-critical scenarios?
Java 8: Streams vs Collections Performance Analysis
Evaluating the performance of the recently introduced Streams API in Java 8 compared to the traditional Collections approach is a crucial aspect for developers. To provide insights, an initial benchmark was conducted, which raised questions about the comparative efficacy of these two methods.
Benchmark Setup and Findings
The benchmark involved filtering a sizable list of integers and calculating the square root of even numbers, storing the results in a list of Double. The code snippet below illustrates the implementation:
<code class="java"> // Source list initialization List<Integer> sourceList = new ArrayList<>(); for (int i = 1; i < 1000000; i++) { sourceList.add(i); } // Collections approach List<Double> resultCollection = new LinkedList<>(); long startTimeCollection = System.nanoTime(); // Iterate through the list and perform calculations for (Integer i : sourceList) { if (i % 2 == 0) { resultCollection.add(Math.sqrt(i)); } } long elapsedTimeCollection = System.nanoTime() - startTimeCollection; // Stream approach Stream<Integer> stream = sourceList.stream(); long startTimeStream = System.nanoTime(); // Filter even numbers and calculate square roots resultStream = stream.filter(i -> i % 2 == 0) .map(i -> Math.sqrt(i)) .collect(Collectors.toList()); long elapsedTimeStream = System.nanoTime() - startTimeStream; // Parallel stream approach stream = sourceList.stream().parallel(); long startTimeParallelStream = System.nanoTime(); resultParallelStream = stream.filter(i -> i % 2 == 0) .map(i -> Math.sqrt(i)) .collect(Collectors.toList()); long elapsedTimeParallelStream = System.nanoTime() - startTimeParallelStream;</code>
The results on a dual-core machine revealed that:
- Collections approach performed noticeably faster, taking approximately 0.094 seconds.
- Stream approach showed a slower performance, requiring about 0.201 seconds.
- Parallel stream approach exhibited similar performance to the stream approach, completing in 0.357 seconds.
Analysis of Benchmark Results
Based on these initial findings, it was initially concluded that streams were slower than collections, with even parallelism failing to improve performance. However, the benchmark methodology employed raised concerns about potential flaws.
Improved Performance Verification
To address these concerns, the benchmark was revised with the following refinements:
- Execution: The benchmark was run 1,000 times after JVM warmup to stabilize performance.
- Profiling: JMH (Java Microbenchmarking Harness) was used to execute the benchmark accurately and collect performance data.
Updated Benchmark Results
The revised benchmark yielded the following results:
- Collections approach: Average time of 0.207 seconds
- Stream approach: Average time of 0.098 seconds
- Parallel stream approach: Average time of 0.168 seconds
In this revised benchmark, streams outperformed collections, contrary to the initial findings. The faster execution time of the stream approach can be attributed to JIT optimizations and improved code generation by the compiler.
Conclusion
Based on these updated findings, it can be concluded that streams in Java 8 offer both coding convenience and performance enhancements when compared to traditional collections. While streams are not always superior, their use can significantly simplify code and improve efficiency in many scenarios.
Best Practices
To leverage the benefits of streams effectively, consider the following best practices:
- Use inline lambda expressions for brevity and efficiency.
- Avoid unnecessary intermediate Lists and focus on using a target collection directly.
- Explore the parallel stream capabilities to optimize performance in certain situations.
The above is the detailed content of Is Java 8\'s Streams API faster than traditional Collections in performance-critical scenarios?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











Troubleshooting and solutions to the company's security software that causes some applications to not function properly. Many companies will deploy security software in order to ensure internal network security. ...

Solutions to convert names to numbers to implement sorting In many application scenarios, users may need to sort in groups, especially in one...

Field mapping processing in system docking often encounters a difficult problem when performing system docking: how to effectively map the interface fields of system A...

Start Spring using IntelliJIDEAUltimate version...

When using MyBatis-Plus or other ORM frameworks for database operations, it is often necessary to construct query conditions based on the attribute name of the entity class. If you manually every time...

Conversion of Java Objects and Arrays: In-depth discussion of the risks and correct methods of cast type conversion Many Java beginners will encounter the conversion of an object into an array...

Detailed explanation of the design of SKU and SPU tables on e-commerce platforms This article will discuss the database design issues of SKU and SPU in e-commerce platforms, especially how to deal with user-defined sales...

How does the Redis caching solution realize the requirements of product ranking list? During the development process, we often need to deal with the requirements of rankings, such as displaying a...
