Analysis of the application case analysis of the JSR 166 frame retrospective version in the Java class library

The JSR 166 framework is an important part of Java concurrent programming. It provides a set of powerful tools and classes to simplify multi -threaded programming and concurrent data structure operations.This article will go back to the history of the JSR 166 framework, and introduce its application in the Java class library through case analysis. The JSR 166 framework was first released in 2004 and became part of the Java class library in Java SE 5.This framework provides a series of thread -safe sets, including ConcurrenThashMap, ConcurrenTlinkedQueue, ConcurrentSklistMap, etc., as well as the Executor framework for concurrent task scheduling.Below we will use a specific case to show the application of the JSR 166 framework in the Java library. Assuming that we have a need, we need to read data from a large file and perform statistics. At the same time, multiple threads are required to process different parts of data.Without concurrent treatment, it may cause performance bottlenecks.By using the class provided by the JSR 166 framework, we can easily implement this demand. First of all, we can use ConcurrenThashMap as the data structure of the storage statistics. It not only supports efficient concurrent reading, but also ensures thread security for writing operations. The following is an example code: ConcurrentHashMap<String, Integer> wordCountMap = new ConcurrentHashMap<>(); class WordProcessor implements Runnable { private String[] words; public WordProcessor(String[] words) { this.words = words; } @Override public void run() { for (String word : words) { wordCountMap.compute(word, (key, value) -> value == null ? 1 : value + 1); } } } // Assume that the large file has been divided by the line, and each row is stored as a string in the list List<String> lines = Files.readAllLines(Paths.get("large_file.txt")); ExecutorService executor = Executors.newFixedThreadPool(4); // Divide the file data to 4 parts, and each part is handed over to one thread to process int partitionSize = lines.size() / 4; for (int i = 0; i < 4; i++) { int startIndex = i * partitionSize; int endIndex = (i + 1) * partitionSize; String[] words = lines.subList(startIndex, endIndex).stream() .flatMap(line -> Arrays.stream(line.split(" "))) .toArray(String[]::new); executor.execute(new WordProcessor(words)); } executor.shutdown(); executor.awaitTermination(1, TimeUnit.MINUTES); // Output statistics results for (Map.Entry<String, Integer> entry : wordCountMap.entrySet()) { System.out.println(entry.getKey() + ": " + entry.getValue()); } In the above code, we first created a statistical result of the CONCURRENTHASHMAP to store the number of times.Then, we created a WordProcessor class that implements the Runnable interface to handle statistics for handling array.Next, we created a thread pool using the Executor framework and divided the file data into 4 parts, each part was treated by one thread.When each thread is processed, the compute method of ConcurrenThashmap uses the compute method to update the statistical results. Finally, we wait for all threads to complete the processing task, and then output statistical results.In this way, we use the concurrent tools and classes provided by the JSR 166 framework to achieve the needs of high -efficiency multi -threaded concurrent processing large files. Through the above cases, we can see the application advantage of the JSR 166 framework in the Java class library.It provides developers with a set of high -performance, thread security concurrent tools and classes, which greatly simplifies the complexity of multi -threaded programming and concurrent data operations.Whether it is to deal with a large amount of data, high and send access to shared resources, or to achieve asynchronous task scheduling, the JSR 166 framework can help us easily cope with the challenges of various concurrent programming.