面试题：Java中StringTokenizer在海量数据解析场景下的性能优化

使用StringTokenizer解析单条数据：
- 由于文件每一行格式为'key1=value1;key2=value2;...'，可以使用StringTokenizer按';'分割字符串，再按'='分割每个子串来获取键值对。
- 示例代码如下：

import java.util.StringTokenizer;

public class TextParser {
    public static void main(String[] args) {
        String line = "key1=value1;key2=value2";
        StringTokenizer outerTokenizer = new StringTokenizer(line, ";");
        while (outerTokenizer.hasMoreTokens()) {
            String pair = outerTokenizer.nextToken();
            StringTokenizer innerTokenizer = new StringTokenizer(pair, "=");
            if (innerTokenizer.countTokens() == 2) {
                String key = innerTokenizer.nextToken();
                String value = innerTokenizer.nextToken();
                System.out.println(key + " : " + value);
            }
        }
    }
}

避免内存溢出的策略：
- 逐行读取：使用BufferedReader逐行读取大文件，而不是一次性加载整个文件到内存。示例代码如下：

import java.io.BufferedReader;
import java.io.FileReader;
import java.io.IOException;

public class BigFileParser {
    public static void main(String[] args) {
        try (BufferedReader br = new BufferedReader(new FileReader("largeFile.txt"))) {
            String line;
            while ((line = br.readLine()) != null) {
                // 在这里对每一行进行解析
                StringTokenizer outerTokenizer = new StringTokenizer(line, ";");
                while (outerTokenizer.hasMoreTokens()) {
                    String pair = outerTokenizer.nextToken();
                    StringTokenizer innerTokenizer = new StringTokenizer(pair, "=");
                    if (innerTokenizer.countTokens() == 2) {
                        String key = innerTokenizer.nextToken();
                        String value = innerTokenizer.nextToken();
                        System.out.println(key + " : " + value);
                    }
                }
            }
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
}

及时释放资源：在处理完每一行后，确保及时释放相关资源，如StringTokenizer对象。在上述代码中，StringTokenizer对象在每一行处理完毕后，会等待垃圾回收机制回收其占用的内存。

多线程环境下的优化：
- 任务划分：将大文件按行划分成多个任务，每个线程负责处理一部分行。例如，可以使用ExecutorService和Callable来实现多线程处理。
- 示例代码如下：

import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.*;

public class MultithreadedBigFileParser {
    public static void main(String[] args) {
        int numThreads = 4;
        ExecutorService executorService = Executors.newFixedThreadPool(numThreads);
        List<Future<List<String>>> futures = new ArrayList<>();
        try (BufferedReader br = new BufferedReader(new FileReader("largeFile.txt"))) {
            List<String> lines = new ArrayList<>();
            String line;
            int lineCount = 0;
            while ((line = br.readLine()) != null) {
                lines.add(line);
                lineCount++;
                if (lineCount % (numThreads) == 0) {
                    Callable<List<String>> task = new ParseTask(lines);
                    futures.add(executorService.submit(task));
                    lines = new ArrayList<>();
                }
            }
            if (!lines.isEmpty()) {
                Callable<List<String>> task = new ParseTask(lines);
                futures.add(executorService.submit(task));
            }
            for (Future<List<String>> future : futures) {
                try {
                    List<String> result = future.get();
                    for (String res : result) {
                        System.out.println(res);
                    }
                } catch (InterruptedException | ExecutionException e) {
                    e.printStackTrace();
                }
            }
        } catch (IOException e) {
            e.printStackTrace();
        } finally {
            executorService.shutdown();
        }
    }

    static class ParseTask implements Callable<List<String>> {
        private final List<String> lines;

        public ParseTask(List<String> lines) {
            this.lines = lines;
        }

        @Override
        public List<String> call() throws Exception {
            List<String> results = new ArrayList<>();
            for (String line : lines) {
                StringTokenizer outerTokenizer = new StringTokenizer(line, ";");
                while (outerTokenizer.hasMoreTokens()) {
                    String pair = outerTokenizer.nextToken();
                    StringTokenizer innerTokenizer = new StringTokenizer(pair, "=");
                    if (innerTokenizer.countTokens() == 2) {
                        String key = innerTokenizer.nextToken();
                        String value = innerTokenizer.nextToken();
                        results.add(key + " : " + value);
                    }
                }
            }
            return results;
        }
    }
}

数据一致性和解析准确性：
- 同步访问共享资源：如果多线程处理过程中有共享资源（例如统计解析结果的总数等），需要使用synchronized关键字或者java.util.concurrent.atomic包下的原子类来保证数据一致性。
- 解析准确性：在解析过程中，严格按照文件格式进行处理，对每个StringTokenizer的结果进行有效性检查，如上述代码中检查innerTokenizer.countTokens() == 2，确保键值对的正确解析。

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面试题：Java中StringTokenizer在海量数据解析场景下的性能优化

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