使用多个fork和join类来分割任务，是不是一个好习惯？

Question

对于我的工作，我必须开发一个解析非常大的文本文件（〜6800 kb）的小型Java应用程序，所以我正在尝试优化它以创建更进一步的流程。用equalto（=）分割线作为第一个分叉任务，并用逗号分割并使用第二个分叉任务进行一些计算。这将导致对单个应用程序执行多个分叉任务的良好性能。

1）首先fork和join过程：

@Override 
protected Map < String, String > compute() { 
SplitString lineSplit = new SplitString(); 
Map < String, String > splitUrl = new HashMap < >(); 
// list size is less than limit process actual task. 

if (readAllLines.size() < Constant.LIMIT) { 
    // splitUrl map stores the splitter lines with equal_to 
    splitUrl = lineSplit.splittingLines(readAllLines); 

} else { // list size greater than limit splits task in to two and process it. 
    // split task into sub task and stores it in list 
    List <String> left = readAllLines.subList(Constant.ZERO, readAllLines.size()/2); 
    List <String> right = readAllLines.subList(readAllLines.size()/2, readAllLines.size()); 
    SplitTask firstTask = new SplitTask(left); 
    SplitTask secondTask = new SplitTask(right); 
    // forks the firstTask 
    firstTask.fork(); 
    // forks the secondTask 
    secondTask.fork(); 
    // join the task in splitUrl map 
    splitUrl.putAll(firstTask.join()); 
    splitUrl.putAll(secondTask.join()); 
} 
return splitUrl; 
} 

2）第二fork和join过程：

@Override 
protected Map < String, Map < String, Integer >> compute() { 
    SplitString ruleSplit = new SplitString(); 
    Map < String, Map < String, Integer >> response = new HashMap < >(); 
    // list size is less than limit process actual task. 

    if (KeyList.size() < Constant.LIMIT) { 
     // splitUrl map stores the splitter lines with equal_to 
     response = ruleSplit.calculatingRuleTime(result, KeyList); 

    } else { // list size greater than limit splits task in to two and process it. 
     // split task into sub task and stores it in list. 
     List <String> left = KeyList.subList(Constant.ZERO, KeyList.size()/2); 
     List <String> right = KeyList.subList(KeyList.size()/2, KeyList.size()); 
     SplitRuleTask firstTask = new SplitRuleTask(result, left); 
     SplitRuleTask secondTask = new SplitRuleTask(result, right); 
     // forks the firstTask 
     firstTask.fork(); 
     // forks the firstTask 
     secondTask.fork(); 
     // join the task in response map 
     response.putAll(firstTask.join()); 
     response.putAll(secondTask.join()); 
    } 
    return response; 
} 

任何人都可以请帮我吗？

Answer 1

叉子也创造一个沉重的重量过程。我建议你阅读线程概念，然后在其上实现多线程。 更高级的方法是创建线程池来工作。我建议你阅读下面的链接。