我有一个超过400 GB的文件，例如：

ID Data ...4000+columns
001 dsa
002 Data
… …
17201297 asdfghjkl

我希望按照ID对文件进行分块，以更快地检索数据，例如：

mylocation/0/0/1/data.json
mylocation/0/0/2/data.json
.....
mylocation/1/7/2/0/1/2/9/7/data.json

我的代码工作正常，但是无论我使用哪种循环结束器，都至少需要159,206 milisoconds才能完成文件创建的0.001％。

在那种情况下，多线程是否可以降低时间复杂度（例如一次写入100或1k文件）？

我当前的代码是：

int percent = 0;
File file = new File(fileLocation + fileName);
FileReader fileReader = new FileReader(file); // to read input file

BufferedReader bufReader = new BufferedReader(fileReader);
BufferedWriter fw = null;
LinkedHashMap<String,BufferedWriter> fileMap = new LinkedHashMap<>();
int dataCounter = 0;

while ((theline = bufReader.readLine()) != null) {
    String generatedFilename = generatedFile + chrNo + "//" + directory + "gnomeV3.json";
    Path generatedJsonFilePath = Paths.get(generatedFilename);
    if (!Files.exists(generatedJsonFilePath)) {// create directory
        Files.createDirectories(generatedJsonFilePath.getParent());
        files.createFile(generatedJsonFilePath);
    }
    String jsonData = DBFileMaker(chrNo,theline,pos);
    if (fileMap.containsKey(generatedFilename)) {
        fw = fileMap.get(generatedFilename);
        fw.write(jsonData);
    } else {
        fw = new BufferedWriter(new OutputStreamWriter(new FileOutputStream(generatedFilename)));
        fw.write(jsonData);
        fileMap.put(generatedFilename,fw);
    }
    if (dataCounter == 172 * percent) {// As I know my number of rows
        long millisec = stopwatch.elapsed(TimeUnit.MILLISECONDS);
        System.out.println("Upto: " + pos + " as " + (Double) (0.001 * percent)
        + "% completion successful." + " took: " + millisec + " miliseconds");
        percent++;
    }
    dataCounter++;
}
for (BufferedWriter generatedFiles : fileMap.values()) {
    generatedFiles.close();
}