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1. Traditional method: reading file content in memory
Standards for reading file lines The way is to read in memory. Both Guava and Apache Commons IO provide a method to quickly read file lines as follows:
Files.readLines(new File(path), Charsets.UTF_8); FileUtils.readLines(new File(path));
In fact, use BufferedReader or other Subclass LineNumberReader to read.
The problem with the traditional approach: is that all lines of the file are stored in memory. When the file is large enough, it will soon cause the program to throw an OutOfMemoryError exception. .
Thinking about the problem: We usually don’t need to put all the lines of the file into memory at once. Instead, we only need to traverse each line of the file, and then Deal with it accordingly and throw it away when you're done. So we can read it by row iteration instead of putting all rows in memory.
2. Large file reading processing method
Without repeated reading and without running out of memory Processing large files:
(1) File stream method: Use the java.util.Scanner class to scan the contents of the file and read continuously line by line
FileInputStream inputStream = null; Scanner sc = null; try { inputStream = new FileInputStream(path); sc = new Scanner(inputStream, UTF-8); while (sc.hasNextLine()) { String line = sc.nextLine(); // System.out.println(line); } }catch(IOException e){ logger.error(e); }finally { if (inputStream != null) { inputStream.close(); } if (sc != null) { sc.close(); } }
This scheme will iterate through all lines in the file, allowing each line to be processed without maintaining a reference to it. In short, they are not stored in memory!
(2) Apache Commons IO stream: Implemented using the Commons IO library, using the custom LineIterator provided by the library
LineIterator it = FileUtils.lineIterator(theFile, UTF-8); try { while (it.hasNext()) { String line = it.nextLine(); // do something with line } } finally { LineIterator.closeQuietly(it); }
In this solution, the entire file is not all stored in the memory , which also leads to quite conservative memory consumption.
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