BufferedReader.readLine()与大char数组FileReader.read的性能及存在意义探讨

Great question—this gets right to how Java’s I/O classes are optimized and when to pick which tool. Let’s break it down step by step:

First, let’s clarify why a large char[] gives FileReader such a big performance boost:
FileReader’s read(char[]) method delegates directly to the underlying native I/O layer to fill the array in one go. The biggest overhead in disk I/O isn’t moving data—it’s the context switching between user space and kernel space for each system call. A large array cuts down the number of these expensive calls drastically, which is exactly what BufferedReader does internally with its built-in buffer. So in bulk-read scenarios with a properly sized array, their performance can be very close.

But BufferedReader is still almost always the better choice, and here’s why:

1. No manual buffer management (less error-prone code) #

With FileReader, you’re stuck doing all the legwork:

• Creating and maintaining your own large char array
• Tracking exactly how many characters were read each time (via the return value of read())
• Handling partial buffer fills (especially near the end of a file)
  BufferedReader takes care of all this under the hood. You can call read() or readLine() without worrying about buffer sizes or partial reads—cleaner, simpler code that’s less likely to have bugs.

2. Built-in convenience methods FileReader lacks #

BufferedReader’s readLine() is a game-changer for text files. Implementing line-by-line reading with raw FileReader would mean manually scanning the char array for newline characters, handling splits across buffer boundaries, and building strings from partial reads—tedious and easy to mess up.

It also has other handy tools like skip(long) (optimized to skip within the buffer first before touching the underlying stream) and mark(int)/reset() for re-reading portions of the stream—features FileReader doesn’t offer at all.

3. Consistent performance no matter your read pattern #

If you ever switch from bulk reads to reading individual characters (e.g., reader.read()), FileReader’s performance will tank—each call triggers a separate system call. BufferedReader, though, reads chunks into its buffer first, so individual read() calls pull from memory, not the disk. This consistency is huge if your read pattern changes, or if you’re writing reusable code that might handle different read styles.

4. Flexibility via the decorator pattern #

BufferedReader works with any Reader implementation—not just FileReader. Want to wrap an InputStreamReader for custom charset handling? Or a StringReader for in-memory text? Just pass it to the BufferedReader constructor. With manual buffer management, you’d have to replicate that logic for every type of Reader you use, leading to duplicated, messy code.

5. Battle-tested, optimized buffer handling #

BufferedReader uses a default buffer size (8192 chars, 16KB) tuned for most common I/O scenarios. While you can pick a good size for your FileReader array, BufferedReader’s implementation is rigorously tested—it handles edge cases like stream interruptions, partial reads, and configurable buffer resizing seamlessly.

Quick performance comparison examples #

Bad FileReader usage (single char reads—terrible performance):

try (FileReader fr = new FileReader("file.txt")) {
    int c;
    while ((c = fr.read()) != -1) {
        // process character
    }
}

Good FileReader usage (bulk reads—decent performance):

try (FileReader fr = new FileReader("file.txt")) {
    char[] buf = new char[8192];
    int len;
    while ((len = fr.read(buf)) != -1) {
        // process buf[0..len-1]
    }
}

BufferedReader usage (clean, consistent performance):

try (BufferedReader br = new BufferedReader(new FileReader("file.txt"))) {
    String line;
    while ((line = br.readLine()) != null) {
        // process line
    }
}

In short: Using a large char array with FileReader can match BufferedReader’s bulk-read performance, but BufferedReader offers far more convenience, flexibility, and robust handling of real-world scenarios. It’s not just about speed—it’s about writing maintainable, error-free code.

内容的提问来源于stack exchange，提问作者user3233451