Home > Article > Backend Development > How to choose a Go file reading solution
First, we need to have a comparison object. In view of the limited computer disk space, this article compares the differences in file reading at the three levels of KB, MB, and GB.
package main import ( "bufio" "math/rand" "os" "time" ) const charset = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789" var seededRand = rand.New(rand.NewSource(time.Now().UnixNano())) func StringWithCharset(length int) string { b := make([]byte, length) for i := range b { b[i] = charset[seededRand.Intn(len(charset))] } return string(b) } func main() { files := map[string]int{"4KB.txt": 4, "4MB.txt": 4096, "4GB.txt": 4194304, "16GB.txt": 16777216} for name, number := range files { file, err := os.OpenFile(name, os.O_WRONLY|os.O_CREATE, 0666) if err != nil { panic(err) } write := bufio.NewWriter(file) for i := 0; i < number; i++ { s := StringWithCharset(1023) + "\n" write.WriteString(s) } file.Close() } }
Executing the above code, we get files of 4KB, 4MB, 4GB, and 16GB in sequence, which are composed of the contents of random strings of 1KB per line.
$ ls -alh 4kb.txt 4MB.txt 4GB.txt 16GB.txt -rw-r--r-- 1 slp staff 16G Mar 6 15:57 16GB.txt -rw-r--r-- 1 slp staff 4.0G Mar 6 15:54 4GB.txt -rw-r--r-- 1 slp staff 4.0M Mar 6 15:53 4MB.txt -rw-r--r-- 1 slp staff 4.0K Mar 6 15:16 4kb.txt
Next, we use different ways to read the contents of these files.
Go provides methods to read the file contents at once: os.ReadFile and ioutil.ReadFile. Starting in Go 1.16, ioutil.ReadFile is equivalent to os.ReadFile.
func BenchmarkOsReadFile4KB(b *testing.B) { for i := 0; i < b.N; i++ { _, err := os.ReadFile("./4KB.txt") if err != nil { b.Fatal(err) } } } func BenchmarkOsReadFile4MB(b *testing.B) { for i := 0; i < b.N; i++ { _, err := os.ReadFile("./4MB.txt") if err != nil { b.Fatal(err) } } } func BenchmarkOsReadFile4GB(b *testing.B) { for i := 0; i < b.N; i++ { _, err := os.ReadFile("./4GB.txt") if err != nil { b.Fatal(err) } } } func BenchmarkOsReadFile16GB(b *testing.B) { for i := 0; i < b.N; i++ { _, err := os.ReadFile("./16GB.txt") if err != nil { b.Fatal(err) } } }
The advantages and disadvantages of one-time loading of files are very obvious. It can reduce the number of IOs, but it will load all the file contents into the memory. For large files, there is a possibility of memory overflow. risk.
在很多情况下,例如日志分析,对文件的处理都是按行进行的。Go 中 bufio.Reader 对象提供了一个 ReadLine() 方法,但其实我们更多地是使用 ReadBytes('\n') 或者 ReadString('\n') 代替。
// ReadLine is a low-level line-reading primitive. Most callers should use // ReadBytes('\n') or ReadString('\n') instead or use a Scanner.
我们以 ReadString('\n') 为例,对 4 个文件分别进行逐行读取
func ReadLines(filename string) { fi, err := os.Open(filename) if err != nil{ panic(err) } defer fi.Close() reader := bufio.NewReader(fi) for { _, err = reader.ReadString('\n') if err != nil { if err == io.EOF { break } panic(err) } } } func BenchmarkReadLines4KB(b *testing.B) { for i := 0; i < b.N; i++ { ReadLines("./4KB.txt") } } func BenchmarkReadLines4MB(b *testing.B) { for i := 0; i < b.N; i++ { ReadLines("./4MB.txt") } } func BenchmarkReadLines4GB(b *testing.B) { for i := 0; i < b.N; i++ { ReadLines("./4GB.txt") } } func BenchmarkReadLines16GB(b *testing.B) { for i := 0; i < b.N; i++ { ReadLines("./16GB.txt") } }
块读取也称为分片读取,这也很好理解,我们可以将内容分成一块块的,每次读取指定大小的块内容。这里,我们将块大小设置为 4KB。
func ReadChunk(filename string) { f, err := os.Open(filename) if err != nil { panic(err) } defer f.Close() buf := make([]byte, 4*1024) r := bufio.NewReader(f) for { _, err = r.Read(buf) if err != nil { if err == io.EOF { break } panic(err) } } } func BenchmarkReadChunk4KB(b *testing.B) { for i := 0; i < b.N; i++ { ReadChunk("./4KB.txt") } } func BenchmarkReadChunk4MB(b *testing.B) { for i := 0; i < b.N; i++ { ReadChunk("./4MB.txt") } } func BenchmarkReadChunk4GB(b *testing.B) { for i := 0; i < b.N; i++ { ReadChunk("./4GB.txt") } } func BenchmarkReadChunk16GB(b *testing.B) { for i := 0; i < b.N; i++ { ReadChunk("./16GB.txt") } }
汇总结果
BenchmarkOsReadFile4KB-8 92877 12491 ns/op BenchmarkOsReadFile4MB-8 1620 744460 ns/op BenchmarkOsReadFile4GB-8 1 7518057733 ns/op signal: killed BenchmarkReadLines4KB-8 90846 13184 ns/op BenchmarkReadLines4MB-8 493 2338170 ns/op BenchmarkReadLines4GB-8 1 3072629047 ns/op BenchmarkReadLines16GB-8 1 12472749187 ns/op BenchmarkReadChunk4KB-8 99848 12262 ns/op BenchmarkReadChunk4MB-8 913 1233216 ns/op BenchmarkReadChunk4GB-8 1 2095515009 ns/op BenchmarkReadChunk16GB-8 1 8547054349 ns/op
在本文的测试条件下(每行数据 1KB),对于小对象 4KB 的读取,三种方式差距并不大;在 MB 级别的读取中,直接加载最快,但块读取也慢不了多少;上了 GB 后,块读取方式会最快。
且有一点可以注意到的是,在整个文件加载的方式中,对于 16 GB 的文件数据(测试机器运行内存为 8GB),会内存耗尽出错,没法执行。
不管是什么大小的文件,均不推荐整个文件加载的方式,因为它在小文件时的速度优势并没有那么大,相较于安全隐患,不值得选择它。
块读取是优先选择,尤其对于一些没有换行符的文件,例如音视频等。通过设定合适的块读取大小,能让速度和内存得到很好的平衡。且在读取过程中,往往伴随着处理内容的逻辑。每块内容可以赋给一个工作 goroutine 来处理,能更好地并发。
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