How golang handles large files

PHPz
Release: 2023-04-27 09:19:08
Original
1355 people have browsed it

In development, we often encounter situations where we need to process large files. As an efficient and suitable language for concurrent processing, the Go language will naturally involve the processing of large files. Whether you are reading, writing or modifying large files, you need to consider some issues, such as: How to avoid memory leaks? How to deal with it efficiently? In this article, we will introduce several methods for processing large files, and focus on how to handle files that are too large to avoid program crashes.

  1. Use segmentation processing

Generally speaking, whether you are reading, writing or modifying large files, you need to consider how to avoid memory leaks and program crashes. . In order to effectively process large files, split processing is often used to divide the large file into multiple small files, and then read and write the small files.

In the Go language, we can split files through the io.LimitReader() and io.MultiReader() methods to split a large file into multiple small ones. Files are processed using multi-threading.

Read large files exceeding 500MB through the following code:

var (
    maxSize int64 = 100 * 1024 * 1024 //100MB
)
func readBigFile(filename string) (err error) {
    file, err := os.Open(filename)
    if err != nil {
        return err
    }
    defer file.Close()

    fileInfo, err := file.Stat()
    if err != nil {
        return err
    }

    if fileInfo.Size() <= maxSize {
        _, err = io.Copy(os.Stdout, file)
    } else {
        n := (fileInfo.Size() + (maxSize - 1)) / maxSize
        var err error
        for i := int64(0); i < n; i++ {
            eachSize := maxSize
            if i == n-1 {
                eachSize = fileInfo.Size() - (n-1)*maxSize
            }
            sectionReader := io.NewSectionReader(file, i*maxSize, eachSize)
            _, err = io.Copy(os.Stdout, sectionReader)
            if err != nil {
                return err
            }
        }
    }
    return nil
}
Copy after login

In the above code, when the file size read exceeds the maximum allowed value, the compound reading method will be used , divide the large file into multiple blocks of the same size for reading, and finally merge them into the final result.

The above method is of course optimized for the process of reading large files. Sometimes we also have file writing needs.

  1. Write a large file

The simplest way to write a large file in Go is to use the bufio.NewWriterSize() function package Go to os.File(), and determine whether the current buffer is full before writing. After it is full, call the Flush() method to write the data in the buffer to the hard disk. . This method of writing large files is simple and easy to implement and is suitable for writing large files.

    writer := bufio.NewWriterSize(file, size)
    defer writer.Flush()
    _, err = writer.Write(data)
Copy after login
  1. Processing large CSV files

In addition to reading and writing large files, we may also process large CSV files. When processing CSV files, if the file is too large, it will cause some program crashes, so we need to use some tools to process these large CSV files. The Go language provides a mechanism called goroutine and channel, which can process multiple files at the same time to achieve the purpose of quickly processing large CSV files.

In the Go language, we can use the csv.NewReader() and csv.NewWriter() methods to build processors for reading and writing CSV files respectively. , and then scan the file line by line to read the data. Use a pipeline in the CSV file to process the way the data is stored row by row.

func readCSVFile(path string, ch chan []string) {
    file, err := os.Open(path)
    if err != nil {
        log.Fatal("读取文件失败:", err)
    }
    defer file.Close()
    reader := csv.NewReader(file)
    for {
        record, err := reader.Read()
        if err == io.EOF {
            break
        } else if err != nil {
            log.Fatal("csv文件读取失败:", err)
        }
        ch <- record
    }
    close(ch)
}

func writeCSVFile(path string, ch chan []string) {
    file, err := os.Create(path)
    if err != nil {
        log.Fatal("创建csv文件失败:", err)
    }
    defer file.Close()
    writer := csv.NewWriter(file)
    for record := range ch {
        if err := writer.Write(record); err != nil {
            log.Fatal("csv文件写入失败: ", err)
        }
        writer.Flush()
    }
}
Copy after login

In the above code, use the csv.NewReader() method to traverse the file, store each line of data in an array, and then send the array to the channel. During reading the CSV file, we used goroutines and channels to scan the entire file concurrently. After reading, we close the channel to show that we have finished reading the file.

Through the above method, it is no longer necessary to read the entire data into memory when processing large files, avoiding memory leaks and program crashes, and also improving program running efficiency.

Summary:

In the above introduction, we discussed some methods of processing large files, including using split processing, writing large files and processing large CSV files. In actual development, we can choose an appropriate way to process large files based on business needs to improve program performance and efficiency. At the same time, when processing large files, we need to focus on memory issues, reasonably plan memory usage, and avoid memory leaks.

When using Go language to process large files, we can make full use of the features of Go language, such as goroutine and channel, so that the program can process large files efficiently and avoid memory leaks and program crashes. Although this article introduces relatively basic content, these methods can be applied to large file processing during development, thereby improving program performance and efficiency.

The above is the detailed content of How golang handles large files. For more information, please follow other related articles on the PHP Chinese website!

source:php.cn
Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Popular Tutorials
More>
Latest Downloads
More>
Web Effects
Website Source Code
Website Materials
Front End Template
About us Disclaimer Sitemap
php.cn:Public welfare online PHP training,Help PHP learners grow quickly!