How can I efficiently process large files in Go with limited RAM?

Rapid File Reading with Limited RAM in Go

Introduction

Parsing large files can be challenging, especially with limited system memory. This guide explores the most efficient approaches for reading and processing extensive text, JSON, and CSV files in Go with minimal RAM usage.

Document vs. Stream Parsing

There are two primary parsing methods: document parsing and stream parsing. Document parsing converts the entire file into in-memory data structures, making querying and manipulation convenient. However, this approach requires storing the entire file in memory.

Stream parsing reads the file one element at a time, allowing for immediate processing. This method saves memory, but data must be handled as it becomes available.

Go's File Processing Libraries

Go offers libraries for handling common file formats, such as CSV, JSON, and XML. These libraries provide efficient mechanisms for both document and stream parsing.

Processing CSV Files

CSV files can be parsed using the encoding/csv package. You can load the entire file into memory or process rows one at a time using a stream parser.

Processing JSON and XML Files

The Go standard library offers the encoding/json and encoding/xml packages for handling JSON and XML files. These packages provide both document parsing and streaming.

Concurrency with Channels

To leverage concurrency when processing files, you can use channels. Create a channel and a goroutine to asynchronously feed data to other concurrent processes.

Example

The following code demonstrates how to asynchronously process a CSV file:

<code class="go">package main

import (
    "encoding/csv"
    "fmt"
    "log"
    "os"
    "io"
)

func main() {
    file, err := os.Open("test.csv")
    if err != nil {
        log.Fatal(err)
    }

    parser := csv.NewReader(file)

    records := make( chan []string )
    go func() {
        defer close(records)
        for {
            record, err := parser.Read()
            if err == io.EOF {
                break
            }
            if err != nil {
                log.Fatal(err)
            }

            records </code>

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