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HomeBackend DevelopmentGolangHow to Read Multiple Channels Simultaneously in Golang?

How to Read Multiple Channels Simultaneously in Golang?

Reading Multiple Channels Simultaneously in Golang

When working with concurrency in Golang, tasks are often divided into multiple goroutines communicating through channels. In situations where several goroutines produce values to be consumed by a single recipient, the need arises for a channel that collects data from multiple sources concurrently. This article addresses this requirement by exploring an efficient approach to constructing such "any-to-one" channels in Go.

Understanding the Challenge

Consider two goroutines, numgen1 and numgen2, writing numbers to separate channels, num1 and num2, respectively. The goal is to create a new process, addnum, that sums the numbers received from these channels.

A Proposed Solution

An initial attempt might involve using individual receive operations on both channels within a single goroutine:

func addnum(num1, num2, sum chan int) {
    done := make(chan bool)
    go func() {
        n1 := <p>However, this approach suffers from a fundamental issue: it only reads from one channel at a time, waiting for each value before proceeding to the next.</p><p><strong>A More Efficient Approach</strong></p><p>To enable concurrent reading from multiple channels, the select statement can be employed. This construct allows a goroutine to wait for operations on multiple channels simultaneously:</p><pre class="brush:php;toolbar:false">func main() {
    c1 := make(chan int)
    c2 := make(chan int)
    out := make(chan int)

    go func(in1, in2 <p>In this example, the select statement continuously waits for data on either c1 or c2. When a value is received from one channel, it is added to a sum, which is then output to the out channel.</p><p><strong>Conclusion</strong></p><p>By employing the select statement, it is possible to create an "any-to-one" channel in Golang, allowing multiple goroutines to write to a single channel concurrently. This approach enables efficient communication and data aggregation in complex concurrent systems.</p>

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