How to Effectively "Max Out" Concurrent HTTP Requests?
When experimenting with Go's performance, you may encounter limitations while attempting to execute a high volume of HTTP requests concurrently. This article explores the challenges faced and provides a solution to achieve maximum concurrency.
The Problem
Your initial approach involves launching a large number of goroutines to send HTTP requests in parallel, expecting them to utilize all available CPUs. However, you encounter errors due to file descriptor limits.
The Solution
To overcome these limitations, consider the following approaches:
- Use a bounded semaphore channel to control concurrency: Implement a buffered channel that serves as a semaphore, limiting the number of concurrent requests. By adjusting the channel buffer size and tuning GOMAXPROCS, you can optimize concurrency for your system.
- Leverage a worker pool with a dispatcher: Employ a worker pool pattern where requests are queued into a channel. A dispatcher populates the channel, while a pool of workers processes requests one at a time. This approach ensures that the maximum number of concurrent requests is maintained.
- Utilize a dedicated consumer goroutine to process responses: To avoid blocking request processing, employ a dedicated goroutine to consume responses from the worker pool. This ensures continuous request execution, allowing your system to handle more concurrent requests.
Optimized Code
Here's a modified version of your code that incorporates these optimizations:
package main import ( "fmt" "net/http" "runtime" "sync" "time" ) var ( reqs int concurrent int work chan *http.Request results chan *http.Response ) func init() { reqs = 1000000 concurrent = 200 } func main() { runtime.GOMAXPROCS(runtime.NumCPU()) work = make(chan *http.Request, concurrent) results = make(chan *http.Response) start := time.Now() // Create a semaphore channel to limit concurrency sem := make(chan struct{}, concurrent) // Create a dispatcher to populate the work channel go func() { for i := 0; i <p>By adjusting the concurrent variable and observing the results, you can determine the optimal concurrency level for your system, "maxing out" its capacity for concurrent HTTP requests.</p>
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