Go language is inefficient in processing massive URL access, how to optimize it?

Optimization of the efficiency of the Go language processing of million-level URL access

This article provides a series of performance optimization strategies for the inefficiency of Go's processing of massive URL access. Existing programs read 100 million URLs from CSV files, access and record accessible URLs one by one to another CSV file. Currently, it takes two hours to process one million URLs, and the efficiency needs to be improved. The program has adopted pipeline and coroutine concurrent processing, but there are still performance bottlenecks.

The main problem is that the http.Get method is used to download the entire web page content and increase the processing time. The following optimization solutions are designed to improve efficiency:

1. HEAD request replaces GET request:

The current code uses http.Get to get the full HTTP response, including all web page content. Just determine whether the URL is accessible, you can use the http.Head method to obtain only HTTP header information, significantly reducing the network request time and data transmission amount. Simply replace client.Get(url) with client.Head(url) and use res.StatusCode to determine whether the URL is accessible.

2. Batch exclusion based on domain name:

If you find that the URL under a domain name is inaccessible (such as DNS error, SSL error or connection failure), you can directly exclude all URLs under the domain name to avoid repeated attempts. This requires adding a domain name filtering mechanism in the code, such as using map to store known inaccessible domain names. Before sending the http.Head request, check whether the domain name corresponding to the URL is in the map , and skip it if it exists.

3. Adjust the timeout time and retry mechanism:

The current timeout is set to 1 second, which can be tried to shorten to 500 milliseconds or even shorter, speeding up processing speed. At the same time, you need to add a retry mechanism to retry a limited number of times on timeout or failed requests to avoid misjudgment. It is recommended to use an exponential backoff algorithm to control the retry interval to avoid excessive pressure on the server.

4. Optimize the number of coroutines and pipeline size:

The current code uses 100 coroutines, and the number of coroutines and pipeline size need to be adjusted according to actual conditions. Too many coroutines may increase context switching overhead, and too small pipelines may cause blockage. The best value needs to be found through experiments to balance concurrency and resource consumption.

Through the above optimization, the efficiency of Go language processing massive URL access can be significantly improved. It should be noted that these optimization solutions may reduce accuracy and need to weigh speed and accuracy based on actual needs. For example, reducing the timeout may cause some accessible URLs to be misjudged; adding retry mechanisms can improve accuracy, but also increase processing time.

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