Greetings!
I have been presented with an interesting task, but I am unfamiliar with it and would prefer to avoid reinventing the wheel.
The task at hand involves an online store consisting of 10,000 pages. Due to the weight of the website, page load times range from 2 to 8 seconds. However, there is a static caching module installed that caches the page upon first opening, reducing load times to 0.2 seconds. The cache lifetime is set to 1 day for both search engine spiders and users alike.
To tackle this issue, my objective is to write a PHP script that will take a list of site URLs from a database, and sequentially open them to launch the cache creation mechanism. The challenge here is to execute the script without causing a time-out or an overabundance on the server's resources.
One possible solution is to crawl the pages in chunks, with intervals between each page opening. A date field could be created in the URL table, whereupon the script can be initiated for selected records as required, with a limit of 10 records per cycle. In the event of a successful page opening, the date field will then be updated. This script should then be scheduled for automatic running at intervals of one minute between 2 and 6 am.
However, I believe there might be a more elegant solution to this issue and perhaps there already exist scripts designed for this specific purpose.
Do you have any suggestions or thoughts on this matter?
It is possible to simplify the task of crawling a list of URLs by uploading it to a text file and configuring siege to crawl the file daily.
This one-line solution can be configured with siege options, allowing for flexible management of the process such as adjusting the number of threads or timeouts. Additionally, disk space won't be clogged up, and a detailed report will be generated for analysis.
In my opinion, the best approach would be to profile your online store. The process is fairly straightforward - you make a local copy and run profiling, then optimize based on the results. Typically, xdebug, blackfire, and tambourine are used during this process.
For a simpler solution, you can upload a list of URLs to a separate table or file, and then run your script using cron with 20-30 threads. To address the issue of multiple threads, you can use two GET parameters (such as "s" and "f") and add tasks to your cron job accordingly.
You can add as many cron tasks as you need, as providers typically do not have limits on their number. If a URL is opened twice, it is not a big deal, but you should be mindful of potential hosting load. You can experimentally determine the optimal number of threads and records to pass at a time.
Regardless of the approach you choose, you will need to mark the list of URLs in some way, such as recording the timestamp of the last pass. You can also set CRON tasks to run once a minute and ignore URLs that have been passed within 24 hours. Additionally, you can set limits for script work hours.
While this approach can be seen as a temporary fix, it can provide a valuable solution until you can do more extensive profiling or migrate to another platform.
You do not require a script to run wget recursively and download everything. One bash command can be used to run wget through the website with multiple threads, search for links and proceed to download them.
This method can be useful for downloading entire websites or specific directories. However, it is important to consider the legal implications and copyright laws before downloading any content. Additionally, be mindful of the potential strain this may put on the website's server.
The solution you're suggesting is indeed a good start, but let's discuss some potential improvements and additional considerations that might help you to streamline the process more effectively.
First, the basic idea of chunking the URLs and processing them in intervals is sound. However, there are a few aspects we should refine:
Parallel Processing: Instead of opening URLs sequentially, you can process multiple URLs in parallel, but still keep the total number low enough to avoid stressing the server. Using something like cURL multi-handle in PHP, you can handle multiple requests at once, which will significantly speed up the process while keeping the server load under control.
Error Handling and Retry Mechanism: It's important to implement robust error handling. Sometimes, a page might fail to load due to temporary issues, so having a retry mechanism in place would be beneficial. If a page fails to cache properly, the script could wait a few seconds and then try again.
Throttling: Throttling is critical here. Instead of a hard limit of 10 URLs per minute, consider dynamically adjusting the rate based on the server's current load. You could implement a monitoring function that checks the server load before deciding how many URLs to process in the next cycle. This would make the script more adaptive and less likely to cause server issues.
Database Optimization: When pulling URLs from the database, it's a good idea to optimize the queries to ensure that they are fast and efficient. Indexing the date field can improve performance, especially if you're frequently querying and updating it.
Script Execution: Instead of relying on cron jobs, you might consider using a long-running PHP process that sleeps between cycles. This approach can be more efficient than starting a new script every minute, as it reduces the overhead associated with repeatedly initiating the script. Just be sure to include memory management in your script to prevent it from becoming bloated over time.
Logging and Reporting: Implementing logging is key for tracking the script's performance and diagnosing any issues. You could log how long it takes to cache each page, any errors encountered, and overall execution times. Having this information would be valuable for troubleshooting and optimizing the process.
External Tools: Depending on your hosting environment, you might have access to tools or services that can handle this task more efficiently. For example, if you're using a Content Delivery Network (CDN), some CDNs have features that automatically cache pages at regular intervals. Alternatively, you might consider using a headless browser (like Puppeteer or PhantomJS) to pre-render and cache pages more accurately.
While your approach is solid, consider leveraging parallel processing, implementing adaptive throttling, optimizing your database interactions, and exploring any external tools that might simplify the task. By taking these steps, you should be able to create a more efficient and reliable script to handle the caching of your large online store without causing unnecessary strain on your server.
Why not ditch the DIY struggle and leverage a proper queue system like RabbitMQ or Redis to handle URL processing without choking your server? Your 1-minute cron idea during witching hours is cute, but it's still a gamble on timeouts if the server's a potato. And cURL-ing pages in batches without throttling? You're begging for a 503 error party.
Get real - use a battle-tested library like Guzzle for async requests or just grab a cache-preloading bot off the shelf.