Pholcus is a distributed, high concurrency, and powerful web crawler software written in Go. Monitoring the performance of your Pholcus scraping tasks can involve the following steps:
1. Logging
Pholcus provides logging capabilities which can be used to monitor the performance of your scraping tasks. You can log various metrics such as the number of requests made, the number of successful responses, the number of errors, and the time taken to execute requests.
log.Println("Total requests sent: ", totalRequests)
log.Println("Successful responses: ", successfulResponses)
log.Println("Error count: ", errorCount)
log.Println("Time taken for the task: ", timeTaken)
You can also implement custom logging to record performance metrics.
2. Real-time Monitoring Tools
You can integrate real-time monitoring tools such as Prometheus and Grafana with your Pholcus application to monitor performance.
- Prometheus: It can collect and store metrics as time series data. You would expose an endpoint from your Pholcus application to provide metrics to Prometheus.
- Grafana: It can be used for visualizing the data collected by Prometheus.
3. Custom Monitoring System
Implement a custom monitoring system within your Pholcus application where you collect and store performance metrics and then visualize them using a web dashboard or through logs.
4. Profiling
Go provides various profiling tools that can be used to monitor the performance of your application. You can analyze CPU usage, memory allocation, and execution traces.
To start a CPU profile, you can use the following code snippet in your Go application:
import "runtime/pprof"
f, err := os.Create("cpu.prof")
if err != nil {
log.Fatal(err)
}
pprof.StartCPUProfile(f)
defer pprof.StopCPUProfile()
And to get a heap profile:
f, err := os.Create("heap.prof")
if err != nil {
log.Fatal(err)
}
pprof.WriteHeapProfile(f)
f.Close()
Later, you can analyze these files using Go's pprof tool.
5. Health Checks
Implement health check endpoints in your application to ensure that your scraping tasks are running correctly. A health check endpoint could return basic information about the health of the application and any errors that may have occurred.
6. Error Handling
Proper error handling can help you identify performance issues. Make sure you catch and log exceptions or unexpected behaviors within your scraping tasks.
7. Using Middleware
If Pholcus supports middleware, you can write middleware functions that measure the time taken for requests to be processed and log any other relevant performance metrics.
8. Command Tools
You can use Go's built-in tools or third-party tools to monitor the performance of your system while Pholcus is running. For instance, top command in Unix-based systems or Get-Process in PowerShell for Windows can help you monitor the overall resource usage of your Pholcus tasks.
Conclusion
Monitoring the performance of Pholcus scraping tasks involves a combination of logging, using real-time monitoring tools, profiling, health checks, error handling, and potentially middleware. You should choose the appropriate strategy based on your application's needs and complexity.
Remember to always respect the target websites' terms of service and robots.txt files when scraping, and ensure that your scraping activities are not causing any harm or overload to the servers you are accessing.
