Table of contents
1. Cause Analysis of CPU Bottleneck
2. The process is using too much CPU
3. Disk I/O read/write speed is too slow
2. CPU bottleneck tuning solution
1. Use the top command to view the CPU usage
Foreword:
During server operation, performance bottlenecks often occur. Among them, CPU bottleneck is one of the most common problems. This article will introduce the causes and tuning solutions of server CPU bottlenecks.
1. Cause Analysis of CPU Bottleneck
1. CPU usage is too high
High CPU usage is one of the main causes of CPU bottlenecks. When various processes and services are running at the same time, the CPU usage will increase accordingly, making the processing speed slower and causing CPU bottlenecks.
2. The process is using too much CPU
Processes can also consume CPU resources of the server, causing server CPU bottlenecks. The reason why the process uses too much CPU may be that there are problems such as infinite loops and recursion in the code, or it may be caused by reasons such as poor program design.
3. Disk I/O read/write speed is too slow
Slow disk I/O read and write speeds may also cause CPU bottlenecks. When a process needs to read and write a large number of disks, if the disk I/O speed cannot keep up, the CPU will be made to wait for the disk I/O operations to complete, wasting CPU resources and causing CPU bottlenecks.
2. CPU bottleneck tuning solution
1. Use the top command to view the CPU usage
top is a very important command, you can view the system status of the server, including CPU usage, memory usage, CPU usage of the process, etc. With the top command, it is easy to detect which process occupies too much CPU resources, so as to provide a tuning solution.
2. Optimize program design
Optimizing program design is an effective method to solve the CPU bottleneck problem. By optimizing the code and reducing problems such as invalid loop operations and recursion in the program, the CPU usage rate can be effectively reduced and the CPU utilization rate can be improved.
Below is an example of a Python program to test the amount of CPU time a program takes. By using the cProfile and pstats modules, it is easy to find functions in your code that consume more CPU time:
import cProfile, pstats
def test():
sum = 0
for i in range(1, 10000001):
sum += i
if __name__ == '__main__':
cProfile.run('test()', 'result')
p = pstats.Stats('result')
p.sort_stats('cumulative').print_stats()3. Use caching technology
Using caching technology can effectively reduce the disk I/O burden and improve the overall performance of the system. When data needs to be read and written frequently, the data can be stored in the cache, thereby reducing the read and write operations on the disk. You can use cache systems such as redis and memcached, or you can use local cache technologies, such as LRU cache in Python.
The following is a sample code using LRU cache in Python:
from functools import lru_cache
@lru_cache(maxsize=128)
def test(num):
sum = 0
for i in range(1, num + 1):
sum += i
return sum
if __name__ == '__main__':
print(test(1000000))In this example, the lru_cache decorator in Python's functools module is used to save the running results of the test function in the local cache, avoiding repeated calculations, and thus saving CPU resources.
Summarize:
This article introduces the causes of server CPU bottlenecks and tuning solutions, including using the top command to view CPU usage, optimizing program design, and using caching technology. In order to ensure the high performance of the server, it is necessary to reasonably plan the hardware configuration, reasonably arrange the operation mode of the process and service, find and solve the problem in time, so as to improve the stability and reliability of the server. At the same time, pay attention to using appropriate monitoring tools to monitor the status and performance of the server in a timely manner, and deal with problems in a timely manner to ensure the normal operation of the server.
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