How to solve the problems of high concurrency and large traffic in PHP

This article mainly introduces how to solve the problems of high concurrency and large traffic in PHP. It has certain reference value. Now I share it with everyone. Friends in need can refer to it

Basic knowledge

## TFS: Throughput (Throughput refers to the number of requests the system handles per unit time)

RT: Response time (from the time the request is sent to the response time)

Number of concurrent users: The number of users who access the site at the same time within a period of time

QPS: Query rate per second (requests or responses per second, in the Internet field, the number of responses per second (HTTP requests))

PV ： page view page visits

UV：user view user visits

Generally speaking, the daily pv (visits) is greater than 10 million It can be calculated as high concurrency

Daily website bandwidth = PV / statistical time (seconds) * average page size (KB) * 8

Stress Test

It is recommended to use apache’s own stress testing tool ab

How to use : Enter the apache directory and run in the current directory (windows):

ab.exe -n 总请求量 -c 并发请求量 http://请求地址

After the request is completed, we can get the data:

Server Software: Apache/2.4.18 服务器类型 Server Hostname: eko.xiao.com 域名 Server Port: 80 端口 Document Path: /index.html 请求文件 Document Length: 529 bytes 文件大小 Concurrency Level: 100 并发数 Time taken for tests: 1.240 seconds 总响应时间 Complete requests: 1000 请求数 Failed requests: 0 失败次数 Total transferred: 800000 bytes 总共传输数据量 HTML transferred: 529000 bytes Requests per second: 806.41 [#/sec] (mean) QPS（每秒查询率） Time per request: 124.007 [ms] (mean) 平均响应时间 Time per request: 1.240 [ms] (mean, across all concurrent requests) Transfer rate: 630.00 [Kbytes/sec] received Connection Times (ms) min mean[+/-sd] median max Connect: 0 1 1.4 1 38 Processing: 42 114 34.2 103 204 Waiting: 41 113 33.9 102 204 Total: 43 115 34.5 104 207 Percentage of the requests served within a certain time (ms) 50% 104 66% 117 75% 133 80% 136 90% 173 95% 197 98% 204 99% 204 100% 207 (longest request)　　

Optimization

As QPS increases, different optimization measures are required at each stage. The optimization plan is also related to hardware and network conditions.

QPS reaches 50

No optimization is required

QPS reaches 100 (database layer)

Assuming that each database query is 0.01S and each page has only one sql query, then the database limit is reached at this time

Optimization measures : Database cache, database load balancing, redis, memcache

QPS reaches 800 (network bandwidth)

Assuming that each page is only 10K, then at 800QPS, the bandwidth has been exhausted

Optimization measures: CDN acceleration Load balancing

QPS reaches 1000

Optimization measures: Static page

Traffic optimization:

Anti-leeching processing

Front-end optimization:

Reduce HTTP requests

Add asynchronous requests

Enable browser cache

Server optimization:

Page Static

Concurrency processing

Queue processing

Database optimization:

Database cache

Sub-database and table, partition operation

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