根據wiki百科解釋: benchmark問題就是基准測試問題.
1996 International Workshop on Structural Control 會議上提議組建歐洲、亞洲、和美國3個有關SHM的研究小組,並由 Chen倡導建立Benchmark結構,以便進行各種技術的直接比較.
許多業內比較出名的工具都提供benchmark 功能
- Apache Benchmark 簡稱(ab)
他是apache 組織下的一款web壓力測試工具, 因使用方便簡單而著稱.
ab一般常用參數是 –n -t 和 -c
-c（concurrency）表示用多少並發來進行測試(模擬並發數);
-t表示並發測試持續時間;
-n表示要發送多少次請求;
注意: 大小寫敏感
ab [get] 請求
ab -n 10 -c 3 https://www.baidu.com/
發送10個請求, 模擬3個並發數
Concurrency Level: 3 #當前並發數
Time taken for tests: 0.624 seconds #測試消耗時間
Complete requests: 10 # 完成請求數量
Failed requests: 0 #失敗的請求數
Total transferred: 8930 bytes # 共傳輸數據量
Requests per second: 20.24 [#/sec] (mean) #平均每秒完成請求個數
Time per request: 148.231 [ms] (mean) #每組請求消耗時間
Time per request: 49.410 [ms] (mean, across all concurrent requests) #每個請求消耗時間
Transfer rate: 17.65 [Kbytes/sec] received #傳輸速率
Percentage of the requests served within a certain time (ms)
50% 104 #104ms內已經完成了50%的請求
80% 161 #161ms內已經完成了80%的請求
ab [post] 請求
ab -n 100 -c 10 -p 'postdata.txt' -T 'application/x-www-form-urlencoded' 'http://xxx.api.com/'
-p postfile
-T Content-type header to use for POST/PUT data,
'application/x-www-form-urlencoded' Default is 'text/plain'
2 Redis-Beachmark
測試實例:
redis-benchmark -h localhost -p 6379 -c 3 -n 6
3個並發, 6個請求 檢測端口號6379的redis 性能
$ redis-benchmark -h localhost -p 6379 -c 3 -n 6
====== PING_INLINE ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
6000.00 requests per second
====== PING_BULK ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
inf requests per second
====== SET ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
6000.00 requests per second
====== GET ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
inf requests per second
====== INCR ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
inf requests per second
====== LPUSH ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
6000.00 requests per second
====== RPUSH ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
inf requests per second
====== LPOP ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
inf requests per second
====== RPOP ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
6000.00 requests per second
====== SADD ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
inf requests per second
====== HSET ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
inf requests per second
====== SPOP ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
inf requests per second
====== LPUSH (needed to benchmark LRANGE) ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
inf requests per second
====== LRANGE_100 (first 100 elements) ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
66.67% <= 1 milliseconds
100.00% <= 1 milliseconds
3000.00 requests per second
====== LRANGE_300 (first 300 elements) ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
3000.00 requests per second
====== LRANGE_500 (first 450 elements) ======
6 requests completed in 0.01 seconds
3 parallel clients
3 bytes payload
keep alive: 1
50.00% <= 1 milliseconds
100.00% <= 1 milliseconds
1000.00 requests per second
====== LRANGE_600 (first 600 elements) ======
6 requests completed in 0.01 seconds
3 parallel clients
3 bytes payload
keep alive: 1
66.67% <= 1 milliseconds
100.00% <= 1 milliseconds
1000.00 requests per second
====== MSET (10 keys) ======
6 requests completed in 0.00 seconds
3 parallel clients
3 bytes payload
keep alive: 1
100.00% <= 0 milliseconds
inf requests per second
redis-benchmark -h localhost -p 6379 -q -d 100
測試存取大小為100字節的數據包的性能
$ redis-benchmark -t set,lpush -n 100 -q //測試操作-t(set, lpush)的性能
SET: 20000.00 requests per second
LPUSH: 6666.67 requests per second
$ redis-benchmark -r 1000000 -n 2000000 -t get,set,lpush,lpop -P 16 -q //redis 管道Pipelining
SET: 142857.14 requests per second
GET: 117647.05 requests per second
LPUSH: 181818.19 requests per second
LPOP: 200000.00 requests per second
Redis是一種基於客戶端/服務端模型, reques/Response遵循TCP協議的服務
也就說:
客戶端向服務端發送一個查詢請求, 監聽socket返回, 通常以阻塞模式, 等待服務端響應. 服務端處理命令, 並將結果返回給客戶端.
Redis很早就支持管道（pipelining）技術，因此無論你運行的是什么版本，你都可以使用管道（pipelining）操作Redis。
下面是一個使用的例子：
$ (printf "PING\r\nPING\r\nPING\r\n"; sleep 1) | nc localhost 6379
+PONG
+PONG
+PONG
$ (echo -en "PING\r\n SET key redis\r\nGET key\r\nINCR x\r\nINCR x\r\nINCR x\r\n"; sleep 10) | nc localhost 6379
Using the TCP loopback:
louie-mac:~ louiezhou$ redis-benchmark -q -n 100000 -d 256
PING_INLINE: 36023.05 requests per second
PING_BULK: 36697.25 requests per second
SET: 34710.17 requests per second
GET: 35919.54 requests per second
INCR: 36927.62 requests per second
LPUSH: 27151.78 requests per second
RPUSH: 37160.91 requests per second
LPOP: 25348.54 requests per second
RPOP: 29958.06 requests per second
SADD: 34176.35 requests per second
HSET: 33411.29 requests per second
SPOP: 34002.04 requests per second
LPUSH (needed to benchmark LRANGE): 37105.75 requests per second
LRANGE_100 (first 100 elements): 10824.85 requests per second
LRANGE_300 (first 300 elements): 3895.90 requests per second
LRANGE_500 (first 450 elements): 2820.95 requests per second
LRANGE_600 (first 600 elements): 2107.26 requests per second
MSET (10 keys): 27987.69 requests per second
Benchmark測試中最重要的是標准規范，也就是說他是一個評價方式，工具等因素已經不重要，只要大家都用同一標准規范、同一工具進行系統測試，那么測試結果也就具有了比較意義。Benchmark 測試實際上就成了各個廠商展示技術實力的舞台, 任何廠家或者測試者都可以根據組織公布的規范標准, 構建自己最優的系統.
參考文獻:
https://redis.io/topics/pipelining
https://en.wikipedia.org/wiki/HTTP_pipelining
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