下面是JMeter负载测试场景：
500 VU负载（分布在50个Docker示例上，每个示例10 VU）
我正在使用bzm -并发线程组，其中：

Target Concurrency: 10
Ramp up Time: 300 Sec
Ramp Up Steps Count: 12
Hold Target Rate Time ( sec ) : 150

我使用的是“一次性控制器”，共有5个样本x1c 0d1x

start: Thu May 12 15:02:22 UTC 2022
end:   Thu May 12 15:12:49 UTC 2022

如果我们看一下日志的最后几行：

summary +    168 in 00:00:29 =    5.7/s Avg: 42368 Min:   268 Max: 102718 Err:    38 (22.62%) Active: 423 Started: 32453 Finished: 32122
summary =   1197 in 00:04:51 =    4.1/s Avg: 20447 Min:     8 Max: 102718 Err:   179 (14.95%)
summary +    171 in 00:00:31 =    5.6/s Avg: 52979 Min:  1817 Max: 108987 Err:    57 (33.33%) Active: 456 Started: 185979 Finished: 185615
summary =   1368 in 00:05:22 =    4.2/s Avg: 24513 Min:     8 Max: 108987 Err:   236 (17.25%)
summary +    165 in 00:00:31 =    5.2/s Avg: 47737 Min:  2400 Max: 135806 Err:    92 (55.76%) Active: 469 Started: 465197 Finished: 464820
summary =   1533 in 00:05:53 =    4.3/s Avg: 27013 Min:     8 Max: 135806 Err:   328 (21.40%)
summary +    226 in 00:00:28 =    8.1/s Avg: 45517 Min:  2391 Max: 138464 Err:   136 (60.18%) Active: 460 Started: 781788 Finished: 781420
summary =   1759 in 00:06:21 =    4.6/s Avg: 29390 Min:     8 Max: 138464 Err:   464 (26.38%)
summary +    213 in 00:00:31 =    7.0/s Avg: 41327 Min:   172 Max: 169472 Err:   121 (56.81%) Active: 452 Started: 1194172 Finished: 1193812
summary =   1972 in 00:06:52 =    4.8/s Avg: 30680 Min:     8 Max: 169472 Err:   585 (29.67%)
summary +    247 in 00:00:29 =    8.4/s Avg: 46833 Min:   305 Max: 189829 Err:   133 (53.85%) Active: 455 Started: 1625193 Finished: 1624830
summary =   2219 in 00:07:21 =    5.0/s Avg: 32478 Min:     8 Max: 189829 Err:   718 (32.36%)
summary +    179 in 00:00:30 =    5.9/s Avg: 49431 Min:  6934 Max: 186370 Err:    68 (37.99%) Active: 389 Started: 2079677 Finished: 2079380
summary =   2398 in 00:07:52 =    5.1/s Avg: 33743 Min:     8 Max: 189829 Err:   786 (32.78%)
summary +    206 in 00:00:31 =    6.7/s Avg: 60255 Min:    35 Max: 204533 Err:    89 (43.20%) Active: 247 Started: 2407457 Finished: 2407302
summary =   2604 in 00:08:22 =    5.2/s Avg: 35841 Min:     8 Max: 204533 Err:   875 (33.60%)
summary +    190 in 00:00:29 =    6.5/s Avg: 52622 Min:   326 Max: 261898 Err:    95 (50.00%) Active: 136 Started: 2502691 Finished: 2502647
summary =   2794 in 00:08:52 =    5.3/s Avg: 36982 Min:     8 Max: 261898 Err:   970 (34.72%)
summary +    282 in 00:00:29 =    9.6/s Avg: 49788 Min:    58 Max: 195675 Err:   140 (49.65%) Active: 14 Started: 2502691 Finished: 2502769
summary =   3076 in 00:09:21 =    5.5/s Avg: 38156 Min:     8 Max: 261898 Err:  1110 (36.09%)
summary +     50 in 00:00:30 =    1.7/s Avg: 29200 Min:   176 Max: 120778 Err:    17 (34.00%) Active: 3 Started: 2502691 Finished: 2502780
summary =   3126 in 00:09:51 =    5.3/s Avg: 38013 Min:     8 Max: 261898 Err:  1127 (36.05%)
summary +     16 in 00:00:12 =    1.3/s Avg: 17752 Min:   236 Max: 37998 Err:     6 (37.50%) Active: 0 Started: 2502691 Finished: 2502783
summary =   3142 in 00:10:03 =    5.2/s Avg: 37909 Min:     8 Max: 261898 Err:  1133 (36.06%)
Tidying up remote @ Thu May 12 15:12:42 GMT 2022 (1652368362418)
... end of run
++ date
+ echo 'END Running Jmeter on Thu May 12 15:12:49 UTC 2022'

10分钟运行500个虚拟线程（用户）
问：那么，如果负载为500个用户，我们为什么会有“Started：2502691英寸螺纹
我试着这样解释：您在“线程组”下定义了模拟真实的用户的线程（虚拟用户
JMeter启动线程，以尽可能快的速度执行采样器，并每秒生成一定数量的请求。
1.虚拟用户数
1.应用程序响应时间
查看：

summary +     16 in 00:00:12 =    1.3/s Avg: 17752 Min:   236 Max: 37998 Err:     6 (37.50%) Active: 0 Started: 2502691 Finished: 2502783
and
summary =   3142 in 00:10:03 =    5.2/s Avg: 37909 Min:     8 Max: 261898 Err:  1133 (36.06%)

这是否意味着，（最后一步：激发了3142个请求，整个测试花费了10分3秒，激发了每秒5.2个请求或每秒5.2个线程？
如果您有500个虚拟用户，并且应用程序响应时间为1秒，则您将拥有500 RPS
如果您有500个虚拟用户，并且应用程序响应时间为2秒，则您将拥有250 RPS
如果您有500个虚拟用户，并且应用程序响应时间为500毫秒，则您将拥有1000 RPS。

那么，“开始：2502691完成日期：2502783”数字代表什么？
这是否意味着目标系统可以处理10分钟内完成的2502783个线程或每秒4171个请求？但这与500 VU负载有何关系？
但是由于响应时间更长，所以这个数字应该更低，对吗？