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先来看一段,官方的说明:
Solution: The 90th percentile is the value for which 90% of the data points are smaller
The 90th percentile is a measure of stastical distribution, not unlike the median. The median is the middle value. The median is the value for which 50% of the values were bigger, and 50% smaller. The 90th percentile tells you the value for which 90% of the data points are smaller and 10% are bigger.
Statistically, to calculate the 90th percentile value:
1. Sort the transaction instances by their value.
2. Remove the top 10% instances.
3. The highest value left is the 90th percentile.
Example:
There are ten instances of transaction "t1" with the values 1,3,2,4,5,20,7,8,9,6 (in sec).
1. Sort by value -- 1,2,3,4,5,6,7,8,9,20.
2. Remove top 10 % -- remove the value "20."
3. The highest value left is the 90th percentile -- 9 is the 90th percentile value.
The 90th percentile value answers the question, "What percentage of my transactions have a response time less than or equal to the 90th percentile value?" Given the above information, here is how LoadRunner calculates the 90th percentile.
In Analysis 6.5:
The values for the transaction are ordered in a list.
The 90% is taken from the ordered list of values. The place from which it is taken is
Rounding to the small value the number: 0.9 * (Number of Values - 1) + 1
In Analysis 7 and above:
Each value is counted in a range of values. For example, 5 can be counted in a range of 4.95 to 5.05, 7.2 in a range of 7.15 to 7.25. The 90% is taken from the range of values that the number of transaction in it and before it is >= ( 0.9 * Number of Values).
This difference in the methods can lead to different 90% values. Again, both methods lead to correct values as defined by the 90th percentile. However, the algorithm to calculate these figures has changed in LoadRunner 7 and above.
依照我的理解是这样的,它只是一个统计响应时间的参数。这个事务所有的运行次数中,90%的次数落在这个响应时间里。这个参数在tools-option里面是可以修改的,从而界定一个响应时间的范围,比如:
一个事务运行了10次时间分别如下:
12.3 15.4 15.9 16.6 17.8 18.5 19.5 20.5 21.5 22.5 (我随便写的数字哈)
那么这个90 percent 的值是21.5,即有10%个响应时间大于它,90%的时间小于或等于它。
那么,这个界定时间的统计值有什么作用呢?
我大概这样想的,如果这个值很大(我这里拿90%来说),那么就只说明了有很多事务响应时间很大,而这是个模糊而笼统的值。如果我定义到50%,且得到的值挺小,那对于性能来说又说明了什么?
如果我们只来分析大于这个界定值的点,也就是说,哪些响应时间大于这个值(因为可以定义所以当它大的时候我们把它能调小,再来和我们的要求达到一致),我们就只来分析这个点以上的响应时间的原因,就可以尽快分析出系统的瓶颈所在(当然这个也不是肯定的,因为瓶颈的分析要依赖很多方面的信息)。
不知道坛子上兄弟姐妹们是怎么来理解的?能通过它再联系到其他的什么信息呢?
[ 本帖最后由 Zee 于 2006-4-17 13:47 编辑 ] |
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