【转载】关于分析器中的90 percent
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下一篇 2011-10-20 17:18:53
/ 个人分类：LoadRunner
此文转自Zee的博客。
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）。
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