Analyzing Computer Systems Performance: With Perl: PDQ by Neil J. Gunther

By Neil J. Gunther

 

The major motivation for this e-book stems from the remark that the folk who such a lot have to know how to do functionality research are quite often thwarted through the quantity of

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5. Response time represented as links in a timing chain Another way to think about the role of time-sinks or bottlenecks is to view each processing stage as a link in a chain of processing events. Each link corresponds to a processing stage. Borrowing a term well-known to auto mechanics, we call the chain in Fig. 5 a timing chain. , processing stages that can be measured with probes. This is usually best achieved by including the probes within the application code. In order for the end-to-end response time to be the sum of the time spent in each stage, the measurements must be sequential and the probe points must be contiguous.

5) The combinatorial factor accounts for the possible arrangements of intervals with events among intervals with none. More formally, the probability density function (PDF) is: f(n, t) = e−λt (λt)n , n = 1, 2, . . n! 6) is called the discrete probability mass function (PMF) when the random variable is discrete. 6) that the probability that there are no events at all during the period T is: f(0, t) = e−λt . 7) In other words, the distribution of time intervals is exponential. This is the basis for the important connection between the Poisson and the exponential distributions.

Representing the number of seconds since midnight January 1, 1900. The same as the ctime() or calendar time function in the C library. Returns the time is expressed in seconds and microseconds since midnight (00:00) UTC, January 1, 1970. The resolution is never worse than 100 HZ, which is equal to 10 ms. h>. The field tm year is the number of years since 1900. The calendar year 2003 is therefore represented as tm year = 103. 2 can be seen most easily by running the following Perl script on your favorite platform: #!

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