Analyzing Computer System Performance with Perl::PDQ by Neil J. Gunther PDF
By Neil J. Gunther
To clear up functionality difficulties in smooth computing infrastructures, usually comprising millions of servers operating countless numbers of purposes, spanning a number of degrees, you wish instruments that transcend mere reporting. you would like instruments that let functionality research of program workflow around the whole company. that is what PDQ (Pretty rattling quickly) offers. PDQ is an open-source functionality analyzer in accordance with the paradigm of queues. Queues are ubiquitous in each computing surroundings as buffers, and because any program structure could be represented as a circuit of queueing delays, PDQ is a average healthy for studying method performance.
Building at the luck of the 1st version, this significantly elevated moment variation now contains 4 elements. half I comprises the foundational suggestions, in addition to a brand new first bankruptcy that explains the valuable function of queues in winning functionality research. half II offers the fundamentals of queueing thought in a hugely intelligible variety for the non-mathematician; little greater than high-school algebra being required. half III offers many useful examples of ways PDQ could be utilized. The PDQ guide has been relegated to an appendix partly IV, in addition to suggestions to the routines contained in each one chapter.
Throughout, the Perl code listings were newly formatted to enhance clarity. The PDQ code and updates to the PDQ handbook can be found from the author's site at www.perfdynamics.com
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Extra info for Analyzing Computer System Performance with Perl::PDQ
This is all very convenient, but beware the overhead! Notice that the each task executed for 4 cpu-seconds but post-processing the results caused the script to take more than 2 min of wall-clock time to complete. It is also important to be aware that certain Benchmark functions must be explicitly imported into your scripts in order to become activated. One of these is the cmpthese() function. Notice also that the second argument in cmpthese() is a Perlhash reference. 8. pm, which updates the description of the Benchmark module in Wall et al.
5 shows one possible timing chain arrangement. There are only three links in the chain because only gross system instrumentation is available. In other words, there are only contiguous probes in the client application, the start and end of network services, and the database server. Client NIC LAN Router WAN Server Disk Fig. 6. Further decomposition of the timing chain in Fig. 5 Suppose the bottleneck is now found to be present somewhere in the network. It would useful if the network services link in the timing chain of Fig.
The disk is the primary bottleneck, taking approximately 30 ms to retrieve 8 KB of data. Since the RPC mechanism involves memory-to-memory copying, it is a major contributor to the 7 ms at the secondary bottleneck. The cautious reader should note that Redundant Arrays of Inexpensive Disks (RAID), and Storage Area Networks (SAN) usually do not oﬀer the possibility of resolving timing chains in this way. For the most part, they remain proprietary black boxes. 7 Failing Big Time Achievable performance can be constrained signiﬁcantly by poor reliability or lack of stability in a computer system.
Analyzing Computer System Performance with Perl::PDQ by Neil J. Gunther