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  • Linux - real-world hardware RAID controller tuning (scsi and cciss)

    - by ewwhite
    Most of the Linux systems I manage feature hardware RAID controllers (mostly HP Smart Array). They're all running RHEL or CentOS. I'm looking for real-world tunables to help optimize performance for setups that incorporate hardware RAID controllers with SAS disks (Smart Array, Perc, LSI, etc.) and battery-backed or flash-backed cache. Assume RAID 1+0 and multiple spindles (4+ disks). I spend a considerable amount of time tuning Linux network settings for low-latency and financial trading applications. But many of those options are well-documented (changing send/receive buffers, modifying TCP window settings, etc.). What are engineers doing on the storage side? Historically, I've made changes to the I/O scheduling elevator, recently opting for the deadline and noop schedulers to improve performance within my applications. As RHEL versions have progressed, I've also noticed that the compiled-in defaults for SCSI and CCISS block devices have changed as well. This has had an impact on the recommended storage subsystem settings over time. However, it's been awhile since I've seen any clear recommendations. And I know that the OS defaults aren't optimal. For example, it seems that the default read-ahead buffer of 128kb is extremely small for a deployment on server-class hardware. The following articles explore the performance impact of changing read-ahead cache and nr_requests values on the block queues. http://zackreed.me/articles/54-hp-smart-array-p410-controller-tuning http://www.overclock.net/t/515068/tuning-a-hp-smart-array-p400-with-linux-why-tuning-really-matters http://yoshinorimatsunobu.blogspot.com/2009/04/linux-io-scheduler-queue-size-and.html For example, these are suggested changes for an HP Smart Array RAID controller: echo "noop" > /sys/block/cciss\!c0d0/queue/scheduler blockdev --setra 65536 /dev/cciss/c0d0 echo 512 > /sys/block/cciss\!c0d0/queue/nr_requests echo 2048 > /sys/block/cciss\!c0d0/queue/read_ahead_kb What else can be reliably tuned to improve storage performance? I'm specifically looking for sysctl and sysfs options in production scenarios.

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  • Server Performance

    - by sb12
    I know very little about performance tuning of servers etc... so i thought i'd put this up here as i start some research on it, just to get some direction. I am in the process of migrating from my old server to a new one - both are 64 bit machines. One is a few years old, the other brand new (PowerEdge R410). The old server spec is: 2 cpus, 3.4GHz Pentiums, 8G of RAM, Fedora 11 currently installed The new server spec is: 16 cpus, 3.2 GHz Xeon, 16G of RAM, CentOS 6.2 installed. Also RAID10 is on the new server - no RAID on the old one. Both servers currently have the same database (MySQL) with the same data migrated. I wrote a Perl script that simply steps through each row of a table in the database (about 18000 rows) and updates a value in that row. Every row in the table is updated. Out of curiosity i ran this perl script on both machines, just to see how the new server would perform vs. the old one, and it produced interesting results: The old server was twice as fast as the new one to complete. Looking at the database, both are configured exactly the same (the new one being a dump of the old one...)... Anyone any ideas why this would be given the hardware gap between both? As i said i'm about to start some digging, but thought i'd put this up here to maybe get some good direction.... Many thanks in advance..

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  • How can I tell which page is creating a high-CPU-load httpd process?

    - by Greg
    I have a LAMP server (CentOS-based MediaTemple (DV) Extreme with 2GB RAM) running a customized Wordpress+bbPress combination . At about 30k pageviews per day the server is starting to groan. It stumbled earlier today for about 5 minutes when there was an influx of traffic. Even under normal conditions I can see that the virtual server is sometimes at 90%+ CPU load. Using Top I can often see 5-7 httpd processes that are each using 15-30% (and sometimes even 50%) CPU. Before we do a big optimization pass (our use of MySQL is probably the culprit) I would love to find the pages that are the main offenders and deal with them first. Is there a way that I can find out which specific requests were responsible for the most CPU-hungry httpd processes? I have found a lot of info on optimization in general, but nothing on this specific question. Secondly, I know there are a million variables, but if you have any insight on whether we should be at the boundaries of performance with a single dedicated virtual server with a site of this size, then I would love to hear your opinion. Should we be thinking about moving to a more powerful server, or should we be focused on optimization on the current server?

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  • How to collect the performance data of a server during an unreachable/down period using Nagios?

    - by gsc-frank
    Some time services and host stop responding due to a poor server performance. I mean, if for some reason (could be lot of concurrency services access, a expensive backup execution on the server or whatever that consume tons of server resources) a server performance is very degraded, that could lead that the server isn't capable to establish any "normal network communication" (without trigger whatever standards timeouts defined for such communication). Knowing host's performance data (cpu, memory, ...) in case of available during that period (host is not down and despite of its performance degradation still allow plugins collect performance data) could be very useful for sysadmin to try to determine what cause the problem, or at least, if the host performance was good and don't interfered at all in the host/service down. This problem could be solved using remote active (NRPE) or remote passive (NSCA) if such remote solutions could store (buffered) perf data to be send to central Nagios server when host performance or network outage allow it. I read the doc of both solutions and can't find any reference to such buffer mechanism neither what happened in case that NSCA can't reach Nagios server. Any idea of how solve this lack of info? so useful for forensic analysis. EDIT: My questions isn about which tools I can use to debug perf problems or gather perf data to analysis, but is about how collect (using Nagios) host perf data even during a network outage for its posterior analysis (kind of forensic analysis). The idea is integrate such data to Nagios graphers like pnp4nagios and NagiosGrapther. I know that I could install tools like Cacti in each of my host, and have a kind of performance data collection redundancy, but I really want avoid that and try to solve all perf analysis requirements with one tools: Nagios

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  • SQL Server 2005 standard filegroups / files for performance on SAN

    - by Blootac
    I submitted this to stack overflow (here) but realised it should really be on serverfault. so apologies for the incorrect and duplicate posting: Ok so I've just been on a SQL Server course and we discussed the usage scenarios of multiple filegroups and files when in use over local RAID and local disks but we didn't touch SAN scenarios so my question is as follows; I currently have a 250 gig database running on SQL Server 2005 where some tables have a huge number of writes and others are fairly static. The database and all objects reside in a single file group with a single data file. The log file is also on the same volume. My interpretation is that separate data files should be used across different disks to lessen disk contention and that file groups should be used for partitioning of data. However, with a SAN you obviously don't really have the same issue of disk contention that you do with a small RAID setup (or at least we don't at the moment), and standard edition doesn't support partitioning. So in order to improve parallelism what should I do? My understanding of various Microsoft publications is that if I increase the number of data files, separate threads can act across each file separately. Which leads me to the question how many files should I have. One per core? Should I be putting tables and indexes with high levels of activity in separate file groups, each with the same number of data files as we have cores? Thank you

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  • KVM Slow performance on XP Guest

    - by Gregg Leventhal
    The system is very slow to do anything, even browse a local folder, and CPU sits at 100% frequently. Guest is XP 32 bit. Host is Scientific Linux 6.2, Libvirt 0.10, Guest XP OS shows ACPI Multiprocessor HAL and a virtIO driver for NIC and SCSI. Installed. CPUInfo on host: processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 42 model name : Intel(R) Core(TM) i7-2600 CPU @ 3.40GHz stepping : 7 cpu MHz : 3200.000 cache size : 8192 KB physical id : 0 siblings : 8 core id : 0 cpu cores : 4 apicid : 0 initial apicid : 0 fpu : yes fpu_exception : yes cpuid level : 13 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx rdtscp lm constant_tsc arch_perfmon pebs bts rep_good xtopology nonstop_tsc aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic popcnt tsc_deadline_timer aes xsave avx lahf_lm ida arat epb xsaveopt pln pts dts tpr_shadow vnmi flexpriority ept vpid bogomips : 6784.93 clflush size : 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: <memory unit='KiB'>4194304</memory> <currentMemory unit='KiB'>4194304</currentMemory> <vcpu placement='static' cpuset='0'>1</vcpu> <os> <type arch='x86_64' machine='rhel6.3.0'>hvm</type> <boot dev='hd'/> </os> <features> <acpi/> <apic/> <pae/> </features> <cpu mode='custom' match='exact'> <model fallback='allow'>SandyBridge</model> <vendor>Intel</vendor> <feature policy='require' name='vme'/> <feature policy='require' name='tm2'/> <feature policy='require' name='est'/> <feature policy='require' name='vmx'/> <feature policy='require' name='osxsave'/> <feature policy='require' name='smx'/> <feature policy='require' name='ss'/> <feature policy='require' name='ds'/> <feature policy='require' name='tsc-deadline'/> <feature policy='require' name='dtes64'/> <feature policy='require' name='ht'/> <feature policy='require' name='pbe'/> <feature policy='require' name='tm'/> <feature policy='require' name='pdcm'/> <feature policy='require' name='ds_cpl'/> <feature policy='require' name='xtpr'/> <feature policy='require' name='acpi'/> <feature policy='require' name='monitor'/> <feature policy='force' name='sse'/> <feature policy='force' name='sse2'/> <feature policy='force' name='sse4.1'/> <feature policy='force' name='sse4.2'/> <feature policy='force' name='ssse3'/> <feature policy='force' name='x2apic'/> </cpu> <clock offset='localtime'> <timer name='rtc' tickpolicy='catchup'/> </clock> <on_poweroff>destroy</on_poweroff> <on_reboot>restart</on_reboot> <on_crash>restart</on_crash> <devices> <emulator>/usr/libexec/qemu-kvm</emulator> <disk type='file' device='disk'> <driver name='qemu' type='qcow2' cache='none'/> <source file='/var/lib/libvirt/images/Server-10-9-13.qcow2'/> <target dev='vda' bus='virtio'/> <alias name='virtio-disk0'/> <address type='pci' domain='0x0000' bus='0x00' slot='0x08' function='0x0'/> </disk>

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  • Application Performance: The Best of the Web

    - by Michaela Murray
    Wisdom A deep understanding and realization […] resulting in the ability to apply perceptions, judgements and actions. It is also the comprehension of what is true coupled with optimum judgment as to action. - Wikipedia We’re writing a book for ASP.NET developers, and we want you to be a part of it. We know that there’s a huge amount of web developer wisdom that never gets shared, and we want to find those golden nuggets of knowledge and experience, and make sure everyone can learn from them. Right now, we want to find out about your top tips, hard-won lessons, and sage advice for avoiding, finding, and fixing application performance problems. If you work with .NET and SQL, even better – a lot of application performance relies on the interaction with the database, so we want to hear from you! “How Do You Want Me To Be Involved?” Right! Details! We want you, our most excellent readers, to email us with the Best Advice you would give to other developers for getting the best performance out of their applications. It doesn’t matter if your advice is for newbies or veterans, .NET or SQL – so long as it’s about application performance, we want to hear from you. (And if you think that there’s developer wisdom out there that “everyone knows”, a) I’m willing to bet you could find someone who doesn’t know about it, and b) it probably bears repeating anyway!) “I’m Interested. What Can You Do For Me?” Excellent question. For starters, there’s a chance to win a Microsoft Surface (the tablet, not the table-top). Once all the ASP.NET Wisdom has been collected, tallied, and labelled, it will then be weighed and measured by a team of expert judges (whose identities are still a closely-guarded secret).  The top tip in both SQL & .NET categories will each win their author their very own MS Surface. But that’s not all! We can also give you… immortality! More details? Ok. We’ll be collecting all of the tips sent in by our readers (and we can’t wait to learn from you all,) and with the help of our Simple-Talk editors, we will publish and distribute your combined and documented knowledge as a free, community-created, professionally typeset eBook. You will naturally be credited by name / pseudonym / twitter handle / GitHub username / StackOverflow profile / Whatever, as the clearly ingenious author of hot performance tips. The Not-Very-Fine Print Here’s the breakdown: We want to bring together the best application performance knowledge from ASP.NET developers. Closing date for submissions will be 9am GMT, December 4th. Submissions should be made by email – [email protected] Submissions will be judged by a panel of expert judges (who will be revealed soon). The top submission in both the SQL & .NET categories will each win a Microsoft Surface. ALL the tips which make it through the judging process will be polished by Simple-Talk editors, and turned into a professionally typeset eBook, which will be freely available, and promoted alongside the ANTS Performance Profiler tool. Anyone whose entry makes it into the book will be clearly and profusely credited in the method of their choice (or can remain anonymous.) The really REALLY short version Share what you know about ASP.NET application performance for a chance to win a Microsoft Surface, and then get your name credited in a slick eBook with top-notch production values. For more details, see above. We can’t wait to learn from you!

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  • Analysing and measuring the performance of a .NET application (survey results)

    - by Laila
    Back in December last year, I asked myself: could it be that .NET developers think that you need three days and a PhD to do performance profiling on their code? What if developers are shunning profilers because they perceive them as too complex to use? If so, then what method do they use to measure and analyse the performance of their .NET applications? Do they even care about performance? So, a few weeks ago, I decided to get a 1-minute survey up and running in the hopes that some good, hard data would clear the matter up once and for all. I posted the survey on Simple Talk and got help from a few people to promote it. The survey consisted of 3 simple questions: Amazingly, 533 developers took the time to respond - which means I had enough data to get representative results! So before I go any further, I would like to thank all of you who contributed, because I now have some pretty good answers to the troubling questions I was asking myself. To thank you properly, I thought I would share some of the results with you. First of all, application performance is indeed important to most of you. In fact, performance is an intrinsic part of the development cycle for a good 40% of you, which is much higher than I had anticipated, I have to admit. (I know, "Have a little faith Laila!") When asked what tool you use to measure and analyse application performance, I found that nearly half of the respondents use logging statements, a third use performance counters, and 70% of respondents use a profiler of some sort (a 3rd party performance profilers, the CLR profiler or the Visual Studio profiler). The importance attributed to logging statements did surprise me a little. I am still not sure why somebody would go to the trouble of manually instrumenting code in order to measure its performance, instead of just using a profiler. I personally find the process of annotating code, calculating times from log files, and relating it all back to your source terrifyingly laborious. Not to mention that you then need to remember to turn it all off later! Even when you have logging in place throughout all your code anyway, you still have a fair amount of potentially error-prone calculation to sift through the results; in addition, you'll only get method-level rather than line-level timings, and you won't get timings from any framework or library methods you don't have source for. To top it all, we all know that bottlenecks are rarely where you would expect them to be, so you could be wasting time looking for a performance problem in the wrong place. On the other hand, profilers do all the work for you: they automatically collect the CPU and wall-clock timings, and present the results from method timing all the way down to individual lines of code. Maybe I'm missing a trick. I would love to know about the types of scenarios where you actively prefer to use logging statements. Finally, while a third of the respondents didn't have a strong opinion about code performance profilers, those who had an opinion thought that they were mainly complex to use and time consuming. Three respondents in particular summarised this perfectly: "sometimes, they are rather complex to use, adding an additional time-sink to the process of trying to resolve the existing problem". "they are simple to use, but the results are hard to understand" "Complex to find the more advanced things, easy to find some low hanging fruit". These results confirmed my suspicions: Profilers are seen to be designed for more advanced users who can use them effectively and make sense of the results. I found yet more interesting information when I started comparing samples of "developers for whom performance is an important part of the dev cycle", with those "to whom performance is only looked at in times of crisis", and "developers to whom performance is not important, as long as the app works". See the three graphs below. Sample of developers to whom performance is an important part of the dev cycle: Sample of developers to whom performance is important only in times of crisis: Sample of developers to whom performance is not important, as long as the app works: As you can see, there is a strong correlation between the usage of a profiler and the importance attributed to performance: indeed, the more important performance is to a development team, the more likely they are to use a profiler. In addition, developers to whom performance is an important part of the dev cycle have a higher tendency to use a much wider range of methods for performance measurement and analysis. And, unsurprisingly, the less important performance is, the less varied the methods of measurement are. So all in all, to come back to my random questions: .NET developers do care about performance. Those who care the most use a wider range of performance measurement methods than those who care less. But overall, logging statements, performance counters and third party performance profilers are the performance measurement methods of choice for most developers. Finally, although most of you find code profilers complex to use, those of you who care the most about performance tend to use profilers more than those of you to whom performance is not so important.

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  • C# Performance Pitfall – Interop Scenarios Change the Rules

    - by Reed
    C# and .NET, overall, really do have fantastic performance in my opinion.  That being said, the performance characteristics dramatically differ from native programming, and take some relearning if you’re used to doing performance optimization in most other languages, especially C, C++, and similar.  However, there are times when revisiting tricks learned in native code play a critical role in performance optimization in C#. I recently ran across a nasty scenario that illustrated to me how dangerous following any fixed rules for optimization can be… The rules in C# when optimizing code are very different than C or C++.  Often, they’re exactly backwards.  For example, in C and C++, lifting a variable out of loops in order to avoid memory allocations often can have huge advantages.  If some function within a call graph is allocating memory dynamically, and that gets called in a loop, it can dramatically slow down a routine. This can be a tricky bottleneck to track down, even with a profiler.  Looking at the memory allocation graph is usually the key for spotting this routine, as it’s often “hidden” deep in call graph.  For example, while optimizing some of my scientific routines, I ran into a situation where I had a loop similar to: for (i=0; i<numberToProcess; ++i) { // Do some work ProcessElement(element[i]); } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This loop was at a fairly high level in the call graph, and often could take many hours to complete, depending on the input data.  As such, any performance optimization we could achieve would be greatly appreciated by our users. After a fair bit of profiling, I noticed that a couple of function calls down the call graph (inside of ProcessElement), there was some code that effectively was doing: // Allocate some data required DataStructure* data = new DataStructure(num); // Call into a subroutine that passed around and manipulated this data highly CallSubroutine(data); // Read and use some values from here double values = data->Foo; // Cleanup delete data; // ... return bar; Normally, if “DataStructure” was a simple data type, I could just allocate it on the stack.  However, it’s constructor, internally, allocated it’s own memory using new, so this wouldn’t eliminate the problem.  In this case, however, I could change the call signatures to allow the pointer to the data structure to be passed into ProcessElement and through the call graph, allowing the inner routine to reuse the same “data” memory instead of allocating.  At the highest level, my code effectively changed to something like: DataStructure* data = new DataStructure(numberToProcess); for (i=0; i<numberToProcess; ++i) { // Do some work ProcessElement(element[i], data); } delete data; Granted, this dramatically reduced the maintainability of the code, so it wasn’t something I wanted to do unless there was a significant benefit.  In this case, after profiling the new version, I found that it increased the overall performance dramatically – my main test case went from 35 minutes runtime down to 21 minutes.  This was such a significant improvement, I felt it was worth the reduction in maintainability. In C and C++, it’s generally a good idea (for performance) to: Reduce the number of memory allocations as much as possible, Use fewer, larger memory allocations instead of many smaller ones, and Allocate as high up the call stack as possible, and reuse memory I’ve seen many people try to make similar optimizations in C# code.  For good or bad, this is typically not a good idea.  The garbage collector in .NET completely changes the rules here. In C#, reallocating memory in a loop is not always a bad idea.  In this scenario, for example, I may have been much better off leaving the original code alone.  The reason for this is the garbage collector.  The GC in .NET is incredibly effective, and leaving the allocation deep inside the call stack has some huge advantages.  First and foremost, it tends to make the code more maintainable – passing around object references tends to couple the methods together more than necessary, and overall increase the complexity of the code.  This is something that should be avoided unless there is a significant reason.  Second, (unlike C and C++) memory allocation of a single object in C# is normally cheap and fast.  Finally, and most critically, there is a large advantage to having short lived objects.  If you lift a variable out of the loop and reuse the memory, its much more likely that object will get promoted to Gen1 (or worse, Gen2).  This can cause expensive compaction operations to be required, and also lead to (at least temporary) memory fragmentation as well as more costly collections later. As such, I’ve found that it’s often (though not always) faster to leave memory allocations where you’d naturally place them – deep inside of the call graph, inside of the loops.  This causes the objects to stay very short lived, which in turn increases the efficiency of the garbage collector, and can dramatically improve the overall performance of the routine as a whole. In C#, I tend to: Keep variable declarations in the tightest scope possible Declare and allocate objects at usage While this tends to cause some of the same goals (reducing unnecessary allocations, etc), the goal here is a bit different – it’s about keeping the objects rooted for as little time as possible in order to (attempt) to keep them completely in Gen0, or worst case, Gen1.  It also has the huge advantage of keeping the code very maintainable – objects are used and “released” as soon as possible, which keeps the code very clean.  It does, however, often have the side effect of causing more allocations to occur, but keeping the objects rooted for a much shorter time. Now – nowhere here am I suggesting that these rules are hard, fast rules that are always true.  That being said, my time spent optimizing over the years encourages me to naturally write code that follows the above guidelines, then profile and adjust as necessary.  In my current project, however, I ran across one of those nasty little pitfalls that’s something to keep in mind – interop changes the rules. In this case, I was dealing with an API that, internally, used some COM objects.  In this case, these COM objects were leading to native allocations (most likely C++) occurring in a loop deep in my call graph.  Even though I was writing nice, clean managed code, the normal managed code rules for performance no longer apply.  After profiling to find the bottleneck in my code, I realized that my inner loop, a innocuous looking block of C# code, was effectively causing a set of native memory allocations in every iteration.  This required going back to a “native programming” mindset for optimization.  Lifting these variables and reusing them took a 1:10 routine down to 0:20 – again, a very worthwhile improvement. Overall, the lessons here are: Always profile if you suspect a performance problem – don’t assume any rule is correct, or any code is efficient just because it looks like it should be Remember to check memory allocations when profiling, not just CPU cycles Interop scenarios often cause managed code to act very differently than “normal” managed code. Native code can be hidden very cleverly inside of managed wrappers

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  • How often is software speed evident in the eyes of customers?

    - by rwong
    In theory, customers should be able to feel the software performance improvements from first-hand experience. In practice, sometimes the improvements are not noticible enough, such that in order to monetize from the improvements, it is necessary to use quotable performance figures in marketing in order to attract customers. We already know the difference between perceived performance (GUI latency, etc) and server-side performance (machines, networks, infrastructure, etc). How often is it that programmers need to go the extra length to "write up" performance analyses for which the audience is not fellow programmers, but managers and customers?

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  • Strange C++ performance difference?

    - by STingRaySC
    I just stumbled upon a change that seems to have counterintuitive performance ramifications. Can anyone provide a possible explanation for this behavior? Original code: for (int i = 0; i < ct; ++i) { // do some stuff... int iFreq = getFreq(i); double dFreq = iFreq; if (iFreq != 0) { // do some stuff with iFreq... // do some calculations with dFreq... } } While cleaning up this code during a "performance pass," I decided to move the definition of dFreq inside the if block, as it was only used inside the if. There are several calculations involving dFreq so I didn't eliminate it entirely as it does save the cost of multiple run-time conversions from int to double. I expected no performance difference, or if any at all, a negligible improvement. However, the perfomance decreased by nearly 10%. I have measured this many times, and this is indeed the only change I've made. The code snippet shown above executes inside a couple other loops. I get very consistent timings across runs and can definitely confirm that the change I'm describing decreases performance by ~10%. I would expect performance to increase because the int to double conversion would only occur when iFreq != 0. Chnaged code: for (int i = 0; i < ct; ++i) { // do some stuff... int iFreq = getFreq(i); if (iFreq != 0) { // do some stuff with iFreq... double dFreq = iFreq; // do some stuff with dFreq... } } Can anyone explain this? I am using VC++ 9.0 with /O2. I just want to understand what I'm not accounting for here.

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  • mysql settings - using the available resources

    - by Christian Payne
    I've got a lot of processing work I need to run on a mysql server. I've installed mysql 5.1.45-community on a Win 2007 64bit. Its running on a xenon, 3ghz 6 processors with 8 gig ram. It doesn't seem to matter what queries I run (or the number I run at the same time), when I look in task manager, I'll see one processor is out at 100%. The other 5 are idol. Memory is static at 1.54 gig. When I installed mysql, I used the wizard and selected the default "server" (not workstation) option. I feel like I should be getting more bang for my buck. Is there something else I should be monitoring or something I should change to use the other system resources???

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  • SQL SERVER – Server Side Paging in SQL Server 2011 Performance Comparison

    - by pinaldave
    Earlier, I have written about SQL SERVER – Server Side Paging in SQL Server 2011 – A Better Alternative. I got many emails asking for performance analysis of paging. Here is the quick analysis of it. The real challenge of paging is all the unnecessary IO reads from the database. Network traffic was one of the reasons why paging has become a very expensive operation. I have seen many legacy applications where a complete resultset is brought back to the application and paging has been done. As what you have read earlier, SQL Server 2011 offers a better alternative to an age-old solution. This article has been divided into two parts: Test 1: Performance Comparison of the Two Different Pages on SQL Server 2011 Method In this test, we will analyze the performance of the two different pages where one is at the beginning of the table and the other one is at its end. Test 2: Performance Comparison of the Two Different Pages Using CTE (Earlier Solution from SQL Server 2005/2008) and the New Method of SQL Server 2011 We will explore this in the next article. This article will tackle test 1 first. Test 1: Retrieving Page from two different locations of the table. Run the following T-SQL Script and compare the performance. SET STATISTICS IO ON; USE AdventureWorks2008R2 GO DECLARE @RowsPerPage INT = 10, @PageNumber INT = 5 SELECT * FROM Sales.SalesOrderDetail ORDER BY SalesOrderDetailID OFFSET @PageNumber*@RowsPerPage ROWS FETCH NEXT 10 ROWS ONLY GO USE AdventureWorks2008R2 GO DECLARE @RowsPerPage INT = 10, @PageNumber INT = 12100 SELECT * FROM Sales.SalesOrderDetail ORDER BY SalesOrderDetailID OFFSET @PageNumber*@RowsPerPage ROWS FETCH NEXT 10 ROWS ONLY GO You will notice that when we are reading the page from the beginning of the table, the database pages read are much lower than when the page is read from the end of the table. This is very interesting as when the the OFFSET changes, PAGE IO is increased or decreased. In the normal case of the search engine, people usually read it from the first few pages, which means that IO will be increased as we go further in the higher parts of navigation. I am really impressed because using the new method of SQL Server 2011,  PAGE IO will be much lower when the first few pages are searched in the navigation. Test 2: Retrieving Page from two different locations of the table and comparing to earlier versions. In this test, we will compare the queries of the Test 1 with the earlier solution via Common Table Expression (CTE) which we utilized in SQL Server 2005 and SQL Server 2008. Test 2 A : Page early in the table -- Test with pages early in table USE AdventureWorks2008R2 GO DECLARE @RowsPerPage INT = 10, @PageNumber INT = 5 ;WITH CTE_SalesOrderDetail AS ( SELECT *, ROW_NUMBER() OVER( ORDER BY SalesOrderDetailID) AS RowNumber FROM Sales.SalesOrderDetail PC) SELECT * FROM CTE_SalesOrderDetail WHERE RowNumber >= @PageNumber*@RowsPerPage+1 AND RowNumber <= (@PageNumber+1)*@RowsPerPage ORDER BY SalesOrderDetailID GO SET STATISTICS IO ON; USE AdventureWorks2008R2 GO DECLARE @RowsPerPage INT = 10, @PageNumber INT = 5 SELECT * FROM Sales.SalesOrderDetail ORDER BY SalesOrderDetailID OFFSET @PageNumber*@RowsPerPage ROWS FETCH NEXT 10 ROWS ONLY GO Test 2 B : Page later in the table -- Test with pages later in table USE AdventureWorks2008R2 GO DECLARE @RowsPerPage INT = 10, @PageNumber INT = 12100 ;WITH CTE_SalesOrderDetail AS ( SELECT *, ROW_NUMBER() OVER( ORDER BY SalesOrderDetailID) AS RowNumber FROM Sales.SalesOrderDetail PC) SELECT * FROM CTE_SalesOrderDetail WHERE RowNumber >= @PageNumber*@RowsPerPage+1 AND RowNumber <= (@PageNumber+1)*@RowsPerPage ORDER BY SalesOrderDetailID GO SET STATISTICS IO ON; USE AdventureWorks2008R2 GO DECLARE @RowsPerPage INT = 10, @PageNumber INT = 12100 SELECT * FROM Sales.SalesOrderDetail ORDER BY SalesOrderDetailID OFFSET @PageNumber*@RowsPerPage ROWS FETCH NEXT 10 ROWS ONLY GO From the resultset, it is very clear that in the earlier case, the pages read in the solution are always much higher than the new technique introduced in SQL Server 2011 even if we don’t retrieve all the data to the screen. If you carefully look at both the comparisons, the PAGE IO is much lesser in the case of the new technique introduced in SQL Server 2011 when we read the page from the beginning of the table and when we read it from the end. I consider this as a big improvement as paging is one of the most used features for the most part of the application. The solution introduced in SQL Server 2011 is very elegant because it also improves the performance of the query and, at large, the database. Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL Server – Learning SQL Server Performance: Indexing Basics – Interview of Vinod Kumar by Pinal Dave

    - by pinaldave
    Recently I just wrote a blog post on about Learning SQL Server Performance: Indexing Basics and I received lots of request that if we can share some insight into the course. Every single time when Performance is discussed, Indexes are mentioned along with it. In recent times, data and application complexity is continuously growing.  The demand for faster query response, performance, and scalability by organizations is increasing and developers and DBAs need to now write efficient code to achieve this. When we developed the course – we made sure that this course remains practical and demo heavy instead of just theories on this subject. Vinod Kumar and myself we often thought about this and realized that practical understanding of the indexes is very important. One can not master every single aspects of the index. However there are some minimum expertise one should gain if performance is one of the concern. Here is 200 seconds interview of Vinod Kumar I took right after completing the course. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Index, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology, Video

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  • Understanding Performance Profiling Targets

    In this sample chapter from his upcoming book, Paul Glavich explains performance metrics and walks us through the steps needed to establish meaningful performance targets. He covers many metrics such as "time to first byte" and explains why you should add some contingency into your estimated performance requirements.

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  • System Wide Performance Sanity Check Procedures

    - by user702295
    Do you need to boost your overall implementation performance? Do you need a direction to pinpoint possible performance opportunities? Are you looking for a general performance guide? Try MOS note 69565.1.  This paper describes a holistic methodology that defines a systematic approach to resolve complex Application performance problems.  It has been successfully used on many critical accounts.  The 'end-to-end' tuning approach encompasses the client, network and database and has proven far more effective than isolated tuning exercises.  It has been used to define and measure targets to ensure success.  Even though it was checked for relevance on 13-Oct-2008, the procedure is still very valuable. Regards!  

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  • Building Performance Metrics into ASP.NET MVC Applications

    When you're instrumenting an ASP.NET MVC or Web API application to monitor its performance while it is running, it makes sense to use custom performance counters.There are plenty of tools available that read performance counter data, report on it and create alerts based on it. You can then plot application metrics against all sorts of server and workstation metrics.This way, there will always be the right data to guide your tuning efforts.

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  • Performance Monitor (perfmon) showing some unusual statistics

    - by Param
    Recently i have thought to used perfmon.msc to monitor process utilization of remote computer. But i am faced with some peculiar situation. Please see the below Print-screen I have selected three computer -- QDIT049, QDIT199V6 & QNIVN014. Please observer the processor Time % which i have marked in Red Circle. How it can be more than 100%.? The Total Processor Time can never go above 100%, am i right? If i am right? than why the processor time % is showing 200% Please let me know, how it is possible or where i have done mistake. Thanks & Regards, Param

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  • Tuning GlassFish for Production

    - by arungupta
    The GlassFish distribution is optimized for developers and need simple deployment and server configuration changes to provide the performance typically required for production usage. The formal Performance Tuning Guide provides an explanation of capacity planning and tuning tips for application, GlassFish, JVM, and the operating system. The GlassFish Server Control (only with the commercial edition) also comes with Performance Tuner that optimizes the runtime for optimal throughput and scalability. And then there are multiple blogs that provide more insights as well: • Optimizing GlassFish for Production (Diego Silva, Mar 2012) • GlassFish Production Tuning (Vegard Skjefstad, Nov 2011) • GlassFish in Production (Sunny Saxena, Jul 2011) • Putting GlassFish v3 in Production: Essential Surviving Guide (JeanFrancois, Nov 2009) • A GlassFish Tuning Primer (Scott Oaks, Dec 2007) What is your favorite source for GlassFish Performance Tuning ?

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  • New Exadata, Exalogic, Exalytics Public References

    - by Javier Puerta
    Deutschetelekom (Germany) Exalytics, OBIEE, Essbase, ACS (with partners T-Systems and Deloitte Consulting) - Published: June 04, 2014 Daelim Industrial (Korea) [Korean] Oracle Exalytics, Oracle Exadata, Oracle Hyperion (with partner Kolon Benit) - Published: May 29, 2014 Algar Telecom (Brazil) [also in Portuguese] Oracle Exadata, Oracle Advanced Customer Support Services - Published: May 23, 2014 Globacom (Nigeria) [also in Spanish] Big Data Appliance, NoSQL DB Community Edition, ACS (with partner mCentric, Ltd.) - Published: May 22, 2014 MagtiCom LTD (Georgia) Oracle Exadata, Oracle Consulting (with partner UGT) - Published: May 21, 2014 Hospital Alemão Oswaldo Cruz (Brazil - local language) Oracle Exadata, Oracle Active Data Guard, Oracle ZFS (with partner Teiko) - Published: May 13, 2014 Accelya Kale (India) Oracle Exadata (with partner Softcell Technologies Limited) - Published: May 12, 2014 Autoridade Tributária e Aduaneira (Portugal) [also Portuguese] Exadata, Exalogic (with partner Timestamp) - Published: May 06, 2014 Reliance Commercial Finance (India) Oracle Exadata, Oracle Exalogic, Oracle WebLogic Suite, Oracle Advanced Customer Support Services - Published: May 01, 2014

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  • Updated copy of the OBIEE Tuning whitepaper

    - by inowodwo
    The Product Assurance team have released an updated copy of the OBIEE Tuning Whitepaper. You can find it on the PA blog https://blogs.oracle.com/pa/entry/test or via Support note OBIEE 11g Infrastructure Performance Tuning Guide (Doc ID 1333049.1) https://support.us.oracle.com/oip/faces/secure/km/DocumentDisplay.jspx?id=1333049.1&recomm=Y This new revised document contains following useful tuning items: 1.    New improved HTTP Server caching algorithm. 2.    Oracle iPlanet Web Server tuning parameters. 3.    New tuning parameters settings / values for OPIS/OBIS components.

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  • Exalytics Webcast - Extreme Analytics Without Limits

    - by Rob Reynolds
    Event Date: October 18, 2012 Event Time: 11 a.m. PT / 2 p.m. ET If your organization is like most, you grapple with an ongoing struggle to obtain timely and relevant information from your enterprise systems. So, while you may have the data needed to answer key questions, the volume, complexity, and dispersal of that data makes getting those answers tough. Attend this Webcast to learn how the combination of Oracle Exalytics In- Memory Machine and Oracle’s market leading analytic applications enables you to go beyond the traditional boundaries of data analysis and get the insight you need from massive volumes of data – all at the speed of thought. See how you can benefit from running your analytic applications on Oracle Exalytics to: Lower TCO Improve Operational Decision Making and Enhance Competitive Advantage Deliver Speed-of-thought Analysis – Anytime, Anywhere Register today. Learn how Oracle Business Analytics can move your business ahead. Register Here

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  • Setting Up and Running Summary Advisor on an Exalytics Machine (Oracle-by-Example)

    - by Saresh
    If you are running Oracle BI on an Exalytics machine, you can use Summary Advisor to identify the aggregates that will increase query performance. Summary Advisor intelligently recommends an optimal list of aggregate tables based on query patterns that will achieve maximum query performance gain while meeting specific resource constraints. Summary Advisor then generates an aggregate creation script that can be run to create the recommended aggregate tables. Aggregate tables reduce query times by storing precomputed results for queries that include rolled-up data. This tutorial covers steps to set up, configure, and run Summary Advisor on an Exalytics machine using TimesTen database as a target for storing aggregates. You can find the Oracle By Example (OBE) in the Oracle Learning Library (OLL). The content in OLL is available to all customers, partners, and employees.

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