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  • How to verify power provided to processors is clean

    - by GregC
    Once in a blue moon, I am seeing a blue screen of death on a shiny new Dell R7610 with a single 1100 Watt Dell-provided power supply on a beefy UPS. BCode is 101 (A clock interrupt was not received...), which some say is caused by under-volting a CPU. Naturally, I would have to contact Dell support, and their natural reaction would be to replace a motherboard, a power supply, or CPU, or a mixture of the above components. In synthetic benchmarks, system memory and CPU, as well as graphics memory and CPU perform admirably, staying up for hours and days. My questions are: Is power supply good enough for the application? Does it provide clean enough power to VRMs on the motherboard? Are VRMs good enough for dual Xeon E5-2665? Does C-states logic work correctly? Is there sufficient current provided to PCIe peripherals, such as disk controllers? P.S. Recently, I've gone through the ordeal with HP. They were nice and professional about it, but root cause was not established, and the HP machine still is less than 100%, giving me a blue screen of death once in a couple of months. Here's what quick web-searching turns up: http://www.sevenforums.com/bsod-help-support/35427-win-7-clock-interrupt-bsod-101-error.html#post356791 It appears Dell has addressed the above issue by clocking PCIe bus down to 5GT/sec in A03 BIOS. My disk controllers support PCIe 3.0, meaning that I would have to re-validate stability. Early testing shows improvements. Further testing shows significant decrease in performance on each of the x16 slots with Dell R7610 with A03 BIOS. But now it's running stable. HP machine has received a microcode update in September 2013 SUM (July BIOS) that makes it stable.

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  • Would an array of SSD drives be able to succesfully substitute the system memory?

    - by Florin Mircea
    I watched a few videos trying to answer this. This video (youtube.com/watch?v=eULFf6F5Ri8) shows a bunch of guys stacking 24 SSD's reaching a peak of around 2GBps r/w. That's under the limit of the worst DDR3 in this list (memorybenchmark.net/write_ddr3_amd.html) - that shows DDR3 memory performance varying from 2.78 to 6.55 Gb per second, but that video is over 3 years old. This video (youtube.com/watch?v=27GmBzQWwP0) shows a more optimistic situation, but for PCI-E SSD drives: 5 drives peaking at around 4Gb. And this other video shows that stacking up more than 3 SSD's doesn't realistically offer a substantial added performance. This and the fact that in all benchmarks the drives act quite poorly when dealing with small files (5k file read/write averaging from 10MB to around 30-40MBps) as opposed to how native memory handles such files, seems to indicate a definite NO to this question. Also, the write life cycle is indeed limited and the drives might wear out quickly, as kindly pointed out by paddy. However, I wanted to get more opinions on this. Would it be possible to at least obtain current memory performance with SSD's in RAID 0? And if so, in what circumstances? I am assuming using this configuration with a Windows OS that has a memory pagefile resident to that stack of SSD's, thus making it very fast to work with.

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  • Is there a utility to visualise / isolate and watch application calls

    - by MyStream
    Note: I'm not sure what to search for so guidance on that may be just as valuable as an answer. I'm looking for a way to visually compare activity of two applications (in this case a webserver with php communicating with the system or mysql or network devices, etc) such that I can compare the performance at a glance. I know there are tools to generate data dumps from benchmarks for apache and some available for php for tracing that you can dump and analyse but what I'm looking for is something that can report performance metrics visually from data on calls (what called what, how long did it take, how much memory did it consume, how can that be represented visually in a call stack) and present it graphically as if it were a topology or layered visual with different elements of system calls occupying different layers. A typical visual may consist of (e.g. using swim diagrams as just one analogy): Network (details here relevant to network diagnostics) | ^ back out v | Linux (details here related to firewall/routing diagnostics) ^ back to network | | V ^ back to system Apache (details here related to web request) | | ^ response to V | apache PHP (etc) PHP---------->other accesses to php files/resources----- | ^ v | MySQL (total time) MySQL | ^ V | Each call listed + time + tables hit/record returned My aim would be to be able to 'inspect' a request/range of requests over a period of time to see what constituted the activity at that point in time and trace it from beginning to end as a diagnostic tool. Is there any such work in this direction? I realise it would be intensive on the server, but the intention is to benchmark and analyse processes against each other for both educational and professional reasons and a visual aid is a great eye-opener compared to raw statistics or dozens of discrete activity vs time graphs. It's hard to show the full cycle. Any pointers welcome. Thanks! FROM COMMENTS: > XHProf in conjunction with other programs such as Perconna toolkit > (percona.com/doc/percona-toolkit/2.0/pt-pmp.html) for mySQL run apache > with httpd -X & (Single threaded debug mode and background) then > attach with strace -> kcache grind

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  • Xen or KVM? Please help me decide and implement the one which is better

    - by JohnAdams
    I have been doing research for implementing virtualization for a server running 3 guests - two linux based and one windows. After trying my hands on Xenserver, I am impressed with the architecture and wanted to use the opensource XEN, which is when I am hearing a lot more about KVM, about how good it is and it's the future etc. So, could anyone here please help me answer some of my queries, between KVM and XEN. Based on my requirement of three VMs on one server, which is better for performance - KVM or XEN, considering one the linux vm's will works a file-server, one as a mailserver and the third one a Windows server? Is KVM stable? What about upgrades.. What about XEN, I cannot find support for it Ubuntu? Are there any published benchmarks on both Xen and KVM? I cannot seem to find any. If I go with Xen, will it possible to move to KVM later or vice versa? In summary, I am looking for real answers on which one I should use.. Xen or KVM?

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  • Servers - Buying New vs Buying Second-hand

    - by Django Reinhardt
    We're currently in the process of adding additional servers to our website. We have a pretty simple topology planned: A Firewall/Router Server infront of a Web Application Server and Database Server. Here's a simple (and technically incorrect) diagram that I used in a previous question to illustrate what I mean: We're now wondering about the specs of our two new machines (the Web App and Firewall servers) and whether we can get away with buying a couple of old servers. (Note: Both machines will be running Windows Server 2008 R2.) We're not too concerned about our Firewall/Router server as we're pretty sure it won't be taxed too heavily, but we are interested in our Web App server. I realise that answering this type of question is really difficult without a ton of specifics on users, bandwidth, concurrent sessions, etc, etc., so I just want to focus on the general wisdom on buying old versus new. I had originally specced a new Dell PowerEdge R300 (1U Rack) for our company. In short, because we're going to be caching as much data as possible, I focussed on Processor Speed and Memory: Quad-Core Intel Xeon X3323 2.5Ghz (2x3M Cache) 1333Mhz FSB 16GB DDR2 667Mhz But when I was looking for a cheap second-hand machine for our Firewall/Router, I came across several machines that made our engineer ask a very reasonable question: If we stuck a boat load of RAM in this thing, wouldn't it do for the Web App Server and save us a ton of money in the process? For example, what about a second-hand machine with the following specs: 2x Dual-Core AMD Opteron 2218 2.6Ghz (2MB Cache) 1000Mhz HT 16GB DDR2 667Mhz Would it really be comparable with the more expensive (new) server above? Our engineer postulated that the reason companies upgrade their servers to newer processors is often because they want to reduce their power costs, and that a 2.6Ghz processor was still a 2.6Ghz processor, no matter when it was made. Benchmarks on various sites don't really support this theory, but I was wondering what server admin thought. Thanks for any advice.

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  • Scaling a node.js application, nginx as a base server, but varnish or redis for caching?

    - by AntelopeSalad
    I'm not close to being well versed in using nginx or varnish but this is my setup at the moment. I have a node.js server running which is serving either json, html templates, or socket.io events. Then I have nginx running in front of node which is serving all static content (css, js, etc.). At this point I would like to cache both static content and dynamic content to memory. It's to my understanding that varnish can cache static content quite well and it wouldn't require touching my application code. I also think it's capable of caching dynamic content too but there cannot be any cookie headers? I do use redis at the moment for holding session data and planned to use it for other things in the future like keeping track of non-crucial but fun stats. I just have no idea how I should handle caching everything on the site. I think it comes down to these options but there might be more: Throw varnish in front of nginx and let varnish cache static pages, no app code changes. Redis would cache dynamic db calls which would require modifying my app code. Ignore using varnish completely and let redis handle caching everything, then use one of the nginx-redis modules. I'm not sure if this would require a lot of app code changes (for the static files). I'm not having any luck finding benchmarks that compare nginx+varnish vs nginx+redis and I'm too inexperienced to bench it myself (high chances of my configs being awful). I'm basically looking for the solution that would be the most efficient in terms of req/sec and scalable in the future (throw new hardware at the problem + maybe adjust some values in a config = new servers up and running semi-painlessly).

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  • Common business drivers that lead to creating and sustaining a project

    Common business drivers that lead to creating and sustaining a project include and are not limited to: cost reduction, increased return on investment (ROI), reduced time to market, increased speed and efficiency, increased security, and increased interoperability. These drivers primarily focus on streamlining and reducing cost to make a company more profitable with less overhead. According to Answers.com cost reduction is defined as reducing costs to improve profitability, and may be implemented when a company is having financial problems or prevent problems. ROI is defined as the amount of value received relative to the amount of money invested according to PayperclickList.com.  With the ever increasing demands on businesses to compete in today’s market, companies are constantly striving to reduce the time it takes for a concept to become a product and be sold within the global marketplace. In business, some people say time is money, so if a project can reduce the time a business process takes it in fact saves the company which is always good for the bottom line. The Social Security Administration states that data security is the protection of data from accidental or intentional but unauthorized modification, destruction. Interoperability is the capability of a system or subsystem to interact with other systems or subsystems. In my personal opinion, these drivers would not really differ for a profit-based organization, compared to a non-profit organization. Both corporate entities strive to reduce cost, and strive to keep operation budgets low. However, the reasoning behind why they want to achieve this does contrast. Typically profit based organizations strive to increase revenue and market share so that the business can grow. Alternatively, not-for-profit businesses are more interested in increasing their reach within communities whether it is to increase annual donations or invest in the lives of others. Success or failure of a project can be determined by one or more of these drivers based on the scope of a project and the company’s priorities associated with each of the drivers. In addition, if a project attempts to incorporate multiple drivers and is only partially successful, then the project might still be considered to be a success due to how close the project was to meeting each of the priorities. Continuous evaluation of the project could lead to a decision to abort a project, because it is expected to fail before completion. Evaluations should be executed after the completion of every software development process stage. Pfleeger notes that software development process stages include: Requirements Analysis and Definition System Design Program Design Program Implementation Unit Testing Integration Testing System Delivery Maintenance Each evaluation at every state should consider all the business drivers included in the scope of a project for how close they are expected to meet expectations. In addition, minimum requirements of acceptance should also be included with the scope of the project and should be reevaluated as the project progresses to ensure that the project makes good economic sense to continue. If the project falls below these benchmarks then the project should be put on hold until it does make more sense or the project should be aborted because it does not meet the business driver requirements.   References Cost Reduction Program. (n.d.). Dictionary of Accounting Terms. Retrieved July 19, 2009, from Answers.com Web site: http://www.answers.com/topic/cost-reduction-program Government Information Exchange. (n.d.). Government Information Exchange Glossary. Retrieved July 19, 2009, from SSA.gov Web site: http://www.ssa.gov/gix/definitions.html PayPerClickList.com. (n.d.). Glossary Term R - Pay Per Click List. Retrieved July 19, 2009, from PayPerClickList.com Web site: http://www.payperclicklist.com/glossary/termr.html Pfleeger, S & Atlee, J.(2009). Software Engineering: Theory and Practice. Boston:Prentice Hall Veluchamy, Thiyagarajan. (n.d.). Glossary « Thiyagarajan Veluchamy’s Blog. Retrieved July 19, 2009, from Thiyagarajan.WordPress.com Web site: http://thiyagarajan.wordpress.com/glossary/

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  • Do your filesystems have un-owned files ?

    - by darrenm
    As part of our work for integrated compliance reporting in Solaris we plan to provide a check for determining if the system has "un-owned files", ie those which are owned by a uid that does not exist in our configured nameservice.  Tests such as this already exist in the Solaris CIS Benchmark (9.24 Find Un-owned Files and Directories) and other security benchmarks. The obvious method of doing this would be using find(1) with the -nouser flag.  However that requires we bring into memory the metadata for every single file and directory in every local file system we have mounted.  That is probaby not an acceptable thing to do on a production system that has a large amount of storage and it is potentially going to take a long time. Just as I went to bed last night an idea for a much faster way of listing file systems that have un-owned files came to me. I've now implemented it and I'm happy to report it works very well and peforms many orders of magnatude better than using find(1) ever will.   ZFS (since pool version 15) has per user space accounting and quotas.  We can report very quickly and without actually reading any files at all how much space any given user id is using on a ZFS filesystem.  Using that information we can implement a check to very quickly list which filesystems contain un-owned files. First a few caveats because the output data won't be exactly the same as what you get with find but it answers the same basic question.  This only works for ZFS and it will only tell you which filesystems have files owned by unknown users not the actual files.  If you really want to know what the files are (ie to give them an owner) you still have to run find(1).  However it has the huge advantage that it doesn't use find(1) so it won't be dragging the metadata for every single file and directory on the system into memory. It also has the advantage that it can check filesystems that are not mounted currently (which find(1) can't do). It ran in about 4 seconds on a system with 300 ZFS datasets from 2 pools totalling about 3.2T of allocated space, and that includes the uid lookups and output. #!/bin/sh for fs in $(zfs list -H -o name -t filesystem -r rpool) ; do unknowns="" for uid in $(zfs userspace -Hipn -o name,used $fs | cut -f1); do if [ -z "$(getent passwd $uid)" ]; then unknowns="$unknowns$uid " fi done if [ ! -z "$unknowns" ]; then mountpoint=$(zfs list -H -o mountpoint $fs) mounted=$(zfs list -H -o mounted $fs) echo "ZFS File system $fs mounted ($mounted) on $mountpoint \c" echo "has files owned by unknown user ids: $unknowns"; fi done Sample output: ZFS File system rpool/ROOT/solaris-30/var mounted (no) on /var has files owned by unknown user ids: 6435 33667 101 ZFS File system rpool/ROOT/solaris-32/var mounted (yes) on /var has files owned by unknown user ids: 6435 33667ZFS File system builds/bob mounted (yes) on /builds/bob has files owned by unknown user ids: 101 Note that the above might not actually appear exactly like that in any future Solaris product or feature, it is provided just as an example of what you can do with ZFS user space accounting to answer questions like the above.

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  • Guest blog: A Closer Look at Oracle Price Analytics by Will Hutchinson

    - by Takin Babaei
    Overview:  Price Analytics helps companies understand how much of each sale goes into discounts, special terms, and allowances. This visibility lets sales management see the panoply of discounts and start seeing whether each discount drives desired behavior. In Price Analytics monitors parts of the quote-to-order process, tracking quotes, including the whole price waterfall and seeing which result in orders. The “price waterfall” shows all discounts between list price and “pocket price”. Pocket price is the final price the vendor puts in its pocket after all discounts are taken. The value proposition: Based on benchmarks from leading consultancies and companies I have talked to, where they have studied the effects of discounting and started enforcing what many of them call “discount discipline”, they find they can increase the pocket price by 0.8-3%. Yes, in today’s zero or negative inflation environment, one can, through better monitoring of discounts, collect what amounts to a price rise of a few percent. We are not talking about selling more product, merely about collecting a higher pocket price without decreasing quantities sold. Higher prices fall straight to the bottom line. The best reference I have ever found for understanding this phenomenon comes from an article from the September-October 1992 issue of Harvard Business Review called “Managing Price, Gaining Profit” by Michael Marn and Robert Rosiello of McKinsey & Co. They describe the outsized impact price management has on bottom line performance compared to selling more product or cutting variable or fixed costs. Price Analytics manages what Marn and Rosiello call “transaction pricing”, namely the prices of a given transaction, as opposed to what is on the price list or pricing according to the value received. They make the point that if the vendor does not manage the price waterfall, customers will, to the vendor’s detriment. It also discusses its findings that in companies it studied, there was no correlation between discount levels and any indication of customer value. I urge you to read this article. What Price Analytics does: Price analytics looks at quotes the company issues and tracks them until either the quote is accepted or rejected or it expires. There are prebuilt adapters for EBS and Siebel as well as a universal adapter. The target audience includes pricing analysts, product managers, sales managers, and VP’s of sales, marketing, finance, and sales operations. It tracks how effective discounts have been, the win rate on quotes, how well pricing policies have been followed, customer and product profitability, and customer performance against commitments. It has the concept of price waterfall, the deal lifecycle, and price segmentation built into the product. These help product and sales managers understand their pricing and its effectiveness on driving revenue and profit. They also help understand how terms are adhered to during negotiations. They also help people understand what segments exist and how well they are adhered to. To help your company increase its profits and revenues, I urge you to look at this product. If you have questions, please contact me. Will HutchinsonMaster Principal Sales Consultant – Analytics, Oracle Corp. Will Hutchinson has worked in the business intelligence and data warehousing for over 25 years. He started building data warehouses in 1986 at Metaphor, advancing to running Metaphor UK’s sales consulting area. He also worked in A.T. Kearney’s business intelligence practice for over four years, running projects and providing training to new consultants in the IT practice. He also worked at Informatica and then Siebel, before coming to Oracle with the Siebel acquisition. He became Master Principal Sales Consultant in 2009. He has worked on developing ROI and TCO models for business intelligence for over ten years. Mr. Hutchinson has a BS degree in Chemical Engineering from Princeton University and an MBA in Finance from the University of Chicago.

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  • HOWTO Turn off SPARC T4 or Intel AES-NI crypto acceleration.

    - by darrenm
    Since we released hardware crypto acceleration for SPARC T4 and Intel AES-NI support we have had a common question come up: 'How do I test without the hardware crypto acceleration?'. Initially this came up just for development use so developers can do unit testing on a machine that has hardware offload but still cover the code paths for a machine that doesn't (our integration and release testing would run on all supported types of hardware anyway).  I've also seen it asked in a customer context too so that we can show that there is a performance gain from the hardware crypto acceleration, (not just the fact that SPARC T4 much faster performing processor than T3) and measure what it is for their application. With SPARC T2/T3 we could easily disable the hardware crypto offload by running 'cryptoadm disable provider=n2cp/0'.  We can't do that with SPARC T4 or with Intel AES-NI because in both of those classes of processor the encryption doesn't require a device driver instead it is unprivileged user land callable instructions. Turns out there is away to do this by using features of the Solaris runtime loader (ld.so.1). First I need to expose a little bit of implementation detail about how the Solaris Cryptographic Framework is implemented in Solaris 11.  One of the new Solaris 11 features of the linker/loader is the ability to have a single ELF object that has multiple different implementations of the same functions that are selected at runtime based on the capabilities of the machine.  The alternate to this is having the application coded to call getisax() and make the choice itself.  We use this functionality of the linker/loader when we build the userland libraries for the Solaris Cryptographic Framework (specifically libmd.so, and the unfortunately misnamed due to historical reasons libsoftcrypto.so) The Solaris linker/loader allows control of a lot of its functionality via environment variables, we can use that to control the version of the cryptographic functions we run.  To do this we simply export the LD_HWCAP environment variable with values that tell ld.so.1 to not select the HWCAP section matching certain features even if isainfo says they are present.  For SPARC T4 that would be: export LD_HWCAP="-aes -des -md5 -sha256 -sha512 -mont -mpul" and for Intel systems with AES-NI support: export LD_HWCAP="-aes" This will work for consumers of the Solaris Cryptographic Framework that use the Solaris PKCS#11 libraries or use libmd.so interfaces directly.  It also works for the Oracle DB and Java JCE.  However does not work for the default enabled OpenSSL "t4" or "aes-ni" engines (unfortunately) because they do explicit calls to getisax() themselves rather than using multiple ELF cap sections. However we can still use OpenSSL to demonstrate this by explicitly selecting "pkcs11" engine  using only a single process and thread.  $ openssl speed -engine pkcs11 -evp aes-128-cbc ... type 16 bytes 64 bytes 256 bytes 1024 bytes 8192 bytes aes-128-cbc 54170.81k 187416.00k 489725.70k 805445.63k 1018880.00k $ LD_HWCAP="-aes" openssl speed -engine pkcs11 -evp aes-128-cbc ... type 16 bytes 64 bytes 256 bytes 1024 bytes 8192 bytes aes-128-cbc 29376.37k 58328.13k 79031.55k 86738.26k 89191.77k We can clearly see the difference this makes in the case where AES offload to the SPARC T4 was disabled. The "t4" engine is faster than the pkcs11 one because there is less overhead (again on a SPARC T4-1 using only a single process/thread - using -multi you will get even bigger numbers). $ openssl speed -evp aes-128-cbc ... type 16 bytes 64 bytes 256 bytes 1024 bytes 8192 bytes aes-128-cbc 85526.61k 89298.84k 91970.30k 92662.78k 92842.67k Yet another cool feature of the Solaris linker/loader, thanks Rod and Ali. Note these above openssl speed output is not intended to show the actual performance of any particular benchmark just that there is a significant improvement from using hardware acceleration on SPARC T4. For cryptographic performance benchmarks see the http://blogs.oracle.com/BestPerf/ postings.

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  • Crime Scene Investigation: SQL Server

    - by Rodney Landrum
    “The packages are running slower in Prod than they are in Dev” My week began with this simple declaration from one of our lead BI developers, quickly followed by an emailed spreadsheet demonstrating that, over 5 executions, an extensive ETL process was running average 630 seconds faster on Dev than on Prod. The situation needed some scientific investigation to determine why the same code, the same data, the same schema would yield consistently slower results on a more powerful server. Prod had yet to be officially christened with a “Go Live” date so I had the time, and having recently been binge watching CSI: New York, I also had the inclination. An inspection of the two systems, Prod and Dev, revealed the first surprise: although Prod was indeed a “bigger” system, with double the amount of RAM of Dev, the latter actually had twice as many processor cores. On neither system did I see much sign of resources being heavily taxed, while the ETL process was running. Without any real supporting evidence, I jumped to a conclusion that my years of performance tuning should have helped me avoid, and that was that the hardware differences explained the better performance on Dev. We spent time setting up a Test system, similarly scoped to Prod except with 4 times the cores, and ported everything across. The results of our careful benchmarks left us truly bemused; the ETL process on the new server was slower than on both other systems. We burned more time tweaking server configurations, monitoring IO and network latency, several times believing we’d uncovered the smoking gun, until the results of subsequent test runs pitched us back into confusion. Finally, I decided, enough was enough. Hadn’t I learned very early in my DBA career that almost all bottlenecks were caused by code and database design, not hardware? It was time to get back to basics. With over 100 SSIS packages and hundreds of queries, each handling specific tasks such as file loads, bulk inserts, transforms, logging, and so on, the task seemed formidable. And yet, after barely an hour spent with Profiler, Extended Events, and wait statistics DMVs, I had a lead in the shape of a query that joined three tables, containing millions of rows, returned 3279 results, but performed 239K logical reads. As soon as I looked at the execution plans for the query in Dev and Test I saw the culprit, an implicit conversion warning on a join predicate field that was numeric in one table and a varchar(50) in another! I turned this information over to the BI developers who quickly resolved the data type mismatches and found and fixed “several” others as well. After the schema changes the same query with the same databases ran in under 1 second on all systems and reduced the logical reads down to fewer than 300. The analysis also revealed that on Dev, the ETL task was pulling data across a LAN, whereas Prod and Test were connected across slower WAN, in large part explaining why the same process ran slower on the latter two systems. Loading the data locally on Prod delivered a further 20% gain in performance. As we progress through our DBA careers we learn valuable lessons. Sometimes, with a project deadline looming and pressure mounting, we choose to forget them. I was close to giving into the temptation to throw more hardware at the problem. I’m pleased at least that I resisted, though I still kick myself for not looking at the code on day one. It can seem a daunting prospect to return to the fundamentals of the code so close to roll out, but with the right tools, and surprisingly little time, you can collect the evidence that reveals the true problem. It is a lesson I trust I will remember for my next 20 years as a DBA, if I’m ever again tempted to bypass the evidence.

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  • DataView.RowFilter Vs DataTable.Select() vs DataTable.Rows.Find()

    - by Aseem Gautam
    Considering the code below: Dataview someView = new DataView(sometable) someView.RowFilter = someFilter; if(someView.count > 0) { …. } Quite a number of articles which say Datatable.Select() is better than using DataViews, but these are prior to VS2008. Solved: The Mystery of DataView's Poor Performance with Large Recordsets Array of DataRecord vs. DataView: A Dramatic Difference in Performance Googling on this topic I found some articles/forum topics which mention Datatable.Select() itself is quite buggy(not sure on this) and underperforms in various scenarios. On this(Best Practices ADO.NET) topic on msdn it is suggested that if there is primary key defined on a datatable the findrows() or find() methods should be used insted of Datatable.Select(). This article here (.NET 1.1) benchmarks all the three approaches plus a couple more. But this is for version 1.1 so not sure if these are valid still now. Accroding to this DataRowCollection.Find() outperforms all approaches and Datatable.Select() outperforms DataView.RowFilter. So I am quite confused on what might be the best approach on finding rows in a datatable. Or there is no single good way to do this, multiple solutions exist depending upon the scenario?

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  • What is the equivalent of memset in C#?

    - by Jedidja
    I need to fill a byte[] with a single non-zero value. How can I do this in C# without looping through each byte in the array? Update: The comments seem to have split this into two questions - Is there a Framework method to fill a byte[] that might be akin to memset What is the most efficient way to do it when we are dealing with a very large array? I totally agree that using a simple loop works just fine, as Eric and others have pointed out. The point of the question was to see if I could learn something new about C# :) I think Juliet's method for a Parallel operation should be even faster than a simple loop. Benchmarks: Thanks to Mikael Svenson: http://techmikael.blogspot.com/2009/12/filling-array-with-default-value.html It turns out the simple for loop is the way to go unless you want to use unsafe code. Apologies for not being clearer in my original post. Eric and Mark are both correct in their comments; need to have more focused questions for sure. Thanks for everyone's suggestions and responses.

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  • Is parsing JSON faster than parsing XML

    - by geme_hendrix
    I'm creating a sophisticated JavaScript library for working with my company's server side framework. The server side framework encodes its data to a simple XML format. There's no fancy namespacing or anything like that. Ideally I'd like to parse all of the data in the browser as JSON. However, if I do this I need to rewrite some of the server side code to also spit out JSON. This is a pain because we have public APIs that I can't easily change. What I'm really concerned about here is performance in the browser of parsing JSON versus XML. Is there really a big difference to be concerned about? Or should I exclusively go for JSON? Does anyone have any experience or benchmarks in the performance difference between the two? I realize that most modern web developers would probably opt for JSON and I can see why. However, I really am just interested in performance. If there's a proven massive difference then I'm prepared to spend the extra effort in generating JSON server side for the client.

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  • Java and tomcat vs ASP.NET and IIS

    - by Mark Cooper
    Until recently I'd considered myself to be a pretty good web programmer (coming up for 10yrs commercial experience on a variety of e-commerce, static and enterprise applications). I'm self taught and have always used the Microsoft product stack (ASP, ASP.NET)... My applications are always functional, relatively bug free, but have never been lightening quick. As a frequent web user I always found this to be the norm... how fast are the websites from the big tech players (eBay, Facebook, Microsoft, IBM, Dell, Telerik etc etc) - in truth none are particularly fast. I always attributed this to "the way things are with web apps"... ...then I cam across a product called Jira from atlasian and this has stopped me in my tracks... This application is fast, and I mean blindingly fast.. too fast to time the switches between pages, fully live content, lots of images and data and cross references etc etc... I run this on an intranet, with a large application DB, and this is running on a very normal server (single processor, SATA HDD, 8GB RAM). Am I missing something?? Are my programming techniques that bad?? I am wondering if this speed gain is down to it being written in Java and running on Tomcat. Does anyone have any benchmarks to compare JSP / ASP or Tomcat / IIS??? Thanks, Mark NOTE: this isn't a blatant plug for Jira. I don't work for them or have any affiliation to them... but I would like to be able to write applications like them :)

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  • html5 vs flash - full comparison chart anywhere?

    - by iddqd
    So since Steve Jobs said Flash sucks and implied that HTML5 can do everything Flash can without the need for a Plugin, I keep hearing those exact words from a lot of People. I would really like to have a Chart somewhere (similar to http://en.wikipedia.org/wiki/Comparison_of_layout_engines_%28HTML5%29#Form_elements_and_attributes ) that I can just show to those people. Showing all the little things that Flash can do right now, that HTML5/Ajax/CSS is not yet even thinking about. But of course also the things that HTML5 does better. I would like to see details compared like audio playback, realtime audio processing, byte level access, bitmap data manipulation, webcam access, binary sockets, stuff in the works such as P2P technology (adobe stratus) and all the stuff I don't know about myself. Ideally with examples of what can be accomplished with, lets say Binary Sockets (such as a POP3 client) because otherwise it won't mean a lot to non-programmers since they will just say "well we can do without Binary Sockets". And ideally with some current benchmarks and some examples of websites that use this technology. I've searched the web and am surprised not to find anything. So is there such a comparison somewhere? Or does anybody want to create this and post it to Wikipedia? ;-)

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  • How can I test this SQL Server performance Utility?

    - by Martin Smith
    As part of my MSc I need to do a three month project later this year. I have decided to do something which will likely be useful for me in the workplace and spend the time getting to understand SQL Server internals. The deliverable for this project will be a performance advisor looking at a variety of different rules. Some static such as finding redundant indexes, some more dynamic such as using XEvents to find outlying invocations of stored procedure execution times when certain parameters are passed. I am struggling to come up with a good way of testing this though. I can obviously design a "bad" database and a synthetic workload that my tool will pick up issues on but I also need to demonstrate that it has real world utility. Looking at the self tuning database literature it is common to use TPC benchmarks but I've had a look at the TPCC site and it looks very time consuming to implement and not that good a fit to my project's testing needs in any event (I would still be able to "rig" it by the decisions I made on indexing or physical architecture). Plan A would be to find willing beta tester(s) but in the event that isn't possible I will need a fallback plan. The best idea I have come up with so far is to use the various MS sample applications as examples of real world applications. e.g. http://msftdpprodsamples.codeplex.com/ http://www.asp.net/community/projects/ Does anyone have any better suggestions?

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  • PostgreSQL: BYTEA vs OID+Large Object?

    - by mlaverd
    I started an application with Hibernate 3.2 and PostgreSQL 8.4. I have some byte[] fields that were mapped as @Basic (= PG bytea) and others that got mapped as @Lob (=PG Large Object). Why the inconsistency? Because I was a Hibernate noob. Now, those fields are max 4 Kb (but average is 2-3 kb). The PostgreSQL documentation mentioned that the LOs are good when the fields are big, but I didn't see what 'big' meant. I have upgraded to PostgreSQL 9.0 with Hibernate 3.6 and I was stuck to change the annotation to @Type(type="org.hibernate.type.PrimitiveByteArrayBlobType"). This bug has brought forward a potential compatibility issue, and I eventually found out that Large Objects are a pain to deal with, compared to a normal field. So I am thinking of changing all of it to bytea. But I am concerned that bytea fields are encoded in Hex, so there is some overhead in encoding and decoding, and this would hurt the performance. Are there good benchmarks about the performance of both of these? Anybody has made the switch and saw a difference?

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  • EPIPE blocks server

    - by timn
    I have written a single-threaded asynchronous server in C running on Linux: The socket is non-blocking and as for polling, I am using epoll. Benchmarks show that the server performs fine and according to Valgrind, there are no memory leaks or other problems. The only problem is that when a write() command is interrupted (because the client closed the connection), the server will encounter a SIGPIPE. I am doing the interrupted artifically by running the benchmarking utility "siege" with the parameter -b. It does lots of requests in a row which all work perfectly. Now I press CTRL-C and restart the "siege". Sometimes I am lucky and the server does not manage to send the full response because the client's fd is invalid. As expected errno is set to EPIPE. I handle this situation, execute close() on the fd and then free the memory related to the connection. Now the problem is that the server blocks and does not answer properly anymore. Here is the strace output: accept(3, {sa_family=AF_INET, sin_port=htons(50611), sin_addr=inet_addr("127.0.0.1")}, [16]) = 5 fcntl64(5, F_GETFD) = 0 fcntl64(5, F_SETFL, O_RDONLY|O_NONBLOCK) = 0 epoll_ctl(4, EPOLL_CTL_ADD, 5, {EPOLLIN|EPOLLERR|EPOLLHUP|EPOLLET, {u32=158310248, u64=158310248}}) = 0 epoll_wait(4, {{EPOLLIN, {u32=158310248, u64=158310248}}}, 128, -1) = 1 read(5, "GET /user/register HTTP/1.1\r\nHos"..., 4096) = 161 write(5, "HTTP/1.1 200 OK\r\nContent-Type: t"..., 106) = 106 <<<<< write(5, "00001000\r\n", 10) = -1 EPIPE (Broken pipe) <<<<< Why did the previous write() work fine but not this one? --- SIGPIPE (Broken pipe) @ 0 (0) --- As you can see, the client establishes a new connection which consequently is accepted. Then, it's added to the EPOLL queue. epoll_wait() signalises that the client sent data (EPOLLIN). The request is parsed and and a response is composed. Sending the headers works fine but when it comes to the body, write() results in an EPIPE. It is not a bug in "siege" because it blocks any incoming connections, no matter from which client.

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  • What is faster- Java or C# (Or good old C)?

    - by Rexsung
    I'm currently deciding on a platform to build a scientific computational product on, and am deciding on either C#, Java, or plain C with Intels compiler on Core2 Quad CPU's. It's mostly integer arithmetic. My benchmarks so far show Java and C are about on par with each other, and dotNET/C# trails by about 5%- however a number of my coworkers are claiming that dotNET with the right optimizations will beat both of these given enough time for the JIT to do its work. I always assume that the JIT would have done it's job within a few minutes of the app starting (Probably a few seconds in my case, as it's mostly tight loops), so I'm not sure whether to believe them Can anyone shed any light on the situation? Would dotNET beat Java? (Or am I best just sticking with C at this point?). The code is highly multithreaded and data sets are several terabytes in size. Haskell/erlang etc are not options in this case as there is a significant quantity of existing legacy C code that will be ported to the new system, and porting C to Java/C# is a lot simpler than to Haskell or Erlang. (Unless of course these provide a significant speedup). Edit: We are considering moving to C# or Java because they may, in theory, be faster. Every percent we can shave off our processing time saves us tens of thousands of dollars per year. At this point we are just trying to evaluate whether C, Java, or c# would be faster.

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  • Fastest PNG decoder for .NET

    - by sboisse
    Our web server needs to process many compositions of large images together before sending the results to web clients. This process is performance critical because the server can receive several thousands of requests per hour. Right now our solution loads PNG files (around 1MB each) from the HD and sends them to the video card so the composition is done on the GPU. We first tried loading our images using the PNG decoder exposed by the XNA API. We saw the performance was not too good. To understand if the problem was loading from the HD or the decoding of the PNG, we modified that by loading the file in a memory stream, and then sending that memory stream to the .NET PNG decoder. The difference of performance using XNA or using System.Windows.Media.Imaging.PngBitmapDecoder class is not significant. We roughly get the same levels of performance. Our benchmarks show the following performance results: Load images from disk: 37.76ms 1% Decode PNGs: 2816.97ms 77% Load images on Video Hardware: 196.67ms 5% Composition: 87.80ms 2% Get composition result from Video Hardware: 166.21ms 5% Encode to PNG: 318.13ms 9% Store to disk: 3.96ms 0% Clean up: 53.00ms 1% Total: 3680.50ms 100% From these results we see that the slowest parts are when decoding the PNG. So we are wondering if there wouldn't be a PNG decoder we could use that would allow us to reduce the PNG decoding time. We also considered keeping the images uncompressed on the hard disk, but then each image would be 10MB in size instead of 1MB and since there are several tens of thousands of these images stored on the hard disk, it is not possible to store them all without compression.

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  • Memory Bandwidth Performance for Modern Machines

    - by porgarmingduod
    I'm designing a real-time system that occasionally has to duplicate a large amount of memory. The memory consists of non-tiny regions, so I expect the copying performance will be fairly close to the maximum bandwidth the relevant components (CPU, RAM, MB) can do. This led me to wonder what kind of raw memory bandwidth modern commodity machine can muster? My aging Core2Duo gives me 1.5 GB/s if I use 1 thread to memcpy() (and understandably less if I memcpy() with both cores simultaneously.) While 1.5 GB is a fair amount of data, the real-time application I'm working on will have have something like 1/50th of a second, which means 30 MB. Basically, almost nothing. And perhaps worst of all, as I add multiple cores, I can process a lot more data without any increased performance for the needed duplication step. But a low-end Core2Due isn't exactly hot stuff these days. Are there any sites with information, such as actual benchmarks, on raw memory bandwidth on current and near-future hardware? Furthermore, for duplicating large amounts of data in memory, are there any shortcuts, or is memcpy() as good as it will get? Given a bunch of cores with nothing to do but duplicate as much memory as possible in a short amount of time, what's the best I can do?

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  • Why not use tables for layout in HTML?

    - by Bno
    It seems to be the general opinion that tables should not be used for layout in HTML. Why? I have never (or rarely to be honest) seen good arguments for this. The usual answers are: It's good to separate content from layoutBut this is a fallacious argument; Cliche Thinking. I guess it's true that using the table element for layout has little to do with tabular data. So what? Does my boss care? Do my users care?Perhaps me or my fellow developers who have to maintain a web page care... Is a table less maintainable? I think using a table is easier than using divs and CSS.By the way... why is using a div or a span good separation of content from layout and a table not? Getting a good layout with only divs often requires a lot of nested divs. Readability of the codeI think it's the other way around. Most people understand html, few understand CSS. It's better for SEO not to use tablesWhy? Can anybody show some evidence that it is? Or a statement from Google that tables are discouraged from an SEO perspective? Tables are slower.An extra tbody element has to be inserted. This is peanuts for modern web browsers. Show me some benchmarks where the use of a table significantly slows down a page. A layout overhaul is easier without tables, see css Zen Garden.Most web sites that need an upgrade need new content (html) as well. Scenarios where a new version of a web site only needs a new CSS file are not very likely. Zen Garden is a nice web site, but a bit theoretical. Not to mention its misuse of CSS. I am really interested in good arguments to use divs + CSS instead of tables.

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  • What can cause my code to run slower when the server JIT is activated?

    - by durandai
    I am doing some optimizations on an MPEG decoder. To ensure my optimizations aren't breaking anything I have a test suite that benchmarks the entire codebase (both optimized and original) as well as verifying that they both produce identical results (basically just feeding a couple of different streams through the decoder and crc32 the outputs). When using the "-server" option with the Sun 1.6.0_18, the test suite runs about 12% slower on the optimized version after warmup (in comparison to the default "-client" setting), while the original codebase gains a good boost running about twice as fast as in client mode. While at first this seemed to be simply a warmup issue to me, I added a loop to repeat the entire test suite multiple times. Then execution times become constant for each pass starting at the 3rd iteration of the test, still the optimized version stays 12% slower than in the client mode. I am also pretty sure its not a garbage collection issue, since the code involves absolutely no object allocations after startup. The code consists mainly of some bit manipulation operations (stream decoding) and lots of basic floating math (generating PCM audio). The only JDK classes involved are ByteArrayInputStream (feeds the stream to the test and excluding disk IO from the tests) and CRC32 (to verify the result). I also observed the same behaviour with Sun JDK 1.7.0_b98 (only that ist 15% instead of 12% there). Oh, and the tests were all done on the same machine (single core) with no other applications running (WinXP). While there is some inevitable variation on the measured execution times (using System.nanoTime btw), the variation between different test runs with the same settings never exceeded 2%, usually less than 1% (after warmup), so I conclude the effect is real and not purely induced by the measuring mechanism/machine. Are there any known coding patterns that perform worse on the server JIT? Failing that, what options are available to "peek" under the hood and observe what the JIT is doing there?

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  • fastest way to crawl recursive ntfs directories in C++

    - by Peter Parker
    I have written a small crawler to scan and resort directory structures. It based on dirent(which is a small wrapper around FindNextFileA) In my first benchmarks it is surprisingy slow: around 123473ms for 4500 files(thinkpad t60p local samsung 320 GB 2.5" HD). 121481 files found in 123473 milliseconds Is this speed normal? This is my code: int testPrintDir(std::string strDir, std::string strPattern="*", bool recurse=true){ struct dirent *ent; DIR *dir; dir = opendir (strDir.c_str()); int retVal = 0; if (dir != NULL) { while ((ent = readdir (dir)) != NULL) { if (strcmp(ent->d_name, ".") !=0 && strcmp(ent->d_name, "..") !=0){ std::string strFullName = strDir +"\\"+std::string(ent->d_name); std::string strType = "N/A"; bool isDir = (ent->data.dwFileAttributes & FILE_ATTRIBUTE_DIRECTORY) !=0; strType = (isDir)?"DIR":"FILE"; if ((!isDir)){ //printf ("%s <%s>\n", strFullName.c_str(),strType.c_str());//ent->d_name); retVal++; } if (isDir && recurse){ retVal += testPrintDir(strFullName, strPattern, recurse); } } } closedir (dir); return retVal; } else { /* could not open directory */ perror ("DIR NOT FOUND!"); return -1; } }

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