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• Should I host my entire web application using https?

  - by user54455

  Actually my only requirement for using SSL encryption is that when a user logs in, the password is transferred encrypted. However after reading a bit about protocol switching, that an HTTPS session can't be taken over as an HTTP session etc. I've been asking myself if it's so bad to just have the entire application use HTTPS only. What are the reasons against it and how would you rate their importance? Please also mention: How much performance do I lose on server side (roughly)? How much performance do I lose on client side (roughly)? Any other problems on server / client side?

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• Which type of Form factor (motherboard) i should buy and why?

  - by metal gear solid

  If budged is not a problem. I just need best performance with less power consumption. I can purchase any cabinet , power supply and Motherboard. Is Power supply has any relation with Form factor, should i purchase PSU according to Form factor of motherboard? Is the size of motherboard and number of Slots only difference between all form factors? Is there any differences among form factors, related to performance of motherboard? Is bigger in Size (ATX) motherboard always better? Is it so smaller in Size motherboard will consume less power? What are pros and cons of each Form factor? What there are so many Form factor were created?

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• Please Help Me Optimize This

  - by Zero

  I'm trying to optimize my .htaccess file to avoid performance issues. In my .htaccess file I have something that looks like this: RewriteEngine on RewriteCond %{HTTP_USER_AGENT} bigbadbot [NC,OR] RewriteCond %{HTTP_USER_AGENT} otherbot1 [NC,OR] RewriteCond %{HTTP_USER_AGENT} otherbot2 [NC] RewriteRule ^.* - [F,L] The first rewrite rule (bigbadbot) handles about 100 requests per second, whereas the other two rewrite rules below it only handle a few requests per hour. My question is, since the first rewrite rule (bigbadbot) handles about 99% of the traffic would it be better to place these rules into two separate rulesets? For example: RewriteEngine on RewriteCond %{HTTP_USER_AGENT} bigbadbot [NC] RewriteRule ^.* - [F,L] RewriteCond %{HTTP_USER_AGENT} otherbot1 [NC,OR] RewriteCond %{HTTP_USER_AGENT} otherbot2 [NC] RewriteRule ^.* - [F,L] Can someone tell me what would be better in terms of performance? Has anyone ever benchmarked this? Thanks!

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• What is a proper server for this website

  - by zaidfarekh

  We are using zend framework, doctrine on our website, that will have the minimum of 2000 users daily, please consider that we prefer that the server has opcode caching. And any available technology that speeds up php performance. We have heard that zend server offers an optimal performance for php. Please recommend a hosting server or a vps plan, that can handle such an application. given that our application has some kind of social networking and it applies alot of ajax requests even in minimal usage of the website, for example in 30 min we may have up to 400 requests from an individual user. Thank you in advance

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• Can a SQL Server have a CPU bottleneck when Processor Time is under 30%

  - by Sleepless

  Is it in principle possible for the CPU to be the bottleneck on a SQL Server if the Performance Counter Processor:Processor Time is constantly under 30% on all cores? Or does low Processor Time automatically allow me to rule out the CPU as a potential trouble source? I am asking this because SQL Nexus lists CPU as the top bottleneck on a server with low Processor Time values.

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• perfmon.exe itself taking 52.71% of cpu on windows 7 after chrome dies?

  - by jamesmoorecode

  On my Windows 7 machine (build 7100, x64, Dell XPS M1710 laptop), I'm getting horrible performance after chrome crashes. I kill the chrome process from the Resource Monitor, but after that perfmon.exe itself is shown as taking about 50% of the cpu (52.31% right now). Quitting Performance Monitor, then starting it again, shows perfmon starting out with a reasonable CPU, but it quickly (ten seconds) shoots right back up. Suggestions? So far a reboot seems to be the only way to solve the problem. I'm assuming that the perfmon issue is just a symptom of the real problem. (Update, much later: this never got resolved. I'm not seeing the problem in the RTM Win7 + latest Chrome. Yes, it was a core 2 duo, so presumably Chrome was running full blast on one cpu.)

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• C - struct problems - writing

  - by Catarrunas

  Hello, I'm making a program in C, and I'mm having some troubles with memory, I think. So my problem is: I have 2 functions that return a struct. When I run only one function at a time I have no problem whatsoever. But when I run one after the other I always get an error when writting to the second struct. Function struct item* ReadFileBIN(char *name) -- reads a binary file. struct tables* getMesasInfo(char* Filename) -- reads a text file. My code is this: #include "stdafx.h" #include <stdio.h> #include <stdlib.h> #include <string.h> #include <time.h> int numberOfTables=0; int numberOfItems=0; //struct tables* mesas; //struct item* Menu; typedef struct item{ char nome[100]; int id; float preco; }; typedef struct tables{ int id; int capacity; bool inUse; }; struct tables* getMesasInfo(char* Filename){ struct tables* mesas; char *c; int counter,numberOflines=0,temp=0; char *filename=Filename; FILE * G; G = fopen(filename,"r"); if (G==NULL){ printf("Cannot open file.\n"); } else{ while (!feof(G)){ fscanf(G, "%s", &c); numberOflines++; } fclose(G); } /* Memory allocate for input array */ mesas = (struct tables *)malloc(numberOflines* sizeof(struct tables*)); counter=0; G=fopen(filename,"r"); while (!feof(G)){ mesas[counter].id=counter; fscanf(G, "%d", &mesas[counter].capacity); mesas[counter].inUse= false; counter++; } fclose(G); numberOfTables = counter; return mesas; } struct item* ReadFileBIN(char *name) { int total=0; int counter; FILE *ptr_myfile; struct item my_record; struct item* Menu; ptr_myfile=fopen(name,"r"); if (!ptr_myfile) { printf("Unable to open file!"); } while (!feof(ptr_myfile)){ fread(&my_record,sizeof(struct item),1,ptr_myfile); total=total+1; } numberOfItems=total-1; Menu = (struct item *)calloc(numberOfItems , sizeof(struct item)); fseek(ptr_myfile, sizeof(struct item), SEEK_END); rewind(ptr_myfile); for ( counter=1; counter < total ; counter++) { fread(&my_record,sizeof(struct item),1,ptr_myfile); Menu[counter] = my_record; printf("Nome: %s\n",Menu[counter].nome); printf("ID: %d\n",Menu[counter].id); printf("Preco: %f\n",Menu[counter].preco); } fclose(ptr_myfile); return Menu; } int _tmain(int argc, _TCHAR* argv[]) { struct item* tt = ReadFileBIN("menu.dat"); struct tables* t = getMesasInfo("Capacity.txt"); getchar(); }** Thanks in advance.

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• How to optimize this javascript code?

  - by Andrija

  I have a jsp which uses a lot of javascript and it's just not fast enough. I would like to optimize it so first, here's a part of the code: In the jsp I have the initialization: window.onload = function () { formCollection.pageSize.value = "<%= pagingSize%>"; elemCollection = iDom3.Table.all["spis"].XML.DOM; <% if (resultList != null) { %> elementsNumber = <%= resultList.size() %>; <%} else { %> elementsNumber = 0; <% } %> contextPath = "<%= request.getContextPath() %>"; } In my js file I have two types of js functions: // gets the first element and sets it's value to all the other; //the selectSingleNode function is used because I use XSLT transformation //to generate the table _setTehJed = function(){ var resultId = formCollection.elements["idTehJedinice_spis_1"].value; var resultText = formCollection.elements["tehnicka_spis_1"].value; if (resultId != ""){ var counter = 1; while (counter<elementsNumber){ counter++; if(formCollection.elements["idTehJedinice_spis_"+counter] != null){ formCollection.elements["idTehJedinice_spis_"+counter].value=resultId; formCollection.elements["tehnicka_spis_"+counter].value=resultText; } var node=elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+counter+"']/data[@col = 'tehnicka']/title"); node.text=resultText; var node2=elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+counter+"']/data[@col = 'idTehJedinice']/title"); node2.text=resultId; } } } // sets the elements checkbox to checked or unchecked _SelectCheckRokCuvanja = { all : [], Item : function (oItem, sId) { this.all["spis_"+sId] = oItem.value; if (oItem.checked) { elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+sId+"']/data[@col = 'rokCheck']").setAttribute("default", "true"); }else{ elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+sId+"']/data[@col = 'rokCheck']").setAttribute("default", "false"); } } } I've used these tips: http://blogs.msdn.com/b/ie/archive/2006/08/28/728654.aspx http://code.google.com/speed/articles/optimizing-javascript.html but I still think something could be done like defining the functions like this: In the jsp: window.onload = function () { iDom3.DigitalnaArhivaPrihvat.formCollection=document.forms["controller"]; iDom3.DigitalnaArhivaPrihvat.formCollection.pageSize.value = "<%= pagingSize%>"; iDom3.DigitalnaArhivaPrihvat.elemCollection = iDom3.Table.all["spis"].XML.DOM; <% if (resultList != null) { %> iDom3.DigitalnaArhivaPrihvat.elementsNumber = <%= resultList.size() %> <%} else { %> iDom3.DigitalnaArhivaPrihvat.elementsNumber = 0; <% } %> } in the js: iDom3.DigitalnaArhivaPrihvat = { formCollection:null, elemCollection:null, elementsNumber:null, _setTehJed : function(){ var resultId = this.formCollection.elements.idTehJedinice_spis_1.value; var resultText = this.formCollection.elements.tehnicka_spis_1.value; if (resultId != ""){ var counter = 1; while (counter<this.elementsNumber){ counter++; if(this.formCollection.elements["idTehJedinice_spis_"+counter] !== null){ this.formCollection.elements["idTehJedinice_spis_"+counter].value=resultId; this.formCollection.elements["tehnicka_spis_"+counter].value=resultText; } var node=this.elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+counter+"']/data[@col = 'tehnicka']/title"); node.text=resultText; var node2=this.elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+counter+"']/data[@col = 'idTehJedinice']/title"); node2.text=resultId; } } }, _SelectCheckRokCuvanja = { all : [], Item : function (oItem, sId) { this.all["spis_"+sId] = oItem.value; if (oItem.checked) { this.elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+sId+"']/data[@col = 'rokCheck']").setAttribute("default", "true"); }else{ this.elemCollection.selectSingleNode("/suite/table/rows/row[@id = 'spis_"+sId+"']/data[@col = 'rokCheck']").setAttribute("default", "false"); } } } but the problem is scoping (if I do it like this, the second function does not execute properly). Any suggestions?

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• GTK+ (GTKSharp) poor performance in Windows

  - by nubela

  Hi, In my Mono (C#) project that is meant to be cross-platform, I am using the GTK for the UI. However one thing I noticed is, on my netbook in Archlinux, the performance is really speedy, so events such as mouse hover, and redrawing of widgets, etc, are really fast. Compared to windows (7) on dual core CPUs, the performance is really really weak. Which perplexes me. Am I doing something wrong that is warranting this difference in performance between OSes? What are some ways I can do to optimize GTK on Windows? Its really bad to take around 0.5 secs for a hover event to kick in whereas its almost immediate on a weak(er) netbook with Linux. My code is here for the GUI layer: http://code.google.com/p/subsynct/source/browse/branches/dev/subsync#subsync/GUI Thanks!

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• MDX performance vs. T-SQL

  - by SubPortal

  I have a database containing tables with more than 600 million records and a set of stored procedures that make complex search operations on the database. The performance of the stored procedures is so slow even with suitable indexes on the tables. The design of the database is a normal relational db design. I want to change the database design to be multidimensional and use the MDX queries instead of the traditional T-SQL queries but the question is: Is the MDX query better than the traditional T-SQL query with regard to performance? and if yes, to what extent will that improve the performance of the queries? Thanks for any help.

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• Why better isolation level means better performance in SQL Server

  - by Oleg Zhylin

  When measuring performance on my query I came up with a dependency between isolation level and elapsed time that was surprising to me READUNCOMMITTED - 409024 READCOMMITTED - 368021 REPEATABLEREAD - 358019 SERIALIZABLE - 348019 Left column is table hint, and the right column is elapsed time in microseconds (sys.dm_exec_query_stats.total_elapsed_time). Why better isolation level gives better performance? This is a development machine and no concurrency whatsoever happens. I would expect READUNCOMMITTED to be the fasted due to less locking overhead. Update: I did measure this with DBCC DROPCLEANBUFFERS DBCC FREEPROCCACHE issued and Profiler confirms there're no cache hits happening. Update2: The query in question is an OLAP one and we need to run it as fast as possible. Closing the production server from outside world to get the computation done is not out of question if this gives performance benefits.

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• IN statement performance in PostgreSQL (and in general)

  - by Vasil

  I know this has probably been asked before, but I can't find it with SO's search. Lets say i've TABLE1 and TABLE2, who should I expect the performance of a query such as this: SELECT * FROM TABLE1 WHERE id IN SUBQUERY_ON_TABLE2; as the number of rows in TABLE1 and TABLE2 grow and id is a primary key on TABLE1. Yes, I know using IN is such a n00b mistake, but TABLE2 has a generic relation (django generic relation) to multiple other tables so I can't think of another way to filter the data. At what (aproximate) ammount of rows in TABLE1 and TABLE2 should I expect to notice performance issues because of this? Will performance degrade linearly, exponentially etc. depending on the number of rows?

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• Performance hit from C++ style casts?

  - by Trevor Boyd Smith

  I am new to C++ style casts and I am worried that using C++ style casts will ruin the performance of my application because I have a real-time-critical deadline in my interrupt-service-routine. I heard that some casts will even throw exceptions! I would like to use the C++ style casts because it would make my code more "robust". However, if there is any performance hit then I will probably not use C++ style casts and will instead spend more time testing the code that uses C-style casts. Has anyone done any rigorous testing/profiling to compare the performance of C++ style casts to C style casts? What were your results? What conclusions did you draw?

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• Android Loading Screen: How do I go about using a stack to load elements, and the option of incrementing the size counter?

  - by tom_mai78101

  I have some problems with figuring out what value I should put in the function: int value_needed_to_figure_out = X; ProgressBar.incrementProgressBy(value_needed_to_figure_out); I've been researching about loading screens and how to use them. Some examples I've seen have implemented Thread.sleep() in a Handler.post(new Runnable()) function. To me, I got most of that concept of using the Handler to update the ProgressBar, while pretending to do some heavy crunching work. So, I kept looking. I have read this thread here: How do I load chunks of data from an assest manager during a loading screen? It said that I can try using a stack it needs to load, and adding a size counter as I add elements to the stack. What does it mean? This is the part where I'm totally stumped. If anyone would provide some hints, I'll gladly appreciate it. Thanks in advance.

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• C - is it possible to decrement the max value of a for loop from within the for loop?

  - by hatorade

  for example: void decrement(int counter) { counter--; } int counter = 20; for (int i = 0; i < counter; i++) { for (int j = 0; j < counter, j++) { decrement(counter); } } ideally, what i'd like to see is the counter var being decremented every time the for loop is run, so that it runs fewer than 20 iterations. but gdb shows that within decrement() counter is decremented, but that going back to the for loop counter actually stays the same.

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• Stored procedure performance randomly plummets; trivial ALTER fixes it. Why?

  - by gWiz

  I have a couple of stored procedures on SQL Server 2005 that I've noticed will suddenly take a significantly long time to complete when invoked from my ASP.NET MVC app running in an IIS6 web farm of four servers. Normal, expected completion time is less than a second; unexpected anomalous completion time is 25-45 seconds. The problem doesn't seem to ever correct itself. However, if I ALTER the stored procedure (even if I don't change anything in the procedure, except to perhaps add a space to the script created by SSMS Modify command), the completion time reverts to expected completion time. IIS and SQL Server are running on separate boxes, both running Windows Server 2003 R2 Enterprise Edition. SQL Server is Standard Edition. All machines have dual Xeon E5450 3GHz CPUs and 4GB RAM. SQL Server is accessed using its TCP/IP protocol over gigabit ethernet (not sure what physical medium). The problem is present from all web servers in the web farm. When I invoke the procedure from a query window in SSMS on my development machine, the procedure completes in normal time. This is strange because I was under the impression that SSMS used the same SqlClient driver as in .NET. When I point my development instance of the web app to the production database, I again get the anomalous long completion time. If my SqlCommand Timeout is too short, I get System.Data.SqlClient.SqlException: Timeout expired. The timeout period elapsed prior to completion of the operation or the server is not responding. Question: Why would performing ALTER on the stored procedure, without actually changing anything in it, restore the completion time to less than a second, as expected? Edit: To clarify, when the procedure is running slow for the app, it simultaneously runs fine in SSMS with the same parameters. The only difference I can discern is login credentials (next time I notice the behavior, I'll be checking from SSMS with the same creds). The ultimate goal is to get the procs to sustainably run with expected speed without requiring occasional intervention. Resolution: I wanted to to update this question in case others are experiencing this issue. Following the leads of the answers below, I was able to consistently reproduce this behavior. In order to test, I utilize sp_recompile and pass it one of the susceptible sprocs. I then initiate a website request from my browser that will invoke the sproc with atypical parameters. Lastly, I initiate a website request to a page that invokes the sproc with typical parameters, and observe that the request does not complete because of a SQL timeout on the sproc invocation. To resolve this on SQL Server 2005, I've added OPTIMIZE FOR hints to my SELECT. The sprocs that were vulnerable all have the "all-in-one" pattern described in this article. This pattern is certainly not ideal but was a necessary trade-off given the timeframe for the project.

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• CPU/JVM/JBoss 7 slows down over time

  - by lukas

  I'm experiencing performance slow down on JBoss 7.1.1 Final. I wrote simple program that demostrates this behavior. I generate an array of 100,000 of random integers and run bubble sort on it. @Model public class PerformanceTest { public void proceed() { long now = System.currentTimeMillis(); int[] arr = new int[100000]; for(int i = 0; i < arr.length; i++) { arr[i] = (int) (Math.random() * 200000); } long now2 = System.currentTimeMillis(); System.out.println((now2 - now) + "ms took to generate array"); now = System.currentTimeMillis(); bubbleSort(arr); now2 = System.currentTimeMillis(); System.out.println((now2 - now) + "ms took to bubblesort array"); } public void bubbleSort(int[] arr) { boolean swapped = true; int j = 0; int tmp; while (swapped) { swapped = false; j++; for (int i = 0; i < arr.length - j; i++) { if (arr[i] > arr[i + 1]) { tmp = arr[i]; arr[i] = arr[i + 1]; arr[i + 1] = tmp; swapped = true; } } } } } Just after I start the server, it takes approximately 22 seconds to run this code. After few days of JBoss 7.1.1. running, it takes 330 sec to run this code. In both cases, I launch the code when the CPU utilization is very low (say, 1%). Any ideas why? I run the server with following arguments: -Xms1280m -Xmx2048m -XX:MaxPermSize=2048m -Djava.net.preferIPv4Stack=true -Dorg.jboss.resolver.warning=true -Dsun.rmi.dgc.client.gcInterval=3600000 -Dsun.rmi.dgc.server.gcInterval=3600000 -Djboss.modules.system.pkgs=org.jboss.byteman -Djava.awt.headless=true -Duser.timezone=UTC -Djboss.server.default.config=standalone-full.xml -Xrunjdwp:transport=dt_socket,address=8787,server=y,suspend=n I'm running it on Linux 2.6.32-279.11.1.el6.x86_64 with java version "1.7.0_07". It's within J2EE applicaiton. I use CDI so I have a button on JSF page that will call method "proceed" on @RequestScoped component PerformanceTest. I deploy this as separate war file and even if I undeploy other applications, it doesn't change the performance. It's a virtual machine that is sharing CPUs with another machine but that one doesn't consume anything. Here's yet another observation: when the server is after fresh start and I run the bubble sort, It utilizes 100% of one processor core. It never switches to another core or drops utilization below 95%. However after some time the server is running and I'm experiencing the performance problems, the method above is utilizing CPU core usually 100%, however I just found out from htop that this task is being switched very often to other cores. That is, at the beginning it's running on core #1, after say 2 seconds it's running on #5 then after say 2 seconds #8 etc. Furthermore, the utilization is not kept at 100% at the core but sometimes drops to 80% or even lower. For the server after fresh start, even though If I simulate a load, it never switches the task to another core.

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• What a Performance! MySQL 5.5 and InnoDB 1.1 running on Oracle Linux

  - by zeynep.koch(at)oracle.com

  The MySQL performance team in Oracle has recently completed a series of benchmarks comparing Read / Write and Read-Only performance of MySQL 5.5 with the InnoDB and MyISAM storage engines. Compared to MyISAM, InnoDB delivered 35x higher throughput on the Read / Write test and 5x higher throughput on the Read-Only test, with 90% scalability across 36 CPU cores. A full analysis of results and MySQL configuration parameters are documented in a new whitepaperIn addition to the benchmark, the new whitepaper, also includes:- A discussion of the use-cases for each storage engine- Best practices for users considering the migration of existing applications from MyISAM to InnoDB- A summary of the performance and scalability enhancements introduced with MySQL 5.5 and InnoDB 1.1.The benchmark itself was based on Sysbench, running on AMD Opteron "Magny-Cours" processors, and Oracle Linux with the Unbreakable Enterprise Kernel You can learn more about MySQL 5.5 and InnoDB 1.1 from here and download it from here to test whether you witness performance gains in your real-world applications.  By Mat Keep

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• Is JSF really ready to deliver high performance web applications?

  - by aklin81

  I have heard a lot of good about JSF but as far as I know people also had lots of serious complains with this technology in the past, not aware of how much the situation has improved. We are considering JSF as a probable technology for a social network project. But we are not aware of the performance scores of JSF neither we could really come across any existing high performance website that had been using JSF. People complain about its performance scalability issues. We are still not very sure if we are doing the right thing by choosing jsf, and thus would like to hear from you all about this and take your inputs into consideration. Is it possible to configure JSF to satisfy the high performance needs of social networking service ? Also till what extent is it possible to survive with the current problems in JSF.

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• Romanian parter Omnilogic Delivers “No Limits” Scalability, Performance, Security, and Affordability through Next-Generation, Enterprise-Grade Engineered Systems

  - by swalker

  Omnilogic SRL is a leading technology and information systems provider in Romania and central and Eastern Europe. An Oracle Value-Added Distributor Partner, Omnilogic resells Oracle software, hardware, and engineered systems to Oracle Partner Network members and provides specialized training, support, and testing facilities. Independent software vendors (ISVs) also use Omnilogic’s demonstration and testing facilities to upgrade the performance and efficiency of their solutions and those of their customers by migrating them from competitor technologies to Oracle platforms. Omnilogic also has a dedicated offering for ISV solutions, based on Oracle technology in a hosting service provider model. Omnilogic wanted to help Oracle Partners and ISVs migrate solutions to Oracle Exadata and sell Oracle Exadata to end-customers. It installed Oracle Exadata Database Machine X2-2 Quarter Rack at its data center to create a demonstration and testing environment. Demonstrations proved that Oracle Exadata achieved processing speeds up to 100 times faster than competitor systems, cut typical back-up times from 6 hours to 20 minutes, and stored 10 times more data. Oracle Partners and ISVs learned that migrating solutions to Oracle Exadata’s preconfigured, pre-integrated hardware and software can be completed rapidly, at low cost, without business disruption, and with reduced ongoing operating costs. Challenges A word from Omnilogic “Oracle Exadata is the new killer application—the smartest solution on the market. There is no competition.” – Sorin Dragomir, Chief Operating Officer, Omnilogic SRL Enable Oracle Partners in Romania and central and eastern Europe to achieve Oracle Exadata Ready status by providing facilities to test and optimize existing applications and build real-life proofs of concept (POCs) for new solutions on Oracle Exadata Database Machine Provide technical support and demonstration facilities for ISVs migrating their customers’ solutions from competitor technologies to Oracle Exadata to maximize performance, scalability, and security; optimize hardware and datacenter space; cut maintenance costs; and improve return on investment Demonstrate power of Oracle Exadata’s high-performance, high-capacity engineered systems for customer-facing businesses, such as government organizations, telecommunications, banking and insurance, and utility companies, which typically require continuous availability to support very large data volumes Showcase Oracle Exadata’s unchallenged online transaction processing (OLTP) capabilities that cut application run times to provide unrivalled query turnaround and user response speeds while significantly reducing back-up times and eliminating risk of unplanned outages Capitalize on providing a world-class training and demonstration environment for Oracle Exadata to accelerate sales with Oracle Partners Solutions Created a testing environment to enable Oracle Partners and ISVs to test their own solutions and those of their customers on Oracle Exadata running on Oracle Enterprise Linux or Oracle Solaris Express to benchmark performance prior to migration Leveraged expertise on Oracle Exadata to offer Oracle Exadata training, migration, support seminars and to showcase live demonstrations for Oracle Partners Proved how Oracle Exadata’s pre-engineered systems, that come assembled, configured, and ready to run, reduce deployment time and cost, minimize risk, and help customers achieve the full performance potential immediately after go live Increased processing speeds 10-fold and with zero data loss for a telecommunications provider’s client-facing customer relationship management solution Achieved performance improvements of between 6 and 100 times faster for financial and utility company applications currently running on IBM, Microsoft, or SAP HANA platforms Showed how daily closure procedures carried out overnight by banks, insurance companies, and other financial institutions to analyze each day’s business, can typically be cut from around six hours to 20 minutes, some 18 times faster, when running on Oracle Exadata Simulated concurrent back-ups while running applications under normal working conditions to prove that Oracle Exadata-based solutions can be backed up during business hours without causing bottlenecks or impacting the end-user experience Demonstrated that Oracle Exadata’s built-in analytics, data mining and OLTP capabilities make it the highest-performance, lowest-cost choice for large data warehousing operations Showed how Oracle Exadata’s columnar compression and intelligent storage architecture allows 10 times more data to be stored than on competitor platforms Demonstrated how Oracle Exadata cuts hardware requirements significantly by consolidating workloads on to fewer servers which delivers greater power efficiency and lower operating costs that competing systems from IBM and other manufacturers Proved to ISVs that migrating solutions to Oracle Exadata’s preconfigured, pre-integrated hardware and software can be completed rapidly, at low cost, and with minimal business disruption Demonstrated how storage servers, database servers, and network switches can be added incrementally and inexpensively to the Oracle Exadata platform to support business expansion On track to grow revenues by 10% in year one and by 15% annually thereafter through increased business generated from Oracle Partners and ISVs

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• Mongodb performance on Windows

  - by Chris

  I've been researching nosql options available for .NET lately and MongoDB is emerging as a clear winner in terms of availability and support, so tonight I decided to give it a go. I downloaded version 1.2.4 (Windows x64 binary) from the mongodb site and ran it with the following options: C:\mongodb\bin>mkdir data C:\mongodb\bin>mongod -dbpath ./data --cpu --quiet I then loaded up the latest mongodb-csharp driver from http://github.com/samus/mongodb-csharp and immediately ran the benchmark program. Having heard about how "amazingly fast" MongoDB is, I was rather shocked at the poor benchmark performance. Starting Tests encode (small).........................................320000 00:00:00.0156250 encode (medium)........................................80000 00:00:00.0625000 encode (large).........................................1818 00:00:02.7500000 decode (small).........................................320000 00:00:00.0156250 decode (medium)........................................160000 00:00:00.0312500 decode (large).........................................2370 00:00:02.1093750 insert (small, no index)...............................2176 00:00:02.2968750 insert (medium, no index)..............................2269 00:00:02.2031250 insert (large, no index)...............................778 00:00:06.4218750 insert (small, indexed)................................2051 00:00:02.4375000 insert (medium, indexed)...............................2133 00:00:02.3437500 insert (large, indexed)................................835 00:00:05.9843750 batch insert (small, no index).........................53333 00:00:00.0937500 batch insert (medium, no index)........................26666 00:00:00.1875000 batch insert (large, no index).........................1114 00:00:04.4843750 find_one (small, no index).............................350 00:00:14.2812500 find_one (medium, no index)............................204 00:00:24.4687500 find_one (large, no index).............................135 00:00:37.0156250 find_one (small, indexed)..............................352 00:00:14.1718750 find_one (medium, indexed).............................184 00:00:27.0937500 find_one (large, indexed)..............................128 00:00:38.9062500 find (small, no index).................................516 00:00:09.6718750 find (medium, no index)................................316 00:00:15.7812500 find (large, no index).................................216 00:00:23.0468750 find (small, indexed)..................................532 00:00:09.3906250 find (medium, indexed).................................346 00:00:14.4375000 find (large, indexed)..................................212 00:00:23.5468750 find range (small, indexed)............................440 00:00:11.3593750 find range (medium, indexed)...........................294 00:00:16.9531250 find range (large, indexed)............................199 00:00:25.0625000 Press any key to continue... For starters, I can get better non-batch insert performance from SQL Server Express. What really struck me, however, was the slow performance of the find_nnnn queries. Why is retrieving data from MongoDB so slow? What am I missing? Edit: This was all on the local machine, no network latency or anything. MongoDB's CPU usage ran at about 75% the entire time the test was running. Edit 2: Also, I ran a trace on the benchmark program and confirmed that 50% of the CPU time spent was waiting for MongoDB to return data, so it's not a performance issue with the C# driver.

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• Performance Optimization &ndash; It Is Faster When You Can Measure It

  - by Alois Kraus

  Performance optimization in bigger systems is hard because the measured numbers can vary greatly depending on the measurement method of your choice. To measure execution timing of specific methods in your application you usually use Time Measurement Method Potential Pitfalls Stopwatch Most accurate method on recent processors. Internally it uses the RDTSC instruction. Since the counter is processor specific you can get greatly different values when your thread is scheduled to another core or the core goes into a power saving mode. But things do change luckily: Intel's Designer's vol3b, section 16.11.1 "16.11.1 Invariant TSC The time stamp counter in newer processors may support an enhancement, referred to as invariant TSC. Processor's support for invariant TSC is indicated by CPUID.80000007H:EDX[8]. The invariant TSC will run at a constant rate in all ACPI P-, C-. and T-states. This is the architectural behavior moving forward. On processors with invariant TSC support, the OS may use the TSC for wall clock timer services (instead of ACPI or HPET timers). TSC reads are much more efficient and do not incur the overhead associated with a ring transition or access to a platform resource." DateTime.Now Good but it has only a resolution of 16ms which can be not enough if you want more accuracy.   Reporting Method Potential Pitfalls Console.WriteLine Ok if not called too often. Debug.Print Are you really measuring performance with Debug Builds? Shame on you. Trace.WriteLine Better but you need to plug in some good output listener like a trace file. But be aware that the first time you call this method it will read your app.config and deserialize your system.diagnostics section which does also take time.   In general it is a good idea to use some tracing library which does measure the timing for you and you only need to decorate some methods with tracing so you can later verify if something has changed for the better or worse. In my previous article I did compare measuring performance with quantum mechanics. This analogy does work surprising well. When you measure a quantum system there is a lower limit how accurately you can measure something. The Heisenberg uncertainty relation does tell us that you cannot measure of a quantum system the impulse and location of a particle at the same time with infinite accuracy. For programmers the two variables are execution time and memory allocations. If you try to measure the timings of all methods in your application you will need to store them somewhere. The fastest storage space besides the CPU cache is the memory. But if your timing values do consume all available memory there is no memory left for the actual application to run. On the other hand if you try to record all memory allocations of your application you will also need to store the data somewhere. This will cost you memory and execution time. These constraints are always there and regardless how good the marketing of tool vendors for performance and memory profilers are: Any measurement will disturb the system in a non predictable way. Commercial tool vendors will tell you they do calculate this overhead and subtract it from the measured values to give you the most accurate values but in reality it is not entirely true. After falling into the trap to trust the profiler timings several times I have got into the habit to Measure with a profiler to get an idea where potential bottlenecks are. Measure again with tracing only the specific methods to check if this method is really worth optimizing. Optimize it Measure again. Be surprised that your optimization has made things worse. Think harder Implement something that really works. Measure again Finished! - Or look for the next bottleneck. Recently I have looked into issues with serialization performance. For serialization DataContractSerializer was used and I was not sure if XML is really the most optimal wire format. After looking around I have found protobuf-net which uses Googles Protocol Buffer format which is a compact binary serialization format. What is good for Google should be good for us. A small sample app to check out performance was a matter of minutes: using ProtoBuf; using System; using System.Diagnostics; using System.IO; using System.Reflection; using System.Runtime.Serialization; [DataContract, Serializable] class Data { [DataMember(Order=1)] public int IntValue { get; set; } [DataMember(Order = 2)] public string StringValue { get; set; } [DataMember(Order = 3)] public bool IsActivated { get; set; } [DataMember(Order = 4)] public BindingFlags Flags { get; set; } } class Program { static MemoryStream _Stream = new MemoryStream(); static MemoryStream Stream { get { _Stream.Position = 0; _Stream.SetLength(0); return _Stream; } } static void Main(string[] args) { DataContractSerializer ser = new DataContractSerializer(typeof(Data)); Data data = new Data { IntValue = 100, IsActivated = true, StringValue = "Hi this is a small string value to check if serialization does work as expected" }; var sw = Stopwatch.StartNew(); int Runs = 1000 * 1000; for (int i = 0; i < Runs; i++) { //ser.WriteObject(Stream, data); Serializer.Serialize<Data>(Stream, data); } sw.Stop(); Console.WriteLine("Did take {0:N0}ms for {1:N0} objects", sw.Elapsed.TotalMilliseconds, Runs); Console.ReadLine(); } } The results are indeed promising: Serializer Time in ms N objects protobuf-net   807 1000000 DataContract 4402 1000000 Nearly a factor 5 faster and a much more compact wire format. Lets use it! After switching over to protbuf-net the transfered wire data has dropped by a factor two (good) and the performance has worsened by nearly a factor two. How is that possible? We have measured it? Protobuf-net is much faster! As it turns out protobuf-net is faster but it has a cost: For the first time a type is de/serialized it does use some very smart code-gen which does not come for free. Lets try to measure this one by setting of our performance test app the Runs value not to one million but to 1. Serializer Time in ms N objects protobuf-net 85 1 DataContract 24 1 The code-gen overhead is significant and can take up to 200ms for more complex types. The break even point where the code-gen cost is amortized by its faster serialization performance is (assuming small objects) somewhere between 20.000-40.000 serialized objects. As it turned out my specific scenario involved about 100 types and 1000 serializations in total. That explains why the good old DataContractSerializer is not so easy to take out of business. The final approach I ended up was to reduce the number of types and to serialize primitive types via BinaryWriter directly which turned out to be a pretty good alternative. It sounded good until I measured again and found that my optimizations so far do not help much. After looking more deeper at the profiling data I did found that one of the 1000 calls did take 50% of the time. So how do I find out which call it was? Normal profilers do fail short at this discipline. A (totally undeserved) relatively unknown profiler is SpeedTrace which does unlike normal profilers create traces of your applications by instrumenting your IL code at runtime. This way you can look at the full call stack of the one slow serializer call to find out if this stack was something special. Unfortunately the call stack showed nothing special. But luckily I have my own tracing as well and I could see that the slow serializer call did happen during the serialization of a bool value. When you encounter after much analysis something unreasonable you cannot explain it then the chances are good that your thread was suspended by the garbage collector. If there is a problem with excessive GCs remains to be investigated but so far the serialization performance seems to be mostly ok.  When you do profile a complex system with many interconnected processes you can never be sure that the timings you just did measure are accurate at all. Some process might be hitting the disc slowing things down for all other processes for some seconds as well. There is a big difference between warm and cold startup. If you restart all processes you can basically forget the first run because of the OS disc cache, JIT and GCs make the measured timings very flexible. When you are in need of a random number generator you should measure cold startup times of a sufficiently complex system. After the first run you can try again getting different and much lower numbers. Now try again at least two times to get some feeling how stable the numbers are. Oh and try to do the same thing the next day. It might be that the bottleneck you found yesterday is gone today. Thanks to GC and other random stuff it can become pretty hard to find stuff worth optimizing if no big bottlenecks except bloatloads of code are left anymore. When I have found a spot worth optimizing I do make the code changes and do measure again to check if something has changed. If it has got slower and I am certain that my change should have made it faster I can blame the GC again. The thing is that if you optimize stuff and you allocate less objects the GC times will shift to some other location. If you are unlucky it will make your faster working code slower because you see now GCs at times where none were before. This is where the stuff does get really tricky. A safe escape hatch is to create a repro of the slow code in an isolated application so you can change things fast in a reliable manner. Then the normal profilers do also start working again. As Vance Morrison does point out it is much more complex to profile a system against the wall clock compared to optimize for CPU time. The reason is that for wall clock time analysis you need to understand how your system does work and which threads (if you have not one but perhaps 20) are causing a visible delay to the end user and which threads can wait a long time without affecting the user experience at all. Next time: Commercial profiler shootout.

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• LVM2 vs MDADM performance

  - by archer

  I've used MDADM + LVM2 on many boxes for quite a while. MDADM was serving for both RAID0 and RAID1 arrays, while LVM2 where used for logical volumes on top of MDADM. Recently I've found that LVM2 could be used w/o MDADM (thus minus one layer, as the result - less overhead) for both mirroring and stripping. However, some guys claims that READ PERFORMANCE on LVM2 for mirrored array is not that fast as for LVM2 (linear) on top of MDADM (RAID1) as LVM2 does not read from 2+ devices at a time, but use 2nd and higher devices in case of 1st device failure. MDADM reads from 2 devices at a time (even in mirrored mode). Who could confirm that?

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• How to monitor CPU usage and performance on a Hyper-V server with several VM's

  - by Bjørn

  Hello, I have a server that is running Windows 2008 64 bit Hyper-V, with 8 gigs of RAM and Intel Xeon X3440 @ 2.53 Ghz, which gives me 8 logical cores in the performance monitor on the host system. I have set up three Virtual Machines, all running Windows 2008 32 bit. Build server, running Team City Staging server SQL Server, running SQL Server 2005 I have some troubles with the setup in that the host monitor remains responsive at all times, even though the VM's are seemingly working at 100% cpu and are very sluggish and unresponsive. (I have asked a separate question about that.) So the question here is: What is the best way to monitor how the physical CPU's are actually utilized? The reason I am asking is that I am being told that i cannot reliably use the task manager to monitor CPU usage in a VM.

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• Tweaking Firefox for Performance

  - by Simon Sheehan

  As an avid Firefox user since it began, I've been looking to make some under the hood changes to it, in order to optimize it for speed and performance. I'd also like to limit my RAM usage with it. Are there any settings that can help this? What can be changed in about:config that affects this? I'd also like to know if themes or anything really boost RAM usage, as they are generally very small files to download. Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:7.0a1) Gecko/20110630 Firefox/7.0a1

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