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  • What is better for the overall performance and feel of the game: one setInterval performing all the work, or many of them doing individual tasks?

    - by Bane
    This question is, I suppose, not limited to Javascript, but it is the language I use to create my game, so I'll use it as an example. For now, I have structured my HTML5 game like this: var fps = 60; var game = new Game(); setInterval(game.update, 1000/fps); And game.update looks like this: this.update = function() { this.parseInput(); this.logic(); this.physics(); this.draw(); } This seems a bit inefficient, maybe I don't need to do all of those things at once. An obvious alternative would be to have more intervals performing individual tasks, but is it worth it? var fps = 60; var game = new Game(); setInterval(game.draw, 1000/fps); setInterval(game.physics, 1000/a); //where "a" is some constant, performing the same function as "fps" ... With which approach should I go and why? Is there a better alternative? Also, in case the second approach is the best, how frequently should I perform the tasks?

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  • Why your Netapp is so slow...

    - by Darius Zanganeh
    Have you ever wondered why your Netapp FAS box is slow and doesn't perform well at large block workloads?  In this blog entry I will give you a little bit of information that will probably help you understand why it’s so slow, why you shouldn't use it for applications that read and write in large blocks like 64k, 128k, 256k ++ etc..  Of course since I work for Oracle at this time, I will show you why the ZS3 storage boxes are excellent choices for these types of workloads. Netapp’s Fundamental Problem The fundamental problem you have running these workloads on Netapp is the backend block size of their WAFL file system.  Every application block on a Netapp FAS ends up in a 4k chunk on a disk. Reference:  Netapp TR-3001 Whitepaper Netapp has proven this lacking large block performance fact in at least two different ways. They have NEVER posted an SPC-2 Benchmark yet they have posted SPC-1 and SPECSFS, both recently. In 2011 they purchased Engenio to try and fill this GAP in their portfolio. Block Size Matters So why does block size matter anyways?  Many applications use large block chunks of data especially in the Big Data movement.  Some examples are SAS Business Analytics, Microsoft SQL, Hadoop HDFS is even 64MB! Now let me boil this down for you.  If an application such MS SQL is writing data in a 64k chunk then before Netapp actually writes it on disk it will have to split it into 16 different 4k writes and 16 different disk IOPS.  When the application later goes to read that 64k chunk the Netapp will have to again do 16 different disk IOPS.  In comparison the ZS3 Storage Appliance can write in variable block sizes ranging from 512b to 1MB.  So if you put the same MSSQL database on a ZS3 you can set the specific LUNs for this database to 64k and then when you do an application read/write it requires only a single disk IO.  That is 16x faster!  But, back to the problem with your Netapp, you will VERY quickly run out of disk IO and hit a wall.  Now all arrays will have some fancy pre fetch algorithm and some nice cache and maybe even flash based cache such as a PAM card in your Netapp but with large block workloads you will usually blow through the cache and still need significant disk IO.  Also because these datasets are usually very large and usually not dedupable they are usually not good candidates for an all flash system.  You can do some simple math in excel and very quickly you will see why it matters.  Here are a couple of READ examples using SAS and MSSQL.  Assume these are the READ IOPS the application needs even after all the fancy cache and algorithms.   Here is an example with 128k blocks.  Notice the numbers of drives on the Netapp! Here is an example with 64k blocks You can easily see that the Oracle ZS3 can do dramatically more work with dramatically less drives.  This doesn't even take into account that the ONTAP system will likely run out of CPU way before you get to these drive numbers so you be buying many more controllers.  So with all that said, lets look at the ZS3 and why you should consider it for any workload your running on Netapp today.  ZS3 World Record Price/Performance in the SPC-2 benchmark ZS3-2 is #1 in Price Performance $12.08ZS3-2 is #3 in Overall Performance 16,212 MBPS Note: The number one overall spot in the world is held by an AFA 33,477 MBPS but at a Price Performance of $29.79.  A customer could purchase 2 x ZS3-2 systems in the benchmark with relatively the same performance and walk away with $600,000 in their pocket.

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  • 3 Day Level 400 SQL Tuning Workshop 15 March in London, early bird and referral offer

    - by sqlworkshops
    I want to inform you that we have organized the "3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop" in London, United Kingdom during March 15-17, 2011.This is a truly level 400 hands-on workshop and you can find the Agenda, Prerequisite, Goal of the Workshop and Registration information at www.sqlworkshops.com/ruk. Charges are GBP 1800 (VAT excl.). Early bird discount of GBP 125 until 18 February. We are also introducing a new referral plan. If you refer someone who participates in the workshop you will receive an Amazon gift voucher for GBP 125.Feedback from one of the participants who attended our November London workshop:Andrew, Senior SQL Server DBA from UBS, UK, www.ubs.com, November 26, 2010:Rating: In a scale of 1 to 5 please rate each item below (1=Poor & 5=Excellent) Overall I was satisfied with the workshop 5 Instructor maintained the focus of the course 5 Mix of theory and practice was appropriate 5 Instructor answered the questions asked 5 The training facility met the requirement 5 How confident are you with SQL Server 2008 performance tuning 5 Additional comments from Andrew: The course was expertly delivered and backed up with practical examples. At the end of the course I felt my knowledge of SQL Server had been greatly enhanced and was eager to share with my colleagues. I felt there was one prerequisite missing from the course description, an open mind since the course changed some of my core product beliefs. For Additional workshop feedbacks refer to: www.sqlworkshops.com/feedbacks.I will be delivering the Level 300-400 1 Day Microsoft SQL Server 2008 Performance Monitoring and Tuning Seminar at Istanbul and Ankara, Turkey during March. This event is organized by Microsoft Turkey, let me know if you are in Turkey and would like to attend.During September 2010 I delivered this Level 300-400 1 Day Microsoft SQL Server 2008 Performance Monitoring and Tuning Seminar in Zurich, Switzerland organized by Microsoft Switzerland and the feedback was 4.85 out of 5, there were about 100 participants. During November 2010 when I delivered seminar in Lisbon, Portugal organized by Microsoft Portugal, the feedback was 8.30 out of 9, there were 130 participants.Our Mission: Empower customers to fully realize the Performance potential of Microsoft SQL Server without increasing the total cost of ownership (TCO) and achieve high customer satisfaction in every consulting engagement and workshop delivery.Our Business Plan: Provide useful content in webcasts, articles and seminars to get visibility for consulting engagements and workshop delivery opportunity. Help us by forwarding this email to your SQL Server friends and colleagues.Looking forwardR Meyyappan & Team @ www.SQLWorkshops.comLinkedIn: http://at.linkedin.com/in/rmeyyappan

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  • Performance Improvement: Session State

    Performance is critical to today's successful applications and web sites. If you design with an awareness of the session state management challenges you can always change your strategies to match your performance needs.

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  • Performance Improvement: Session State

    Performance is critical to today's successful applications and web sites. If you design with an awareness of the session state management challenges you can always change your strategies to match your performance needs.

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  • SQL SERVER – Disk Space Monitoring – Detecting Low Disk Space on Server

    - by Pinal Dave
    A very common question I often receive is how to detect if the disk space is running low on SQL Server. There are two different ways to do the same. I personally prefer method 2 as that is very easy to use and I can use it creatively along with database name. Method 1: EXEC MASTER..xp_fixeddrives GO Above query will return us two columns, drive name and MB free. If we want to use this data in our query, we will have to create a temporary table and insert the data from this stored procedure into the temporary table and use it. Method 2: SELECT DISTINCT dovs.logical_volume_name AS LogicalName, dovs.volume_mount_point AS Drive, CONVERT(INT,dovs.available_bytes/1048576.0) AS FreeSpaceInMB FROM sys.master_files mf CROSS APPLY sys.dm_os_volume_stats(mf.database_id, mf.FILE_ID) dovs ORDER BY FreeSpaceInMB ASC GO The above query will give us three columns: drive logical name, drive letter and free space in MB. We can further modify above query to also include database name in the query as well. SELECT DISTINCT DB_NAME(dovs.database_id) DBName, dovs.logical_volume_name AS LogicalName, dovs.volume_mount_point AS Drive, CONVERT(INT,dovs.available_bytes/1048576.0) AS FreeSpaceInMB FROM sys.master_files mf CROSS APPLY sys.dm_os_volume_stats(mf.database_id, mf.FILE_ID) dovs ORDER BY FreeSpaceInMB ASC GO This will give us additional data about which database is placed on which drive. If you see a database name multiple times, it is because your database has multiple files and they are on different drives. You can modify above query one more time to even include the details of actual file location. SELECT DISTINCT DB_NAME(dovs.database_id) DBName, mf.physical_name PhysicalFileLocation, dovs.logical_volume_name AS LogicalName, dovs.volume_mount_point AS Drive, CONVERT(INT,dovs.available_bytes/1048576.0) AS FreeSpaceInMB FROM sys.master_files mf CROSS APPLY sys.dm_os_volume_stats(mf.database_id, mf.FILE_ID) dovs ORDER BY FreeSpaceInMB ASC GO The above query will now additionally include the physical file location as well. As I mentioned earlier, I prefer method 2 as I can creatively use it as per the business need. Let me know which method are you using in your production server. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Week in Geek: Internet Service Providers to Implement New Anti-Piracy Monitoring in July

    - by Asian Angel
    Our latest edition of WIG is filled with news link goodness such as Google’s plans for a Metro version of Chrome, Microsoft’s seeking of a patent for TV-viewing tolls, Encyclopaedia Britannica’s switch to a digital only format, and more. Screenshot by Asian Angel. Make Your Own Windows 8 Start Button with Zero Memory Usage Reader Request: How To Repair Blurry Photos HTG Explains: What Can You Find in an Email Header?

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  • FREE eBook: .NET Performance Testing and Optimization (Part 1)

    In this this first part of complete guide to performance profiling, Paul Glavich and Chris Farrell explain why performance testing is a good idea and walk you through everything you need to know to set up a test environment. This comprehensive guide to getting started is an essential handbook to any programmer looking to set up a .NET testing environment and get the best results out of it. Download your free copy now span.fullpost {display:none;}

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  • Monitoring SQL Server Agent job run times

    - by okeofs
    Introduction A few months back, I was asked how long a particular nightly process took to run. It was a super question and the one thing that struck me was that there were a plethora of factors affecting the processing time. This said, I developed a query to ascertain process run times, the average nightly run times and applied some KPI’s to the end query. The end goal being to enable me to quickly detect anomalies and processes that are running beyond their normal times. As many of you are aware, most of the necessary data for this type of query, lies within the MSDB database. The core portion of the query is shown below.select sj.name,sh.run_date, sh.run_duration, case when len(sh.run_duration) = 6 then convert(varchar(8),sh.run_duration) when len(sh.run_duration) = 5 then '0' + convert(varchar(8),sh.run_duration) when len(sh.run_duration) = 4 then '00' + convert(varchar(8),sh.run_duration) when len(sh.run_duration) = 3 then '000' + convert(varchar(8),sh.run_duration) when len(sh.run_duration) = 2 then '0000' + convert(varchar(8),sh.run_duration) when len(sh.run_duration) = 1 then '00000' + convert(varchar(8),sh.run_duration) end as tt from dbo.sysjobs sj with (nolock) inner join dbo.sysjobHistory sh with (nolock) on sj.job_id = sh.job_id where sj.name = 'My Agent Job' and [sh.Message] like '%The job%') Run_date and run_duration are obvious fields. The field ‘Name’ is the name of the job that we wish to follow. The only major challenge was that the format of the run duration which was not as ‘user friendly’ as I would have liked. As an example, the run duration 1 hour 10 minutes and 3 seconds would be displayed as 11003; whereas I wanted it to display this in a more user friendly manner as 01:10:03. In order to achieve this effect, we need to add leading zeros to the run_duration based upon the case logic shown above. At this point what we need to do add colons between the hours and minutes and one between the minutes and seconds. To achieve this I nested the query shown above (in purple) within a ‘super’ query. Thus the run time ([Run Time]) is constructed concatenating a series of substrings (See below in Blue). select run_date,substring(convert(varchar(20),tt),1,2) + ':' +substring(convert(varchar(20),tt),3,2) + ':' +substring(convert(varchar(20),tt),5,2) as [run_time] from (select sj.name,sh.run_date, sh.run_duration,case when len(sh.run_duration) = 6 then convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 5 then '0' + convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 4 then '00' + convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 3 then '000' + convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 2 then '0000' + convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 1 then '00000' + convert(varchar(8),sh.run_duration)end as ttfrom dbo.sysjobs sj with (nolock)inner join dbo.sysjobHistory sh with (nolock) on sj.job_id = sh.job_id where sj.name = 'My Agent Job'and [sh.Message] like '%The job%') a Now that I had each nightly run time in hours, minutes and seconds (01:10:03), I decided that it would very productive to calculate a rolling run time average. To do this, I decided to do the calculations in base units of seconds. This said, I encapsulated the query shown above into a further ‘super’ query (see the code in RED below). This encapsulation is shown below. The astute reader will note that I used implied casting from integer to string, which is not the best method to use however it works. This said and if I were constructing the query again I would definitely do an explicit convert. To Recap: I now have a key field of ‘1’, each and every applicable run date and the total number of SECONDS that the process ran for each run date, all of this data within the #rawdata1 temporary table. Select 1 as keyy,run_date,(substring(b.run_time,1,2)*3600) + (substring(b.run_time,4,2)*60) + (substring(b.run_time,7,2)) as run_time_in_Seconds,run_time into #rawdata1 from ( select run_date,substring(convert(varchar(20),tt),1,2) + ':' + substring(convert(varchar(20),tt),3,2) + ':' +substring(convert(varchar(20),tt),5,2) as [run_time] from (select sj.name,sh.run_date, sh.run_duration, case when len(sh.run_duration) = 6 then convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 5 then '0' + convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 4 then '00' + convert(varchar(8),sh.run_duration)when len(sh.run_duration)    = 3 then '000' + convert(varchar(8),sh.run_duration)when len(sh.run_duration)    = 2 then '0000' + convert(varchar(8),sh.run_duration)when len(sh.run_duration) = 1 then '00000' + convert(varchar(8),sh.run_duration)end as ttfrom dbo.sysjobs sj with (nolock)inner join dbo.sysjobHistory sh with (nolock)on sj.job_id = sh.job_id where sj.name = 'My Agent Job'and [sh.Message] like '%The job%') a )b   Calculating the average run time We now select each run time in seconds from #rawdata1 and place the values into another temporary table called #rawdata2. Once again we create a ‘key’, a hardwired ‘1’. select 1 as Keyy, run_time_in_Seconds into #rawdata2 from #rawdata1The purpose of doing so is to make the average time AVG() available to the query immediately without having to do adverse grouping. Applying KPI Logic At this point, we shall apply some logic to determine whether processing times are within the norms. We do this by applying colour names. Obviously, this example is a super one for SSRS and traffic light icons.select rd1.run_date, rd1.run_time, rd1.run_time_in_Seconds ,Avg(rd2.run_time_in_Seconds) as Average_run_time_in_seconds,casewhenConvert(decimal(10,1),rd1.run_time_in_Seconds)/Avg(rd2.run_time_in_Seconds)<= 1.2 then 'Green' when Convert(decimal(10,1),rd1.run_time_in_Seconds)/Avg(rd2.run_time_in_Seconds)< 1.4 then 'Yellow' else 'Red'end as [color], Calculating the Average Run Time in Hours Minutes and Seconds and the end of the query. casewhen len(convert(varchar(2),Avg(rd2.run_time_in_Seconds)/(3600))) = 1 then '0' + convert(varchar(2),Avg(rd2.run_time_in_Seconds)/(3600))else convert(varchar(2),Avg(rd2.run_time_in_Seconds)/(3600))end + ':' + case when len(convert(varchar(2),Avg(rd2.run_time_in_Seconds)%(3600)/60)) = 1 then '0' + convert(varchar(2),Avg(rd2.run_time_in_Seconds)%(3600)/60)else convert(varchar(2),Avg(rd2.run_time_in_Seconds)%(3600)/60)end + ':' + case when len(convert(varchar(2),Avg(rd2.run_time_in_Seconds)%60)) = 1 then '0' + convert(varchar(2),Avg(rd2.run_time_in_Seconds)%60)else convert(varchar(2),Avg(rd2.run_time_in_Seconds)%60)end as [Average Run Time HH:MM:SS] from #rawdata2 rd2 innerjoin #rawdata1 rd1on rd1.keyy = rd2.keyygroup by run_date,rd1.run_time ,rd1.run_time_in_Seconds order by run_date descThe complete code example use msdbgo/*drop table #rawdata1drop table #rawdata2go*/select 1 as keyy,run_date,(substring(b.run_time,1,2)*3600) + (substring(b.run_time,4,2)*60) + (substring(b.run_time,7,2)) as run_time_in_Seconds,run_time into #rawdata1 from (select run_date,substring(convert(varchar(20),tt),1,2) + ':' +substring(convert(varchar(20),tt),3,2) + ':' +substring(convert(varchar(20),tt),5,2) as [run_time] from (select name,run_date, run_duration, casewhenlen(run_duration) = 6 then convert(varchar(8),run_duration)whenlen(run_duration) = 5 then '0' + convert(varchar(8),run_duration)whenlen(run_duration) = 4 then '00' + convert(varchar(8),run_duration)whenlen(run_duration) = 3 then '000' + convert(varchar(8),run_duration)whenlen(run_duration) = 2 then '0000' + convert(varchar(8),run_duration)whenlen(run_duration) = 1 then '00000' + convert(varchar(8),run_duration)end as ttfrom dbo.sysjobs sj with (nolock)innerjoin dbo.sysjobHistory sh with (nolock) on sj.job_id = sh.job_id where name = 'My Agent Job'and [Message] like '%The job%') a ) bselect 1 as Keyy, run_time_in_Seconds into #rawdata2 from #rawdata1select rd1.run_date, rd1.run_time, rd1.run_time_in_Seconds ,Avg(rd2.run_time_in_Seconds) as Average_run_time_in_seconds,casewhenConvert(decimal(10,1),rd1.run_time_in_Seconds)/Avg(rd2.run_time_in_Seconds)<= 1.2 then 'Green' when Convert(decimal(10,1),rd1.run_time_in_Seconds)/Avg(rd2.run_time_in_Seconds)< 1.4 then 'Yellow' else 'Red'end as [color],Case when len(convert(varchar(2),Avg(rd2.run_time_in_Seconds)/(3600))) = 1 then '0' + convert(varchar(2),Avg(rd2.run_time_in_Seconds)/(3600))else convert(varchar(2),Avg(rd2.run_time_in_Seconds)/(3600))end + ':' + case when len(convert(varchar(2),Avg(rd2.run_time_in_Seconds)%(3600)/60)) = 1 then '0' + convert(varchar(2),Avg(rd2.run_time_in_Seconds)%(3600)/60)else convert(varchar(2),Avg(rd2.run_time_in_Seconds)%(3600)/60)end + ':' + case when len(convert(varchar(2),Avg(rd2.run_time_in_Seconds)%60)) = 1 then '0' + convert(varchar(2),Avg(rd2.run_time_in_Seconds)%60)else convert(varchar(2),Avg(rd2.run_time_in_Seconds)%60)end as [Average Run Time HH:MM:SS] from #rawdata2 rd2 innerjoin #rawdata1 rd1on rd1.keyy = rd2.keyygroup by run_date,rd1.run_time ,rd1.run_time_in_Seconds order by run_date desc  

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  • Google I/O 2011: High-performance GWT: best practices for writing smaller, faster apps

    Google I/O 2011: High-performance GWT: best practices for writing smaller, faster apps David Chandler The GWT compiler isn't just a Java to JavaScript transliterator. In this session, we'll show you compiler optimizations to shrink your app and make it compile and run faster. Learn common performance pitfalls, how to use lightweight cell widgets, how to use code splitting with Activities and Places, and compiler options to reduce your app's size and compile time. From: GoogleDevelopers Views: 4791 21 ratings Time: 01:01:32 More in Science & Technology

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  • Improved Performance on PeopleSoft Combined Benchmark using SPARC T4-4

    - by Brian
    Oracle's SPARC T4-4 server running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved a world record 18,000 concurrent users experiencing subsecond response time while executing a PeopleSoft Payroll batch job of 500,000 employees in 32.4 minutes. This result was obtained with a SPARC T4-4 server running Oracle Database 11g Release 2, a SPARC T4-4 server running PeopleSoft HCM 9.1 application server and a SPARC T4-2 server running Oracle WebLogic Server in the web tier. The SPARC T4-4 server running the application tier used Oracle Solaris Zones which provide a flexible, scalable and manageable virtualization environment. The average CPU utilization on the SPARC T4-2 server in the web tier was 17%, on the SPARC T4-4 server in the application tier it was 59%, and on the SPARC T4-4 server in the database tier was 47% (online and batch) leaving significant headroom for additional processing across the three tiers. The SPARC T4-4 server used for the database tier hosted Oracle Database 11g Release 2 using Oracle Automatic Storage Management (ASM) for database files management with I/O performance equivalent to raw devices. Performance Landscape Results are presented for the PeopleSoft HRMS Self-Service and Payroll combined benchmark. The new result with 128 streams shows significant improvement in the payroll batch processing time with little impact on the self-service component response time. PeopleSoft HRMS Self-Service and Payroll Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-4 (db) 18,000 0.988 0.539 32.4 128 SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-4 (db) 18,000 0.944 0.503 43.3 64 The following results are for the PeopleSoft HRMS Self-Service benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the payroll component. PeopleSoft HRMS Self-Service 9.1 Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) 2x SPARC T4-2 (db) 18,000 1.048 0.742 N/A N/A The following results are for the PeopleSoft Payroll benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the self-service component. PeopleSoft Payroll (N.A.) 9.1 - 500K Employees (7 Million SQL PayCalc, Unicode) Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-4 (db) N/A N/A N/A 30.84 96 Configuration Summary Application Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 512 GB memory Oracle Solaris 11 11/11 PeopleTools 8.52 PeopleSoft HCM 9.1 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Java Platform, Standard Edition Development Kit 6 Update 32 Database Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 256 GB memory Oracle Solaris 11 11/11 Oracle Database 11g Release 2 PeopleTools 8.52 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Micro Focus Server Express (COBOL v 5.1.00) Web Tier Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory Oracle Solaris 11 11/11 PeopleTools 8.52 Oracle WebLogic Server 10.3.4 Java Platform, Standard Edition Development Kit 6 Update 32 Storage Configuration: 1 x Sun Server X2-4 as a COMSTAR head for data 4 x Intel Xeon X7550, 2.0 GHz 128 GB memory 1 x Sun Storage F5100 Flash Array (80 flash modules) 1 x Sun Storage F5100 Flash Array (40 flash modules) 1 x Sun Fire X4275 as a COMSTAR head for redo logs 12 x 2 TB SAS disks with Niwot Raid controller Benchmark Description This benchmark combines PeopleSoft HCM 9.1 HR Self Service online and PeopleSoft Payroll batch workloads to run on a unified database deployed on Oracle Database 11g Release 2. The PeopleSoft HRSS benchmark kit is a Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark where DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published. PeopleSoft HR SS defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consist of 14 scenarios which emulate users performing typical HCM transactions such as viewing paycheck, promoting and hiring employees, updating employee profile and other typical HCM application transactions. All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. This benchmark metric is the weighted average response search/save time for all the transactions. The PeopleSoft 9.1 Payroll (North America) benchmark demonstrates system performance for a range of processing volumes in a specific configuration. This workload represents large batch runs typical of a ERP environment during a mass update. The benchmark measures five application business process run times for a database representing large organization. They are Paysheet Creation, Payroll Calculation, Payroll Confirmation, Print Advice forms, and Create Direct Deposit File. The benchmark metric is the cumulative elapsed time taken to complete the Paysheet Creation, Payroll Calculation and Payroll Confirmation business application processes. The benchmark metrics are taken for each respective benchmark while running simultaneously on the same database back-end. Specifically, the payroll batch processes are started when the online workload reaches steady state (the maximum number of online users) and overlap with online transactions for the duration of the steady state. Key Points and Best Practices Two PeopleSoft Domain sets with 200 application servers each on a SPARC T4-4 server were hosted in 2 separate Oracle Solaris Zones to demonstrate consolidation of multiple application servers, ease of administration and performance tuning. Each Oracle Solaris Zone was bound to a separate processor set, each containing 15 cores (total 120 threads). The default set (1 core from first and third processor socket, total 16 threads) was used for network and disk interrupt handling. This was done to improve performance by reducing memory access latency by using the physical memory closest to the processors and offload I/O interrupt handling to default set threads, freeing up cpu resources for Application Servers threads and balancing application workload across 240 threads. A total of 128 PeopleSoft streams server processes where used on the database node to complete payroll batch job of 500,000 employees in 32.4 minutes. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN SPARC T4-4 Server oracle.com OTN PeopleSoft Enterprise Human Capital Managementoracle.com OTN PeopleSoft Enterprise Human Capital Management (Payroll) oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 8 November 2012.

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  • Tester la performance de votre réseau avec Iperf, un tutoriel par Nicolas Hennion

    Bonjour à tous !La rubrique Réseaux vous propose un article expliquant comment tester les performances du réseau avec Iperf par nicolargo : Tester la performance de votre réseau avec Iperf. Citation: Iperf est un des outils indispensables pour tout administrateur réseau qui se respecte. En effet, ce logiciel de mesure de performance réseau, disponible sur de nombreuses plateformes (Linux, BSD, Mac, Windows?) se présente sous la forme d'une ligne de commande à exécuter sur deux machines...

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  • A Perspective on Database Performance Tuning

    Fundamentally, database performance tuning is done for two basic reasons, to reduce response time and to reduce resource usage, both of which can apply for any given situation. Julian Stuhler looks at database performance tuning, and why it remains one of the most important topics for any DBA, developer or systems administrator.

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  • Data Quality Services Performance Best Practices Guide

    This guide details high-level performance numbers expected and a set of best practices on getting optimal performance when using Data Quality Services (DQS) in SQL Server 2012 with Cumulative Update 1. Schedule Azure backupsRed Gate’s Cloud Services makes it simple to create and schedule backups of your SQL Azure databases to Azure blob storage or Amazon S3. Try it for free today.

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  • Talend vs. SSIS: A Simple Performance Comparison

    With all of the ETL tools in the marketplace, which one is best? Jeff Singleton brings us simple performance comparison pitting SSIS against open source powerhouse Talend. Optimize SQL Server performance“With SQL Monitor, we can be proactive in our optimization process, instead of waiting until a customer reports a problem,” John Trumbul, Sr. Software Engineer. Optimize your servers with a free trial.

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  • A Perspective on Database Performance Tuning

    Fundamentally, database performance tuning is done for two basic reasons, to reduce response time and to reduce resource usage, both of which can apply for any given situation. Julian Stuhler looks at database performance tuning, and why it remains one of the most important topics for any DBA, developer or systems administrator.

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  • Database Activity Monitoring Part 2 - SQL Injection Attacks

    If you think through the web sites you visit on a daily basis the chances are that you will need to login to verify who you are. In most cases your username would be stored in a relational database along with all the other registered users on that web site. Hopefully your password will be encrypted and not stored in plain text.

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  • Setting up UPS monitoring

    - by Andrew Heath
    I have acquired a second hand Uninterrupted Power Supply (UPS) that I have refurbished (new battery) and hope to use with my Ubuntu 12.10 system. It's a SOLA 330 with serial out. I have installed NUT Metapackage and NUT Monitor from Software Centre, but am not sure how to go about setting it all up. A Google search brings up several ways of configuring Network UPS Tools (NUT) or HAL-Drivers, however, HAL-Drivers appears to be obsolete and many commands and config files mentioned to edit do not exist in 12.10 or the current version of NUT (most articles are a few years old). One tutorial seemed to work except the Error: no UPS definitions found in ups.conf even though ups.conf has values in it as laid out in the tutorial. How do I go about setting my system to monitor the UPS for a shut down signal? Also, is there a command to determine the UPS is communicating through the serial connection and on what port (to help with setup and configuring, eg. /dev/ttyS0 is mentioned in one of the tutorials I read).

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  • Profiling SharePoint with ANTS Performance Profiler 5.2

    Using ANTS Performance Profiler with SharePoint has, previously, been possible, but not easy. Version 5.2 of ANTS Performance Profiler changes all that, and Chris Allen has put together a straight-forward guide to profiling SharePoint, demonstrating just how much easier it has become.

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  • Will using FAT32 provide better pagefile performance than NTFS?

    - by llazzaro
    Hello, I was discussing with my others personalities, and came up with a conflict. In http://technet.microsoft.com/en-us/library/cc938440.aspx , says that FAT32 is faster when using smaller volumes. Ok separate disk, will give more performance than same disk. But did anyone test this? Scenario 1 : Separate hard disk FAT32 (small volume) Scenario 2 : Separate hard disk NTFS which one will win? minimum gain?

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  • JMX Monitoring of GlassFish Servers

    - by tjquinn
    Did you ever wonder what this message in your GlassFish server.log file means? JMXStartupService has started JMXConnector on JMXService URL service:jmx:rmi://192.168.2.102:8686/jndi/rmi://192.168.2.102:8686/jmxrmi It means you can monitor any GlassFish server process, remotely or locally, using any standard Java Management Extensions (JMX) client.  Examples: jconsole or jvisualvm.   Copy the part of the log message that starts with "service:" into the Add JMX Connection dialog of jvisualvm:  or into the New Connection dialog of jconsole: (The full string is truncated in the on-screen display, but if you copied from the server.log and pasted into the form it should all be there.) The examples above are for a DAS, and your host will probably be different.   The server.log files for other GlassFish servers (instances) will have similar log entries giving the JMX connection string to use for those processes.  Look for the host and/or port to be different. Note a few things about security: Here we've assumed you are using the default admin username and password.  If you are not, just enter a valid admin username and password for your installation.  Once connected, you have normal access to all the JVM statistics and controls. You can use JMX clients that support MBeans to view the GlassFish configuration.  When you connect to the DAS, you can also change that configuration, but you can only view configuration when you connect to an instance. To use a JMX client on one system to connect to a GlassFish server running on another system, you need to enable secure admin if you have not already done so: asadmin change-admin-password (respond to the prompts) asadmin enable-secure-admin asadmin restart-domain (as prompted in the output from enable-secure-admin)

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  • Monitoring settings in a configsection of your app.config for changes

    - by dotjosh
    The usage:public static void Main() { using(var configSectionAdapter = new ConfigurationSectionAdapter<ACISSInstanceConfigSection>("MyConfigSectionName")) { configSectionAdapter.ConfigSectionChanged += () => { Console.WriteLine("File has changed! New setting is " + configSectionAdapter.ConfigSection.MyConfigSetting); }; Console.WriteLine("The initial setting is " + configSectionAdapter.ConfigSection.MyConfigSetting); Console.ReadLine(); } }  The meat: public class ConfigurationSectionAdapter<T> : IDisposable where T : ConfigurationSection { private readonly string _configSectionName; private FileSystemWatcher _fileWatcher; public ConfigurationSectionAdapter(string configSectionName) { _configSectionName = configSectionName; StartFileWatcher(); } private void StartFileWatcher() { var configurationFileDirectory = new FileInfo(Configuration.FilePath).Directory; _fileWatcher = new FileSystemWatcher(configurationFileDirectory.FullName); _fileWatcher.Changed += FileWatcherOnChanged; _fileWatcher.EnableRaisingEvents = true; } private void FileWatcherOnChanged(object sender, FileSystemEventArgs args) { var changedFileIsConfigurationFile = string.Equals(args.FullPath, Configuration.FilePath, StringComparison.OrdinalIgnoreCase); if (!changedFileIsConfigurationFile) return; ClearCache(); OnConfigSectionChanged(); } private void ClearCache() { ConfigurationManager.RefreshSection(_configSectionName); } public T ConfigSection { get { return (T)Configuration.GetSection(_configSectionName); } } private System.Configuration.Configuration Configuration { get { return ConfigurationManager.OpenExeConfiguration(ConfigurationUserLevel.None); } } public delegate void ConfigChangedHandler(); public event ConfigChangedHandler ConfigSectionChanged; protected void OnConfigSectionChanged() { if (ConfigSectionChanged != null) ConfigSectionChanged(); } public void Dispose() { _fileWatcher.Changed -= FileWatcherOnChanged; _fileWatcher.EnableRaisingEvents = false; _fileWatcher.Dispose(); } }

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