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  • General monitoring for SQL Server Analysis Services using Performance Monitor

    - by Testas
    A recent customer engagement required a setup of a monitoring solution for SSAS, due to the time restrictions placed upon this, native Windows Performance Monitor (Perfmon) and SQL Server Profiler Monitoring Tools was used as using a third party tool would have meant the customer providing an additional monitoring server that was not available.I wanted to outline the performance monitoring counters that was used to monitor the system on which SSAS was running. Due to the slow query performance that was occurring during certain scenarios, perfmon was used to establish if any pressure was being placed on the Disk, CPU or Memory subsystem when concurrent connections access the same query, and Profiler to pinpoint how the query was being managed within SSAS, profiler I will leave for another blogThis guide is not designed to provide a definitive list of what should be used when monitoring SSAS, different situations may require the addition or removal of counters as presented by the situation. However I hope that it serves as a good basis for starting your monitoring of SSAS. I would also like to acknowledge Chris Webb’s awesome chapters from “Expert Cube Development” that also helped shape my monitoring strategy:http://cwebbbi.spaces.live.com/blog/cns!7B84B0F2C239489A!6657.entrySimulating ConnectionsTo simulate the additional connections to the SSAS server whilst monitoring, I used ascmd to simulate multiple connections to the typical and worse performing queries that were identified by the customer. A similar sript can be downloaded from codeplex at http://www.codeplex.com/SQLSrvAnalysisSrvcs.     File name: ASCMD_StressTestingScripts.zip. Performance MonitorWithin performance monitor,  a counter log was created that contained the list of counters below. The important point to note when running the counter log is that the RUN AS property within the counter log properties should be changed to an account that has rights to the SSAS instance when monitoring MSAS counters. Failure to do so means that the counter log runs under the system account, no errors or warning are given while running the counter log, and it is not until you need to view the MSAS counters that they will not be displayed if run under the default account that has no right to SSAS. If your connection simulation takes hours, this could prove quite frustrating if not done beforehand JThe counters used……  Object Counter Instance Justification System Processor Queue legnth N/A Indicates how many threads are waiting for execution against the processor. If this counter is consistently higher than around 5 when processor utilization approaches 100%, then this is a good indication that there is more work (active threads) available (ready for execution) than the machine's processors are able to handle. System Context Switches/sec N/A Measures how frequently the processor has to switch from user- to kernel-mode to handle a request from a thread running in user mode. The heavier the workload running on your machine, the higher this counter will generally be, but over long term the value of this counter should remain fairly constant. If this counter suddenly starts increasing however, it may be an indicating of a malfunctioning device, especially if the Processor\Interrupts/sec\(_Total) counter on your machine shows a similar unexplained increase Process % Processor Time sqlservr Definately should be used if Processor\% Processor Time\(_Total) is maxing at 100% to assess the effect of the SQL Server process on the processor Process % Processor Time msmdsrv Definately should be used if Processor\% Processor Time\(_Total) is maxing at 100% to assess the effect of the SQL Server process on the processor Process Working Set sqlservr If the Memory\Available bytes counter is decreaing this counter can be run to indicate if the process is consuming larger and larger amounts of RAM. Process(instance)\Working Set measures the size of the working set for each process, which indicates the number of allocated pages the process can address without generating a page fault. Process Working Set msmdsrv If the Memory\Available bytes counter is decreaing this counter can be run to indicate if the process is consuming larger and larger amounts of RAM. Process(instance)\Working Set measures the size of the working set for each process, which indicates the number of allocated pages the process can address without generating a page fault. Processor % Processor Time _Total and individual cores measures the total utilization of your processor by all running processes. If multi-proc then be mindful only an average is provided Processor % Privileged Time _Total To see how the OS is handling basic IO requests. If kernel mode utilization is high, your machine is likely underpowered as it's too busy handling basic OS housekeeping functions to be able to effectively run other applications. Processor % User Time _Total To see how the applications is interacting from a processor perspective, a high percentage utilisation determine that the server is dealing with too many apps and may require increasing thje hardware or scaling out Processor Interrupts/sec _Total  The average rate, in incidents per second, at which the processor received and serviced hardware interrupts. Shoulr be consistant over time but a sudden unexplained increase could indicate a device malfunction which can be confirmed using the System\Context Switches/sec counter Memory Pages/sec N/A Indicates the rate at which pages are read from or written to disk to resolve hard page faults. This counter is a primary indicator of the kinds of faults that cause system-wide delays, this is the primary counter to watch for indication of possible insufficient RAM to meet your server's needs. A good idea here is to configure a perfmon alert that triggers when the number of pages per second exceeds 50 per paging disk on your system. May also want to see the configuration of the page file on the Server Memory Available Mbytes N/A is the amount of physical memory, in bytes, available to processes running on the computer. if this counter is greater than 10% of the actual RAM in your machine then you probably have more than enough RAM. monitor it regularly to see if any downward trend develops, and set an alert to trigger if it drops below 2% of the installed RAM. Physical Disk Disk Transfers/sec for each physical disk If it goes above 10 disk I/Os per second then you've got poor response time for your disk. Physical Disk Idle Time _total If Disk Transfers/sec is above  25 disk I/Os per second use this counter. which measures the percent time that your hard disk is idle during the measurement interval, and if you see this counter fall below 20% then you've likely got read/write requests queuing up for your disk which is unable to service these requests in a timely fashion. Physical Disk Disk queue legnth For the OLAP and SQL physical disk A value that is consistently less than 2 means that the disk system is handling the IO requests against the physical disk Network Interface Bytes Total/sec For the NIC Should be monitored over a period of time to see if there is anb increase/decrease in network utilisation Network Interface Current Bandwidth For the NIC is an estimate of the current bandwidth of the network interface in bits per second (BPS). MSAS 2005: Memory Memory Limit High KB N/A Shows (as a percentage) the high memory limit configured for SSAS in C:\Program Files\Microsoft SQL Server\MSAS10.MSSQLSERVER\OLAP\Config\msmdsrv.ini MSAS 2005: Memory Memory Limit Low KB N/A Shows (as a percentage) the low memory limit configured for SSAS in C:\Program Files\Microsoft SQL Server\MSAS10.MSSQLSERVER\OLAP\Config\msmdsrv.ini MSAS 2005: Memory Memory Usage KB N/A Displays the memory usage of the server process. MSAS 2005: Memory File Store KB N/A Displays the amount of memory that is reserved for the Cache. Note if total memory limit in the msmdsrv.ini is set to 0, no memory is reserved for the cache MSAS 2005: Storage Engine Query Queries from Cache Direct / sec N/A Displays the rate of queries answered from the cache directly MSAS 2005: Storage Engine Query Queries from Cache Filtered / Sec N/A Displays the Rate of queries answered by filtering existing cache entry. MSAS 2005: Storage Engine Query Queries from File / Sec N/A Displays the Rate of queries answered from files. MSAS 2005: Storage Engine Query Average time /query N/A Displays the average time of a query MSAS 2005: Connection Current connections N/A Displays the number of connections against the SSAS instance MSAS 2005: Connection Requests / sec N/A Displays the rate of query requests per second MSAS 2005: Locks Current Lock Waits N/A Displays thhe number of connections waiting on a lock MSAS 2005: Threads Query Pool job queue Length N/A The number of queries in the job queue MSAS 2005:Proc Aggregations Temp file bytes written/sec N/A Shows the number of bytes of data processed in a temporary file MSAS 2005:Proc Aggregations Temp file rows written/sec N/A Shows the number of bytes of data processed in a temporary file 

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  • Kinect va entrer au Guiness Book des Records, il est « l'appareil électronique de grande consommation qui s'est vendu le plus rapidement »

    Kinect va entrer au Guiness Book des Records Il est l'appareil électronique de grande consommation qui s'est vendu le plus rapidement Mise à jour du 10/03/11 Le Guinness World Records, l'autorité mondiale en matière de records, a confirmé aujourd'hui que Kinect, le capteur de mouvement de Microsoft pour la Xbox 360, était « l'appareil électronique de grande consommation qui s'est vendu le plus rapidement ».*Le périphérique s'est en effet vendu à une moyenne de 133.333 unités par jour, pour un total de 8 millions d'unités dans ses 60 premiers jours (lire ci-avant).*« Les chiffres de vente dépassent ceux de l'iPhone et de l'iPad pour leurs périodes ...

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  • Of C# Iterators and Performance

    - by James Michael Hare
    Some of you reading this will be wondering, "what is an iterator" and think I'm locked in the world of C++.  Nope, I'm talking C# iterators.  No, not enumerators, iterators.   So, for those of you who do not know what iterators are in C#, I will explain it in summary, and for those of you who know what iterators are but are curious of the performance impacts, I will explore that as well.   Iterators have been around for a bit now, and there are still a bunch of people who don't know what they are or what they do.  I don't know how many times at work I've had a code review on my code and have someone ask me, "what's that yield word do?"   Basically, this post came to me as I was writing some extension methods to extend IEnumerable<T> -- I'll post some of the fun ones in a later post.  Since I was filtering the resulting list down, I was using the standard C# iterator concept; but that got me wondering: what are the performance implications of using an iterator versus returning a new enumeration?   So, to begin, let's look at a couple of methods.  This is a new (albeit contrived) method called Every(...).  The goal of this method is to access and enumeration and return every nth item in the enumeration (including the first).  So Every(2) would return items 0, 2, 4, 6, etc.   Now, if you wanted to write this in the traditional way, you may come up with something like this:       public static IEnumerable<T> Every<T>(this IEnumerable<T> list, int interval)     {         List<T> newList = new List<T>();         int count = 0;           foreach (var i in list)         {             if ((count++ % interval) == 0)             {                 newList.Add(i);             }         }           return newList;     }     So basically this method takes any IEnumerable<T> and returns a new IEnumerable<T> that contains every nth item.  Pretty straight forward.   The problem?  Well, Every<T>(...) will construct a list containing every nth item whether or not you care.  What happens if you were searching this result for a certain item and find that item after five tries?  You would have generated the rest of the list for nothing.   Enter iterators.  This C# construct uses the yield keyword to effectively defer evaluation of the next item until it is asked for.  This can be very handy if the evaluation itself is expensive or if there's a fair chance you'll never want to fully evaluate a list.   We see this all the time in Linq, where many expressions are chained together to do complex processing on a list.  This would be very expensive if each of these expressions evaluated their entire possible result set on call.    Let's look at the same example function, this time using an iterator:       public static IEnumerable<T> Every<T>(this IEnumerable<T> list, int interval)     {         int count = 0;         foreach (var i in list)         {             if ((count++ % interval) == 0)             {                 yield return i;             }         }     }   Notice it does not create a new return value explicitly, the only evidence of a return is the "yield return" statement.  What this means is that when an item is requested from the enumeration, it will enter this method and evaluate until it either hits a yield return (in which case that item is returned) or until it exits the method or hits a yield break (in which case the iteration ends.   Behind the scenes, this is all done with a class that the CLR creates behind the scenes that keeps track of the state of the iteration, so that every time the next item is asked for, it finds that item and then updates the current position so it knows where to start at next time.   It doesn't seem like a big deal, does it?  But keep in mind the key point here: it only returns items as they are requested. Thus if there's a good chance you will only process a portion of the return list and/or if the evaluation of each item is expensive, an iterator may be of benefit.   This is especially true if you intend your methods to be chainable similar to the way Linq methods can be chained.    For example, perhaps you have a List<int> and you want to take every tenth one until you find one greater than 10.  We could write that as:       List<int> someList = new List<int>();         // fill list here         someList.Every(10).TakeWhile(i => i <= 10);     Now is the difference more apparent?  If we use the first form of Every that makes a copy of the list.  It's going to copy the entire list whether we will need those items or not, that can be costly!    With the iterator version, however, it will only take items from the list until it finds one that is > 10, at which point no further items in the list are evaluated.   So, sounds neat eh?  But what's the cost is what you're probably wondering.  So I ran some tests using the two forms of Every above on lists varying from 5 to 500,000 integers and tried various things.    Now, iteration isn't free.  If you are more likely than not to iterate the entire collection every time, iterator has some very slight overhead:   Copy vs Iterator on 100% of Collection (10,000 iterations) Collection Size Num Iterated Type Total ms 5 5 Copy 5 5 5 Iterator 5 50 50 Copy 28 50 50 Iterator 27 500 500 Copy 227 500 500 Iterator 247 5000 5000 Copy 2266 5000 5000 Iterator 2444 50,000 50,000 Copy 24,443 50,000 50,000 Iterator 24,719 500,000 500,000 Copy 250,024 500,000 500,000 Iterator 251,521   Notice that when iterating over the entire produced list, the times for the iterator are a little better for smaller lists, then getting just a slight bit worse for larger lists.  In reality, given the number of items and iterations, the result is near negligible, but just to show that iterators come at a price.  However, it should also be noted that the form of Every that returns a copy will have a left-over collection to garbage collect.   However, if we only partially evaluate less and less through the list, the savings start to show and make it well worth the overhead.  Let's look at what happens if you stop looking after 80% of the list:   Copy vs Iterator on 80% of Collection (10,000 iterations) Collection Size Num Iterated Type Total ms 5 4 Copy 5 5 4 Iterator 5 50 40 Copy 27 50 40 Iterator 23 500 400 Copy 215 500 400 Iterator 200 5000 4000 Copy 2099 5000 4000 Iterator 1962 50,000 40,000 Copy 22,385 50,000 40,000 Iterator 19,599 500,000 400,000 Copy 236,427 500,000 400,000 Iterator 196,010       Notice that the iterator form is now operating quite a bit faster.  But the savings really add up if you stop on average at 50% (which most searches would typically do):     Copy vs Iterator on 50% of Collection (10,000 iterations) Collection Size Num Iterated Type Total ms 5 2 Copy 5 5 2 Iterator 4 50 25 Copy 25 50 25 Iterator 16 500 250 Copy 188 500 250 Iterator 126 5000 2500 Copy 1854 5000 2500 Iterator 1226 50,000 25,000 Copy 19,839 50,000 25,000 Iterator 12,233 500,000 250,000 Copy 208,667 500,000 250,000 Iterator 122,336   Now we see that if we only expect to go on average 50% into the results, we tend to shave off around 40% of the time.  And this is only for one level deep.  If we are using this in a chain of query expressions it only adds to the savings.   So my recommendation?  If you have a resonable expectation that someone may only want to partially consume your enumerable result, I would always tend to favor an iterator.  The cost if they iterate the whole thing does not add much at all -- and if they consume only partially, you reap some really good performance gains.   Next time I'll discuss some of my favorite extensions I've created to make development life a little easier and maintainability a little better.

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  • C#: LINQ vs foreach - Round 1.

    - by James Michael Hare
    So I was reading Peter Kellner's blog entry on Resharper 5.0 and its LINQ refactoring and thought that was very cool.  But that raised a point I had always been curious about in my head -- which is a better choice: manual foreach loops or LINQ?    The answer is not really clear-cut.  There are two sides to any code cost arguments: performance and maintainability.  The first of these is obvious and quantifiable.  Given any two pieces of code that perform the same function, you can run them side-by-side and see which piece of code performs better.   Unfortunately, this is not always a good measure.  Well written assembly language outperforms well written C++ code, but you lose a lot in maintainability which creates a big techncial debt load that is hard to offset as the application ages.  In contrast, higher level constructs make the code more brief and easier to understand, hence reducing technical cost.   Now, obviously in this case we're not talking two separate languages, we're comparing doing something manually in the language versus using a higher-order set of IEnumerable extensions that are in the System.Linq library.   Well, before we discuss any further, let's look at some sample code and the numbers.  First, let's take a look at the for loop and the LINQ expression.  This is just a simple find comparison:       // find implemented via LINQ     public static bool FindViaLinq(IEnumerable<int> list, int target)     {         return list.Any(item => item == target);     }         // find implemented via standard iteration     public static bool FindViaIteration(IEnumerable<int> list, int target)     {         foreach (var i in list)         {             if (i == target)             {                 return true;             }         }           return false;     }   Okay, looking at this from a maintainability point of view, the Linq expression is definitely more concise (8 lines down to 1) and is very readable in intention.  You don't have to actually analyze the behavior of the loop to determine what it's doing.   So let's take a look at performance metrics from 100,000 iterations of these methods on a List<int> of varying sizes filled with random data.  For this test, we fill a target array with 100,000 random integers and then run the exact same pseudo-random targets through both searches.                       List<T> On 100,000 Iterations     Method      Size     Total (ms)  Per Iteration (ms)  % Slower     Any         10       26          0.00046             30.00%     Iteration   10       20          0.00023             -     Any         100      116         0.00201             18.37%     Iteration   100      98          0.00118             -     Any         1000     1058        0.01853             16.78%     Iteration   1000     906         0.01155             -     Any         10,000   10,383      0.18189             17.41%     Iteration   10,000   8843        0.11362             -     Any         100,000  104,004     1.8297              18.27%     Iteration   100,000  87,941      1.13163             -   The LINQ expression is running about 17% slower for average size collections and worse for smaller collections.  Presumably, this is due to the overhead of the state machine used to track the iterators for the yield returns in the LINQ expressions, which seems about right in a tight loop such as this.   So what about other LINQ expressions?  After all, Any() is one of the more trivial ones.  I decided to try the TakeWhile() algorithm using a Count() to get the position stopped like the sample Pete was using in his blog that Resharper refactored for him into LINQ:       // Linq form     public static int GetTargetPosition1(IEnumerable<int> list, int target)     {         return list.TakeWhile(item => item != target).Count();     }       // traditionally iterative form     public static int GetTargetPosition2(IEnumerable<int> list, int target)     {         int count = 0;           foreach (var i in list)         {             if(i == target)             {                 break;             }               ++count;         }           return count;     }   Once again, the LINQ expression is much shorter, easier to read, and should be easier to maintain over time, reducing the cost of technical debt.  So I ran these through the same test data:                       List<T> On 100,000 Iterations     Method      Size     Total (ms)  Per Iteration (ms)  % Slower     TakeWhile   10       41          0.00041             128%     Iteration   10       18          0.00018             -     TakeWhile   100      171         0.00171             88%     Iteration   100      91          0.00091             -     TakeWhile   1000     1604        0.01604             94%     Iteration   1000     825         0.00825             -     TakeWhile   10,000   15765       0.15765             92%     Iteration   10,000   8204        0.08204             -     TakeWhile   100,000  156950      1.5695              92%     Iteration   100,000  81635       0.81635             -     Wow!  I expected some overhead due to the state machines iterators produce, but 90% slower?  That seems a little heavy to me.  So then I thought, well, what if TakeWhile() is not the right tool for the job?  The problem is TakeWhile returns each item for processing using yield return, whereas our for-loop really doesn't care about the item beyond using it as a stop condition to evaluate. So what if that back and forth with the iterator state machine is the problem?  Well, we can quickly create an (albeit ugly) lambda that uses the Any() along with a count in a closure (if a LINQ guru knows a better way PLEASE let me know!), after all , this is more consistent with what we're trying to do, we're trying to find the first occurence of an item and halt once we find it, we just happen to be counting on the way.  This mostly matches Any().       // a new method that uses linq but evaluates the count in a closure.     public static int TakeWhileViaLinq2(IEnumerable<int> list, int target)     {         int count = 0;         list.Any(item =>             {                 if(item == target)                 {                     return true;                 }                   ++count;                 return false;             });         return count;     }     Now how does this one compare?                         List<T> On 100,000 Iterations     Method         Size     Total (ms)  Per Iteration (ms)  % Slower     TakeWhile      10       41          0.00041             128%     Any w/Closure  10       23          0.00023             28%     Iteration      10       18          0.00018             -     TakeWhile      100      171         0.00171             88%     Any w/Closure  100      116         0.00116             27%     Iteration      100      91          0.00091             -     TakeWhile      1000     1604        0.01604             94%     Any w/Closure  1000     1101        0.01101             33%     Iteration      1000     825         0.00825             -     TakeWhile      10,000   15765       0.15765             92%     Any w/Closure  10,000   10802       0.10802             32%     Iteration      10,000   8204        0.08204             -     TakeWhile      100,000  156950      1.5695              92%     Any w/Closure  100,000  108378      1.08378             33%     Iteration      100,000  81635       0.81635             -     Much better!  It seems that the overhead of TakeAny() returning each item and updating the state in the state machine is drastically reduced by using Any() since Any() iterates forward until it finds the value we're looking for -- for the task we're attempting to do.   So the lesson there is, make sure when you use a LINQ expression you're choosing the best expression for the job, because if you're doing more work than you really need, you'll have a slower algorithm.  But this is true of any choice of algorithm or collection in general.     Even with the Any() with the count in the closure it is still about 30% slower, but let's consider that angle carefully.  For a list of 100,000 items, it was the difference between 1.01 ms and 0.82 ms roughly in a List<T>.  That's really not that bad at all in the grand scheme of things.  Even running at 90% slower with TakeWhile(), for the vast majority of my projects, an extra millisecond to save potential errors in the long term and improve maintainability is a small price to pay.  And if your typical list is 1000 items or less we're talking only microseconds worth of difference.   It's like they say: 90% of your performance bottlenecks are in 2% of your code, so over-optimizing almost never pays off.  So personally, I'll take the LINQ expression wherever I can because they will be easier to read and maintain (thus reducing technical debt) and I can rely on Microsoft's development to have coded and unit tested those algorithm fully for me instead of relying on a developer to code the loop logic correctly.   If something's 90% slower, yes, it's worth keeping in mind, but it's really not until you start get magnitudes-of-order slower (10x, 100x, 1000x) that alarm bells should really go off.  And if I ever do need that last millisecond of performance?  Well then I'll optimize JUST THAT problem spot.  To me it's worth it for the readability, speed-to-market, and maintainability.

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  • Oracle Expands Sun Blade Portfolio for Cloud and Highly Virtualized Environments

    - by Ferhat Hatay
    Oracle announced the expansion of Sun Blade Portfolio for cloud and highly virtualized environments that deliver powerful performance and simplified management as tightly integrated systems.  Along with the SPARC T3-1B blade server, Oracle VM blade cluster reference configuration and Oracle's optimized solution for Oracle WebLogic Suite, Oracle introduced the dual-node Sun Blade X6275 M2 server module with some impressive benchmark results.   Benchmarks on the Sun Blade X6275 M2 server module demonstrate the outstanding performance characteristics critical for running varied commercial applications used in cloud and highly virtualized environments.  These include best-in-class SPEC CPU2006 results with the Intel Xeon processor 5600 series, six Fluent world records and 1.8 times the price-performance of the IBM Power 755 running NAMD, a prominent bio-informatics workload.   Benchmarks for Sun Blade X6275 M2 server module  SPEC CPU2006  The Sun Blade X6275 M2 server module demonstrated best in class SPECint_rate2006 results for all published results using the Intel Xeon processor 5600 series, with a result of 679.  This result is 97% better than the HP BL460c G7 blade, 80% better than the IBM HS22V blade, and 79% better than the Dell M710 blade.  This result demonstrates the density advantage of the new Oracle's server module for space-constrained data centers.     Sun Blade X6275M2 (2 Nodes, Intel Xeon X5670 2.93GHz) - 679 SPECint_rate2006; HP ProLiant BL460c G7 (2.93 GHz, Intel Xeon X5670) - 347 SPECint_rate2006; IBM BladeCenter HS22V (Intel Xeon X5680)  - 377 SPECint_rate2006; Dell PowerEdge M710 (Intel Xeon X5680, 3.33 GHz) - 380 SPECint_rate2006.  SPEC, SPECint, SPECfp reg tm of Standard Performance Evaluation Corporation. Results from www.spec.org as of 11/24/2010 and this report.    For more specifics about these results, please go to see http://blogs.sun.com/BestPerf   Fluent The Sun Fire X6275 M2 server module produced world-record results on each of the six standard cases in the current "FLUENT 12" benchmark test suite at 8-, 12-, 24-, 32-, 64- and 96-core configurations. These results beat the most recent QLogic score with IBM DX 360 M series platforms and QLogic "Truescale" interconnects.  Results on sedan_4m test case on the Sun Blade X6275 M2 server module are 23% better than the HP C7000 system, and 20% better than the IBM DX 360 M2; Dell has not posted a result for this test case.  Results can be found at the FLUENT website.   ANSYS's FLUENT software solves fluid flow problems, and is based on a numerical technique called computational fluid dynamics (CFD), which is used in the automotive, aerospace, and consumer products industries. The FLUENT 12 benchmark test suite consists of seven models that are well suited for multi-node clustered environments and representative of modern engineering CFD clusters. Vendors benchmark their systems with the principal objective of providing comparative performance information for FLUENT software that, among other things, depends on compilers, optimization, interconnect, and the performance characteristics of the hardware.   FLUENT application performance is representative of other commercial applications that require memory and CPU resources to be available in a scalable cluster-ready format.  FLUENT benchmark has six conventional test cases (eddy_417k, turbo_500k, aircraft_2m, sedan_4m, truck_14m, truck_poly_14m) at various core counts.   All information on the FLUENT website (http://www.fluent.com) is Copyrighted1995-2010 by ANSYS Inc. Results as of November 24, 2010. For more specifics about these results, please go to see http://blogs.sun.com/BestPerf   NAMD Results on the Sun Blade X6275 M2 server module running NAMD (a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems) show up to a 1.8X better price/performance than IBM's Power 7-based system.  For space-constrained environments, the ultra-dense Sun Blade X6275 M2 server module provides a 1.7X better price/performance per rack unit than IBM's system.     IBM Power 755 4-way Cluster (16U). Total price for cluster: $324,212. See IBM United States Hardware Announcement 110-008, dated February 9, 2010, pp. 4, 21 and 39-46.  Sun Blade X6275 M2 8-Blade Cluster (10U). Total price for cluster:  $193,939. Price/performance and performance/RU comparisons based on f1ATPase molecule test results. Sun Blade X6275 M2 cluster: $3,568/step/sec, 5.435 step/sec/RU. IBM Power 755 cluster: $6,355/step/sec, 3.189 step/sec/U. See http://www-03.ibm.com/systems/power/hardware/reports/system_perf.html. See http://www.ks.uiuc.edu/Research/namd/performance.html for more information, results as of 11/24/10.   For more specifics about these results, please go to see http://blogs.sun.com/BestPerf   Reverse Time Migration The Reverse Time Migration is heavily used in geophysical imaging and modeling for Oil & Gas Exploration.  The Sun Blade X6275 M2 server module showed up to a 40% performance improvement over the previous generation server module with super-linear scalability to 16 nodes for the 9-Point Stencil used in this Reverse Time Migration computational kernel.  The balanced combination of Oracle's Sun Storage 7410 system with the Sun Blade X6275 M2 server module cluster showed linear scalability for the total application throughput, including the I/O and MPI communication, to produce a final 3-D seismic depth imaged cube for interpretation. The final image write time from the Sun Blade X6275 M2 server module nodes to Oracle's Sun Storage 7410 system achieved 10GbE line speed of 1.25 GBytes/second or better performance. Between subsequent runs, the effects of I/O buffer caching on the Sun Blade X6275 M2 server module nodes and write optimized caching on the Sun Storage 7410 system gave up to 1.8 GBytes/second effective write performance. The performance results and characterization of this Reverse Time Migration benchmark could serve as a useful measure for many other I/O intensive commercial applications. 3D VTI Reverse Time Migration Seismic Depth Imaging, see http://blogs.sun.com/BestPerf/entry/3d_vti_reverse_time_migration for more information, results as of 11/14/2010.                            

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  • Webcast: The ART of Migrating and Modernizing IBM Mainframe Applications

    - by todd.little
    Tuxedo provides an excellent platform to migrate mainframe applications to distributed systems. As the only distributed transaction processing monitor that offers quality of service comparable or better than mainframe systems, Tuxedo allows customers to migrate their existing mainframe based applications to a platform with a much lower total cost of ownership. Please join us on Thursday April 29 at 10:00am Pacific Time for this exciting webcast covering the new Oracle Tuxedo Application Runtime for CICS and Batch 11g. Find out how easy it is to migrate your CICS and mainframe batch applications to Tuxedo.

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  • How to repair an external harddrive?

    - by dodohjk
    I would like to reformat my hard disk, and if possible recover the (somewhat unimportant) contents if possible. I have a Western Digital 1TB hard drive which had a NTFS partition. I unplugged the drive without safely removing it first. At first a pop up was asking me to use a Windows OS to run the chkdsk /f command, however, in the effort to keep using a Linux OS I used the ntfsfix command on the ubuntu terminal Now, when I try to access the hard drive, it doesn't show up anymore in Nautilus. I tried reformatting it using Disk Utility, but it gives me an error message, and Gparted would hang on the "Scanning devices" step infinitely. Please comment any output that you would like to see and I will add it to my question. EDIT disk utility tells me is on /dev/sdb the command sudo fdisk -l gives dodohjk@DodosPC:~$ sudo fdisk -l [sudo] password for dodohjk: Disk /dev/sda: 250.1 GB, 250059350016 bytes 255 heads, 63 sectors/track, 30401 cylinders, total 488397168 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0x0006fa8c Device Boot Start End Blocks Id System /dev/sda1 * 4094 482344959 241170433 5 Extended /dev/sda2 482344960 488396799 3025920 82 Linux swap / Solaris /dev/sda5 4096 31461127 15728516 83 Linux /dev/sda6 31463424 52434943 10485760 83 Linux /dev/sda7 52436992 62923320 5243164+ 83 Linux /dev/sda8 62924800 482344959 209710080 83 Linux Disk /dev/sdb: 1000.2 GB, 1000202043392 bytes 255 heads, 63 sectors/track, 121600 cylinders, total 1953519616 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0x6e697373 This doesn't look like a partition table Probably you selected the wrong device. Device Boot Start End Blocks Id System /dev/sdb1 ? 1936269394 3772285809 918008208 4f QNX4.x 3rd part /dev/sdb2 ? 1917848077 2462285169 272218546+ 73 Unknown /dev/sdb3 ? 1818575915 2362751050 272087568 2b Unknown /dev/sdb4 ? 2844524554 2844579527 27487 61 SpeedStor Partition table entries are not in disk order I wrote something wrong here, however here the output of fsck /dev/sbd is dodohjk@DodosPC:~$ sudo fsck /dev/sdb fsck from util-linux 2.20.1 e2fsck 1.42.5 (29-Jul-2012) ext2fs_open2: Bad magic number in super-block fsck.ext2: Superblock invalid, trying backup blocks... fsck.ext2: Bad magic number in super-block while trying to open /dev/sdb The superblock could not be read or does not describe a correct ext2 filesystem. If the device is valid and it really contains an ext2 filesystem (and not swap or ufs or something else), then the superblock is corrupt, and you might try running e2fsck with an alternate superblock: e2fsck -b 8193 <device&gt;

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  • Some Benefits of Cash Registers

    A cash register is one of the devices that are used within a sales establishment and which are being operated by a sales clerk. This is usually used to calculate the total number of sale a customer w... [Author: Alan Wisdom - Computers and Internet - April 05, 2010]

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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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  • What's New with PeopleTools

    Michael Ni, Vice President of Product Strategy at Oracle, goes through with Cliff the PeopleTools Roadmap that was outlined at OOW, discusses what's in the latest release of PeopleTools and gives an overview of the new features that will be in the next few releases of PeopleTools. Michael also comments to Cliff about the next generation of applications, Fusion Architecture and the Total Ownership Experience (TOE) across the lifecycle of the applications.

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  • Create Ubuntu repository on CentOS server with debmirror

    - by Wilco Groothand
    I want to create a UBUNTU repo mirror on my CentOS reposerver. I read about it and came to the conclusion that for our purpose debmirror was the correct solution, because I then could mirror a subset of the total repository. The problem is that with debmirror I run into the gpg key errors. Already solved in Ubuntu, but the apt-key solutions are not valid within CentOS. The command does not exists. I am totally stuck.

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  • About Google Adwords Ads

    Google AdWords is the flagship advertising model of Google and also the driving force behind its revenue. The total advertising revenues that Google earns in every fiscal year is completely because o... [Author: John Anthony - Computers and Internet - May 03, 2010]

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  • Please recommend a good book on general IT for junior developer

    - by Rachel
    I have just got a job as a junior java developer and I am finding learning the code fine as I taught myself to pass the interview tests, trouble is I have a biology degree and know little about general IT and computer /network jargon. I don't want to be seen as a total idiot and non - techie so please can you recommend a book I can read / study to quickly increase my general background knowledge so that I can compete on a level with IT graduates!

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  • Laser Cutter Plays Portal Theme Song While Cutting Aperture Science Logo [Video]

    - by Jason Fitzpatrick
    We’re at a total loss to think of anything more geeky than a laser cutter programmed to simultaneously laser cut the Aperture Science logo while playing “Stile Alive” from Portal. If you’re unfamiliar with the original tune, check out this video. [via Boing Boing] The HTG Guide to Hiding Your Data in a TrueCrypt Hidden Volume Make Your Own Windows 8 Start Button with Zero Memory Usage Reader Request: How To Repair Blurry Photos

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  • Equal Gifts Algorithm Problem

    - by 7Aces
    Problem Link - http://opc.iarcs.org.in/index.php/problems/EQGIFTS It is Lavanya's birthday and several families have been invited for the birthday party. As is customary, all of them have brought gifts for Lavanya as well as her brother Nikhil. Since their friends are all of the erudite kind, everyone has brought a pair of books. Unfortunately, the gift givers did not clearly indicate which book in the pair is for Lavanya and which one is for Nikhil. Now it is up to their father to divide up these books between them. He has decided that from each of these pairs, one book will go to Lavanya and one to Nikhil. Moreover, since Nikhil is quite a keen observer of the value of gifts, the books have to be divided in such a manner that the total value of the books for Lavanya is as close as possible to total value of the books for Nikhil. Since Lavanya and Nikhil are kids, no book that has been gifted will have a value higher than 300 Rupees... For the problem, I couldn't think of anything except recursion. The code I wrote is given below. But the problem is that the code is time-inefficient and gives TLE (Time Limit Exceeded) for 9 out of 10 test cases! What would be a better approach to the problem? Code - #include<cstdio> #include<climits> #include<algorithm> using namespace std; int n,g[150][2]; int diff(int a,int b,int f) { ++f; if(f==n) { if(a>b) { return a-b; } else { return b-a; } } return min(diff(a+g[f][0],b+g[f][1],f),diff(a+g[f][1],b+g[f][0],f)); } int main() { int i; scanf("%d",&n); for(i=0;i<n;++i) { scanf("%d%d",&g[i][0],&g[i][1]); } printf("%d",diff(g[0][0],g[0][1],0)); } Note - It is just a practice question, & is not part of a competition.

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  • Indie Software Developers - How do I handle taxes?

    - by Connor
    I apologize if this is the wrong site to post on, perhaps someone could point me to the proper place if it is not. Hello, I am 17 years old and currently develop applications/games for Android and iPhone as well as develop internet websites and code a variety of my own projects. I have been very fortunate and have made a large amount of money and continue to make money online to the point where I do not need a stable job, though I'd like to get one after college. I've never held a job anywhere, and have never had to pay taxes. I'm coming into a lot of issues and I am quite confused. I get money from MANY sources- 15 different advertisement networks(!), 4 different payment processors, 5 different affiliate networks and a variety of other sources. All of them pay to different places and at different times (checking account, PayPal, reloadable debit card, ect.) I essentially have a list in a Notepad with names and login information for each source. I have also created a PHP script that uses cURL to grab all the revenue from each service, add it all up, then text me every few hours so I can keep track. It's a mess, but it's working OK, and I can create custom reports (for IRS?). But enough of that, my questions are about taxes in the US, and how indie developers handle it all. I'm at slightly over $250k so far this year, with negligible earnings last year. I have it all stockpiled in a bank account and haven't touched it, I'm a bit scared to. What do I file as? A sole proprietor, a business, just a regular person? How can I handle all of the different revenue sources? (AdSense, CJ, LinkShare) So far none of them have sent me any paperwork on taxes and I've read that I'm supposed to pay taxes quarterly? Do I need paperwork from EACH source to file? Or can I just say I got $x total and that'd be it? What percentage do you pay of total earnings? Average? Should I create an LLC? A corporation? Or stay as a developer? What would be the cheapest options? Could I go to jail? I haven't touched the money except a few dollars to help my parents pay the mortgage once. Any insight would be great. My parents have no idea what I should do, both have no forms of higher education and both have no high school diploma's. They just live day by day with simple jobs. I appreciate any help or experience with this.

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  • SCRIPT REFERENCE PROFILER TO GET JAVASCRIPT REFERENCE DETAILS

    Many of us came through a scenario like, you need the details of total JS files referred to a web page. It's not a matter if all JS are directly referring through physical file. But now a days for cache purose we are embedding JS to the assembly. In these situations how you will get the JS reference details? Here coming ScriptReferenceProfiler.

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  • Why no fortran standard library ?

    - by Stefano Borini
    To be a language focused on mathematics and scientific computing, I am always baffled by the total lack of useful mathematical routines in the Fortran standard library. One would expect it to be shipped at least with a routine to compute standard deviation and mean, but this is not the case. In particular with the introduction of Fortran 90 and the addition of modules (thus reducing namespace pollution), I don't see any reason why of this critical lack of services. I would like to hear your knowledge about why this is the case.

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  • Google Analytics - Showing multiple site stats at once

    - by John
    Is there a way in google analytics to add multiple sites to and show all the stats together? So like the graphs and total visits/unique hits all combined for all the sites added to the google analytics account? For example if I have: site1.com site2.com site3.com Under one google analytics account, is there a way in google analytics tool to merge them together so I can see a sum of all traffic in one report?

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  • Shopping Cart URL Structure

    - by Drew
    In regards to URL structure when it comes to guests and authenticated users, am I able to track traffic associated with both paths, but at the same time track total conversions going through the shopping cart? I have set up the following URL structure: Authenticated users follow this path: /cart /checkout /checkout-confirmation-ty Guests go like such: /cart /checkout-guest /checkout-confirmation-guest-ty can I track the authenticated and guest users separately? is this possible with Google Analytics?

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  • MySQL Enterprise Backup 3.8.2 - Overview

    - by Priya Jayakumar
      MySQL Enterprise Backup (MEB) is the ideal solution for backing up MySQL databases. MEB 3.8.2 is released in June 2013. MySQL Enterprise Backup 3.8.2 release’s main goal is to improve usability. With this release, users can know the progress of backup completed both in terms of size and as a percentage of the total. This release also offers options to be able to manage the behavior of MEB in case the space on the secondary storage is completely exhausted during backup. The progress indicator is a (short) string that indicates how far the execution of a time-consuming MEB command has progressed. It consists of one or more "meters" that measures the progress of the command. There are two options introduced to control the progress reporting function of mysqlbackup command (1) –show-progress (2) –progress-interval. The user can control the progress indicator by using “--show-progress” option in any of the MEB operations. This option instructs MEB to output periodically short reports on the progress of time-consuming commands. The argument of this option instructs where the output could be sent. For example it could be stderr, stdout, file, fifo and table. With the “--show-progress” option both the total size of the backup to be copied and the size that’s already copied will be shown. Along with this, the state of the operation for example data or meta-data being copied or tables being locked and other such operations will also be reported. This gives more clear information to the DBA on the progress of the backup that’s happening. Interval between progress report in seconds is controlled by “--progress-interval” option. For more information on this please refer progress-report-options. MEB can also be accessed through GUI from MySQL WorkBench’s next version. This can be used as the front end interface for MEB users to perform backup operations at the click of a button. This feature was highly requested by DBAs and will be very useful. Refer http://insidemysql.com/mysql-workbench-6-0-a-sneak-preview/ for WorkBench upcoming release info. Along with the progress report feature some of the important issues like below are also addressed in MEB 3.8.2. In MEB 3.8.2 a new command line option “--on-disk-full” is introduced to abort or warn the user when a backup process encounters a full disk condition. When no option is given, by default it would abort. A few issues related to “incremental-backup” are also addressed in this release. Please refer 3.8.2 documentation for more details. It would be good for MEB users to move to 3.8.2 to take incremental backups. Overall the added usability and the important defects fixed in this release makes MySQL Enterprise Backup 3.8.2 a promising release.  

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  • GuestPost: Announcing gmStudio V9.85 for VB6/ASP/COM re-engineering

    - by Eric Nelson
    Mark Juras of GreatMigrations.com kindly sent me an article on gmStudio which I have posted on my old VB focused goto100 site. gmStudio is a programmable VB6/ASP/COM re-engineering tool that enables an agile tool-assisted rewrite methodology and helps teams dramatically lower the total cost, risk, and disruption of ambitious migration projects without sacrificing quality, control, or time to market. You can find the rest of the article over on goto100. Figure 1: the gmStudio Main Form

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  • PowerPivot, Parent/Child and Unary Operators

    - by AlbertoFerrari
    Following my last post about parent/child hierarchies in PowerPivot, I worked a bit more to implement a very useful feature of Parent/Child hierarchies in SSAS which is obviously missing in PowerPivot, i.e. unary operators. A unary operator is simply the aggregation function that needs to be used to aggregate values of children over their parent. Unary operators are very useful in accountings where you might have incomes and expenses in the same hierarchy and, at the total level, you want to subtract...(read more)

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