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  • How come you cannot catch Code Contract exceptions?

    - by Finglas
    System.Diagnostics.Contracts.ContractException is not accessiable in my test project. Note this code is purely myself messing around with my shiney new copy of Visual Studio, but I'd like to know what I'm doing wrong. I'm using the professional edition of VS, therefore I do not have static checking. In order to still use code contracts (which I like) I figured the only way my method can work is to catch the exception that is thrown at runtime, but I'm not finding this possible. TestMethod [TestMethod, ExpectedException(typeof(System.Diagnostics.Contracts.ContractException))] public void returning_a_value_less_than_one_throws_exception() { var person = new Person(); person.Number(); } Method public int Number() { Contract.Ensures(Contract.Result<int>() >= 0); return -1; } Error Error 1 'System.Diagnostics.Contracts.ContractException' is inaccessible due to its protection level.

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  • Is there any explorer.exe problem in windows 7 ?

    - by sml
    s += "<p style=\"text-align: left;\"><a href=\"javascript:window.print()\">PRINT</a></p>"; System.IO.File.WriteAllText(@"CheckForm.html", s); System.Diagnostics.ProcessStartInfo startInfo = new System.Diagnostics.ProcessStartInfo(); startInfo.FileName = "explorer.exe"; startInfo.Arguments = "CheckForm.html"; System.Diagnostics.Process.Start(startInfo); I'm having a trouble when I tried to open my c# windows application in windows 7 otherwise there is no problem. I couldn't open explorer.exe in Windows 7 with above code. Any suggestions?

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  • Simple loop, which one I would get more performance and which one is recommended? defining a variable inside a loop or outside of it?

    - by Grego
    Variable outside of the loop int number = 0; for(int i = 0; i < 10000; i++){ number = 3 * i; printf("%d",number); } or Variable inside of the loop for(int i = 0; i < 10000; i++){ int number = 3 * i; printf("%d",number); } Which one is recommended and which one is better in performance? Edit: This is just an example to exhibit what I mean, All I wanna know is if defining a variable inside a loop and outside a loop means the same thing , or there's a difference.

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  • SQL SERVER – SSIS Look Up Component – Cache Mode – Notes from the Field #028

    - by Pinal Dave
    [Notes from Pinal]: Lots of people think that SSIS is all about arranging various operations together in one logical flow. Well, the understanding is absolutely correct, but the implementation of the same is not as easy as it seems. Similarly most of the people think lookup component is just component which does look up for additional information and does not pay much attention to it. Due to the same reason they do not pay attention to the same and eventually get very bad performance. Linchpin People are database coaches and wellness experts for a data driven world. In this 28th episode of the Notes from the Fields series database expert Tim Mitchell (partner at Linchpin People) shares very interesting conversation related to how to write a good lookup component with Cache Mode. In SQL Server Integration Services, the lookup component is one of the most frequently used tools for data validation and completion.  The lookup component is provided as a means to virtually join one set of data to another to validate and/or retrieve missing values.  Properly configured, it is reliable and reasonably fast. Among the many settings available on the lookup component, one of the most critical is the cache mode.  This selection will determine whether and how the distinct lookup values are cached during package execution.  It is critical to know how cache modes affect the result of the lookup and the performance of the package, as choosing the wrong setting can lead to poorly performing packages, and in some cases, incorrect results. Full Cache The full cache mode setting is the default cache mode selection in the SSIS lookup transformation.  Like the name implies, full cache mode will cause the lookup transformation to retrieve and store in SSIS cache the entire set of data from the specified lookup location.  As a result, the data flow in which the lookup transformation resides will not start processing any data buffers until all of the rows from the lookup query have been cached in SSIS. The most commonly used cache mode is the full cache setting, and for good reason.  The full cache setting has the most practical applications, and should be considered the go-to cache setting when dealing with an untested set of data. With a moderately sized set of reference data, a lookup transformation using full cache mode usually performs well.  Full cache mode does not require multiple round trips to the database, since the entire reference result set is cached prior to data flow execution. There are a few potential gotchas to be aware of when using full cache mode.  First, you can see some performance issues – memory pressure in particular – when using full cache mode against large sets of reference data.  If the table you use for the lookup is very large (either deep or wide, or perhaps both), there’s going to be a performance cost associated with retrieving and caching all of that data.  Also, keep in mind that when doing a lookup on character data, full cache mode will always do a case-sensitive (and in some cases, space-sensitive) string comparison even if your database is set to a case-insensitive collation.  This is because the in-memory lookup uses a .NET string comparison (which is case- and space-sensitive) as opposed to a database string comparison (which may be case sensitive, depending on collation).  There’s a relatively easy workaround in which you can use the UPPER() or LOWER() function in the pipeline data and the reference data to ensure that case differences do not impact the success of your lookup operation.  Again, neither of these present a reason to avoid full cache mode, but should be used to determine whether full cache mode should be used in a given situation. Full cache mode is ideally useful when one or all of the following conditions exist: The size of the reference data set is small to moderately sized The size of the pipeline data set (the data you are comparing to the lookup table) is large, is unknown at design time, or is unpredictable Each distinct key value(s) in the pipeline data set is expected to be found multiple times in that set of data Partial Cache When using the partial cache setting, lookup values will still be cached, but only as each distinct value is encountered in the data flow.  Initially, each distinct value will be retrieved individually from the specified source, and then cached.  To be clear, this is a row-by-row lookup for each distinct key value(s). This is a less frequently used cache setting because it addresses a narrower set of scenarios.  Because each distinct key value(s) combination requires a relational round trip to the lookup source, performance can be an issue, especially with a large pipeline data set to be compared to the lookup data set.  If you have, for example, a million records from your pipeline data source, you have the potential for doing a million lookup queries against your lookup data source (depending on the number of distinct values in the key column(s)).  Therefore, one has to be keenly aware of the expected row count and value distribution of the pipeline data to safely use partial cache mode. Using partial cache mode is ideally suited for the conditions below: The size of the data in the pipeline (more specifically, the number of distinct key column) is relatively small The size of the lookup data is too large to effectively store in cache The lookup source is well indexed to allow for fast retrieval of row-by-row values No Cache As you might guess, selecting no cache mode will not add any values to the lookup cache in SSIS.  As a result, every single row in the pipeline data set will require a query against the lookup source.  Since no data is cached, it is possible to save a small amount of overhead in SSIS memory in cases where key values are not reused.  In the real world, I don’t see a lot of use of the no cache setting, but I can imagine some edge cases where it might be useful. As such, it’s critical to know your data before choosing this option.  Obviously, performance will be an issue with anything other than small sets of data, as the no cache setting requires row-by-row processing of all of the data in the pipeline. I would recommend considering the no cache mode only when all of the below conditions are true: The reference data set is too large to reasonably be loaded into SSIS memory The pipeline data set is small and is not expected to grow There are expected to be very few or no duplicates of the key values(s) in the pipeline data set (i.e., there would be no benefit from caching these values) Conclusion The cache mode, an often-overlooked setting on the SSIS lookup component, represents an important design decision in your SSIS data flow.  Choosing the right lookup cache mode directly impacts the fidelity of your results and the performance of package execution.  Know how this selection impacts your ETL loads, and you’ll end up with more reliable, faster packages. If you want me to take a look at your server and its settings, or if your server is facing any issue we can Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: SSIS

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  • Benchmarking MySQL Replication with Multi-Threaded Slaves

    - by Mat Keep
    0 0 1 1145 6530 Homework 54 15 7660 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} The objective of this benchmark is to measure the performance improvement achieved when enabling the Multi-Threaded Slave enhancement delivered as a part MySQL 5.6. As the results demonstrate, Multi-Threaded Slaves delivers 5x higher replication performance based on a configuration with 10 databases/schemas. For real-world deployments, higher replication performance directly translates to: · Improved consistency of reads from slaves (i.e. reduced risk of reading "stale" data) · Reduced risk of data loss should the master fail before replicating all events in its binary log (binlog) The multi-threaded slave splits processing between worker threads based on schema, allowing updates to be applied in parallel, rather than sequentially. This delivers benefits to those workloads that isolate application data using databases - e.g. multi-tenant systems deployed in cloud environments. Multi-Threaded Slaves are just one of many enhancements to replication previewed as part of the MySQL 5.6 Development Release, which include: · Global Transaction Identifiers coupled with MySQL utilities for automatic failover / switchover and slave promotion · Crash Safe Slaves and Binlog · Optimized Row Based Replication · Replication Event Checksums · Time Delayed Replication These and many more are discussed in the “MySQL 5.6 Replication: Enabling the Next Generation of Web & Cloud Services” Developer Zone article  Back to the benchmark - details are as follows. Environment The test environment consisted of two Linux servers: · one running the replication master · one running the replication slave. Only the slave was involved in the actual measurements, and was based on the following configuration: - Hardware: Oracle Sun Fire X4170 M2 Server - CPU: 2 sockets, 6 cores with hyper-threading, 2930 MHz. - OS: 64-bit Oracle Enterprise Linux 6.1 - Memory: 48 GB Test Procedure Initial Setup: Two MySQL servers were started on two different hosts, configured as replication master and slave. 10 sysbench schemas were created, each with a single table: CREATE TABLE `sbtest` (    `id` int(10) unsigned NOT NULL AUTO_INCREMENT,    `k` int(10) unsigned NOT NULL DEFAULT '0',    `c` char(120) NOT NULL DEFAULT '',    `pad` char(60) NOT NULL DEFAULT '',    PRIMARY KEY (`id`),    KEY `k` (`k`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1 10,000 rows were inserted in each of the 10 tables, for a total of 100,000 rows. When the inserts had replicated to the slave, the slave threads were stopped. The slave data directory was copied to a backup location and the slave threads position in the master binlog noted. 10 sysbench clients, each configured with 10 threads, were spawned at the same time to generate a random schema load against each of the 10 schemas on the master. Each sysbench client executed 10,000 "update key" statements: UPDATE sbtest set k=k+1 WHERE id = <random row> In total, this generated 100,000 update statements to later replicate during the test itself. Test Methodology: The number of slave workers to test with was configured using: SET GLOBAL slave_parallel_workers=<workers> Then the slave IO thread was started and the test waited for all the update queries to be copied over to the relay log on the slave. The benchmark clock was started and then the slave SQL thread was started. The test waited for the slave SQL thread to finish executing the 100k update queries, doing "select master_pos_wait()". When master_pos_wait() returned, the benchmark clock was stopped and the duration calculated. The calculated duration from the benchmark clock should be close to the time it took for the SQL thread to execute the 100,000 update queries. The 100k queries divided by this duration gave the benchmark metric, reported as Queries Per Second (QPS). Test Reset: The test-reset cycle was implemented as follows: · the slave was stopped · the slave data directory replaced with the previous backup · the slave restarted with the slave threads replication pointer repositioned to the point before the update queries in the binlog. The test could then be repeated with identical set of queries but a different number of slave worker threads, enabling a fair comparison. The Test-Reset cycle was repeated 3 times for 0-24 number of workers and the QPS metric calculated and averaged for each worker count. MySQL Configuration The relevant configuration settings used for MySQL are as follows: binlog-format=STATEMENT relay-log-info-repository=TABLE master-info-repository=TABLE As described in the test procedure, the slave_parallel_workers setting was modified as part of the test logic. The consequence of changing this setting is: 0 worker threads:    - current (i.e. single threaded) sequential mode    - 1 x IO thread and 1 x SQL thread    - SQL thread both reads and executes the events 1 worker thread:    - sequential mode    - 1 x IO thread, 1 x Coordinator SQL thread and 1 x Worker thread    - coordinator reads the event and hands it to the worker who executes 2+ worker threads:    - parallel execution    - 1 x IO thread, 1 x Coordinator SQL thread and 2+ Worker threads    - coordinator reads events and hands them to the workers who execute them Results Figure 1 below shows that Multi-Threaded Slaves deliver ~5x higher replication performance when configured with 10 worker threads, with the load evenly distributed across our 10 x schemas. This result is compared to the current replication implementation which is based on a single SQL thread only (i.e. zero worker threads). Figure 1: 5x Higher Performance with Multi-Threaded Slaves The following figure shows more detailed results, with QPS sampled and reported as the worker threads are incremented. The raw numbers behind this graph are reported in the Appendix section of this post. Figure 2: Detailed Results As the results above show, the configuration does not scale noticably from 5 to 9 worker threads. When configured with 10 worker threads however, scalability increases significantly. The conclusion therefore is that it is desirable to configure the same number of worker threads as schemas. Other conclusions from the results: · Running with 1 worker compared to zero workers just introduces overhead without the benefit of parallel execution. · As expected, having more workers than schemas adds no visible benefit. Aside from what is shown in the results above, testing also demonstrated that the following settings had a very positive effect on slave performance: relay-log-info-repository=TABLE master-info-repository=TABLE For 5+ workers, it was up to 2.3 times as fast to run with TABLE compared to FILE. Conclusion As the results demonstrate, Multi-Threaded Slaves deliver significant performance increases to MySQL replication when handling multiple schemas. This, and the other replication enhancements introduced in MySQL 5.6 are fully available for you to download and evaluate now from the MySQL Developer site (select Development Release tab). You can learn more about MySQL 5.6 from the documentation  Please don’t hesitate to comment on this or other replication blogs with feedback and questions. Appendix – Detailed Results

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  • Benchmarking Linux flash player and google chrome built in flash player

    - by Fischer
    I use xubuntu 14.04 64 bit, I installed flash player from software center and xubuntu-restricted-extras too Are there any benchmarks on Linux flash player and google chrome built in flash player? I just want to see their performance because in theory google's flash player should be more updated and have better performance than the one we use in Firefox. (that's what I read everywhere) I have chrome latest version installed and Firefox next, and I found that flash videos in Chrome are laggy and they take long time to load. While the same flash videos load much faster in Firefox and I tend to prefer watching flash videos in firefox, especially the long ones because it loads them so much faster. I can't believe these results on my PC, so is there any way to benchmark flash players performance on both browsers? I want to know if it's because of the flash player or the browsers or something else

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  • Convert Excel File 'xls' to CSV, CAUTION: Bumps Ahead

    - by faizanahmad
    The task was to provide users with an interface where they can upload the 'csv' files, these files were to be processed and loaded to Database by a Console application. The code in Console application could not handle the 'xls' files so we thought, OK, lets convert 'xls' to 'csv' in the code, Seemed like fun. The idea was to convert it right after uploading within 'csv' file. As Microsoft does not recommend using the  Excel objects in ASP.NET, we decided to use the Jet engine to open xls. (Ace driver is used for xlsx) The code was pretty straight, can be found on following links: http://www.c-sharpcorner.com/uploadfile/yuanwang200409/102242008174401pm/1.aspx http://www.devasp.net/net/articles/display/141.html FIRST BUMP 'OleDbException (0x80004005): Unspecified error' ( Impersonation ): The ablove code ran fine in my test web site and test console application, but it gave an 'OleDbException (0x80004005): Unspecified error' in main web site, turns out imperonation was set to True and as soon as I changed it to False, it did work. on My XP box, web site was running under user                   'ASPNET'  with imperosnation set to FALSE                   'IUSR_*' i.e IIS guest user with impersonation set to TRUE The weired part was that both users had same rights on the folders I was saving files to and on Excel app in DCOM Config.  We decided to give it a try on Windows Server 2003 with web site set to windows authentication ( impersonation = true ) and yes it did work. SECOND BUMP 'External table not in correct format': I got this error with some files and it appeared that the file from client has some metadata issues  ( when I opened the file in Excel and try to save it ,excel  would give me this error saying File can not be saved in current format ) and the error was caused by that. Some people were able to reslove the error by using "Extended Properties=HTML Import;" in connection string. But it did not work for me. We decided to detour from here and use Excel object :( as we had no control on client setting the meta deta of Excel files. Before third bump there were a ouple of small thingies like 'Retrieving the COM class factory for component with CLSID {00024500-0000-0000-C000-000000000046} failed due to the following error: 80070005' Fix can be found at http://blog.crowe.co.nz/archive/2006/03/02/589.aspx THIRD BUMP ( Could not get rid of the EXCEL process  ):  I has all the code in place to 'Quiet' the excel, but, it just did not work. work around was done to Kill the process as we knew no other application on server was using EXCEL.  The normal steps to quite the excel application worked just fine in console application though.   FOURTH BUMP: Code worked with one file 1 on my machine and with the other file 2 code will break. and the same code will work perfectly fine with file 2 on some other machine . We moved it to QA  ( Windows Server 2003 )and worked with every file just perfect. But , then there was another problem: one user can upload it and second cant, permissions on folder and DCOM Conifg checked. Another Detour: Uplooad the xls as it is and convert in Console application.   Lesson Learnt:  If its 'xlsx' use 'ACE Driver' or read xml within excel as recommneded by MS. If xls and you know its always going to be properly formatted  'jet Engine'  Code: Imports Microsoft.Office.Interop Private Function ConvertFile(ByVal SourceFolder As String, ByVal FileName As String, ByVal FileExtension As String)As Boolean     Dim appExcel As New Excel.Application     Dim workBooks As Excel.Workbooks = appExcel.Workbooks     Dim objWorkbook As Excel.Workbook      Try                   objWorkbook = workBooks.Open(CompleteFilePath )                            objWorkbook.SaveAs(Filename:=CObj(SourceFolder & FileName & ".csv"), FileFormat:=Excel.XlFileFormat.xlCSV)       Catch ex As Exception         GenerateAlert(ex.Message().Replace("'", "") & " Error Converting File to CSV.")         LogError(ex )         Return False      Finally                      If Not(objWorkbook is Nothing) then               objWorkbook.Close(SaveChanges:=CObj(False))           End If           ReleaseObj(objWorkbook)                                      ReleaseObj(workBooks)           appExcel.Quit()           ReleaseObj(appExcel)                                 Dim proc As System.Diagnostics.Process           For Each proc In System.Diagnostics.Process.GetProcessesByName("EXCEL")               proc.Kill()           Next         DeleteSourceFile(SourceFolder & FileName & FileExtension)     End Try  Return True  End Function   Private Sub ReleaseObj(ByVal o As Object)     Try      System.Runtime.InteropServices.Marshal.ReleaseComObject(o)   Catch ex As Exception           LogError(ex )   Finally      o = Nothing    End Try End Sub     Protected Sub DeleteSourceFile(Byval CompleteFilePath As string)         Try             Dim MyFile As FileInfo = New FileInfo(CompleteFilePath)             If  MyFile.Exists Then                 File.Delete(CompleteFilePath)             Else              Throw New FileNotFoundException()             End If         Catch ex As Exception             GenerateAlert( " Source File could not be deleted.")              LogError(ex)         End Try     End Sub  The code to kill the process ( Avoid it if you can ): Dim proc As System.Diagnostics.Process For Each proc In System.Diagnostics.Process.GetProcessesByName("EXCEL")     proc.Kill() Next

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  • Mark Hurd and Balaji Yelamanchili present Oracle’s Business Analytics Strategy

    - by Mike.Hallett(at)Oracle-BI&EPM
    Join Mark Hurd and Balaji Yelamanchili as they unveil the latest advances in Oracle’s strategy for placing analytics into the hands of every decision-makers—so that they can see more, think smarter, and act faster. Wednesday, April 4, 2012   at 1.0 pm UK BST / 2.0 pm CET Register HERE today for this online event Agenda Keynote: Oracle’s Business Analytics StrategyMark Hurd, President, Oracle, and Balaji Yelamanchili, Senior Vice President, Analytics and Performance Management, Oracle Plus Breakout Sessions: Achieving Predictable Performance with Oracle Hyperion Enterprise Performance Managemen Explore All Relevant Data—Introducing Oracle Endeca Information Discovery Run Your Business Faster and Smarter with Oracle Business Intelligence Applications on Oracle Exalytics In-Memory Machine Analyzing and Deciding with Big Data

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  • BizTalk Server 2009 - Architecture Options

    - by StuartBrierley
    I recently needed to put forward a proposal for a BizTalk 2009 implementation and as a part of this needed to describe some of the basic architecture options available for consideration.  While I already had an idea of the type of environment that I would be looking to recommend, I felt that presenting a range of options while trying to explain some of the strengths and weaknesses of those options was a good place to start.  These outline architecture options should be equally valid for any version of BizTalk Server from 2004, through 2006 and R2, up to 2009.   The following diagram shows a crude representation of the common implementation options to consider when designing a BizTalk environment.         Each of these options provides differing levels of resilience in the case of failure or disaster, with the later options also providing more scope for performance tuning and scalability.   Some of the options presented above make use of clustering. Clustering may best be described as a technology that automatically allows one physical server to take over the tasks and responsibilities of another physical server that has failed. Given that all computer hardware and software will eventually fail, the goal of clustering is to ensure that mission-critical applications will have little or no downtime when such a failure occurs. Clustering can also be configured to provide load balancing, which should generally lead to performance gains and increased capacity and throughput.   (A) Single Servers   This option is the most basic BizTalk implementation that should be considered. It involves the deployment of a single BizTalk server in conjunction with a single SQL server. This configuration does not provide for any resilience in the case of the failure of either server. It is however the cheapest and easiest to implement option of those available.   Using a single BizTalk server does not provide for the level of performance tuning that is otherwise available when using more than one BizTalk server in a cluster.   The common edition of BizTalk used in single server implementations is the standard edition. It should be noted however that if future demand requires increased capacity for a solution, this BizTalk edition is limited to scaling up the implementation and not scaling out the number of servers in use. Any need to scale out the solution would require an upgrade to the enterprise edition of BizTalk.   (B) Single BizTalk Server with Clustered SQL Servers   This option uses a single BizTalk server with a cluster of SQL servers. By utilising clustered SQL servers we can ensure that there is some resilience to the implementation in respect of the databases that BizTalk relies on to operate. The clustering of two SQL servers is possible with the standard edition but to go beyond this would require the enterprise level edition. While this option offers improved resilience over option (A) it does still present a potential single point of failure at the BizTalk server.   Using a single BizTalk server does not provide for the level of performance tuning that is otherwise available when using more than one BizTalk server in a cluster.   The common edition of BizTalk used in single server implementations is the standard edition. It should be noted however that if future demand requires increased capacity for a solution, this BizTalk edition is limited to scaling up the implementation and not scaling out the number of servers in use. You are also unable to take advantage of multiple message boxes, which would allow us to balance the SQL load in the event of any bottlenecks in this area of the implementation. Any need to scale out the solution would require an upgrade to the enterprise edition of BizTalk.   (C) Clustered BizTalk Servers with Clustered SQL Servers   This option makes use of a cluster of BizTalk servers with a cluster of SQL servers to offer high availability and resilience in the case of failure of either of the server types involved. Clustering of BizTalk is only available with the enterprise edition of the product. Clustering of two SQL servers is possible with the standard edition but to go beyond this would require the enterprise level edition.    The use of a BizTalk cluster also provides for the ability to balance load across the servers and gives more scope for performance tuning any implemented solutions. It is also possible to add more BizTalk servers to an existing cluster, giving scope for scaling out the solution as future demand requires.   This might be seen as the middle cost option, providing a good level of protection in the case of failure, a decent level of future proofing, but at a higher cost than the single BizTalk server implementations.   (D) Clustered BizTalk Servers with Clustered SQL Servers – with disaster recovery/service continuity   This option is similar to that offered by (C) and makes use of a cluster of BizTalk servers with a cluster of SQL servers to offer high availability and resilience in case of failure of either of the server types involved. Clustering of BizTalk is only available with the enterprise edition of the product. Clustering of two SQL servers is possible with the standard edition but to go beyond this would require the enterprise level edition.    As with (C) the use of a BizTalk cluster also provides for the ability to balance load across the servers and gives more scope for performance tuning the implemented solution. It is also possible to add more BizTalk servers to an existing cluster, giving scope for scaling the solution out as future demand requires.   In this scenario however, we would be including some form of disaster recovery or service continuity. An example of this would be making use of multiple sites, with the BizTalk server cluster operating across sites to offer resilience in case of the loss of one or more sites. In this scenario there are options available for the SQL implementation depending on the network implementation; making use of either one cluster per site or a single SQL cluster across the network. A multi-site SQL implementation would require some form of data replication across the sites involved.   This is obviously an expensive and complex option, but does provide an extraordinary amount of protection in the case of failure.

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  • How can Swift be so much faster than Objective-C in these comparisons?

    - by Yellow
    Apple launched its new programming language Swift at WWDC14. In the presentation, they made some performance comparisons between Objective-C and Python. The following is a picture of one of their slides, of a comparison of those three languages performing some complex object sort: There was an even more incredible graph about a performance comparison using the RC4 encryption algorithm. Obviously this is a marketing talk, and they didn't go into detail on how this was implemented in each. I leaves me wondering though: How can a new programming language be so much faster? Are the Objective-C results caused by a bad compiler or is there something less efficient in Objective-C than Swift? How would you explain a 40% performance increase? I understand that garbage collection/automated reference control might produce some additional overhead, but this much?

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  • EntLib for Windows Azure

    - by kaleidoscope
    Enterprise Library popularly known as EntLib is a collection of Application Blocks targeted at managing oft needed redundant tasks in enterprise development, like Logging, Caching, Validation, Cryptography etc. Entlib currently exposes 9 application blocks: Caching Application Block Cryptography Application Block Data Access Application Block Exception Handling Application Block Logging Application Block Policy Injection Application Block Security Application Block Validation Application Block Unity Dependency Injection and Interception Mechanism Ever since the Honeymoon period of PoCs and tryouts is over and Azure started to mainstream and more precisely started to go “Enterprise”, Azure developers have been demanding EntLib for Azure. The demands seems to have finally been heard and the powers that be have bestowed us with the current beta release EntLib 5.0 which supports Windows Azure. The application blocks tailored for Azure are: Data Access Application Block (Think SQL Azure) Exception Handling Application Block (Windows Azure Diagnostics) Logging Application Block (Windows Azure Diagnostics) Validation Application Block Unity Dependency Injection Mechanism The EntLib 5.0 beta is now available for download. Technorati Tags: Sarang,EntLib,Azure

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  • Running Jetty under Windows Azure Using RoleEntryPoint in a Worker Role

    - by Shawn Cicoria
    This post is built upon the work of Mario Kosmiskas and David C. Chou’s prior postings – from here: http://blogs.msdn.com/b/mariok/archive/2011/01/05/deploying-java-applications-in-azure.aspx  http://blogs.msdn.com/b/dachou/archive/2010/03/21/run-java-with-jetty-in-windows-azure.aspx As Mario points out in his post, when you need to have more control over the process that starts, it generally is better left to a RoleEntryPoint capability that as of now, requires the use of a CLR based assembly that is deployed as part of the package to Azure. There were things I liked especially about Mario’s post – specifically, the ability to pull down the JRE and Jetty runtimes at role startup and instantiate the process using the extracted bits.  The way Mario initialized the java process (and Jetty) was to take advantage of a role startup task configured as part of the service definition.  This is a great quick way to kick off processes or tasks prior to your role entry point.  However, if you need access to service configuration values or role events, that’s where RoleEntryPoint comes in.  For this PoC sample I moved the logic for retrieving the bits for the jre and jetty to the worker roles OnStart – in addition to moving the process kickoff to the OnStart method.  The Run method at this point is there to loop and just report the status of the java process. Beyond just making things more parameterized, both Mario’s and David’s articles still form the essence of the approach. The solution that accompanies this post provides all the necessary .NET based Visual Studio project.  In addition, you’ll need: 1. Jetty 7 runtime http://www.eclipse.org/jetty/downloads.php 2. JRE http://www.oracle.com/technetwork/java/javase/downloads/index.html Once you have these the first step is to create archives (zips) of the distributions.  For this PoC, the structure of the archive requires that the root of the archive looks as follows: JRE6.zip jetty---.zip Upload the contents to a storage container (block blob), and for this example I used /archives as the location.  The service configuration has several settings that allow, which is the advantage of using RoleEntryPoint, the ability to provide these things via native configuration support from Azure in a worker role. Storage Explorer You can use development storage for testing this out – the zipped version of the solution is configured for development storage.  When you’re ready to deploy, you update the two settings – 1 for diagnostics and the other for the storage container where the /archives are going to be stored. <?xml version="1.0" encoding="utf-8"?> <ServiceConfiguration serviceName="HostedJetty" osFamily="2" osVersion="*"> <Role name="JettyWorker"> <Instances count="1" /> <ConfigurationSettings> <!--<Setting name="Microsoft.WindowsAzure.Plugins.Diagnostics.ConnectionString" value="DefaultEndpointsProtocol=https;AccountName=<accountName>;AccountKey=<accountKey>" />--> <Setting name="Microsoft.WindowsAzure.Plugins.Diagnostics.ConnectionString" value="UseDevelopmentStorage=true" /> <Setting name="JettyArchive" value="jetty-distribution-7.3.0.v20110203b.zip" /> <Setting name="StartRole" value="true" /> <Setting name="BlobContainer" value="archives" /> <Setting name="JreArchive" value="jre6.zip" /> <!--<Setting name="StorageCredentials" value="DefaultEndpointsProtocol=https;AccountName=<accountName>;AccountKey=<accountKey>"/>--> <Setting name="StorageCredentials" value="UseDevelopmentStorage=true" />   For interacting with Storage you can use several tools – one tool that I like is from the Windows Azure CAT team located here: http://appfabriccat.com/2011/02/exploring-windows-azure-storage-apis-by-building-a-storage-explorer-application/  and shown in the prior picture At runtime, during role initialization and startup, Azure will call into your RoleEntryPoint.  At that time the code will do a dynamic pull of the 2 archives and extract – using the Sharp Zip Lib <link> as Mario had demonstrated in his sample.  The only different here is the use of CLR code vs. PowerShell (which is really CLR, but that’s another discussion). At this point, once the 2 zips are extracted, the Role’s file system looks as follows: Worker Role approot From there, the OnStart method (which also does the download and unzip using a simple StorageHelper class) kicks off the Java path and now you have Java! Task Manager Jetty Sample Page A couple of things I’m working on to enhance this is to extract the jre and jetty bits not to the appRoot but to a resource location defined as part of the service definition. ServiceDefinition.csdef <?xml version="1.0" encoding="utf-8"?> <ServiceDefinition name="HostedJetty" xmlns="http://schemas.microsoft.com/ServiceHosting/2008/10/ServiceDefinition"> <WorkerRole name="JettyWorker"> <Imports> <Import moduleName="Diagnostics" /> <Import moduleName="RemoteAccess" /> <Import moduleName="RemoteForwarder" /> </Imports> <Endpoints> <InputEndpoint name="JettyPort" protocol="tcp" port="80" localPort="8080" /> </Endpoints> <LocalResources> <LocalStorage name="Archives" cleanOnRoleRecycle="false" sizeInMB="100" /> </LocalResources>   As the concept matures a bit, being able to update dynamically the content or jar files as part of a running java solution is something that is possible through continued enhancement of this simple model. The Visual Studio 2010 Solution is located here: HostingJavaSln_NDA.zip

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  • GDC 2012: From Console to Chrome

    GDC 2012: From Console to Chrome (Pre-recorded GDC content) Cutting-edge HTML5 brings high performance console-style 3d games to the browser, but developing a modern HTML5 game engine can be a challenge. Adapting to HTML5 and Javascript can be bewildering to game programmers coming from C / C++. This talk is an overview of the tools, techniques, and topics you need to be familiar with to adapt to programming high performance 3D games for the web. Topics will include cutting edge HTML5 APIs, writing high performance Javascript, and profiling / debugging tools. Speaker: Lilli Thompson From: GoogleDevelopers Views: 3845 80 ratings Time: 01:02:14 More in Science & Technology

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  • Links from UK TechDays 2010 sessions on Entity Framework, Parallel Programming and Azure

    - by Eric Nelson
    [I will do some longer posts around my sessions when I get back from holiday next week] Big thanks to all those who attended my 3 sessions at TechDays this week (April 13th and 14th, 2010). I really enjoyed both days and watched some great session – my personal fave being the Silverlight/Expression session by my friend and colleague Mike Taulty. The following links should help get you up and running on each of the technologies. Entity Framework 4 Entity Framework 4 Resources http://bit.ly/ef4resources Entity Framework Team Blog http://blogs.msdn.com/adonet Entity Framework Design Blog http://blogs.msdn.com/efdesign/ Parallel Programming Parallel Computing Developer Center http://msdn.com/concurrency Code samples http://code.msdn.microsoft.com/ParExtSamples Managed Team Blog http://blogs.msdn.com/pfxteam Tools Team Blog http://blogs.msdn.com/visualizeparallel My code samples http://gist.github.com/364522  And PDC 2009 session recordings to watch: Windows Azure Platform UK Site http://bit.ly/landazure UK Community http://bit.ly/ukazure (http://ukazure.ning.com ) Feedback www.mygreatwindowsazureidea.com Azure Diagnostics Manager - A client for Windows Azure Diagnostics Cloud Storage Studio - A client for Windows Azure Storage SQL Azure Migration Wizard http://sqlazuremw.codeplex.com

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  • IBM "per core" comparisons for SPECjEnterprise2010

    - by jhenning
    I recently stumbled upon a blog entry from Roman Kharkovski (an IBM employee) comparing some SPECjEnterprise2010 results for IBM vs. Oracle. Mr. Kharkovski's blog claims that SPARC delivers half the transactions per core vs. POWER7. Prior to any argument, I should say that my predisposition is to like Mr. Kharkovski, because he says that his blog is intended to be factual; that the intent is to try to avoid marketing hype and FUD tactic; and mostly because he features a picture of himself wearing a bike helmet (me too). Therefore, in a spirit of technical argument, rather than FUD fight, there are a few areas in his comparison that should be discussed. Scaling is not free For any benchmark, if a small system scores 13k using quantity R1 of some resource, and a big system scores 57k using quantity R2 of that resource, then, sure, it's tempting to divide: is  13k/R1 > 57k/R2 ? It is tempting, but not necessarily educational. The problem is that scaling is not free. Building big systems is harder than building small systems. Scoring  13k/R1  on a little system provides no guarantee whatsoever that one can sustain that ratio when attempting to handle more than 4 times as many users. Choosing the denominator radically changes the picture When ratios are used, one can vastly manipulate appearances by the choice of denominator. In this case, lots of choices are available for the resource to be compared (R1 and R2 above). IBM chooses to put cores in the denominator. Mr. Kharkovski provides some reasons for that choice in his blog entry. And yet, it should be noted that the very concept of a core is: arbitrary: not necessarily comparable across vendors; fluid: modern chips shift chip resources in response to load; and invisible: unless you have a microscope, you can't see it. By contrast, one can actually see processor chips with the naked eye, and they are a bit easier to count. If we put chips in the denominator instead of cores, we get: 13161.07 EjOPS / 4 chips = 3290 EjOPS per chip for IBM vs 57422.17 EjOPS / 16 chips = 3588 EjOPS per chip for Oracle The choice of denominator makes all the difference in the appearance. Speaking for myself, dividing by chips just seems to make more sense, because: I can see chips and count them; and I can accurately compare the number of chips in my system to the count in some other vendor's system; and Tthe probability of being able to continue to accurately count them over the next 10 years of microprocessor development seems higher than the probability of being able to accurately and comparably count "cores". SPEC Fair use requirements Speaking as an individual, not speaking for SPEC and not speaking for my employer, I wonder whether Mr. Kharkovski's blog article, taken as a whole, meets the requirements of the SPEC Fair Use rule www.spec.org/fairuse.html section I.D.2. For example, Mr. Kharkovski's footnote (1) begins Results from http://www.spec.org as of 04/04/2013 Oracle SUN SPARC T5-8 449 EjOPS/core SPECjEnterprise2010 (Oracle's WLS best SPECjEnterprise2010 EjOPS/core result on SPARC). IBM Power730 823 EjOPS/core (World Record SPECjEnterprise2010 EJOPS/core result) The questionable tactic, from a Fair Use point of view, is that there is no such metric at the designated location. At www.spec.org, You can find the SPEC metric 57422.17 SPECjEnterprise2010 EjOPS for Oracle and You can also find the SPEC metric 13161.07 SPECjEnterprise2010 EjOPS for IBM. Despite the implication of the footnote, you will not find any mention of 449 nor anything that says 823. SPEC says that you can, under its fair use rule, derive your own values; but it emphasizes: "The context must not give the appearance that SPEC has created or endorsed the derived value." Substantiation and transparency Although SPEC disclaims responsibility for non-SPEC information (section I.E), it says that non-SPEC data and methods should be accurate, should be explained, should be substantiated. Unfortunately, it is difficult or impossible for the reader to independently verify the pricing: Were like units compared to like (e.g. list price to list price)? Were all components (hw, sw, support) included? Were all fees included? Note that when tpc.org shows IBM pricing, there are often items such as "PROCESSOR ACTIVATION" and "MEMORY ACTIVATION". Without the transparency of a detailed breakdown, the pricing claims are questionable. T5 claim for "Fastest Processor" Mr. Kharkovski several times questions Oracle's claim for fastest processor, writing You see, when you publish industry benchmarks, people may actually compare your results to other vendor's results. Well, as we performance people always say, "it depends". If you believe in performance-per-core as the primary way of looking at the world, then yes, the POWER7+ is impressive, spending its chip resources to support up to 32 threads (8 cores x 4 threads). Or, it just might be useful to consider performance-per-chip. Each SPARC T5 chip allows 128 hardware threads to be simultaneously executing (16 cores x 8 threads). The Industry Standard Benchmark that focuses specifically on processor chip performance is SPEC CPU2006. For this very well known and popular benchmark, SPARC T5: provides better performance than both POWER7 and POWER7+, for 1 chip vs. 1 chip, for 8 chip vs. 8 chip, for integer (SPECint_rate2006) and floating point (SPECfp_rate2006), for Peak tuning and for Base tuning. For example, at the 8-chip level, integer throughput (SPECint_rate2006) is: 3750 for SPARC 2170 for POWER7+. You can find the details at the March 2013 BestPerf CPU2006 page SPEC is a trademark of the Standard Performance Evaluation Corporation, www.spec.org. The two specific results quoted for SPECjEnterprise2010 are posted at the URLs linked from the discussion. Results for SPEC CPU2006 were verified at spec.org 1 July 2013, and can be rechecked here.

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  • SPARC T4-4 Delivers World Record First Result on PeopleSoft Combined Benchmark

    - by Brian
    Oracle's SPARC T4-4 servers running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved World Record 18,000 concurrent users while executing a PeopleSoft Payroll batch job of 500,000 employees in 43.32 minutes and maintaining online users response time at < 2 seconds. This world record is the first to run online and batch workloads concurrently. 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 35% (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. This is the first three tier mixed workload (online and batch) PeopleSoft benchmark also processing PeopleSoft payroll batch workload. Performance Landscape PeopleSoft HR 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 T4-2 (db) 18,000 0.944 0.503 43.32 64 Configuration Summary Application Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 512 GB memory 5 x 300 GB SAS internal disks 1 x 100 GB and 2 x 300 GB internal SSDs 2 x 10 Gbe HBA 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 3 x 300 GB SAS internal disks Oracle Solaris 11 11/11 Oracle Database 11g Release 2 Web Tier Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 2 x 300 GB SAS internal disks 1 x 100 GB internal SSD 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 Oracle 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. 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 Management oracle.com OTN PeopleSoft Enterprise Human Capital Management (Payroll) oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Oracle's PeopleSoft HR and Payroll combined benchmark, www.oracle.com/us/solutions/benchmark/apps-benchmark/peoplesoft-167486.html, results 09/30/2012.

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  • NoSQL Java API for MySQL Cluster: Questions & Answers

    - by Mat Keep
    The MySQL Cluster engineering team recently ran a live webinar, available now on-demand demonstrating the ClusterJ and ClusterJPA NoSQL APIs for MySQL Cluster, and how these can be used in building real-time, high scale Java-based services that require continuous availability. Attendees asked a number of great questions during the webinar, and I thought it would be useful to share those here, so others are also able to learn more about the Java NoSQL APIs. First, a little bit about why we developed these APIs and why they are interesting to Java developers. ClusterJ and Cluster JPA ClusterJ is a Java interface to MySQL Cluster that provides either a static or dynamic domain object model, similar to the data model used by JDO, JPA, and Hibernate. A simple API gives users extremely high performance for common operations: insert, delete, update, and query. ClusterJPA works with ClusterJ to extend functionality, including - Persistent classes - Relationships - Joins in queries - Lazy loading - Table and index creation from object model By eliminating data transformations via SQL, users get lower data access latency and higher throughput. In addition, Java developers have a more natural programming method to directly manage their data, with a complete, feature-rich solution for Object/Relational Mapping. As a result, the development of Java applications is simplified with faster development cycles resulting in accelerated time to market for new services. MySQL Cluster offers multiple NoSQL APIs alongside Java: - Memcached for a persistent, high performance, write-scalable Key/Value store, - HTTP/REST via an Apache module - C++ via the NDB API for the lowest absolute latency. Developers can use SQL as well as NoSQL APIs for access to the same data set via multiple query patterns – from simple Primary Key lookups or inserts to complex cross-shard JOINs using Adaptive Query Localization Marrying NoSQL and SQL access to an ACID-compliant database offers developers a number of benefits. MySQL Cluster’s distributed, shared-nothing architecture with auto-sharding and real time performance makes it a great fit for workloads requiring high volume OLTP. Users also get the added flexibility of being able to run real-time analytics across the same OLTP data set for real-time business insight. OK – hopefully you now have a better idea of why ClusterJ and JPA are available. Now, for the Q&A. Q & A Q. Why would I use Connector/J vs. ClusterJ? A. Partly it's a question of whether you prefer to work with SQL (Connector/J) or objects (ClusterJ). Performance of ClusterJ will be better as there is no need to pass through the MySQL Server. A ClusterJ operation can only act on a single table (e.g. no joins) - ClusterJPA extends that capability Q. Can I mix different APIs (ie ClusterJ, Connector/J) in our application for different query types? A. Yes. You can mix and match all of the API types, SQL, JDBC, ODBC, ClusterJ, Memcached, REST, C++. They all access the exact same data in the data nodes. Update through one API and new data is instantly visible to all of the others. Q. How many TCP connections would a SessionFactory instance create for a cluster of 8 data nodes? A. SessionFactory has a connection to the mgmd (management node) but otherwise is just a vehicle to create Sessions. Without using connection pooling, a SessionFactory will have one connection open with each data node. Using optional connection pooling allows multiple connections from the SessionFactory to increase throughput. Q. Can you give details of how Cluster J optimizes sharding to enhance performance of distributed query processing? A. Each data node in a cluster runs a Transaction Coordinator (TC), which begins and ends the transaction, but also serves as a resource to operate on the result rows. While an API node (such as a ClusterJ process) can send queries to any TC/data node, there are performance gains if the TC is where most of the result data is stored. ClusterJ computes the shard (partition) key to choose the data node where the row resides as the TC. Q. What happens if we perform two primary key lookups within the same transaction? Are they sent to the data node in one transaction? A. ClusterJ will send identical PK lookups to the same data node. Q. How is distributed query processing handled by MySQL Cluster ? A. If the data is split between data nodes then all of the information will be transparently combined and passed back to the application. The session will connect to a data node - typically by hashing the primary key - which then interacts with its neighboring nodes to collect the data needed to fulfil the query. Q. Can I use Foreign Keys with MySQL Cluster A. Support for Foreign Keys is included in the MySQL Cluster 7.3 Early Access release Summary The NoSQL Java APIs are packaged with MySQL Cluster, available for download here so feel free to take them for a spin today! Key Resources MySQL Cluster on-line demo  MySQL ClusterJ and JPA On-demand webinar  MySQL ClusterJ and JPA documentation MySQL ClusterJ and JPA whitepaper and tutorial

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  • Implementing Oracle Exadata for Oracle Utilities Customer Care And Billing

    - by ACShorten
    In association with our performance team, a new whitepaper has been released for Oracle Utilities Customer Care And Billing that outlines the best practices for using Oracle Exadata with that product. The advice in the whitepaper is based upon certification and performance testing performed by our internal performance teams to assit in sites implementing the database component of Oracle Utilities Customer Care And Billing on an Oracle Exadata platform. It is recommended that the contents of this whitepaper be used alongside existing best practices for the Oracle Exadata platform. The whitepaper is available from My Oracle Support under Implementing Oracle Exadata with Oracle Utilities Customer Care and Billing (Dod Id: 1486886.1)

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  • Visual Studio Load Testing using Windows Azure

    - by Tarun Arora
    In my opinion the biggest adoption barrier in performance testing on smaller projects is not the tooling but the high infrastructure and administration cost that comes with this phase of testing. Only if a reusable solution was possible and infrastructure management wasn’t as expensive, adoption would certainly spike. It certainly is possible if you bring Visual Studio and Windows Azure into the equation. It is possible to run your test rig in the cloud without getting tangled in SCVMM or Lab Management. All you need is an active Azure subscription, Windows Azure endpoint enabled developer workstation running visual studio ultimate on premise, windows azure endpoint enabled worker roles on azure compute instances set up to run as test controllers and test agents. My test rig is running SQL server 2012 and Visual Studio 2012 RC agents. The beauty is that the solution is reusable, you can open the azure project, change the subscription and certificate, click publish and *BOOM* in less than 15 minutes you could have your own test rig running in the cloud. In this blog post I intend to show you how you can use the power of Windows Azure to effectively abstract the administration cost of infrastructure management and lower the total cost of Load & Performance Testing. As a bonus, I will share a reusable solution that you can use to automate test rig creation for both VS 2010 agents as well as VS 2012 agents. Introduction The slide show below should help you under the high level details of what we are trying to achive... Leveraging Azure for Performance Testing View more PowerPoint from Avanade Scenario 1 – Running a Test Rig in Windows Azure To start off with the basics, in the first scenario I plan to discuss how to, - Automate deployment & configuration of Windows Azure Worker Roles for Test Controller and Test Agent - Automate deployment & configuration of SQL database on Test Controller on the Test Controller Worker Role - Scaling Test Agents on demand - Creating a Web Performance Test and a simple Load Test - Managing Test Controllers right from Visual Studio on Premise Developer Workstation - Viewing results of the Load Test - Cleaning up - Have the above work in the shape of a reusable solution for both VS2010 and VS2012 Test Rig Scenario 2 – The scaled out Test Rig and sharing data using SQL Azure A scaled out version of this implementation would involve running multiple test rigs running in the cloud, in this scenario I will show you how to sync the load test database from these distributed test rigs into one SQL Azure database using Azure sync. The selling point for this scenario is being able to collate the load test efforts from across the organization into one data store. - Deploy multiple test rigs using the reusable solution from scenario 1 - Set up and configure Windows Azure Sync - Test SQL Azure Load Test result database created as a result of Windows Azure Sync - Cleaning up - Have the above work in the shape of a reusable solution for both VS2010 and VS2012 Test Rig The Ingredients Though with an active MSDN ultimate subscription you would already have access to everything and more, you will essentially need the below to try out the scenarios, 1. Windows Azure Subscription 2. Windows Azure Storage – Blob Storage 3. Windows Azure Compute – Worker Role 4. SQL Azure Database 5. SQL Data Sync 6. Windows Azure Connect – End points 7. SQL 2012 Express or SQL 2008 R2 Express 8. Visual Studio All Agents 2012 or Visual Studio All Agents 2010 9. A developer workstation set up with Visual Studio 2012 – Ultimate or Visual Studio 2010 – Ultimate 10. Visual Studio Load Test Unlimited Virtual User Pack. Walkthrough To set up the test rig in the cloud, the test controller, test agent and SQL express installers need to be available when the worker role set up starts, the easiest and most efficient way is to pre upload the required software into Windows Azure Blob storage. SQL express, test controller and test agent expose various switches which we can take advantage of including the quiet install switch. Once all the 3 have been installed the test controller needs to be registered with the test agents and the SQL database needs to be associated to the test controller. By enabling Windows Azure connect on the machines in the cloud and the developer workstation on premise we successfully create a virtual network amongst the machines enabling 2 way communication. All of the above can be done programmatically, let’s see step by step how… Scenario 1 Video Walkthrough–Leveraging Windows Azure for performance Testing Scenario 2 Work in progress, watch this space for more… Solution If you are still reading and are interested in the solution, drop me an email with your windows live id. I’ll add you to my TFS preview project which has a re-usable solution for both VS 2010 and VS 2012 test rigs as well as guidance and demo performance tests.   Conclusion Other posts and resources available here. Possibilities…. Endless!

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  • How can Swift be so much faster than Objective-C?

    - by Yellow
    Apple launched its new programming language Swift today. In the presentation, they made some performance comparisons between Objective-C and Python. The following is a picture of one of their slides, of a comparison of those three languages performing some complex object sort: There was an even more incredible graph about a performance comparison working on some encryption algorithm. Obviously this is a marketing talk, and they didn't go into detail on how this was implemented in each. I leaves me wondering though: how can a new programming language be so much faster? In this example, surely you just have a bad Objective-C compiler or you're doing something in a less efficient way? How else would you explain a 40% performance increase? I understand that garbage collection/automated reference control might produce some additional overhead, but this much?

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  • Oracle FLEXCUBE delivers 'Bank-in-a-Box' with Oracle Database Appliance

    - by margaret hamburger
    Another great example of how Oracle Database Appliance simplifies the deployment of high availability database solutions making it easy for Oracle Partners and ISVs to deliver value added solutions to customers on a simple, reliable and affordable database platform. Oracle FLEXCUBE Universal Banking recently announced that it runs on Oracle Database Appliance X3-2 to deliver mid-size banks a compelling banking-in-a-box solution. With this certification, banks can benefit from a low-IT-footprint, high-performance, full-scale banking technology that is engineered to support end-to-end business requirements. In a recent performance test of Oracle FLEXCUBE Universal Banking on Oracle Database Appliance X3-2, the system managed more than 2.6 million online transactions in 60 minutes. This equated to roughly 744 transactions per second with an average response time of 156 milliseconds for 98 percent of the transactions. Likewise, the solution completed end-of-month batch processing for 10 million customer accounts in 123 minutes during the performance test.  Learn more about Oracle Database Appliance Solution-in-a-Box.

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  • SAP Applications Run Better on Oracle Exadata

    - by jgelhaus
    To yield the results necessary to stay competitive, your business-critical applications must be able to access the most reliable and up-to-date information. That’s why a growing number of SAP application customers are turning to Oracle Exadata Database Machine for better performance, better productivity—and big savings. Watch our latest Webcast to find out why Oracle Exadata is the ideal platform for running your SAP applications. You’ll learn how you can: Increase the performance of SAP applications Enhance reliability with a centralized, scalable platform Ensure quick, safe, and easy deployments Watch it now. Highlights include customer case studies and practical deployment strategies. Watch our latest on-demand Webcast to find out why Oracle Exadata is the ideal platform for running your SAP applications. Learn how to increase the performance of SAP applications, enhance reliability with a centralized, scalable platform and ensure quick, safe and easy deployments.

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  • Verizon Business Delivers New Sales and Support Tools

    - by michael.seback
    Verizon Business Delivers New Sales and Support Tools and Improves System Performance by 35% Verizon Business, a unit of Verizon Communications, is a global leader in communications and IT solutions. With one of the world's most connected internet protocol networks, Verizon Business delivers communications, IT, security, and network solutions to many of the largest businesses and governments. ..."Our work with Accenture to upgrade our Oracle systems has improved system performance significantly. In a recent survey, 84% of users said performance was 'faster' or 'much faster.' Plus, our sales and support staff have new tools to improve productivity and customer service, which ultimately drives customer retention and revenue." - Rob Moore, Director Verizon Business ...Read more.

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  • Adding Column to a SQL Server Table

    - by Dinesh Asanka
    Adding a column to a table is  common task for  DBAs. You can add a column to a table which is a nullable column or which has default values. But are these two operations are similar internally and which method is optimal? Let us start this with an example. I created a database and a table using following script: USE master Go --Drop Database if exists IF EXISTS (SELECT 1 FROM SYS.databases WHERE name = 'AddColumn') DROP DATABASE AddColumn --Create the database CREATE DATABASE AddColumn GO USE AddColumn GO --Drop the table if exists IF EXISTS ( SELECT 1 FROM sys.tables WHERE Name = 'ExistingTable') DROP TABLE ExistingTable GO --Create the table CREATE TABLE ExistingTable (ID BIGINT IDENTITY(1,1) PRIMARY KEY CLUSTERED, DateTime1 DATETIME DEFAULT GETDATE(), DateTime2 DATETIME DEFAULT GETDATE(), DateTime3 DATETIME DEFAULT GETDATE(), DateTime4 DATETIME DEFAULT GETDATE(), Gendar CHAR(1) DEFAULT 'M', STATUS1 CHAR(1) DEFAULT 'Y' ) GO -- Insert 100,000 records with defaults records INSERT INTO ExistingTable DEFAULT VALUES GO 100000 Before adding a Column Before adding a column let us look at some of the details of the database. DBCC IND (AddColumn,ExistingTable,1) By running the above query, you will see 637 pages for the created table. Adding a Column You can add a column to the table with following statement. ALTER TABLE ExistingTable Add NewColumn INT NULL Above will add a column with a null value for the existing records. Alternatively you could add a column with default values. ALTER TABLE ExistingTable Add NewColumn INT NOT NULL DEFAULT 1 The above statement will add a column with a 1 value to the existing records. In the below table I measured the performance difference between above two statements. Parameter Nullable Column Default Value CPU 31 702 Duration 129 ms 6653 ms Reads 38 116,397 Writes 6 1329 Row Count 0 100000 If you look at the RowCount parameter, you can clearly see the difference. Though column is added in the first case, none of the rows are affected while in the second case all the rows are updated. That is the reason, why it has taken more duration and CPU to add column with Default value. We can verify this by several methods. Number of Pages The number of data pages can be obtained by using DBCC IND command. Though, this an undocumented dbcc command, many experts are ok to use this command in production. However, since there is no official word from Microsoft, use this “at your own risk”. DBCC IND (AddColumn,ExistingTable,1) Before Adding the Columns 637 Adding a Column with NULL 637 Adding a column with DEFAULT value 1270 This clearly shows that pages are physically modified. Please note, a high value indicated in the Adding a column with DEFAULT value  column is also a result of page splits. Continues…

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  • Speaking at AMD Fusion conference

    - by Daniel Moth
    Next Wednesday at 2pm I will be presenting a session at the AMD Fusion developer summit in Bellevue, Washington State. For more on this conference please visit the official website. If you filter the catalog by 'Speaker Last Name' to "Moth", you'll find my talk. For your convenience, below is the title and abstract Blazing-fast code using GPUs and more, with Microsoft Visual C++ To get full performance out of mainstream hardware, high-performance code needs to harness, not only multi-core CPUs, but also GPUs (whether discrete cards or integrated in the processor) and other compute accelerators to achieve orders-of-magnitude speed-up for data parallel algorithms. How can you as a C++ developer fully utilize all that heterogeneous hardware from your Visual Studio environment? How can your code benefit from this tremendous performance boost without sacrificing your developer productivity or the portability of your solution? The answers will be presented in this session that introduces a new technology from Microsoft. Hope to see many of you there! Comments about this post welcome at the original blog.

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