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  • Protecting offline IRM rights and the error "Unable to Connect to Offline database"

    - by Simon Thorpe
    One of the most common problems I get asked about Oracle IRM is in relation to the error message "Unable to Connect to Offline database". This error message is a result of how Oracle IRM is protecting the cached rights on the local machine and if that cache has become invalid in anyway, this error is thrown. Offline rights and security First we need to understand how Oracle IRM handles offline use. The way it is implemented is one of the main reasons why Oracle IRM is the leading document security solution and demonstrates our methodology to ensure that solutions address both security and usability and puts the balance of these two in your control. Each classification has a set of predefined roles that the manager of the classification can assign to users. Each role has an offline period which determines the amount of time a user can access content without having to communicate with the IRM server. By default for the context model, which is the classification system that ships out of the box with Oracle IRM, the offline period for each role is 3 days. This is easily changed however and can be as low as under an hour to as long as years. It is also possible to switch off the ability to access content offline which can be useful when content is very sensitive and requires a tight leash. So when a user is online, transparently in the background, the Oracle IRM Desktop communicates with the server and updates the users rights and offline periods. This transparent synchronization period is determined by the server and communicated to all IRM Desktops and allows for users rights to be kept up to date without their intervention. This allows us to support some very important scenarios which are key to a successful IRM solution. A user doesn't have to make any decision when going offline, they simply unplug their laptop and they already have their offline periods synchronized to the maximum values. Any solution that requires a user to make a decision at the point of going offline isn't going to work because people forget to do this and will therefore be unable to legitimately access their content offline. If your rights change to REMOVE your access to content, this also happens in the background. This is very useful when someone has an offline duration of a week and they happen to make a connection to the internet 3 days into that offline period, the Oracle IRM Desktop detects this online state and automatically updates all rights for the user. This means the business risk is reduced when setting long offline periods, because of the daily transparent sync, you can reflect changes as soon as the user is online. Of course, if they choose not to come online at all during that week offline period, you cannot effect change, but you take that risk in giving the 7 day offline period in the first place. If you are added to a NEW classification during the day, this will automatically be synchronized without the user even having to open a piece of content secured against that classification. This is very important, consider the scenario where a senior executive downloads all their email but doesn't open any of it. Disconnects the laptop and then gets on a plane. During the flight they attempt to open a document attached to a downloaded email which has been secured against an IRM classification the user was not even aware they had access to. Because their new role in this classification was automatically synchronized their experience is a good one and the document opens. More information on how the Oracle IRM classification model works can be found in this article by Martin Abrahams. So what about problems accessing the offline rights database? So onto the core issue... when these rights are cached to your machine they are stored in an encrypted database. The encryption of this offline database is keyed to the instance of the installation of the IRM Desktop and the Windows user account. Why? Well what you do not want to happen is for someone to get their rights for content and then copy these files across hundreds of other machines, therefore getting access to sensitive content across many environments. The IRM server has a setting which controls how many times you can cache these rights on unique machines. This is because people typically access IRM content on more than one computer. Their work desktop, a laptop and often a home computer. So Oracle IRM allows for the usability of caching rights on more than one computer whilst retaining strong security over this cache. So what happens if these files are corrupted in someway? That's when you will see the error, Unable to Connect to Offline database. The most common instance of seeing this is when you are using virtual machines and copy them from one computer to the next. The virtual machine software, VMWare Workstation for example, makes changes to the unique information of that virtual machine and as such invalidates the offline database. How do you solve the problem? Resolution is however simple. You just delete all of the offline database files on the machine and they will be recreated with working encryption when the Oracle IRM Desktop next starts. However this does mean that the IRM server will think you have your rights cached to more than one computer and you will need to rerequest your rights, even though you are only going to be accessing them on one. Because it still thinks the old cache is valid. So be aware, it is good practice to increase the server limit from the default of 1 to say 3 or 4. This is done using the Enterprise Manager instance of IRM. So to delete these offline files I have a simple .bat file you can use; Download DeleteOfflineDBs.bat Note that this uses pskillto stop the irmBackground.exe from running. This is part of the IRM Desktop and holds open a lock to the offline database. Either kill this from task manager or use pskillas part of the script.

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  • BizTalk host throttling &ndash; Singleton pattern and High database size

    - by S.E.R.
    Originally posted on: http://geekswithblogs.net/SERivas/archive/2013/06/30/biztalk-host-throttling-ndash-singleton-pattern-and-high-database-size.aspxI have worked for some days around the singleton pattern (for those unfamiliar with it, read this post by Victor Fehlberg) and have come across a few very interesting posts, among which one dealt with performance issues (here, also by Victor Fehlberg). Simply put: if you have an orchestration which implements the singleton pattern, then performances will continuously decrease as the orchestration receives and consumes messages, and that behavior is more obvious when the orchestration never ends (ie : it keeps looping and never terminates or completes). As I experienced the same kind of problem (actually I was alerted by SCOM, which told me that the host was being throttled because of High database size), I thought it would be a good idea to dig a little bit a see what happens deep inside BizTalk and thus understand the reasons for this behavior. NOTE: in this article, I will focus on this High database size throttling condition. I will try and work on the other conditions in some not too distant future… Test conditions The singleton orchestration For the purpose of this study, I have created the following orchestration, which is a very basic implementation of a singleton that piles up incoming messages, then does something else when a certain timeout has been reached without receiving another message: Throttling settings I have two distinct hosts : one that hosts the receive port (basic FILE port) : Ports_ReceiveHostone that hosts the orchestration : ProcessingHost In order to emphasize the throttling mechanism, I have modified the throttling settings for each of these hosts are as follows (all other parameters are set to the default value): [Throttling thresholds] Message count in database: 500 (default value : 50000) Evolution of performance counters when submitting messages Since we are investigating the High database size throttling condition, here are the performance counter that we should take a look at (all of them are in the BizTalk:Message Agent performance object): Database sizeHigh database sizeMessage delivery throttling stateMessage publishing throttling stateMessage delivery delay (ms)Message publishing delay (ms)Message delivery throttling state durationMessage publishing throttling state duration (If you are not used to Perfmon, I strongly recommend that you start using it right now: it is a wonderful tool that allows you to open the hood and see what is going on inside BizTalk – and other systems) Database size It is quite obvious that we will start by watching the database size and high database size counters, just to see when the first reaches the configured threshold (500) and when the second rings the alarm. NOTE : During this test I submitted 600 messages, one message at a time every 10ms to see the evolution of the counters we have previously selected. It might not show very well on this screenshot, but here is what happened: From 15:46:50 to 15:47:50, the database size for the Ports_ReceiveHost host (blue line) kept growing until it reached a maximum of 504.At 15:47:50, the high database size alert fires At first I was surprised by this result: why is it the database size of the receiving host that keeps growing since it is the processing host that piles up messages? Actually, it makes total sense. This counter measures the size of the database queue that is being filled by the host, not consumed. Therefore, the high database size alert is raised on the host that fills the queue: Ports_ReceiveHost. More information is available on the Public MPWiki page. Now, looking at the Message publishing throttling state for the receiving host (green line), we can see that a throttling condition has been reached at 15:47:50: We can also see that the Message publishing delay(ms) (blue line) has begun growing slowly from this point. All of this explains why performances keep decreasing when a singleton keeps processing new messages: the database size grows and when it has exceeded the Message count in database threshold, the host is throttled and the publishing delay keeps increasing. Digging further So, what happens to the database queue then? Is it flushed some day or does it keep growing and growing indefinitely? The real question being: will the host be throttled forever because of this singleton? To answer this question, I set the Message count in database threshold to 20 (this value is very low in order not to wait for too long, otherwise I certainly would have fallen asleep in front of my screen) and I submitted 30 messages. The test was started at 18:26. At 18:56 (ie : exactly 30min later) the throttling was stopped and the database size was divided by 2. 30 min later again, the database size had dropped to almost zero: I guess I’ll have to find some documentation and do some more testing before I sort this out! My guess is that some maintenance job is at work here, though I cannot tell which one Digging even further If we take a look at the Message delivery throttling state counter for the processing host, we can see that this host was also throttled during the submission of the 600 documents: The value for the counter was 1, meaning that Message delivery incoming rate for the host instance exceeds the Message delivery outgoing rate * the specified Rate overdrive factor (percent) value. We will see this another day… :) A last word Let’s end this article with a warning: DO NOT CHANGE THE THROTTLING SETTINGS LIGHTLY! The temptation can be great to just bypass throttling by setting very high values for each parameter (or zero in some cases, which simply disables throttling). Nevertheless, always keep in mind that this mechanism is here for a very good reason: prevent your BizTalk infrastructure from exploding!! So whatever you do with those settings, do a lot of testing and benchmarking!

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  • Algorithmia Source Code released on CodePlex

    - by FransBouma
    Following the release of our BCL Extensions Library on CodePlex, we have now released the source-code of Algorithmia on CodePlex! Algorithmia is an algorithm and data-structures library for .NET 3.5 or higher and is one of the pillars LLBLGen Pro v3's designer is built on. The library contains many data-structures and algorithms, and the source-code is well documented and commented, often with links to official descriptions and papers of the algorithms and data-structures implemented. The source-code is shared using Mercurial on CodePlex and is licensed under the friendly BSD2 license. User documentation is not available at the moment but will be added soon. One of the main design goals of Algorithmia was to create a library which contains implementations of well-known algorithms which weren't already implemented in .NET itself. This way, more developers out there can enjoy the results of many years of what the field of Computer Science research has delivered. Some algorithms and datastructures are known in .NET but are re-implemented because the implementation in .NET isn't efficient for many situations or lacks features. An example is the linked list in .NET: it doesn't have an O(1) concat operation, as every node refers to the containing LinkedList object it's stored in. This is bad for algorithms which rely on O(1) concat operations, like the Fibonacci heap implementation in Algorithmia. Algorithmia therefore contains a linked list with an O(1) concat feature. The following functionality is available in Algorithmia: Command, Command management. This system is usable to build a fully undo/redo aware system by building your object graph using command-aware classes. The Command pattern is implemented using a system which allows transparent undo-redo and command grouping so you can use it to make a class undo/redo aware and set properties, use its contents without using commands at all. The Commands namespace is the namespace to start. Classes you'd want to look at are CommandifiedMember, CommandifiedList and KeyedCommandifiedList. See the CommandQueueTests in the test project for examples. Graphs, Graph algorithms. Algorithmia contains a sophisticated graph class hierarchy and algorithms implemented onto them: non-directed and directed graphs, as well as a subgraph view class, which can be used to create a view onto an existing graph class which can be self-maintaining. Algorithms include transitive closure, topological sorting and others. A feature rich depth-first search (DFS) crawler is available so DFS based algorithms can be implemented quickly. All graph classes are undo/redo aware, as they can be set to be 'commandified'. When a graph is 'commandified' it will do its housekeeping through commands, which makes it fully undo-redo aware, so you can remove, add and manipulate the graph and undo/redo the activity automatically without any extra code. If you define the properties of the class you set as the vertex type using CommandifiedMember, you can manipulate the properties of vertices and the graph contents with full undo/redo functionality without any extra code. Heaps. Heaps are data-structures which have the largest or smallest item stored in them always as the 'root'. Extracting the root from the heap makes the heap determine the next in line to be the 'maximum' or 'minimum' (max-heap vs. min-heap, all heaps in Algorithmia can do both). Algorithmia contains various heaps, among them an implementation of the Fibonacci heap, one of the most efficient heap datastructures known today, especially when you want to merge different instances into one. Priority queues. Priority queues are specializations of heaps. Algorithmia contains a couple of them. Sorting. What's an algorithm library without sort algorithms? Algorithmia implements a couple of sort algorithms which sort the data in-place. This aspect is important in situations where you want to sort the elements in a buffer/list/ICollection in-place, so all data stays in the data-structure it already is stored in. PropertyBag. It re-implements Tony Allowatt's original idea in .NET 3.5 specific syntax, which is to have a generic property bag and to be able to build an object in code at runtime which can be bound to a property grid for editing. This is handy for when you have data / settings stored in XML or other format, and want to create an editable form of it without creating many editors. IEditableObject/IDataErrorInfo implementations. It contains default implementations for IEditableObject and IDataErrorInfo (EditableObjectDataContainer for IEditableObject and ErrorContainer for IDataErrorInfo), which make it very easy to implement these interfaces (just a few lines of code) without having to worry about bookkeeping during databinding. They work seamlessly with CommandifiedMember as well, so your undo/redo aware code can use them out of the box. EventThrottler. It contains an event throttler, which can be used to filter out duplicate events in an event stream coming into an observer from an event. This can greatly enhance performance in your UI without needing to do anything other than hooking it up so it's placed between the event source and your real handler. If your UI is flooded with events from data-structures observed by your UI or a middle tier, you can use this class to filter out duplicates to avoid redundant updates to UI elements or to avoid having observers choke on many redundant events. Small, handy stuff. A MultiValueDictionary, which can store multiple unique values per key, instead of one with the default Dictionary, and is also merge-aware so you can merge two into one. A Pair class, to quickly group two elements together. Multiple interfaces for helping with building a de-coupled, observer based system, and some utility extension methods for the defined data-structures. We regularly update the library with new code. If you have ideas for new algorithms or want to share your contribution, feel free to discuss it on the project's Discussions page or send us a pull request. Enjoy!

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  • Oracle Day 2013 Istanbul – 14.Kasim.2013

    - by TUFEKCIOGLU,FATIH
    Oracle Day 2013 Istanbul – 14.Kasim.2013 Yeni Teknolojiler. Yeni Dünya.  Sayfa duzgun goruntulenemiyorsa etkinlik takvimine asagidaki linkten ulasabilirsiniz : https://blogs.oracle.com/fatihtufekcioglu/resource/Oracle_Day_Istanbul_14.Kasim.2013_blogs.oracle.com.fatihtufekcioglu.html#! charset=iso-8859-1"> "> Hemen Kaydolun! Oracle Day 2013 Istanbul Istanbul Kongre Merkezi Taskisla Caddesi Harbiye 34367 Istanbul / Türkiye 14 Kasim 2013, Persembe 08:30 - 18:00 LCV: [email protected] Oracle Day 2013 Istanbul Yeni Teknolojiler. Yeni Dünya. 14 Kasim 2013 Sayin Davetlimiz, Teknoloji, dünyayi sürekli degistirmeye devam ediyor. Bulut bilisim, mobil çözümler, büyük veri ve nesnelerin interneti güçlerini birlestirerek, eski is modellerini altüst edip inovasyonu ön plana çikartiyorlar. Organizasyonlar ise bu yeni dünyaya ayak uydurmak için bir yandan sürekli degisimi saglamaya çalisirken, diger yandan da isletmelerini en iyi sekilde yönetmeye devam etmek zorundalar. Peki organizasyonlar bu dengeyi nasil koruyorlar? Oracle Day 2013 Istanbul'da birçok Oracle müsterisinden dinleyeceginiz basari hikayeleriyle bunun nasil mümkün oldugunu görebilirsiniz. Etkinlige katilarak: Teknolojinin, yeni is modellerini ve firsatlarini nasil atesledigini ögrenebilir, Inovasyonu ön plana çikartmak için bilgi teknolojilerini sadelestiren sirketlerin basari hikayelerini dinleyebilir, Sizinle ayni zorluklari tecrübe eden sektör profesyonelleriyle biraraya gelebilir, Oracle'dan en yeni ürün haberlerini ve duyurularini takip etme firsati bulabilirsiniz. Oracle ve is ortaklariyla bulusmak, müsteri basari hikayelerini dinlemek, sosyal ve mobil etkilesimler için firsatlar yakalamak, uygulamali demolar izlemek ve daha fazlasi için Oracle Day 2013 Istanbul'da bize katilmanizdan memnuniyet duyacagiz. Hemen Kaydolun. Saygilarimizla, Oracle Türkiye Oracle Is Ortagi Müsteri Basari Hikayesi TROUG Sunum Ingilizcedir Program 08:30-09:30 Kayit 09:30-10:00 Hos Geldiniz Filiz Dogan, Genel Müdür, Oracle Türkiye 10:00-10:30 Keynote Andrew Sutherland, SVP, EMEA Technology, Oracle 10:30-11:00 Yapi Kredi ve Oracle Cahit Erdogan, Bilisim Teknolojileri ve Operasyon Yönetimi Genel Müdür Yardimcisi, Yapi Kredi Bankasi 11:00-11:30 150. Yasinda Ziraat'te Teknolojinin Dünü, Bugünü, Yarini Yunus Uygur Kocaoglu, Ziraat Teknoloji Genel Müdürü & Bilgi Teknolojileri Yönetimi Genel Müdür Yardimcisi, Ziraat Bankasi 11:30-11:45 Oracle Day'de 5. Yil Sezgin Aslan, Is Gelistirme Grup Yöneticisi, Innova 11:45-13:00 Ögle Yemegi Salon 1 Salon 2 Salon 3 Salon 4 Salon 5 Salon 6 Salon 7 Salon 8 Bulut Bilisim Çözümleri Büyük Veri & Analitik Çözümler Mobil Dünyada Orta Katman Çözümleri Is Uygulamalari I Is Uygulamalari II Modern Veri Merkezi Oracle & Is Ortaklari Çözümleri & Basari Hikayeleri TROUG (Oracle User Group) 13:00-13:30 Bulutunuza Yön Verin! Big Data at Work: Transform Your Business with Analytics Your Blueprint For Driving Enterprise Mobile Strategy Empowering Modern Business in the Cloud - Is Optimizasyonu Hayal Degil! Degisime Dünden Hazir Olmak: "BAT E-Fatura Projesi” Panel: "Türkiye'de Nitelikli Bilisim Elemani Yetistirilmesi" Oracle Oracle Oracle Oracle Oracle Idea Teknoloji British American Tobacco Oracle TROUG 13:30-13:40 Kahve Molasi 13:40-14:10 12c ile Veritabani Buluta Tasindi, Peki ya Siz? Büyüklük Sizde Kalsin BT Öncüleri için Uygulama Sunucusu Platformu Vakif Emeklilik Muhasebe ve Lojistik Sistemler Dönüsüm Projesi JD Edwards EnterpriseOne: Kapsamli, Kullanici Dostu ve Yenilikçi Modern Veri Merkezleri için Etkin Oracle Sunuculari Ziraat Bankasi Exadata Basari Hikayesi Oracle Database 12c Önemli Özellikler (DB/DWH) Oracle Etiya Oracle Innova Oracle Oracle Ziraat Bankasi TROUG 14:10-14:20 Kahve Molasi 14:20-14:50 Oracle Bulutunuza Bir Mimarin Bakisi Odakliligin Gücü: Oracle BI Dashboard Kullanimiyla Performans Yönetimi Kurumsal Uygulamalarin Mobil Dünyaya Entegrasyonu Müsteri Karsisinda Tutarli, Etkin ve Tekil Durus: Mükemmel Müsteri Deneyimi Etkin Planlama ve Satin Alma ile Tedarik Zincirinden "Deger Zinciri"ne Dönüsüm Oracle Uygulamalari için Tasarlanmis Veri Depolama Sistemleri Bütünlesik Sistemler (Engineered Systems) için Platinum Hizmetler Sql/PLSQL Yeni Özellikler Oracle ING Oracle Oracle Oracle Oracle Oracle TROUG 14:50-15:00 Kahve Molasi 15:00-15:30 Oracle Enterprise Manager 12c: How Does It Support the Cloud? Veri Analizinde Yeni Yorum, Endeca ile Yeni Bakis Kurumsal Bilginin Yolculugu Basariya Giden Yol: Satis, Pazarlama ve Sosyal Medya Elele Kurumsal Performans Yönetimi (EPM) ile Is Potansiyelinizi Açiga Çikarin! Oracle Sunucu ve Veri Depolama Teknolojilerine Hizli Geçis - Avea Basari Hikayesi SAP Uygulamalari Oracle Engineered (Bütünlesik) Sistemler ile Daha Iyi Çalisiyor - Koçtas Basari Hikayesi Oracle EBS R12.2 Yeni Özellikler Oracle Gtech Oracle Innova Oracle Oracle Avea Oracle Koçtas TROUG 15:30-15:40 Kahve Molasi 15:40-16:10 Oracle Real Application Testing (RAT) ile Partitioning Islemleri, Oracle RAT'in Finansbank'taki Kullanim Alanlari Degisen Pazar Kosullarina Hizli Bütçe Revizyonu ile Adaptasyon Mobil Cihazlar için Erisim Yönetimi ve Güvenlik Yönetisim, Yasal Uyumluluk ve Süreç Optimizasyonu Lider Ise Alim Çözümü Taleo ile Bireysel Basaridan Kurumsal Basariya Oracle Bütünlesik Sistemleri ile Kendi Bulut Ortaminizi Yaratin Akçelik ERP Seçimi JDEdwards Exadata - Maximum Availability Architecture Best Practices Avea Finansbank IBTECH Gtech Oracle PwC Oracle Oracle Akçelik Kora Oracle 16:10-16:20 Kahve Molasi 16:20-16:50 Orta Katman da Bulutlu Hizli Veri mi Büyük Veri mi? Her Tür Süreç Ihtiyaci için Oracle BPM - Demo CRM Dünyasinin Tecrübeli Yildizi Siebel'in Bugünü ve Yarini Fusion ile IK Stratejilerinizi Bulutlara Tasimak Esnek ve Dinamik Veri Merkezi Altyapilari Kurulum Süresi En SADE ERP. Oracle Business Accelerator ile ERP'de Jet Hizi! Nefis: EDQ, OGG ve ODI Exadata Üzerinde Oracle Oracle Oracle KRBB Oracle Oracle AWR Oracle SADE Organik Labrys Danismanlik TROUG 16:50-18:00 Kokteyl & Oracle Infiniband Konseri PANELISTLER: Esref Adali: ITÜ Bilgisayar Mühendisligi Bölüm Baskani ve Bilisim Enstitüsü Bilgi Teknolojileri Programi Anabilim Dali Baskani Kemal Ciliz: TÜBISAD Yönetim Kurulu Baskani Zekeriya Besiroglu: Oracle Bilgisayar Programcilar Dernegi Yönetim Kurulu Baskani MODERATÖR: Cem Satana, Oracle Genel Müdür Yardimcisi ">Eger bir kamu kurumunun/kurulusunun çalisani veya görevlisi iseniz, bu etkinlige iliskin önemli etik kurallara iliskin bilgi için lütfen buraya tiklayiniz -- Copyright 2013, Oracle and/or its affiliates. All rights reserved. Bize Ulasin | Yasal Uyarilar | Gizlilik Beyani Etkinlik takvimi : https://blogs.oracle.com/fatihtufekcioglu/resource/Oracle_Day_Istanbul_14.Kasim.2013_blogs.oracle.com.fatihtufekcioglu.html#!

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  • SQL SERVER – Example of Performance Tuning for Advanced Users with DB Optimizer

    - by Pinal Dave
    Performance tuning is such a subject that everyone wants to master it. In beginning everybody is at a novice level and spend lots of time learning how to master the art of performance tuning. However, as we progress further the tuning of the system keeps on getting very difficult. I have understood in my early career there should be no need of ego in the technology field. There are always better solutions and better ideas out there and we should not resist them. Instead of resisting the change and new wave I personally adopt it. Here is a similar example, as I personally progress to the master level of performance tuning, I face that it is getting harder to come up with optimal solutions. In such scenarios I rely on various tools to teach me how I can do things better. Once I learn about tools, I am often able to come up with better solutions when I face the similar situation next time. A few days ago I had received a query where the user wanted to tune it further to get the maximum out of the performance. I have re-written the similar query with the help of AdventureWorks sample database. SELECT * FROM HumanResources.Employee e INNER JOIN HumanResources.EmployeeDepartmentHistory edh ON e.BusinessEntityID = edh.BusinessEntityID INNER JOIN HumanResources.Shift s ON edh.ShiftID = s.ShiftID; User had similar query to above query was used in very critical report and wanted to get best out of the query. When I looked at the query – here were my initial thoughts Use only column in the select statements as much as you want in the application Let us look at the query pattern and data workload and find out the optimal index for it Before I give further solutions I was told by the user that they need all the columns from all the tables and creating index was not allowed in their system. He can only re-write queries or use hints to further tune this query. Now I was in the constraint box – I believe * was not a great idea but if they wanted all the columns, I believe we can’t do much besides using *. Additionally, if I cannot create a further index, I must come up with some creative way to write this query. I personally do not like to use hints in my application but there are cases when hints work out magically and gives optimal solutions. Finally, I decided to use Embarcadero’s DB Optimizer. It is a fantastic tool and very helpful when it is about performance tuning. I have previously explained how it works over here. First open DBOptimizer and open Tuning Job from File >> New >> Tuning Job. Once you open DBOptimizer Tuning Job follow the various steps indicates in the following diagram. Essentially we will take our original script and will paste that into Step 1: New SQL Text and right after that we will enable Step 2 for Generating Various cases, Step 3 for Detailed Analysis and Step 4 for Executing each generated case. Finally we will click on Analysis in Step 5 which will generate the report detailed analysis in the result pan. The detailed pan looks like. It generates various cases of T-SQL based on the original query. It applies various hints and available hints to the query and generate various execution plans of the query and displays them in the resultant. You can clearly notice that original query had a cost of 0.0841 and logical reads about 607 pages. Whereas various options which are just following it has different execution cost as well logical read. There are few cases where we have higher logical read and there are few cases where as we have very low logical read. If we pay attention the very next row to original query have Merge_Join_Query in description and have lowest execution cost value of 0.044 and have lowest Logical Reads of 29. This row contains the query which is the most optimal re-write of the original query. Let us double click over it. Here is the query: SELECT * FROM HumanResources.Employee e INNER JOIN HumanResources.EmployeeDepartmentHistory edh ON e.BusinessEntityID = edh.BusinessEntityID INNER JOIN HumanResources.Shift s ON edh.ShiftID = s.ShiftID OPTION (MERGE JOIN) If you notice above query have additional hint of Merge Join. With the help of this Merge Join query hint this query is now performing much better than before. The entire process takes less than 60 seconds. Please note that it the join hint Merge Join was optimal for this query but it is not necessary that the same hint will be helpful in all the queries. Additionally, if the workload or data pattern changes the query hint of merge join may be no more optimal join. In that case, we will have to redo the entire exercise once again. This is the reason I do not like to use hints in my queries and I discourage all of my users to use the same. However, if you look at this example, this is a great case where hints are optimizing the performance of the query. It is humanly not possible to test out various query hints and index options with the query to figure out which is the most optimal solution. Sometimes, we need to depend on the efficiency tools like DB Optimizer to guide us the way and select the best option from the suggestion provided. Let me know what you think of this article as well your experience with DB Optimizer. Please leave a comment. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Joins, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • PHP OCI8 and Oracle 11g DRCP Connection Pooling in Pictures

    - by christopher.jones
    Here is a screen shot from a PHP OCI8 connection pooling demo that I like to run. It graphically shows how little database host memory is needed when using DRCP connection pooling with Oracle Database 11g. Migrating to DRCP can be as simple as starting the pool and changing the connection string in your PHP application. The script that generated the data for this graph was a simple "Parts" query application being run under various simulated user loads. I was running the database on a small Oracle Linux server with just 2G of memory. I used PHP OCI8 1.4. Apache is in pre-fork mode, as needed for PHP. Each graph has time on the horizontal access in arbitrary 'tick' time units. Click the image to see it full sized. Pooled connections Beginning with the top left graph, At tick time 65 I used Apache's 'ab' tool to start 100 concurrent 'users' running the application. These users connected to the database using DRCP: $c = oci_pconnect('phpdemo', 'welcome', 'myhost/orcl:pooled'); A second hundred DRCP users were added to the system at tick 80 and a final hundred users added at tick 100. At about tick 110 I stopped the test and restarted Apache. This closed all the connections. The bottom left graph shows the number of statements being executed by the database per second, with some spikes for background database activity and some variability for this small test. Each extra batch of users adds another 'step' of load to the system. Looking at the top right Server Process graph shows the database server processes doing the query work for each web user. As user load is added, the DRCP server pool increases (in green). The pool is initially at its default size 4 and quickly ramps up to about (I'm guessing) 35. At tick time 100 the pool increases to my configured maximum of 40 processes. Those 40 processes are doing the query work for all 300 web users. When I stopped the test at tick 110, the pooled processes remained open waiting for more users to connect. If I had left the test quiet for the DRCP 'inactivity_timeout' period (300 seconds by default), the pool would have shrunk back to 4 processes. Looking at the bottom right, you can see the amount of memory being consumed by the database. During the initial quiet period about 500M of memory was in use. The absolute number is just an indication of my particular DB configuration. As the number of pooled processes increases, each process needs more memory. You can see the shape of the memory graph echoes the Server Process graph above it. Each of the 300 web users will also need a few kilobytes but this is almost too small to see on the graph. Non-pooled connections Compare the DRCP case with using 'dedicated server' processes. At tick 140 I started 100 web users who did not use pooled connections: $c = oci_pconnect('phpdemo', 'welcome', 'myhost/orcl'); This connection string change is the only difference between the two tests. At ticks 155 and 165 I started two more batches of 100 simulated users each. At about tick 195 I stopped the user load but left Apache running. Apache then gradually returned to its quiescent state, killing idle httpd processes and producing the downward slope at the right of the graphs as the persistent database connection in each Apache process was closed. The Executions per Second graph on the bottom left shows the same step increases as for the earlier DRCP case. The database is handling this load. But look at the number of Server processes on the top right graph. There is now a one-to-one correspondence between Apache/PHP processes and DB server processes. Each PHP processes has one DB server processes dedicated to it. Hence the term 'dedicated server'. The memory required on the database is proportional to all those database server processes started. Almost all my system's memory was consumed. I doubt it would have coped with any more user load. Summary Oracle Database 11g DRCP connection pooling significantly reduces database host memory requirements allow more system memory to be allocated for the SGA and allowing the system to scale to handled thousands of concurrent PHP users. Even for small systems, using DRCP allows more web users to be active. More information about PHP and DRCP can be found in the PHP Scalability and High Availability chapter of The Underground PHP and Oracle Manual.

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  • Identity Management Monday at Oracle OpenWorld

    - by Tanu Sood
    What a great start to Oracle OpenWorld! Did you catch Larry Ellison’s keynote last evening? As expected, it was a packed house and the keynote received a tremendous response both from the live audience as well as the online community as evidenced by the frequent spontaneous applause in house and the twitter buzz. Here’s but a sampling of some of the tweets that flowed in: @paulvallee: I freaking love that #oracle has been born again in it's interest in core tech #oow (so good for #pythian) @rwang0: MyPOV: #oracle just leapfrogged the competition on the tech front across the board. All they need is the content delivery network #oow12 @roh1: LJE more astute & engaging this year. Nice announcements this year with 12c the MTDB sounding real good. #oow12 @brooke: Cool to see @larryellison interrupted multiple times by applause from the audience. Great speaker. #OOW And there’s lot more to come this week. Identity Management sessions kick-off today. Here’s a quick preview of what’s in store for you today for Identity Management: CON9405: Trends in Identity Management 10:45 a.m. – 11:45 a.m., Moscone West 3003 Hear directly from subject matter experts from Kaiser Permanente and SuperValu who would share the stage with Amit Jasuja, Senior Vice President, Oracle Identity Management and Security, to discuss how the latest advances in Identity Management that made it in Oracle Identity Management 11g Release 2 are helping customers address emerging requirements for securely enabling cloud, social and mobile environments. CON9492: Simplifying your Identity Management Implementation 3:15 p.m. – 4:15 p.m., Moscone West 3008 Implementation experts from British Telecom, Kaiser Permanente and UPMC participate in a panel to discuss best practices, key strategies and lessons learned based on their own experiences. Attendees will hear first-hand what they can do to streamline and simplify their identity management implementation framework for a quick return-on-investment and maximum efficiency. This session will also explore the architectural simplifications of Oracle Identity Governance 11gR2, focusing on how these enhancements simply deployments. CON9444: Modernized and Complete Access Management 4:45 p.m. – 5:45 p.m., Moscone West 3008 We have come a long way from the days of web single sign-on addressing the core business requirements. Today, as technology and business evolves, organizations are seeking new capabilities like federation, token services, fine grained authorizations, web fraud prevention and strong authentication. This session will explore the emerging requirements for access management, what a complete solution is like, complemented with real-world customer case studies from ETS, Kaiser Permanente and TURKCELL and product demonstrations. HOL10478: Complete Access Management Monday, October 1, 1:45 p.m. – 2:45 p.m., Marriott Marquis - Salon 1/2 And, get your hands on technology today. Register and attend the Hands-On-Lab session that demonstrates Oracle’s complete and scalable access management solution, which includes single sign-on, authorization, federation, and integration with social identity providers. Further, the session shows how to securely extend identity services to mobile applications and devices—all while leveraging a common set of policies and a single instance. Product Demonstrations The latest technology in Identity Management is also being showcased in the Exhibition Hall so do find some time to visit our product demonstrations there. Experts will be at hand to answer any questions. DEMOS LOCATION EXHIBITION HALL HOURS Access Management: Complete and Scalable Access Management Moscone South, Right - S-218 Monday, October 1 9:30 a.m.–6:00 p.m. 9:30 a.m.–10:45 a.m. (Dedicated Hours) Tuesday, October 2 9:45 a.m.–6:00 p.m. 2:15 p.m.–2:45 p.m. (Dedicated Hours) Wednesday, October 3 9:45 a.m.–4:00 p.m. 2:15 p.m.–3:30 p.m. (Dedicated Hours) Access Management: Federating and Leveraging Social Identities Moscone South, Right - S-220 Access Management: Mobile Access Management Moscone South, Right - S-219 Access Management: Real-Time Authorizations Moscone South, Right - S-217 Access Management: Secure SOA and Web Services Security Moscone South, Right - S-223 Identity Governance: Modern Administration and Tooling Moscone South, Right - S-210 Identity Management Monitoring with Oracle Enterprise Manager Moscone South, Right - S-212 Oracle Directory Services Plus: Performant, Cloud-Ready Moscone South, Right - S-222 Oracle Identity Management: Closed-Loop Access Certification Moscone South, Right - S-221 We recommend you keep the Focus on Identity Management document handy. And don’t forget, if you are not on site, you can catch all the keynotes LIVE from the comfort of your desk on YouTube.com/Oracle. Keep the conversation going on @oracleidm. Use #OOW and #IDM and get engaged today. Photo Courtesy: @OracleOpenWorld

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  • Big Data – Role of Cloud Computing in Big Data – Day 11 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the NewSQL. In this article we will understand the role of Cloud in Big Data Story What is Cloud? Cloud is the biggest buzzword around from last few years. Everyone knows about the Cloud and it is extremely well defined online. In this article we will discuss cloud in the context of the Big Data. Cloud computing is a method of providing a shared computing resources to the application which requires dynamic resources. These resources include applications, computing, storage, networking, development and various deployment platforms. The fundamentals of the cloud computing are that it shares pretty much share all the resources and deliver to end users as a service.  Examples of the Cloud Computing and Big Data are Google and Amazon.com. Both have fantastic Big Data offering with the help of the cloud. We will discuss this later in this blog post. There are two different Cloud Deployment Models: 1) The Public Cloud and 2) The Private Cloud Public Cloud Public Cloud is the cloud infrastructure build by commercial providers (Amazon, Rackspace etc.) creates a highly scalable data center that hides the complex infrastructure from the consumer and provides various services. Private Cloud Private Cloud is the cloud infrastructure build by a single organization where they are managing highly scalable data center internally. Here is the quick comparison between Public Cloud and Private Cloud from Wikipedia:   Public Cloud Private Cloud Initial cost Typically zero Typically high Running cost Unpredictable Unpredictable Customization Impossible Possible Privacy No (Host has access to the data Yes Single sign-on Impossible Possible Scaling up Easy while within defined limits Laborious but no limits Hybrid Cloud Hybrid Cloud is the cloud infrastructure build with the composition of two or more clouds like public and private cloud. Hybrid cloud gives best of the both the world as it combines multiple cloud deployment models together. Cloud and Big Data – Common Characteristics There are many characteristics of the Cloud Architecture and Cloud Computing which are also essentially important for Big Data as well. They highly overlap and at many places it just makes sense to use the power of both the architecture and build a highly scalable framework. Here is the list of all the characteristics of cloud computing important in Big Data Scalability Elasticity Ad-hoc Resource Pooling Low Cost to Setup Infastructure Pay on Use or Pay as you Go Highly Available Leading Big Data Cloud Providers There are many players in Big Data Cloud but we will list a few of the known players in this list. Amazon Amazon is arguably the most popular Infrastructure as a Service (IaaS) provider. The history of how Amazon started in this business is very interesting. They started out with a massive infrastructure to support their own business. Gradually they figured out that their own resources are underutilized most of the time. They decided to get the maximum out of the resources they have and hence  they launched their Amazon Elastic Compute Cloud (Amazon EC2) service in 2006. Their products have evolved a lot recently and now it is one of their primary business besides their retail selling. Amazon also offers Big Data services understand Amazon Web Services. Here is the list of the included services: Amazon Elastic MapReduce – It processes very high volumes of data Amazon DynammoDB – It is fully managed NoSQL (Not Only SQL) database service Amazon Simple Storage Services (S3) – A web-scale service designed to store and accommodate any amount of data Amazon High Performance Computing – It provides low-tenancy tuned high performance computing cluster Amazon RedShift – It is petabyte scale data warehousing service Google Though Google is known for Search Engine, we all know that it is much more than that. Google Compute Engine – It offers secure, flexible computing from energy efficient data centers Google Big Query – It allows SQL-like queries to run against large datasets Google Prediction API – It is a cloud based machine learning tool Other Players Besides Amazon and Google we also have other players in the Big Data market as well. Microsoft is also attempting Big Data with the Cloud with Microsoft Azure. Additionally Rackspace and NASA together have initiated OpenStack. The goal of Openstack is to provide a massively scaled, multitenant cloud that can run on any hardware. Thing to Watch The cloud based solutions provides a great integration with the Big Data’s story as well it is very economical to implement as well. However, there are few things one should be very careful when deploying Big Data on cloud solutions. Here is a list of a few things to watch: Data Integrity Initial Cost Recurring Cost Performance Data Access Security Location Compliance Every company have different approaches to Big Data and have different rules and regulations. Based on various factors, one can implement their own custom Big Data solution on a cloud. Tomorrow In tomorrow’s blog post we will discuss about various Operational Databases supporting Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • World Record Oracle Business Intelligence Benchmark on SPARC T4-4

    - by Brian
    Oracle's SPARC T4-4 server configured with four SPARC T4 3.0 GHz processors delivered the first and best performance of 25,000 concurrent users on Oracle Business Intelligence Enterprise Edition (BI EE) 11g benchmark using Oracle Database 11g Release 2 running on Oracle Solaris 10. A SPARC T4-4 server running Oracle Business Intelligence Enterprise Edition 11g achieved 25,000 concurrent users with an average response time of 0.36 seconds with Oracle BI server cache set to ON. The benchmark data clearly shows that the underlying hardware, SPARC T4 server, and the Oracle BI EE 11g (11.1.1.6.0 64-bit) platform scales within a single system supporting 25,000 concurrent users while executing 415 transactions/sec. The benchmark demonstrated the scalability of Oracle Business Intelligence Enterprise Edition 11g 11.1.1.6.0, which was deployed in a vertical scale-out fashion on a single SPARC T4-4 server. Oracle Internet Directory configured on SPARC T4 server provided authentication for the 25,000 Oracle BI EE users with sub-second response time. A SPARC T4-4 with internal Solid State Drive (SSD) using the ZFS file system showed significant I/O performance improvement over traditional disk for the Web Catalog activity. In addition, ZFS helped get past the UFS limitation of 32767 sub-directories in a Web Catalog directory. The multi-threaded 64-bit Oracle Business Intelligence Enterprise Edition 11g and SPARC T4-4 server proved to be a successful combination by providing sub-second response times for the end user transactions, consuming only half of the available CPU resources at 25,000 concurrent users, leaving plenty of head room for increased load. The Oracle Business Intelligence on SPARC T4-4 server benchmark results demonstrate that comprehensive BI functionality built on a unified infrastructure with a unified business model yields best-in-class scalability, reliability and performance. Oracle BI EE 11g is a newer version of Business Intelligence Suite with richer and superior functionality. Results produced with Oracle BI EE 11g benchmark are not comparable to results with Oracle BI EE 10g benchmark. Oracle BI EE 11g is a more difficult benchmark to run, exercising more features of Oracle BI. Performance Landscape Results for the Oracle BI EE 11g version of the benchmark. Results are not comparable to the Oracle BI EE 10g version of the benchmark. Oracle BI EE 11g Benchmark System Number of Users Response Time (sec) 1 x SPARC T4-4 (4 x SPARC T4 3.0 GHz) 25,000 0.36 Results for the Oracle BI EE 10g version of the benchmark. Results are not comparable to the Oracle BI EE 11g version of the benchmark. Oracle BI EE 10g Benchmark System Number of Users 2 x SPARC T5440 (4 x SPARC T2+ 1.6 GHz) 50,000 1 x SPARC T5440 (4 x SPARC T2+ 1.6 GHz) 28,000 Configuration Summary Hardware Configuration: SPARC T4-4 server 4 x SPARC T4-4 processors, 3.0 GHz 128 GB memory 4 x 300 GB internal SSD Storage Configuration: "> Sun ZFS Storage 7120 16 x 146 GB disks Software Configuration: Oracle Solaris 10 8/11 Oracle Solaris Studio 12.1 Oracle Business Intelligence Enterprise Edition 11g (11.1.1.6.0) Oracle WebLogic Server 10.3.5 Oracle Internet Directory 11.1.1.6.0 Oracle Database 11g Release 2 Benchmark Description Oracle Business Intelligence Enterprise Edition (Oracle BI EE) delivers a robust set of reporting, ad-hoc query and analysis, OLAP, dashboard, and scorecard functionality with a rich end-user experience that includes visualization, collaboration, and more. The Oracle BI EE benchmark test used five different business user roles - Marketing Executive, Sales Representative, Sales Manager, Sales Vice-President, and Service Manager. These roles included a maximum of 5 different pre-built dashboards. Each dashboard page had an average of 5 reports in the form of a mix of charts, tables and pivot tables, returning anywhere from 50 rows to approximately 500 rows of aggregated data. The test scenario also included drill-down into multiple levels from a table or chart within a dashboard. The benchmark test scenario uses a typical business user sequence of dashboard navigation, report viewing, and drill down. For example, a Service Manager logs into the system and navigates to his own set of dashboards using Service Manager. The BI user selects the Service Effectiveness dashboard, which shows him four distinct reports, Service Request Trend, First Time Fix Rate, Activity Problem Areas, and Cost Per Completed Service Call spanning 2002 to 2005. The user then proceeds to view the Customer Satisfaction dashboard, which also contains a set of 4 related reports, drills down on some of the reports to see the detail data. The BI user continues to view more dashboards – Customer Satisfaction and Service Request Overview, for example. After navigating through those dashboards, the user logs out of the application. The benchmark test is executed against a full production version of the Oracle Business Intelligence 11g Applications with a fully populated underlying database schema. The business processes in the test scenario closely represent a real world customer scenario. See Also SPARC T4-4 Server oracle.com OTN Oracle Business Intelligence oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN WebLogic Suite oracle.com OTN Oracle Solaris 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 30 September 2012.

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  • NET Math Libraries

    - by JoshReuben
    NET Mathematical Libraries   .NET Builder for Matlab The MathWorks Inc. - http://www.mathworks.com/products/netbuilder/ MATLAB Builder NE generates MATLAB based .NET and COM components royalty-free deployment creates the components by encrypting MATLAB functions and generating either a .NET or COM wrapper around them. .NET/Link for Mathematica www.wolfram.com a product that 2-way integrates Mathematica and Microsoft's .NET platform call .NET from Mathematica - use arbitrary .NET types directly from the Mathematica language. use and control the Mathematica kernel from a .NET program. turns Mathematica into a scripting shell to leverage the computational services of Mathematica. write custom front ends for Mathematica or use Mathematica as a computational engine for another program comes with full source code. Leverages MathLink - a Wolfram Research's protocol for sending data and commands back and forth between Mathematica and other programs. .NET/Link abstracts the low-level details of the MathLink C API. Extreme Optimization http://www.extremeoptimization.com/ a collection of general-purpose mathematical and statistical classes built for the.NET framework. It combines a math library, a vector and matrix library, and a statistics library in one package. download the trial of version 4.0 to try it out. Multi-core ready - Full support for Task Parallel Library features including cancellation. Broad base of algorithms covering a wide range of numerical techniques, including: linear algebra (BLAS and LAPACK routines), numerical analysis (integration and differentiation), equation solvers. Mathematics leverages parallelism using .NET 4.0's Task Parallel Library. Basic math: Complex numbers, 'special functions' like Gamma and Bessel functions, numerical differentiation. Solving equations: Solve equations in one variable, or solve systems of linear or nonlinear equations. Curve fitting: Linear and nonlinear curve fitting, cubic splines, polynomials, orthogonal polynomials. Optimization: find the minimum or maximum of a function in one or more variables, linear programming and mixed integer programming. Numerical integration: Compute integrals over finite or infinite intervals, over 2D and higher dimensional regions. Integrate systems of ordinary differential equations (ODE's). Fast Fourier Transforms: 1D and 2D FFT's using managed or fast native code (32 and 64 bit) BigInteger, BigRational, and BigFloat: Perform operations with arbitrary precision. Vector and Matrix Library Real and complex vectors and matrices. Single and double precision for elements. Structured matrix types: including triangular, symmetrical and band matrices. Sparse matrices. Matrix factorizations: LU decomposition, QR decomposition, singular value decomposition, Cholesky decomposition, eigenvalue decomposition. Portability and performance: Calculations can be done in 100% managed code, or in hand-optimized processor-specific native code (32 and 64 bit). Statistics Data manipulation: Sort and filter data, process missing values, remove outliers, etc. Supports .NET data binding. Statistical Models: Simple, multiple, nonlinear, logistic, Poisson regression. Generalized Linear Models. One and two-way ANOVA. Hypothesis Tests: 12 14 hypothesis tests, including the z-test, t-test, F-test, runs test, and more advanced tests, such as the Anderson-Darling test for normality, one and two-sample Kolmogorov-Smirnov test, and Levene's test for homogeneity of variances. Multivariate Statistics: K-means cluster analysis, hierarchical cluster analysis, principal component analysis (PCA), multivariate probability distributions. Statistical Distributions: 25 29 continuous and discrete statistical distributions, including uniform, Poisson, normal, lognormal, Weibull and Gumbel (extreme value) distributions. Random numbers: Random variates from any distribution, 4 high-quality random number generators, low discrepancy sequences, shufflers. New in version 4.0 (November, 2010) Support for .NET Framework Version 4.0 and Visual Studio 2010 TPL Parallellized – multicore ready sparse linear program solver - can solve problems with more than 1 million variables. Mixed integer linear programming using a branch and bound algorithm. special functions: hypergeometric, Riemann zeta, elliptic integrals, Frensel functions, Dawson's integral. Full set of window functions for FFT's. Product  Price Update subscription Single Developer License $999  $399  Team License (3 developers) $1999  $799  Department License (8 developers) $3999  $1599  Site License (Unlimited developers in one physical location) $7999  $3199    NMath http://www.centerspace.net .NET math and statistics libraries matrix and vector classes random number generators Fast Fourier Transforms (FFTs) numerical integration linear programming linear regression curve and surface fitting optimization hypothesis tests analysis of variance (ANOVA) probability distributions principal component analysis cluster analysis built on the Intel Math Kernel Library (MKL), which contains highly-optimized, extensively-threaded versions of BLAS (Basic Linear Algebra Subroutines) and LAPACK (Linear Algebra PACKage). Product  Price Update subscription Single Developer License $1295 $388 Team License (5 developers) $5180 $1554   DotNumerics http://www.dotnumerics.com/NumericalLibraries/Default.aspx free DotNumerics is a website dedicated to numerical computing for .NET that includes a C# Numerical Library for .NET containing algorithms for Linear Algebra, Differential Equations and Optimization problems. The Linear Algebra library includes CSLapack, CSBlas and CSEispack, ports from Fortran to C# of LAPACK, BLAS and EISPACK, respectively. Linear Algebra (CSLapack, CSBlas and CSEispack). Systems of linear equations, eigenvalue problems, least-squares solutions of linear systems and singular value problems. Differential Equations. Initial-value problem for nonstiff and stiff ordinary differential equations ODEs (explicit Runge-Kutta, implicit Runge-Kutta, Gear's BDF and Adams-Moulton). Optimization. Unconstrained and bounded constrained optimization of multivariate functions (L-BFGS-B, Truncated Newton and Simplex methods).   Math.NET Numerics http://numerics.mathdotnet.com/ free an open source numerical library - includes special functions, linear algebra, probability models, random numbers, interpolation, integral transforms. A merger of dnAnalytics with Math.NET Iridium in addition to a purely managed implementation will also support native hardware optimization. constants & special functions complex type support real and complex, dense and sparse linear algebra (with LU, QR, eigenvalues, ... decompositions) non-uniform probability distributions, multivariate distributions, sample generation alternative uniform random number generators descriptive statistics, including order statistics various interpolation methods, including barycentric approaches and splines numerical function integration (quadrature) routines integral transforms, like fourier transform (FFT) with arbitrary lengths support, and hartley spectral-space aware sequence manipulation (signal processing) combinatorics, polynomials, quaternions, basic number theory. parallelized where appropriate, to leverage multi-core and multi-processor systems fully managed or (if available) using native libraries (Intel MKL, ACMS, CUDA, FFTW) provides a native facade for F# developers

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  • Handling Trailing Delimiters in HL7 Messages

    - by Thomas Canter
    Applies to: BizTalk Server 2006 with the HL7 1.3 Accelerator Outline of the problem Trailing Delimiters are empty values at the end of an object in a HL7 ER7 formatted message. Examples: Empty Field NTE|P| NTE|P|| Empty component ORC|1|725^ Empty Subcomponent ORC|1|||||27& Empty repeat OBR|1||||||||027~ Trailing delimiters indicate the following object exists and is empty, which is quite different from null, null is an explicit value indicated by a pair of double quotes -> "". The BizTalk HL7 Accelerator by default does not allow trailing delimiters. There are three methods to allow trailing delimiters. NOTE: All Schemas always allow trailing delimiters in the MSH Segment Using party identifiers MSH3.1 – Receive/inbound processing, using this value as a party allows you to configure the system to allow inbound trailing delimiters. MSH5.1 – Send/outbound processing, using this value as a party allows you to configure the system to allow outbound trailing delimiters. Generally, if you allow inbound trailing delimiters, unless you are willing to programmatically remove all trailing delimiters, then you need to configure the send to allow trailing delimiters. Add the appropriate parties to the BizTalk Parties list from these two fields in your message stream. Open the BizTalk HL7 Configuration tool and for each party check the "Allow trailing delimiters (separators)" check box on the Validation tab. Disadvantage – Each MSH3.1 and MSH5.1 value must be represented in the parties list and configured. Advantage – granular control over system behavior for each inbound/outbound system. Using instance properties of a pipeline used in a send port or receive location. Open the BizTalk Server Administration console locate the send port or receive location that contains the BTAHL72XReceivePipeline or BTAHL72XSendPipeline pipeline. Open the properties To the right of the pipeline selected locate the […] ellipses button In the property list, locate the "TrailingDelimiterAllowed" property and set it to True. Advantage – All messages through a particular Send Port or Receive Location will allow trailing delimiters. Disadvantage – Must configure each Send Port or Receive Location. No granular control over which remote parties will send or receive messages with trailing delimiters. Using a custom pipeline that uses a pre-configured BTA HL7 Pipeline component. Use Visual Studio to construct a custom receive and send pipeline using the appropriate assembler or dissasembler. Set the component property to "TrailingDelimitersAllowed" to True Compile and deploy the custom pipeline Use the custom pipeline instead of the standard pipeline for all HL7 message processing Advantage – All messages using the custom pipeline will automatically allow trailing delimiters. Disadvantage – Requires custom coding and development to create and deploy the custom pipeline. No granular control over which remote parties will send or receive messages with trailing delimiters. What does a Trailing Delimiter do to the XML Schema? Allowing trailing delimiters does not have the impact often expected in the actual XML Schema.The Schema reproduces the message with no data loss.Thus, the message when represented in XML must contain the extra fields, in order to reproduce the outbound message.Thus, a trialing delimiter results in an empty XML field.Trailing Delmiters are not stripped from the inbound message. Example:<PID_21>44172</PID_21><PID_21>9257</PID_21> -> the original maximum number of repeats<PID_21></PID_21> -> The empty repeated field Allowing trailing delimiters not remove the trailing delimiters from the message, it simply suppresses the check that will cause the message to fail parse with trailing delimiters. When can you not fix the problem by enabling trailing delimiters Each object in a message must have a location in the target BTAHL7 schema for its content to reside.If you have more objects in the message than are contained at that location, then enabling trailing delimiters will not resolve the problem. The schema must be extended to accommodate the empty message content.Examples: Extra Field NTE|P||||Only 4 fields in NTE Segment, the 4th field exists, but is empty. Extra component PID|1|1523|47^^^^^^^Only 5 components in a CX data type, the 5th component exists, but is empty Extra subcomponent ORC|1|||||27&&Only 2 subcomponents in a CQ data type, the 3rd subcomponent is empty, but exists. Extra Repeat PID|1||||||||||||||||||||4419~5217~Only 2 repeats allowed for the field "Mother's identifier", the repeat is empty, but exists. In each of these cases, you must locate the failing object and extend the type to allow an additional object of that type. FieldAdd a field of ST to the end of the segment with a suitable name in the segments_nnn.xsd Component Create a new Custom CX data type (i.e. CX_XtraComp) in the datatypes_nnn.xsd and add a new component to the custom CX data type. Update the field in the segments_nnn.xsd file to use the custom data type instead of the standard datatype. Subcomponent Create a new Custom CQ data type that accepts an additional TS value at the end of the data type. Create a custom TQ data type that uses the new custom CQ data type as the first subcomponent. Modify the ORC segment to use the new CQ data type at ORC.7 instead of the standard CQ data type. RepeatModify the Field definition for PID.21 in the segments_nnn.xsd to allow more repeats in the field.

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  • AWS: setting up auto-scale for EC2 instances

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/10/16/aws-setting-up-auto-scale-for-ec2-instances.aspxWith Amazon Web Services, there’s no direct equivalent to Azure Worker Roles – no Elastic Beanstalk-style application for .NET background workers. But you can get the auto-scale part by configuring an auto-scaling group for your EC2 instance. This is a step-by-step guide, that shows you how to create the auto-scaling configuration, which for EC2 you need to do with the command line, and then link your scaling policies to CloudWatch alarms in the Web console. I’m using queue size as my metric for CloudWatch,  which is a good fit if your background workers are pulling messages from a queue and processing them.  If the queue is getting too big, the “high” alarm will fire and spin up a new instance to share the workload. If the queue is draining down, the “low” alarm will fire and shut down one of the instances. To start with, you need to manually set up your app in an EC2 VM, for a background worker that would mean hosting your code in a Windows Service (I always use Topshelf). If you’re dual-running Azure and AWS, then you can isolate your logic in one library, with a generic entry point that has Start() and Stop()  functions, so your Worker Role and Windows Service are essentially using the same code. When you have your instance set up with the Windows Service running automatically, and you’ve tested it starts up and works properly from a reboot, shut the machine down and take an image of the VM, using Create Image (EBS AMI) from the Web Console: When that completes, you’ll have your own AMI which you can use to spin up new instances, and you’re ready to create your auto-scaling group. You need to dip into the command-line tools for this, so follow this guide to set up the AWS autoscale command line tool. Now we’re ready to go. 1. Create a launch configuration This launch configuration tells AWS what to do when a new instance needs to be spun up. You create it with the as-create-launch-config command, which looks like this: as-create-launch-config sc-xyz-launcher # name of the launch config --image-id ami-7b9e9f12 # id of the AMI you extracted from your VM --region eu-west-1 # which region the new instance gets created in --instance-type t1.micro # size of the instance to create --group quicklaunch-1 #security group for the new instance 2. Create an auto-scaling group The auto-scaling group links to the launch config, and defines the overall configuration of the collection of instances: as-create-auto-scaling-group sc-xyz-asg # auto-scaling group name --region eu-west-1 # region to create in --launch-configuration sc-xyz-launcher # name of the launch config to invoke for new instances --min-size 1 # minimum number of nodes in the group --max-size 5 # maximum number of nodes in the group --default-cooldown 300 # period to wait (in seconds) after each scaling event, before checking if another scaling event is required --availability-zones eu-west-1a eu-west-1b eu-west-1c # which availability zones you want your instances to be allocated in – multiple entries means EC@ will use any of them 3. Create a scale-up policy The policy dictates what will happen in response to a scaling event being triggered from a “high” alarm being breached. It links to the auto-scaling group; this sample results in one additional node being spun up: as-put-scaling-policy scale-up-policy # policy name -g sc-psod-woker-asg # auto-scaling group the policy works with --adjustment 1 # size of the adjustment --region eu-west-1 # region --type ChangeInCapacity # type of adjustment, this specifies a fixed number of nodes, but you can use PercentChangeInCapacity to make an adjustment relative to the current number of nodes, e.g. increasing by 50% 4. Create a scale-down policy The policy dictates what will happen in response to a scaling event being triggered from a “low” alarm being breached. It links to the auto-scaling group; this sample results in one node from the group being taken offline: as-put-scaling-policy scale-down-policy -g sc-psod-woker-asg "--adjustment=-1" # in Windows, use double-quotes to surround a negative adjustment value –-type ChangeInCapacity --region eu-west-1 5. Create a “high” CloudWatch alarm We’re done with the command line now. In the Web Console, open up the CloudWatch view and create a new alarm. This alarm will monitor your metrics and invoke the scale-up policy from your auto-scaling group, when the group is working too hard. Configure your metric – this example will fire the alarm if there are more than 10 messages in my queue for over a minute: Then link the alarm to the scale-up policy in your group: 6. Create a “low” CloudWatch alarm The opposite of step 4, this alarm will trigger when the instances in your group don’t have enough work to do (e.g fewer than 2 messages in the queue for 1 minute), and will invoke the scale-down policy. And that’s it. You don’t need your original VM as the auto-scale group has a minimum number of nodes connected. You can test out the scaling by flexing your CloudWatch metric – in this example, filling up a queue from a  stub publisher – and watching AWS create new nodes as required, then stopping the publisher and watch AWS kill off the spare nodes.

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  • An Alphabet of Eponymous Aphorisms, Programming Paradigms, Software Sayings, Annoying Alliteration

    - by Brian Schroer
    Malcolm Anderson blogged about “Einstein’s Razor” yesterday, which reminded me of my favorite software development “law”, the name of which I can never remember. It took much Wikipedia-ing to find it (Hofstadter’s Law – see below), but along the way I compiled the following list: Amara’s Law: We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run. Brook’s Law: Adding manpower to a late software project makes it later. Clarke’s Third Law: Any sufficiently advanced technology is indistinguishable from magic. Law of Demeter: Each unit should only talk to its friends; don't talk to strangers. Einstein’s Razor: “Make things as simple as possible, but not simpler” is the popular paraphrase, but what he actually said was “It can scarcely be denied that the supreme goal of all theory is to make the irreducible basic elements as simple and as few as possible without having to surrender the adequate representation of a single datum of experience”, an overly complicated quote which is an obvious violation of Einstein’s Razor. (You can tell by looking at a picture of Einstein that the dude was hardly an expert on razors or other grooming apparati.) Finagle's Law of Dynamic Negatives: Anything that can go wrong, will—at the worst possible moment. - O'Toole's Corollary: The perversity of the Universe tends towards a maximum. Greenspun's Tenth Rule: Any sufficiently complicated C or Fortran program contains an ad hoc, informally-specified, bug-ridden, slow implementation of half of Common Lisp. (Morris’s Corollary: “…including Common Lisp”) Hofstadter's Law: It always takes longer than you expect, even when you take into account Hofstadter's Law. Issawi’s Omelet Analogy: One cannot make an omelet without breaking eggs - but it is amazing how many eggs one can break without making a decent omelet. Jackson’s Rules of Optimization: Rule 1: Don't do it. Rule 2 (for experts only): Don't do it yet. Kaner’s Caveat: A program which perfectly meets a lousy specification is a lousy program. Liskov Substitution Principle (paraphrased): Functions that use pointers or references to base classes must be able to use objects of derived classes without knowing it Mason’s Maxim: Since human beings themselves are not fully debugged yet, there will be bugs in your code no matter what you do. Nils-Peter Nelson’s Nil I/O Rule: The fastest I/O is no I/O.    Occam's Razor: The simplest explanation is usually the correct one. Parkinson’s Law: Work expands so as to fill the time available for its completion. Quentin Tarantino’s Pie Principle: “…you want to go home have a drink and go and eat pie and talk about it.” (OK, he was talking about movies, not software, but I couldn’t find a “Q” quote about software. And wouldn’t it be cool to write a program so great that the users want to eat pie and talk about it?) Raymond’s Rule: Computer science education cannot make anybody an expert programmer any more than studying brushes and pigment can make somebody an expert painter.  Sowa's Law of Standards: Whenever a major organization develops a new system as an official standard for X, the primary result is the widespread adoption of some simpler system as a de facto standard for X. Turing’s Tenet: We shall do a much better programming job, provided we approach the task with a full appreciation of its tremendous difficulty, provided that we respect the intrinsic limitations of the human mind and approach the task as very humble programmers.  Udi Dahan’s Race Condition Rule: If you think you have a race condition, you don’t understand the domain well enough. These rules didn’t exist in the age of paper, there is no reason for them to exist in the age of computers. When you have race conditions, go back to the business and find out actual rules. Van Vleck’s Kvetching: We know about as much about software quality problems as they knew about the Black Plague in the 1600s. We've seen the victims' agonies and helped burn the corpses. We don't know what causes it; we don't really know if there is only one disease. We just suffer -- and keep pouring our sewage into our water supply. Wheeler’s Law: All problems in computer science can be solved by another level of indirection... Except for the problem of too many layers of indirection. Wheeler also said “Compatibility means deliberately repeating other people's mistakes.”. The Wrong Road Rule of Mr. X (anonymous): No matter how far down the wrong road you've gone, turn back. Yourdon’s Rule of Two Feet: If you think your management doesn't know what it's doing or that your organisation turns out low-quality software crap that embarrasses you, then leave. Zawinski's Law of Software Envelopment: Every program attempts to expand until it can read mail. Zawinski is also responsible for “Some people, when confronted with a problem, think 'I know, I'll use regular expressions.' Now they have two problems.” He once commented about X Windows widget toolkits: “Using these toolkits is like trying to make a bookshelf out of mashed potatoes.”

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  • World Record Batch Rate on Oracle JD Edwards Consolidated Workload with SPARC T4-2

    - by Brian
    Oracle produced a World Record batch throughput for single system results on Oracle's JD Edwards EnterpriseOne Day-in-the-Life benchmark using Oracle's SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2. The workload includes both online and batch workload. The SPARC T4-2 server delivered a result of 8,000 online users while concurrently executing a mix of JD Edwards EnterpriseOne Long and Short batch processes at 95.5 UBEs/min (Universal Batch Engines per minute). In order to obtain this record benchmark result, the JD Edwards EnterpriseOne, Oracle WebLogic and Oracle Database 11g Release 2 servers were executed each in separate Oracle Solaris Containers which enabled optimal system resources distribution and performance together with scalable and manageable virtualization. One SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2 utilized only 55% of the available CPU power. The Oracle DB server in a Shared Server configuration allows for optimized CPU resource utilization and significant memory savings on the SPARC T4-2 server without sacrificing performance. This configuration with SPARC T4-2 server has achieved 33% more Users/core, 47% more UBEs/min and 78% more Users/rack unit than the IBM Power 770 server. The SPARC T4-2 server with 2 processors ran the JD Edwards "Day-in-the-Life" benchmark and supported 8,000 concurrent online users while concurrently executing mixed batch workloads at 95.5 UBEs per minute. The IBM Power 770 server with twice as many processors supported only 12,000 concurrent online users while concurrently executing mixed batch workloads at only 65 UBEs per minute. This benchmark demonstrates more than 2x cost savings by consolidating the complete solution in a single SPARC T4-2 server compared to earlier published results of 10,000 users and 67 UBEs per minute on two SPARC T4-2 and SPARC T4-1. The Oracle DB server used mirrored (RAID 1) volumes for the database providing high availability for the data without impacting performance. Performance Landscape JD Edwards EnterpriseOne Day in the Life (DIL) Benchmark Consolidated Online with Batch Workload System Rack Units BatchRate(UBEs/m) Online Users Users /Units Users /Core Version SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 3 95.5 8,000 2,667 500 9.0.2 IBM Power 770 (4 x POWER7, 3.3 GHz, 32 cores) 8 65 12,000 1,500 375 9.0.2 Batch Rate (UBEs/m) — Batch transaction rate in UBEs per minute Configuration Summary Hardware Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 4 x 300 GB 10K RPM SAS internal disk 2 x 300 GB internal SSD 2 x Sun Storage F5100 Flash Arrays Software Configuration: Oracle Solaris 10 Oracle Solaris Containers JD Edwards EnterpriseOne 9.0.2 JD Edwards EnterpriseOne Tools (8.98.4.2) Oracle WebLogic Server 11g (10.3.4) Oracle HTTP Server 11g Oracle Database 11g Release 2 (11.2.0.1) Benchmark Description JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations. Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company. The workload consists of online transactions and the UBE – Universal Business Engine workload of 61 short and 4 long UBEs. LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time. The UBE processes workload runs from the JD Enterprise Application server. Oracle's UBE processes come as three flavors: Short UBEs < 1 minute engage in Business Report and Summary Analysis, Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address, Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs. The UBE workload generates large numbers of PDF files reports and log files. The UBE Queues are categorized as the QBATCHD, a single threaded queue for large and medium UBEs, and the QPROCESS queue for short UBEs run concurrently. Oracle's UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute. Key Points and Best Practices Two JD Edwards EnterpriseOne Application Servers, two Oracle WebLogic Servers 11g Release 1 coupled with two Oracle Web Tier HTTP server instances and one Oracle Database 11g Release 2 database on a single SPARC T4-2 server were hosted in separate Oracle Solaris Containers bound to four processor sets to demonstrate consolidation of multiple applications, web servers and the database with best resource utilizations. Interrupt fencing was configured on all Oracle Solaris Containers to channel the interrupts to processors other than the processor sets used for the JD Edwards Application server, Oracle WebLogic servers and the database server. A Oracle WebLogic vertical cluster was configured on each WebServer Container with twelve managed instances each to load balance users' requests and to provide the infrastructure that enables scaling to high number of users with ease of deployment and high availability. The database log writer was run in the real time RT class and bound to a processor set. The database redo logs were configured on the raw disk partitions. The Oracle Solaris Container running the Enterprise Application server completed 61 Short UBEs, 4 Long UBEs concurrently as the mixed size batch workload. The mixed size UBEs ran concurrently from the Enterprise Application server with the 8,000 online users driven by the LoadRunner. See Also SPARC T4-2 Server oracle.com OTN JD Edwards EnterpriseOne oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Oracle Fusion Middleware 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 09/30/2012.

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  • Building InstallShield based Installers using Team Build 2010

    - by jehan
    Last few weeks, I have been working on Application Packaging stuff using all the widely used tools like InstallShield, WISE, WiX and Visual Studio Installer. So, I thought it would be good to post about how to Build the Installers developed using these tools with Team Build 2010. This post will focus on how to build the InstallShield generated packages using Team Build 2010. For the release of VS2010, Microsoft has partnered with Flexera who are the makers of InstallShield to create InstallShield Limited Edition, especially for the customers of Visual Studio. First Microsoft planned to release WiX (Windows Installer Xml) with VS2010, but later Microsoft dropped  WiX from VS2010 due to reasons which are best known to them and partnered with InstallShield for Limited Edition. It disappointed lot of people because InstallShield Limited Edition provides only few features of InstallShield and it may not feasable to build complex installer packages using this and it also requires License, where as WiX is an open source with no license costs and it has proved efficient in building most complex packages. Only the last three features are available in InstallShield Limited Edition from the total features offered by InstallShield as shown in below list.                                                                                            Feature Limited Edition for Visual Studio 2010 Standalone Build System Maintain a clean build machine by using only the part of InstallShield that compiles the installations. InstallShield Best Practices Validation Suite Avoid common installation issues. Try and Die Functionality RCreate a fully functional trial version of your product. InstallShield Repackager Create Windows Installer setups from any legacy installation. Multilingual Support Present installation text in up to 35 languages. Microsoft App-V™ Support Deploy your applications as App-V virtual packages that run without conflict. Industry-Standard InstallScript Achieve maximum flexibility in your installations. Dialog Editor Modify the layout of existing end-user dialogs, create new custom dialogs, and more. Patch Creation Build updates and patches for your products. Setup Prerequisite Editor Easily control prerequisite restart behavior and source locations. String Editor View Control the localizable text strings displayed at run time with this spreadsheet-like table. Text File Changes View Configure search-and-replace actions for content in text files to be modified at run time. Virtual Machine Detection Block your installations from running on virtual machines. Unicode Support Improve multi-language installation development. Support for 64-Bit COM Extraction Extract COM data from a 64-bit COM server. Windows Installer Installation Chaining Add MSI packages to your main installation and chain them together. XML Support Save time by quickly testing XML configuration changes to installation projects. Billboard Support for Custom Branding Display Adobe Flash billboards and other graphic files during the install process. SaaS Support (IIS 7 and SSL Technologies) Easily deploy Windows-based Web applications. Project Assistant Jumpstart a project by using a simplified set of views. Support for Digital Signatures Save time by digitally signing all your files at build time. Easily Run Custom Actions Schedule a custom action to run at precisely the right moment in your installation. Installation Prerequisites Check for and install prerequisites before your installation is executed. To create a InstallShield project in Visual Studio and Build it using Team Build 2010, first you have to add the InstallShield Project template  to your Solution file. If you want to use InstallShield Limited edition you can add it from FileàNewà project àother Project Types àSetup and Deploymentà InstallShield LE and if you are using other versions of InstallShield, then you have to add it from  from FileàNewà project àInstallShield Projects. Here, I’m using  InstallShield 2011 Premier edition as I already have it Installed. I have created a simple package for TailSpin Application which has a Feature called Web, few components and a IIS Web Site for  TailSpin application.   Before started working on this, I thought I may need to build the package by calling invoke process activity in build process template or have to create a new custom activity. But, it got build without any changes to build process template. But, it was failing with below error message. C:\Program Files (x86)\MSBuild\InstallShield\2011\InstallShield.targets (68): The "InstallShield.Tasks.InstallShield" task could not be loaded from the assembly C:\Program Files (x86)\MSBuild\InstallShield\2010Limited\InstallShield.Tasks.dll. Could not load file or assembly 'file:///C:\Program Files(x86)\MSBuild\InstallShield\2011\InstallShield.Tasks.dll' or one of its dependencies. An attempt was made to load a program with an incorrect format. Confirm that the <UsingTask> declaration is correct, that the assembly and all its dependencies are available, and that the task contains a public class that implements Microsoft.Build.Framework.ITask. This error is due to 64-bit build machine which I’m using. This issue will be replicable if you are queuing a build on a 64-bit build machine. To avoid this you have to ensure that you configured the build definition for your InstallShield project to load the InstallShield.Tasks.dll file (which is a 32-bit file); otherwise, you will encounter this build error informing you that the InstallShield.Tasks.dll file could not be loaded. To select the 32-bit version of MSBuild, click the Process tab of your build definition in Team Explorer. Then, under the Advanced node, find the MSBuild Platform setting, and select x86. Note that if you are using a 32-bit build machine, you can select either Auto or x86 for the MSBuild Platform setting.  Once I did above changes, the build got successful.

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  • Login failed for user 'sa' because the account is currently locked out. The system administrator can

    - by cabhilash
    Login failed for user 'sa' because the account is currently locked out. The system administrator can unlock it. (Microsoft SQL Server, Error: 18486) SQL server has local password policies. If policy is enabled which locks down the account after X number of failed attempts then the account is automatically locked down.This error with 'sa' account is very common. sa is default administartor login available with SQL server. So there are chances that an ousider has tried to bruteforce your system. (This can cause even if a legitimate tries to access the account with wrong password.Sometimes a user would have changed the password without informing others. So the other users would try to lo) You can unlock the account with the following options (use another admin account or connect via windows authentication) Alter account & unlock ALTER LOGIN sa WITH PASSWORD='password' UNLOCK Use another account Almost everyone is aware of the sa account. This can be the potential security risk. Even if you provide strong password hackers can lock the account by providing the wrong password. ( You can provide extra security by installing firewall or changing the default port but these measures are not always practical). As a best practice you can disable the sa account and use another account with same privileges.ALTER LOGIN sa DISABLE You can edit the lock-ot options using gpedit.msc( in command prompt type gpedit.msc and press enter). Navigate to Account Lokout policy as shown in the figure The Following options are available Account lockout threshold This security setting determines the number of failed logon attempts that causes a user account to be locked out. A locked-out account cannot be used until it is reset by an administrator or until the lockout duration for the account has expired. You can set a value between 0 and 999 failed logon attempts. If you set the value to 0, the account will never be locked out. Failed password attempts against workstations or member servers that have been locked using either CTRL+ALT+DELETE or password-protected screen savers count as failed logon attempts. Account lockout duration This security setting determines the number of minutes a locked-out account remains locked out before automatically becoming unlocked. The available range is from 0 minutes through 99,999 minutes. If you set the account lockout duration to 0, the account will be locked out until an administrator explicitly unlocks it. If an account lockout threshold is defined, the account lockout duration must be greater than or equal to the reset time. Default: None, because this policy setting only has meaning when an Account lockout threshold is specified. Reset account lockout counter after This security setting determines the number of minutes that must elapse after a failed logon attempt before the failed logon attempt counter is reset to 0 bad logon attempts. The available range is 1 minute to 99,999 minutes. If an account lockout threshold is defined, this reset time must be less than or equal to the Account lockout duration. Default: None, because this policy setting only has meaning when an Account lockout threshold is specified.When creating SQL user you can set CHECK_POLICY=on which will enforce the windows password policy on the account. The following policies will be applied Define the Enforce password history policy setting so that several previous passwords are remembered. With this policy setting, users cannot use the same password when their password expires.  Define the Maximum password age policy setting so that passwords expire as often as necessary for your environment, typically, every 30 to 90 days. With this policy setting, if an attacker cracks a password, the attacker only has access to the network until the password expires.  Define the Minimum password age policy setting so that passwords cannot be changed until they are more than a certain number of days old. This policy setting works in combination with the Enforce password historypolicy setting. If a minimum password age is defined, users cannot repeatedly change their passwords to get around the Enforce password history policy setting and then use their original password. Users must wait the specified number of days to change their passwords.  Define a Minimum password length policy setting so that passwords must consist of at least a specified number of characters. Long passwords--seven or more characters--are usually stronger than short ones. With this policy setting, users cannot use blank passwords, and they have to create passwords that are a certain number of characters long.  Enable the Password must meet complexity requirements policy setting. This policy setting checks all new passwords to ensure that they meet basic strong password requirements.  Password must meet the following complexity requirement, when they are changed or created: Not contain the user's entire Account Name or entire Full Name. The Account Name and Full Name are parsed for delimiters: commas, periods, dashes or hyphens, underscores, spaces, pound signs, and tabs. If any of these delimiters are found, the Account Name or Full Name are split and all sections are verified not to be included in the password. There is no check for any character or any three characters in succession. Contain characters from three of the following five categories:  English uppercase characters (A through Z) English lowercase characters (a through z) Base 10 digits (0 through 9) Non-alphabetic characters (for example, !, $, #, %) A catch-all category of any Unicode character that does not fall under the previous four categories. This fifth category can be regionally specific.

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  • Slow boot on Ubuntu 12.04

    - by Hailwood
    My Ubuntu is booting really slow (Windows is booting faster...). I am using Ubuntu a Dell Inspiron 1545 Pentium(R) Dual-Core CPU T4300 @ 2.10GHz, 4GB Ram, 500GB HDD running Ubuntu 12.04 with gnome-shell 3.4.1. After running dmesg the culprit seems to be this section, in particular the last three lines: [26.557659] ADDRCONF(NETDEV_UP): eth0: link is not ready [26.565414] ADDRCONF(NETDEV_UP): eth0: link is not ready [27.355355] Console: switching to colour frame buffer device 170x48 [27.362346] fb0: radeondrmfb frame buffer device [27.362347] drm: registered panic notifier [27.362357] [drm] Initialized radeon 2.12.0 20080528 for 0000:01:00.0 on minor 0 [27.617435] init: udev-fallback-graphics main process (1049) terminated with status 1 [30.064481] init: plymouth-stop pre-start process (1500) terminated with status 1 [51.708241] CE: hpet increased min_delta_ns to 20113 nsec [59.448029] eth2: no IPv6 routers present But I have no idea how to start debugging this. sudo lshw -C video $ sudo lshw -C video *-display description: VGA compatible controller product: RV710 [Mobility Radeon HD 4300 Series] vendor: Hynix Semiconductor (Hyundai Electronics) physical id: 0 bus info: pci@0000:01:00.0 version: 00 width: 32 bits clock: 33MHz capabilities: pm pciexpress msi vga_controller bus_master cap_list rom configuration: driver=fglrx_pci latency=0 resources: irq:48 memory:e0000000-efffffff ioport:de00(size=256) memory:f6df0000-f6dfffff memory:f6d00000-f6d1ffff After loading the propriety driver my new dmesg log is below (starting from the first major time gap): [2.983741] EXT4-fs (sda6): mounted filesystem with ordered data mode. Opts: (null) [25.094327] ADDRCONF(NETDEV_UP): eth0: link is not ready [25.119737] udevd[520]: starting version 175 [25.167086] lp: driver loaded but no devices found [25.215341] fglrx: module license 'Proprietary. (C) 2002 - ATI Technologies, Starnberg, GERMANY' taints kernel. [25.215345] Disabling lock debugging due to kernel taint [25.231924] wmi: Mapper loaded [25.318414] lib80211: common routines for IEEE802.11 drivers [25.318418] lib80211_crypt: registered algorithm 'NULL' [25.331631] [fglrx] Maximum main memory to use for locked dma buffers: 3789 MBytes. [25.332095] [fglrx] vendor: 1002 device: 9552 count: 1 [25.334206] [fglrx] ioport: bar 1, base 0xde00, size: 0x100 [25.334229] pci 0000:01:00.0: PCI INT A -> GSI 16 (level, low) -> IRQ 16 [25.334235] pci 0000:01:00.0: setting latency timer to 64 [25.337109] [fglrx] Kernel PAT support is enabled [25.337140] [fglrx] module loaded - fglrx 8.96.4 [Mar 12 2012] with 1 minors [25.342803] Adding 4189180k swap on /dev/sda7. Priority:-1 extents:1 across:4189180k [25.364031] type=1400 audit(1338241723.027:2): apparmor="STATUS" operation="profile_load" name="/sbin/dhclient" pid=606 comm="apparmor_parser" [25.364491] type=1400 audit(1338241723.031:3): apparmor="STATUS" operation="profile_load" name="/usr/lib/NetworkManager/nm-dhcp-client.action" pid=606 comm="apparmor_parser" [25.364760] type=1400 audit(1338241723.031:4): apparmor="STATUS" operation="profile_load" name="/usr/lib/connman/scripts/dhclient-script" pid=606 comm="apparmor_parser" [25.394328] wl 0000:0c:00.0: PCI INT A -> GSI 17 (level, low) -> IRQ 17 [25.394343] wl 0000:0c:00.0: setting latency timer to 64 [25.415531] acpi device:36: registered as cooling_device2 [25.416688] input: Video Bus as /devices/LNXSYSTM:00/device:00/PNP0A03:00/device:34/LNXVIDEO:00/input/input6 [25.416795] ACPI: Video Device [VID] (multi-head: yes rom: no post: no) [25.416865] [Firmware Bug]: Duplicate ACPI video bus devices for the same VGA controller, please try module parameter "video.allow_duplicates=1"if the current driver doesn't work. [25.425133] lib80211_crypt: registered algorithm 'TKIP' [25.448058] snd_hda_intel 0000:00:1b.0: PCI INT A -> GSI 21 (level, low) -> IRQ 21 [25.448321] snd_hda_intel 0000:00:1b.0: irq 47 for MSI/MSI-X [25.448353] snd_hda_intel 0000:00:1b.0: setting latency timer to 64 [25.738867] eth1: Broadcom BCM4315 802.11 Hybrid Wireless Controller 5.100.82.38 [25.761213] input: HDA Intel Mic as /devices/pci0000:00/0000:00:1b.0/sound/card0/input7 [25.761406] input: HDA Intel Headphone as /devices/pci0000:00/0000:00:1b.0/sound/card0/input8 [25.783432] dcdbas dcdbas: Dell Systems Management Base Driver (version 5.6.0-3.2) [25.908318] EXT4-fs (sda6): re-mounted. Opts: errors=remount-ro [25.928155] input: Dell WMI hotkeys as /devices/virtual/input/input9 [25.960561] udevd[543]: renamed network interface eth1 to eth2 [26.285688] init: failsafe main process (835) killed by TERM signal [26.396426] input: PS/2 Mouse as /devices/platform/i8042/serio2/input/input10 [26.423108] input: AlpsPS/2 ALPS GlidePoint as /devices/platform/i8042/serio2/input/input11 [26.511297] Bluetooth: Core ver 2.16 [26.511383] NET: Registered protocol family 31 [26.511385] Bluetooth: HCI device and connection manager initialized [26.511388] Bluetooth: HCI socket layer initialized [26.511391] Bluetooth: L2CAP socket layer initialized [26.512079] Bluetooth: SCO socket layer initialized [26.530164] Bluetooth: BNEP (Ethernet Emulation) ver 1.3 [26.530168] Bluetooth: BNEP filters: protocol multicast [26.553893] type=1400 audit(1338241724.219:5): apparmor="STATUS" operation="profile_replace" name="/sbin/dhclient" pid=928 comm="apparmor_parser" [26.554860] Bluetooth: RFCOMM TTY layer initialized [26.554866] Bluetooth: RFCOMM socket layer initialized [26.554868] Bluetooth: RFCOMM ver 1.11 [26.557910] type=1400 audit(1338241724.223:6): apparmor="STATUS" operation="profile_load" name="/usr/lib/lightdm/lightdm/lightdm-guest-session-wrapper" pid=927 comm="apparmor_parser" [26.559166] type=1400 audit(1338241724.223:7): apparmor="STATUS" operation="profile_replace" name="/usr/lib/NetworkManager/nm-dhcp-client.action" pid=928 comm="apparmor_parser" [26.559574] type=1400 audit(1338241724.223:8): apparmor="STATUS" operation="profile_replace" name="/usr/lib/connman/scripts/dhclient-script" pid=928 comm="apparmor_parser" [26.575519] type=1400 audit(1338241724.239:9): apparmor="STATUS" operation="profile_load" name="/usr/lib/telepathy/mission-control-5" pid=931 comm="apparmor_parser" [26.581100] type=1400 audit(1338241724.247:10): apparmor="STATUS" operation="profile_load" name="/usr/lib/telepathy/telepathy-*" pid=931 comm="apparmor_parser" [26.582794] type=1400 audit(1338241724.247:11): apparmor="STATUS" operation="profile_load" name="/usr/bin/evince" pid=929 comm="apparmor_parser" [26.605672] ppdev: user-space parallel port driver [27.592475] sky2 0000:09:00.0: eth0: enabling interface [27.604329] ADDRCONF(NETDEV_UP): eth0: link is not ready [27.606962] ADDRCONF(NETDEV_UP): eth0: link is not ready [27.852509] vesafb: mode is 1024x768x32, linelength=4096, pages=0 [27.852513] vesafb: scrolling: redraw [27.852515] vesafb: Truecolor: size=0:8:8:8, shift=0:16:8:0 [27.852523] mtrr: type mismatch for e0000000,400000 old: write-back new: write-combining [27.852527] mtrr: type mismatch for e0000000,200000 old: write-back new: write-combining [27.852531] mtrr: type mismatch for e0000000,100000 old: write-back new: write-combining [27.852534] mtrr: type mismatch for e0000000,80000 old: write-back new: write-combining [27.852538] mtrr: type mismatch for e0000000,40000 old: write-back new: write-combining [27.852541] mtrr: type mismatch for e0000000,20000 old: write-back new: write-combining [27.852544] mtrr: type mismatch for e0000000,10000 old: write-back new: write-combining [27.852548] mtrr: type mismatch for e0000000,8000 old: write-back new: write-combining [27.852551] mtrr: type mismatch for e0000000,4000 old: write-back new: write-combining [27.852554] mtrr: type mismatch for e0000000,2000 old: write-back new: write-combining [27.852558] mtrr: type mismatch for e0000000,1000 old: write-back new: write-combining [27.853154] vesafb: framebuffer at 0xe0000000, mapped to 0xffffc90005580000, using 3072k, total 3072k [27.853405] Console: switching to colour frame buffer device 128x48 [27.853426] fb0: VESA VGA frame buffer device [28.539800] fglrx_pci 0000:01:00.0: irq 48 for MSI/MSI-X [28.540552] [fglrx] Firegl kernel thread PID: 1168 [28.540679] [fglrx] Firegl kernel thread PID: 1169 [28.540789] [fglrx] Firegl kernel thread PID: 1170 [28.540932] [fglrx] IRQ 48 Enabled [29.845620] [fglrx] Gart USWC size:1236 M. [29.845624] [fglrx] Gart cacheable size:489 M. [29.845629] [fglrx] Reserved FB block: Shared offset:0, size:1000000 [29.845632] [fglrx] Reserved FB block: Unshared offset:fc21000, size:3df000 [29.845635] [fglrx] Reserved FB block: Unshared offset:1fffb000, size:5000 [59.700023] eth2: no IPv6 routers present

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  • Do Not Optimize Without Measuring

    - by Alois Kraus
    Recently I had to do some performance work which included reading a lot of code. It is fascinating with what ideas people come up to solve a problem. Especially when there is no problem. When you look at other peoples code you will not be able to tell if it is well performing or not by reading it. You need to execute it with some sort of tracing or even better under a profiler. The first rule of the performance club is not to think and then to optimize but to measure, think and then optimize. The second rule is to do this do this in a loop to prevent slipping in bad things for too long into your code base. If you skip for some reason the measure step and optimize directly it is like changing the wave function in quantum mechanics. This has no observable effect in our world since it does represent only a probability distribution of all possible values. In quantum mechanics you need to let the wave function collapse to a single value. A collapsed wave function has therefore not many but one distinct value. This is what we physicists call a measurement. If you optimize your application without measuring it you are just changing the probability distribution of your potential performance values. Which performance your application actually has is still unknown. You only know that it will be within a specific range with a certain probability. As usual there are unlikely values within your distribution like a startup time of 20 minutes which should only happen once in 100 000 years. 100 000 years are a very short time when the first customer tries your heavily distributed networking application to run over a slow WIFI network… What is the point of this? Every programmer/architect has a mental performance model in his head. A model has always a set of explicit preconditions and a lot more implicit assumptions baked into it. When the model is good it will help you to think of good designs but it can also be the source of problems. In real world systems not all assumptions of your performance model (implicit or explicit) hold true any longer. The only way to connect your performance model and the real world is to measure it. In the WIFI example the model did assume a low latency high bandwidth LAN connection. If this assumption becomes wrong the system did have a drastic change in startup time. Lets look at a example. Lets assume we want to cache some expensive UI resource like fonts objects. For this undertaking we do create a Cache class with the UI themes we want to support. Since Fonts are expensive objects we do create it on demand the first time the theme is requested. A simple example of a Theme cache might look like this: using System; using System.Collections.Generic; using System.Drawing; struct Theme { public Color Color; public Font Font; } static class ThemeCache { static Dictionary<string, Theme> _Cache = new Dictionary<string, Theme> { {"Default", new Theme { Color = Color.AliceBlue }}, {"Theme12", new Theme { Color = Color.Aqua }}, }; public static Theme Get(string theme) { Theme cached = _Cache[theme]; if (cached.Font == null) { Console.WriteLine("Creating new font"); cached.Font = new Font("Arial", 8); } return cached; } } class Program { static void Main(string[] args) { Theme item = ThemeCache.Get("Theme12"); item = ThemeCache.Get("Theme12"); } } This cache does create font objects only once since on first retrieve of the Theme object the font is added to the Theme object. When we let the application run it should print “Creating new font” only once. Right? Wrong! The vigilant readers have spotted the issue already. The creator of this cache class wanted to get maximum performance. So he decided that the Theme object should be a value type (struct) to not put too much pressure on the garbage collector. The code Theme cached = _Cache[theme]; if (cached.Font == null) { Console.WriteLine("Creating new font"); cached.Font = new Font("Arial", 8); } does work with a copy of the value stored in the dictionary. This means we do mutate a copy of the Theme object and return it to our caller. But the original Theme object in the dictionary will have always null for the Font field! The solution is to change the declaration of struct Theme to class Theme or to update the theme object in the dictionary. Our cache as it is currently is actually a non caching cache. The funny thing was that I found out with a profiler by looking at which objects where finalized. I found way too many font objects to be finalized. After a bit debugging I found the allocation source for Font objects was this cache. Since this cache was there for years it means that the cache was never needed since I found no perf issue due to the creation of font objects. the cache was never profiled if it did bring any performance gain. to make the cache beneficial it needs to be accessed much more often. That was the story of the non caching cache. Next time I will write something something about measuring.

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  • Retrieve Performance Data from SOA Infrastructure Database

    - by fip
    My earlier blog posting shows how to enable, retrieve and interpret BPEL engine performance statistics to aid performance troubleshooting. The strength of BPEL engine statistics at EM is its break down per request. But there are some limitations with the BPEL performance statistics mentioned in that blog posting: The statistics were stored in memory instead of being persisted. To avoid memory overflow, the data are stored to a buffer with limited size. When the statistic entries exceed the limitation, old data will be flushed out to give ways to new statistics. Therefore it can only keep the last X number of entries of data. The statistics 5 hour ago may not be there anymore. The BPEL engine performance statistics only includes latencies. It does not provide throughputs. Fortunately, Oracle SOA Suite runs with the SOA Infrastructure database and a lot of performance data are naturally persisted there. It is at a more coarse grain than the in-memory BPEL Statistics, but it does have its own strengths as it is persisted. Here I would like offer examples of some basic SQL queries you can run against the infrastructure database of Oracle SOA Suite 11G to acquire the performance statistics for a given period of time. You can run it immediately after you modify the date range to match your actual system. 1. Asynchronous/one-way messages incoming rates The following query will show number of messages sent to one-way/async BPEL processes during a given time period, organized by process names and states select composite_name composite, state, count(*) Count from dlv_message where receive_date >= to_timestamp('2012-10-24 21:00:00','YYYY-MM-DD HH24:MI:SS') and receive_date <= to_timestamp('2012-10-24 21:59:59','YYYY-MM-DD HH24:MI:SS') group by composite_name, state order by Count; 2. Throughput of BPEL process instances The following query shows the number of synchronous and asynchronous process instances created during a given time period. It list instances of all states, including the unfinished and faulted ones. The results will include all composites cross all SOA partitions select state, count(*) Count, composite_name composite, component_name,componenttype from cube_instance where creation_date >= to_timestamp('2012-10-24 21:00:00','YYYY-MM-DD HH24:MI:SS') and creation_date <= to_timestamp('2012-10-24 21:59:59','YYYY-MM-DD HH24:MI:SS') group by composite_name, component_name, componenttype order by count(*) desc; 3. Throughput and latencies of BPEL process instances This query is augmented on the previous one, providing more comprehensive information. It gives not only throughput but also the maximum, minimum and average elapse time BPEL process instances. select composite_name Composite, component_name Process, componenttype, state, count(*) Count, trunc(Max(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) MaxTime, trunc(Min(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) MinTime, trunc(AVG(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) AvgTime from cube_instance where creation_date >= to_timestamp('2012-10-24 21:00:00','YYYY-MM-DD HH24:MI:SS') and creation_date <= to_timestamp('2012-10-24 21:59:59','YYYY-MM-DD HH24:MI:SS') group by composite_name, component_name, componenttype, state order by count(*) desc;   4. Combine all together Now let's combine all of these 3 queries together, and parameterize the start and end time stamps to make the script a bit more robust. The following script will prompt for the start and end time before querying against the database: accept startTime prompt 'Enter start time (YYYY-MM-DD HH24:MI:SS)' accept endTime prompt 'Enter end time (YYYY-MM-DD HH24:MI:SS)' Prompt "==== Rejected Messages ===="; REM 2012-10-24 21:00:00 REM 2012-10-24 21:59:59 select count(*), composite_dn from rejected_message where created_time >= to_timestamp('&&StartTime','YYYY-MM-DD HH24:MI:SS') and created_time <= to_timestamp('&&EndTime','YYYY-MM-DD HH24:MI:SS') group by composite_dn; Prompt " "; Prompt "==== Throughput of one-way/asynchronous messages ===="; select state, count(*) Count, composite_name composite from dlv_message where receive_date >= to_timestamp('&StartTime','YYYY-MM-DD HH24:MI:SS') and receive_date <= to_timestamp('&EndTime','YYYY-MM-DD HH24:MI:SS') group by composite_name, state order by Count; Prompt " "; Prompt "==== Throughput and latency of BPEL process instances ====" select state, count(*) Count, trunc(Max(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) MaxTime, trunc(Min(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) MinTime, trunc(AVG(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) AvgTime, composite_name Composite, component_name Process, componenttype from cube_instance where creation_date >= to_timestamp('&StartTime','YYYY-MM-DD HH24:MI:SS') and creation_date <= to_timestamp('&EndTime','YYYY-MM-DD HH24:MI:SS') group by composite_name, component_name, componenttype, state order by count(*) desc;  

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  • Code Structure / Level Design: Plants vs Zombies game level dissection

    - by lalan
    Hi Friends, I am interested in learning the class structure of Plants vs Zombies, particularly level design; for those who haven't played it - this video contains nice play-through: http://www.youtube.com/watch?v=89DfdOIJ4xw. How would I go ahead and design the code, mostly structure & classes, which allows for maximum flexibility & clean development? I am familiar with data driven design concepts, and would use events to handle most of dynamic behavior. Dissection at macro level: (Once every Level) Load tilemap, props, etc -- basically build the map (Once every Level) Camera Movement - might consider it as short cut-scene (Once every Level) Show Enemies you'll face during present level (Once every Level) Unit Selection Window/Panel - selection of defensive plants (Once every Level) Camera Movement - might consider it as short cut-scene (Once every Level) HUD Creation - based on unit selection (Level Loop) Enemy creation - based on types of zombies allowed (Level Loop) Sun/Resource generation (Level Loop) Show messages like 'huge wave of zombies coming', 'final wave' (Level Loop) Other unique events - Spawn gifts, money, tombstones, etc (Once every Level) Unlock new plant Potential game scripts: a) Level definitions: Level_1_1.xml, Level_1_2.xml, etc. Level_1_1.xml :: Sample script <map> <tilemap>tilemapFrontLawn</tilemap> <SpawnPoints> tiles where particular type of zombies (land vs water) may spawn</spawnPoints> <props> position, entity array -- lawnmower, </props> </map> <zombies> <... list of zombies who gonna attack by ids...> </zombies> <plants> <... list by plants which are available for defense by ids...> </plants> <progression> <ZombieWave name='first wave' spawnScript='zombieLightWave.lua' unlock='null'> <startMessages time=1.5>Ready</startMessages> <endMessages time=1.5>Huge wave of zombies incoming</endMessages> </ZombieWave> </progression> b) Entities definitions: .xmls containing zombies, plants, sun, lawnmower, coins, etc description. Potential classes: //LevelManager - Based on the level under play, it will load level script. Few of the // functions it may have: class LevelManager { public: bool load(string levelFileName); bool enter(); bool update(float deltatime); bool exit(); private: LevelData* mLevelData; } // LevelData - Contains the details of level loaded by LevelManager. class LevelData { private: string file; // array of camera,dialog,attackwaves, etc in active level LevelCutSceneCamera** mArrayCutSceneCamera; LevelCutSceneDialog** mArrayCutSceneDialog; LevelAttackWave** mArrayAttackWave; .... // which camera,dialog,attackwave is active in level uint mCursorCutSceneCamera; uint mCursorCutSceneDialog; uint mCursorAttackWave; public: // based on cursor, get the next camera,dialog,attackwave,etc in active level // return false/true based on failure/success bool nextCutSceneCamera(LevelCutSceneCamera**); bool nextCutSceneDialog(LevelCutSceneDialog**); } // LevelUnderPlay- LevelManager class LevelUnderPlay { private: LevelCutSceneCamera* mCutSceneCamera; LevelCutSceneDialog* mCutSceneDialog; LevelAttackWave* mAttackWave; Entities** mSelectedPlants; Entities** mAllowedZombies; bool isCutSceneCameraActive; public: bool enter(); bool update(float deltatime); bool exit(); } I am totally confused.. :( Does it make sense of using class composition (have flat class hierarchy) for managing levels. Is it a good idea to just add/remove/update sprites (or any drawable stuff) to current scene from LevelManager or LevelUnderPlay? If I want to make non-linear level design, how should I go ahead? Perhaps I would need a LevelProgression class, which would decide what to do based on decision tree. Any suggestions would be appreciated very much. Thank for your time, lalan

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  • Aggregating cache data from OCEP in CQL

    - by Manju James
    There are several use cases where OCEP applications need to join stream data with external data, such as data available in a Coherence cache. OCEP’s streaming language, CQL, supports simple cache-key based joins of stream data with data in Coherence (more complex queries will be supported in a future release). However, there are instances where you may need to aggregate the data in Coherence based on input data from a stream. This blog describes a sample that does just that. For our sample, we will use a simplified credit card fraud detection use case. The input to this sample application is a stream of credit card transaction data. The input stream contains information like the credit card ID, transaction time and transaction amount. The purpose of this application is to detect suspicious transactions and send out a warning event. For the sake of simplicity, we will assume that all transactions with amounts greater than $1000 are suspicious. The transaction history is available in a Coherence distributed cache. For every suspicious transaction detected, a warning event must be sent with maximum amount, total amount and total number of transactions over the past 30 days, as shown in the diagram below. Application Input Stream input to the EPN contains events of type CCTransactionEvent. This input has to be joined with the cache with all credit card transactions. The cache is configured in the EPN as shown below: <wlevs:caching-system id="CohCacheSystem" provider="coherence"/> <wlevs:cache id="CCTransactionsCache" value-type="CCTransactionEvent" key-properties="cardID, transactionTime" caching-system="CohCacheSystem"> </wlevs:cache> Application Output The output that must be produced by the application is a fraud warning event. This event is configured in the spring file as shown below. Source for cardHistory property can be seen here. <wlevs:event-type type-name="FraudWarningEvent"> <wlevs:properties type="tuple"> <wlevs:property name="cardID" type="CHAR"/> <wlevs:property name="transactionTime" type="BIGINT"/> <wlevs:property name="transactionAmount" type="DOUBLE"/> <wlevs:property name="cardHistory" type="OBJECT"/> </wlevs:properties </wlevs:event-type> Cache Data Aggregation using Java Cartridge In the output warning event, cardHistory property contains data from the cache aggregated over the past 30 days. To get this information, we use a java cartridge method. This method uses Coherence’s query API on credit card transactions cache to get the required information. Therefore, the java cartridge method requires a reference to the cache. This may be set up by configuring it in the spring context file as shown below: <bean class="com.oracle.cep.ccfraud.CCTransactionsAggregator"> <property name="cache" ref="CCTransactionsCache"/> </bean> This is used by the java class to set a static property: public void setCache(Map cache) { s_cache = (NamedCache) cache; } The code snippet below shows how the total of all the transaction amounts in the past 30 days is computed. Rest of the information required by CardHistory object is calculated in a similar manner. Complete source of this class can be found here. To find out more information about using Coherence's API to query a cache, please refer Coherence Developer’s Guide. public static CreditHistoryData(String cardID) { … Filter filter = QueryHelper.createFilter("cardID = :cardID and transactionTime :transactionTime", map); CardHistoryData history = new CardHistoryData(); Double sum = (Double) s_cache.aggregate(filter, new DoubleSum("getTransactionAmount")); history.setTotalAmount(sum); … return history; } The java cartridge method is used from CQL as seen below: select cardID, transactionTime, transactionAmount, CCTransactionsAggregator.execute(cardID) as cardHistory from inputChannel where transactionAmount1000 This produces a warning event, with history data, for every credit card transaction over $1000. That is all there is to it. The complete source for the sample application, along with the configuration files, is available here. In the sample, I use a simple java bean to load the cache with initial transaction history data. An input adapter is used to create and send transaction events for the input stream.

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  • Autoscaling in a modern world&hellip;. Part 2

    - by Steve Loethen
    When we last left off, we had a web application spinning away in the cloud, and a local console application watching it and reacting to changes in demand.  Reactions that were specified by a set of rules.  Let’s talk about those rules. Constraints.  The first set of rules this application answered to were the constraints. Here is what they looked like: <constraintRules> <rule name="default" enabled="true" rank="1" description="The default constraint rule"> <actions> <range min="1" max="4" target="AutoscalingApplicationRole"/> </actions> </rule> </constraintRules> Pretty basic.  We have one role, the “AutoscalingApplicationRole”, and we have decided to have it live within a range of 1 to 4.  This rule does not adjust, but instead, set’s limits on what other rules can do.  It has a rank, so you can have you can specify other sets of constraints, perhaps based on time or date, to allow for deviations from this set.  But for now, let’s keep it simple.  In the real world, you would probably use the minimum to set a lower end SLA.  A common value might be a 2, to prevent the reactive rules from ever taking you down to 1 role.  The maximum is often used to keep a rule from driving the cost up, setting an upper limit to prevent you waking up one morning and find a bill for hundreds of instances you didn’t expect.  So, here we have the range we want our application to live inside.  This is good for our investigation and testing.  Next, let’s take a look at the reactive rules.  These rules are what you use to react (hence reactive rules) to changing demands on your application.  The HOL has two simple rules.  One that looks at a queue depth, and one that looks at a performance counter that reports cpu utilization.  the XML in the rules file looks like this: <reactiveRules> <rule name="ScaleUp" rank="10" description="Scale Up the web role" enabled="true"> <when> <any> <greaterOrEqual operand="Length_05_holqueue" than="10"/> <greaterOrEqual operand="CPU_05_holwebrole" than="65"/> </any> </when> <actions> <scale target="AutoscalingApplicationRole" by="1"/> </actions> </rule> <rule name="ScaleDown" rank="10" description="Scale down the web role" enabled="true"> <when> <all> <less operand="Length_05_holqueue" than="5"/> <less operand="CPU_05_holwebrole" than="40"/> </all> </when> <actions> <scale target="AutoscalingApplicationRole" by="-1"/> </actions> </rule> </reactiveRules> <operands> <performanceCounter alias="CPU_05_holwebrole" performanceCounterName="\Processor(_Total)\% Processor Time" source="AutoscalingApplicationRole" timespan="00:05:00" aggregate="Average" /> <queueLength alias="Length_05_holqueue" queue="hol-queue" timespan="00:05:00" aggregate="Average"/> </operands> These rules are currently contained in a file called rules.xml, that is in the root of the console application.  The console app, starts up, grabs the rules and starts watching the 2 operands.  When it detects a rule has been satisfied, it performs the desired action.  (here, scale up or down my 1). But I want to host the autoscaler  in the cloud.  For my first trick, I will move the rules (and another file called services.xml) to azure blob storage.  Look for part 3.

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  • HPCM 11.1.2.2.x - How to find data in an HPCM Standard Costing database

    - by Jane Story
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* 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-qformat:yes; 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:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} When working with a Hyperion Profitability and Cost Management (HPCM) Standard Costing application, there can often be a requirement to check data or allocated results using reporting tools e.g Smartview. To do this, you are retrieving data directly from the Essbase databases related to your HPCM model. For information, running reports is covered in Chapter 9 of the HPCM User documentation. The aim of this blog is to provide a quick guide to finding this data for reporting in the HPCM generated Essbase database in v11.1.2.2.x of HPCM. In order to retrieve data from an HPCM generated Essbase database, it is important to understand each of the following dimensions in the Essbase database and where data is located within them: Measures dimension – identifies Measures AllocationType dimension – identifies Direct Allocation Data or Genealogy Allocation data Point Of View (POV) dimensions – there must be at least one, maximum of four. Business dimensions: Stage Business dimensions – these will be identified by the Stage prefix. Intra-Stage dimension – these will be identified by the _Intra suffix. Essbase outlines and reporting is explained in the documentation here:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/ch09s02.html For additional details on reporting measures, please review this section of the documentation:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/apas03.html Reporting requirements in HPCM quite often start with identifying non balanced items in the Stage Balancing report. The following documentation link provides help with identifying some of the items within the Stage Balancing report:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/generatestagebalancing.html The following are some types of data upon which you may want to report: Stage Data: Direct Input Assigned Input Data Assigned Output Data Idle Cost/Revenue Unassigned Cost/Revenue Over Driven Cost/Revenue Direct Allocation Data Genealogy Allocation Data Stage Data Stage Data consists of: Direct Input i.e. input data, the starting point of your allocation e.g. in Stage 1 Assigned Input Data i.e. the cost/revenue received from a prior stage (i.e. stage 2 and higher). Assigned Output Data i.e. for each stage, the data that will be assigned forward is assigned post stage data. Reporting on this data is explained in the documentation here:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/ch09s03.html Dimension Selection Measures Direct Input: CostInput RevenueInput Assigned Input (from previous stages): CostReceivedPriorStage RevenueReceivedPriorStage Assigned Output (to subsequent stages): CostAssignedPostStage RevenueAssignedPostStage AllocationType DirectAllocation POV One member from each POV dimension Stage Business Dimensions Any members for the stage business dimensions for the stage you wish to see the Stage data for. All other Dimensions NoMember Idle/Unassigned/OverDriven To view Idle, Unassigned or Overdriven Costs/Revenue, first select which stage for which you want to view this data. If multiple Stages have unassigned/idle, resolve the earliest first and re-run the calculation as differences in early stages will create unassigned/idle in later stages. Dimension Selection Measures Idle: IdleCost IdleRevenue Unassigned: UnAssignedCost UnAssignedRevenue Overdriven: OverDrivenCost OverDrivenRevenue AllocationType DirectAllocation POV One member from each POV dimension Dimensions in the Stage with Unassigned/ Idle/OverDriven Cost All the Stage Business dimensions in the Stage with Unassigned/Idle/Overdriven. Zoom in on each dimension to find the individual members to find which members have Unassigned/Idle/OverDriven data. All other Dimensions NoMember Direct Allocation Data Direct allocation data shows the data received by a destination intersection from a source intersection where a direct assignment(s) exists. Reporting on direct allocation data is explained in the documentation here:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/ch09s04.html You would select the following to report direct allocation data Dimension Selection Measures CostReceivedPriorStage AllocationType DirectAllocation POV One member from each POV dimension Stage Business Dimensions Any members for the SOURCE stage business dimensions and the DESTINATION stage business dimensions for the direct allocations for the stage you wish to report on. All other Dimensions NoMember Genealogy Allocation Data Genealogy allocation data shows the indirect data relationships between stages. Genealogy calculations run in the HPCM Reporting database only. Reporting on genealogy data is explained in the documentation here:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/ch09s05.html Dimension Selection Measures CostReceivedPriorStage AllocationType GenealogyAllocation (IndirectAllocation in 11.1.2.1 and prior versions) POV One member from each POV dimension Stage Business Dimensions Any stage business dimension members from the STARTING stage in Genealogy Any stage business dimension members from the INTERMEDIATE stage(s) in Genealogy Any stage business dimension members from the ENDING stage in Genealogy All other Dimensions NoMember Notes If you still don’t see data after checking the above, please check the following Check the calculation has been run. Here are couple of indicators that might help them with that. Note the size of essbase cube before and after calculations ensure that a calculation was run against the database you are examing. Export the essbase data to a text file to confirm that some data exists. Examine the date and time on task area to see when, if any, calculations were run and what choices were used (e.g. Genealogy choices) If data does not exist in places where they are expecting, it could be that No calculations/genealogy were run No calculations were successfully run The model/data at feeder location were either absent or incompatible, resulting in no allocation e.g no driver data. Smartview Invocation from HPCM From version 11.1.2.2.350 of HPCM (this version will be GA shortly), it is possible to directly invoke Smartview from HPCM. There is guided navigation before the Smartview invocation and it is then possible to see the selected value(s) in SmartView. Click to Download HPCM 11.1.2.2.x - How to find data in an HPCM Standard Costing database (Right click or option-click the link and choose "Save As..." to download this pdf file)

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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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  • Nesting Linq-to-Objects query within Linq-to-Entities query –what is happening under the covers?

    - by carewithl
    var numbers = new int[] { 1, 2, 3, 4, 5 }; var contacts = from c in context.Contacts where c.ContactID == numbers.Max() | c.ContactID == numbers.FirstOrDefault() select c; foreach (var item in contacts) Console.WriteLine(item.ContactID); Linq-to-Entities query is first translated into Linq expression tree, which is then converted by Object Services into command tree. And if Linq-to-Entities query nests Linq-to-Objects query, then this nested query also gets translated into an expression tree. a) I assume none of the operators of the nested Linq-to-Objects query actually get executed, but instead data provider for particular DB (or perhaps Object Services) knows how to transform the logic of Linq-to-Objects operators into appropriate SQL statements? b) Data provider knows how to create equivalent SQL statements only for some of the Linq-to-Objects operators? c) Similarly, data provider knows how to create equivalent SQL statements only for some of the non-Linq methods in the Net Framework class library? EDIT: I know only some Sql so I can't be completely sure, but reading Sql query generated for the above code it seems data provider didn't actually execute numbers.Max method, but instead just somehow figured out that numbers.Max should return the maximum value and then proceed to include in generated Sql query a call to TSQL's build-in MAX function. It also put all the values held by numbers array into a Sql query. SELECT CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN '0X0X' ELSE '0X1X' END AS [C1], [Extent1].[ContactID] AS [ContactID], [Extent1].[FirstName] AS [FirstName], [Extent1].[LastName] AS [LastName], [Extent1].[Title] AS [Title], [Extent1].[AddDate] AS [AddDate], [Extent1].[ModifiedDate] AS [ModifiedDate], [Extent1].[RowVersion] AS [RowVersion], CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN [Project1].[CustomerTypeID] END AS [C2], CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN [Project1].[InitialDate] END AS [C3], CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN [Project1].[PrimaryDesintation] END AS [C4], CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN [Project1].[SecondaryDestination] END AS [C5], CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN [Project1].[PrimaryActivity] END AS [C6], CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN [Project1].[SecondaryActivity] END AS [C7], CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN [Project1].[Notes] END AS [C8], CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN [Project1].[RowVersion] END AS [C9], CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN [Project1].[BirthDate] END AS [C10], CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN [Project1].[HeightInches] END AS [C11], CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN [Project1].[WeightPounds] END AS [C12], CASE WHEN (([Project1].[C1] = 1) AND ([Project1].[C1] IS NOT NULL)) THEN [Project1].[DietaryRestrictions] END AS [C13] FROM [dbo].[Contact] AS [Extent1] LEFT OUTER JOIN (SELECT [Extent2].[ContactID] AS [ContactID], [Extent2].[BirthDate] AS [BirthDate], [Extent2].[HeightInches] AS [HeightInches], [Extent2].[WeightPounds] AS [WeightPounds], [Extent2].[DietaryRestrictions] AS [DietaryRestrictions], [Extent3].[CustomerTypeID] AS [CustomerTypeID], [Extent3].[InitialDate] AS [InitialDate], [Extent3].[PrimaryDesintation] AS [PrimaryDesintation], [Extent3].[SecondaryDestination] AS [SecondaryDestination], [Extent3].[PrimaryActivity] AS [PrimaryActivity], [Extent3].[SecondaryActivity] AS [SecondaryActivity], [Extent3].[Notes] AS [Notes], [Extent3].[RowVersion] AS [RowVersion], cast(1 as bit) AS [C1] FROM [dbo].[ContactPersonalInfo] AS [Extent2] INNER JOIN [dbo].[Customers] AS [Extent3] ON [Extent2].[ContactID] = [Extent3].[ContactID]) AS [Project1] ON [Extent1].[ContactID] = [Project1].[ContactID] LEFT OUTER JOIN (SELECT TOP (1) [c].[C1] AS [C1] FROM (SELECT [UnionAll3].[C1] AS [C1] FROM (SELECT [UnionAll2].[C1] AS [C1] FROM (SELECT [UnionAll1].[C1] AS [C1] FROM (SELECT 1 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable1] UNION ALL SELECT 2 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable2]) AS [UnionAll1] UNION ALL SELECT 3 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable3]) AS [UnionAll2] UNION ALL SELECT 4 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable4]) AS [UnionAll3] UNION ALL SELECT 5 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable5]) AS [c]) AS [Limit1] ON 1 = 1 LEFT OUTER JOIN (SELECT TOP (1) [c].[C1] AS [C1] FROM (SELECT [UnionAll7].[C1] AS [C1] FROM (SELECT [UnionAll6].[C1] AS [C1] FROM (SELECT [UnionAll5].[C1] AS [C1] FROM (SELECT 1 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable6] UNION ALL SELECT 2 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable7]) AS [UnionAll5] UNION ALL SELECT 3 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable8]) AS [UnionAll6] UNION ALL SELECT 4 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable9]) AS [UnionAll7] UNION ALL SELECT 5 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable10]) AS [c]) AS [Limit2] ON 1 = 1 CROSS JOIN (SELECT MAX([UnionAll12].[C1]) AS [A1] FROM (SELECT [UnionAll11].[C1] AS [C1] FROM (SELECT [UnionAll10].[C1] AS [C1] FROM (SELECT [UnionAll9].[C1] AS [C1] FROM (SELECT 1 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable11] UNION ALL SELECT 2 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable12]) AS [UnionAll9] UNION ALL SELECT 3 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable13]) AS [UnionAll10] UNION ALL SELECT 4 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable14]) AS [UnionAll11] UNION ALL SELECT 5 AS [C1] FROM (SELECT 1 AS X) AS [SingleRowTable15]) AS [UnionAll12]) AS [GroupBy1] WHERE [Extent1].[ContactID] IN ([GroupBy1].[A1], (CASE WHEN ([Limit1].[C1] IS NULL) THEN 0 ELSE [Limit2].[C1] END)) Based on this, is it possible that Linq2Entities provider indeed doesn't execute non-Linq and Linq-to-Object methods, but instead creates equivalent SQL statements for some of them ( and for others it throws an exception )? Thank you in advance

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