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  • Programação paralela no .NET Framework 4 – Parte I

    - by anobre
    Introdução O avanço de tecnologia nos últimos anos forneceu, a baixo custo, acesso  a workstations com inúmeros CPUs. Facilmente encontramos hoje máquinas clientes com 2, 4 e até 8 núcleos, sem considerar os “super-servidores” com até 36 processadores :) Da wikipedia: A Unidade central de processamento (CPU, de acordo com as iniciais em inglês) ou o processador é a parte de um sistema de computador que executa as instruções de um programa de computador, e é o elemento primordial na execução das funções de um computador. Este termo tem sido usado na indústria de computadores pelo menos desde o início dos anos 1960[1]. A forma, desenho e implementação de CPUs têm mudado dramaticamente desde os primeiros exemplos, mas o seu funcionamento fundamental permanece o mesmo. Fazendo uma analogia, seria muito interessante delegarmos tarefas no mundo real que podem ser executadas independentemente a pessoas diferentes, atingindo desta forma uma  maior performance / produtividade na sua execução. A computação paralela se baseia na idéia que um problema maior pode ser dividido em problemas menores, sendo resolvidos de forma paralela. Este pensamento é utilizado há algum tempo por HPC (High-performance computing), e através das facilidades dos últimos anos, assim como a preocupação com consumo de energia, tornaram esta idéia mais atrativa e de fácil acesso a qualquer ambiente. No .NET Framework A plataforma .NET apresenta um runtime, bibliotecas e ferramentas para fornecer uma base de acesso fácil e rápido à programação paralela, sem trabalhar diretamente com threads e thread pool. Esta série de posts irá apresentar todos os recursos disponíveis, iniciando os estudos pela TPL, ou Task Parallel Library. Task Parallel Library A TPL é um conjunto de tipos localizados no namespace System.Threading e System.Threading.Tasks, a partir da versão 4 do framework. A partir da versão 4 do framework, o TPL é a maneira recomendada para escrever código paralelo e multithreaded. http://msdn.microsoft.com/en-us/library/dd460717(v=VS.100).aspx Task Parallelism O termo “task parallelism”, ou em uma tradução live paralelismo de tarefas, se refere a uma ou mais tarefas sendo executadas de forma simultanea. Considere uma tarefa como um método. A maneira mais fácil de executar tarefas de forma paralela é o código abaixo: Parallel.Invoke(() => TrabalhoInicial(), () => TrabalhoSeguinte()); O que acontece de verdade? Por trás nos panos, esta instrução instancia de forma implícita objetos do tipo Task, responsável por representar uma operação assíncrona, não exatamente paralela: public class Task : IAsyncResult, IDisposable É possível instanciar Tasks de forma explícita, sendo uma alternativa mais complexa ao Parallel.Invoke. var task = new Task(() => TrabalhoInicial()); task.Start(); Outra opção de instanciar uma Task e já executar sua tarefa é: var t = Task<int>.Factory.StartNew(() => TrabalhoInicialComValor());var t2 = Task<int>.Factory.StartNew(() => TrabalhoSeguinteComValor()); A diferença básica entre as duas abordagens é que a primeira tem início conhecido, mais utilizado quando não queremos que a instanciação e o agendamento da execução ocorra em uma só operação, como na segunda abordagem. Data Parallelism Ainda parte da TPL, o Data Parallelism se refere a cenários onde a mesma operação deva ser executada paralelamente em elementos de uma coleção ou array, através de instruções paralelas For e ForEach. A idéia básica é pegar cada elemento da coleção (ou array) e trabalhar com diversas threads concomitantemente. A classe-chave para este cenário é a System.Threading.Tasks.Parallel // Sequential version foreach (var item in sourceCollection) { Process(item); } // Parallel equivalent Parallel.ForEach(sourceCollection, item => Process(item)); Complicado né? :) Demonstração Acesse aqui um vídeo com exemplos (screencast). Cuidado! Apesar da imensa vontade de sair codificando, tome cuidado com alguns problemas básicos de paralelismo. Neste link é possível conhecer algumas situações. Abraços.

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  • SQL Server 2012 - AlwaysOn

    - by Claus Jandausch
    Ich war nicht nur irritiert, ich war sogar regelrecht schockiert - und für einen kurzen Moment sprachlos (was nur selten der Fall ist). Gerade eben hatte mich jemand gefragt "Wann Oracle denn etwas Vergleichbares wie AlwaysOn bieten würde - und ob überhaupt?" War ich hier im falschen Film gelandet? Ich konnte nicht anders, als meinen Unmut kundzutun und zu erklären, dass die Fragestellung normalerweise anders herum läuft. Zugegeben - es mag vielleicht strittige Punkte geben im Vergleich zwischen Oracle und SQL Server - bei denen nicht unbedingt immer Oracle die Nase vorn haben muss - aber das Thema Clustering für Hochverfügbarkeit (HA), Disaster Recovery (DR) und Skalierbarkeit gehört mit Sicherheit nicht dazu. Dieses Erlebnis hakte ich am Nachgang als Einzelfall ab, der so nie wieder vorkommen würde. Bis ich kurz darauf eines Besseren belehrt wurde und genau die selbe Frage erneut zu hören bekam. Diesmal sogar im Exadata-Umfeld und einem Oracle Stretch Cluster. Einmal ist keinmal, doch zweimal ist einmal zu viel... Getreu diesem alten Motto war mir klar, dass man das so nicht länger stehen lassen konnte. Ich habe keine Ahnung, wie die Microsoft Marketing Abteilung es geschafft hat, unter dem AlwaysOn Brading eine innovative Technologie vermuten zu lassen - aber sie hat ihren Job scheinbar gut gemacht. Doch abgesehen von einem guten Marketing, stellt sich natürlich die Frage, was wirklich dahinter steckt und wie sich das Ganze mit Oracle vergleichen lässt - und ob überhaupt? Damit wären wir wieder bei der ursprünglichen Frage angelangt.  So viel zum Hintergrund dieses Blogbeitrags - von meiner Antwort handelt der restliche Blog. "Windows was the God ..." Um den wahren Unterschied zwischen Oracle und Microsoft verstehen zu können, muss man zunächst das bedeutendste Microsoft Dogma kennen. Es lässt sich schlicht und einfach auf den Punkt bringen: "Alles muss auf Windows basieren." Die Überschrift dieses Absatzes ist kein von mir erfundener Ausspruch, sondern ein Zitat. Konkret stammt es aus einem längeren Artikel von Kurt Eichenwald in der Vanity Fair aus dem August 2012. Er lautet Microsoft's Lost Decade und sei jedem ans Herz gelegt, der die "Microsoft-Maschinerie" unter Steve Ballmer und einige ihrer Kuriositäten besser verstehen möchte. "YOU TALKING TO ME?" Microsoft C.E.O. Steve Ballmer bei seiner Keynote auf der 2012 International Consumer Electronics Show in Las Vegas am 9. Januar   Manche Dinge in diesem Artikel mögen überspitzt dargestellt erscheinen - sind sie aber nicht. Vieles davon kannte ich bereits aus eigener Erfahrung und kann es nur bestätigen. Anderes hat sich mir erst so richtig erschlossen. Insbesondere die folgenden Passagen führten zum Aha-Erlebnis: “Windows was the god—everything had to work with Windows,” said Stone... “Every little thing you want to write has to build off of Windows (or other existing roducts),” one software engineer said. “It can be very confusing, …” Ich habe immer schon darauf hingewiesen, dass in einem SQL Server Failover Cluster die Microsoft Datenbank eigentlich nichts Nenneswertes zum Geschehen beiträgt, sondern sich voll und ganz auf das Windows Betriebssystem verlässt. Deshalb muss man auch die Windows Server Enterprise Edition installieren, soll ein Failover Cluster für den SQL Server eingerichtet werden. Denn hier werden die Cluster Services geliefert - nicht mit dem SQL Server. Er ist nur lediglich ein weiteres Server Produkt, für das Windows in Ausfallszenarien genutzt werden kann - so wie Microsoft Exchange beispielsweise, oder Microsoft SharePoint, oder irgendein anderes Server Produkt das auf Windows gehostet wird. Auch Oracle kann damit genutzt werden. Das Stichwort lautet hier: Oracle Failsafe. Nur - warum sollte man das tun, wenn gleichzeitig eine überlegene Technologie wie die Oracle Real Application Clusters (RAC) zur Verfügung steht, die dann auch keine Windows Enterprise Edition voraussetzen, da Oracle die eigene Clusterware liefert. Welche darüber hinaus für kürzere Failover-Zeiten sorgt, da diese Cluster-Technologie Datenbank-integriert ist und sich nicht auf "Dritte" verlässt. Wenn man sich also schon keine technischen Vorteile mit einem SQL Server Failover Cluster erkauft, sondern zusätzlich noch versteckte Lizenzkosten durch die Lizenzierung der Windows Server Enterprise Edition einhandelt, warum hat Microsoft dann in den vergangenen Jahren seit SQL Server 2000 nicht ebenfalls an einer neuen und innovativen Lösung gearbeitet, die mit Oracle RAC mithalten kann? Entwickler hat Microsoft genügend? Am Geld kann es auch nicht liegen? Lesen Sie einfach noch einmal die beiden obenstehenden Zitate und sie werden den Grund verstehen. Anders lässt es sich ja auch gar nicht mehr erklären, dass AlwaysOn aus zwei unterschiedlichen Technologien besteht, die beide jedoch wiederum auf dem Windows Server Failover Clustering (WSFC) basieren. Denn daraus ergeben sich klare Nachteile - aber dazu später mehr. Um AlwaysOn zu verstehen, sollte man sich zunächst kurz in Erinnerung rufen, was Microsoft bisher an HA/DR (High Availability/Desaster Recovery) Lösungen für SQL Server zur Verfügung gestellt hat. Replikation Basiert auf logischer Replikation und Pubisher/Subscriber Architektur Transactional Replication Merge Replication Snapshot Replication Microsoft's Replikation ist vergleichbar mit Oracle GoldenGate. Oracle GoldenGate stellt jedoch die umfassendere Technologie dar und bietet High Performance. Log Shipping Microsoft's Log Shipping stellt eine einfache Technologie dar, die vergleichbar ist mit Oracle Managed Recovery in Oracle Version 7. Das Log Shipping besitzt folgende Merkmale: Transaction Log Backups werden von Primary nach Secondary/ies geschickt Einarbeitung (z.B. Restore) auf jedem Secondary individuell Optionale dritte Server Instanz (Monitor Server) für Überwachung und Alarm Log Restore Unterbrechung möglich für Read-Only Modus (Secondary) Keine Unterstützung von Automatic Failover Database Mirroring Microsoft's Database Mirroring wurde verfügbar mit SQL Server 2005, sah aus wie Oracle Data Guard in Oracle 9i, war funktional jedoch nicht so umfassend. Für ein HA/DR Paar besteht eine 1:1 Beziehung, um die produktive Datenbank (Principle DB) abzusichern. Auf der Standby Datenbank (Mirrored DB) werden alle Insert-, Update- und Delete-Operationen nachgezogen. Modi Synchron (High-Safety Modus) Asynchron (High-Performance Modus) Automatic Failover Unterstützt im High-Safety Modus (synchron) Witness Server vorausgesetzt     Zur Frage der Kontinuität Es stellt sich die Frage, wie es um diesen Technologien nun im Zusammenhang mit SQL Server 2012 bestellt ist. Unter Fanfaren seinerzeit eingeführt, war Database Mirroring das erklärte Mittel der Wahl. Ich bin kein Produkt Manager bei Microsoft und kann hierzu nur meine Meinung äußern, aber zieht man den SQL AlwaysOn Team Blog heran, so sieht es nicht gut aus für das Database Mirroring - zumindest nicht langfristig. "Does AlwaysOn Availability Group replace Database Mirroring going forward?” “The short answer is we recommend that you migrate from the mirroring configuration or even mirroring and log shipping configuration to using Availability Group. Database Mirroring will still be available in the Denali release but will be phased out over subsequent releases. Log Shipping will continue to be available in future releases.” Damit wären wir endlich beim eigentlichen Thema angelangt. Was ist eine sogenannte Availability Group und was genau hat es mit der vielversprechend klingenden Bezeichnung AlwaysOn auf sich?   SQL Server 2012 - AlwaysOn Zwei HA-Features verstekcne sich hinter dem “AlwaysOn”-Branding. Einmal das AlwaysOn Failover Clustering aka SQL Server Failover Cluster Instances (FCI) - zum Anderen die AlwaysOn Availability Groups. Failover Cluster Instances (FCI) Entspricht ungefähr dem Stretch Cluster Konzept von Oracle Setzt auf Windows Server Failover Clustering (WSFC) auf Bietet HA auf Instanz-Ebene AlwaysOn Availability Groups (Verfügbarkeitsgruppen) Ähnlich der Idee von Consistency Groups, wie in Storage-Level Replikations-Software von z.B. EMC SRDF Abhängigkeiten zu Windows Server Failover Clustering (WSFC) Bietet HA auf Datenbank-Ebene   Hinweis: Verwechseln Sie nicht eine SQL Server Datenbank mit einer Oracle Datenbank. Und auch nicht eine Oracle Instanz mit einer SQL Server Instanz. Die gleichen Begriffe haben hier eine andere Bedeutung - nicht selten ein Grund, weshalb Oracle- und Microsoft DBAs schnell aneinander vorbei reden. Denken Sie bei einer SQL Server Datenbank eher an ein Oracle Schema, das kommt der Sache näher. So etwas wie die SQL Server Northwind Datenbank ist vergleichbar mit dem Oracle Scott Schema. Wenn Sie die genauen Unterschiede kennen möchten, finden Sie eine detaillierte Beschreibung in meinem Buch "Oracle10g Release 2 für Windows und .NET", erhältich bei Lehmanns, Amazon, etc.   Windows Server Failover Clustering (WSFC) Wie man sieht, basieren beide AlwaysOn Technologien wiederum auf dem Windows Server Failover Clustering (WSFC), um einerseits Hochverfügbarkeit auf Ebene der Instanz zu gewährleisten und andererseits auf der Datenbank-Ebene. Deshalb nun eine kurze Beschreibung der WSFC. Die WSFC sind ein mit dem Windows Betriebssystem geliefertes Infrastruktur-Feature, um HA für Server Anwendungen, wie Microsoft Exchange, SharePoint, SQL Server, etc. zu bieten. So wie jeder andere Cluster, besteht ein WSFC Cluster aus einer Gruppe unabhängiger Server, die zusammenarbeiten, um die Verfügbarkeit einer Applikation oder eines Service zu erhöhen. Falls ein Cluster-Knoten oder -Service ausfällt, kann der auf diesem Knoten bisher gehostete Service automatisch oder manuell auf einen anderen im Cluster verfügbaren Knoten transferriert werden - was allgemein als Failover bekannt ist. Unter SQL Server 2012 verwenden sowohl die AlwaysOn Avalability Groups, als auch die AlwaysOn Failover Cluster Instances die WSFC als Plattformtechnologie, um Komponenten als WSFC Cluster-Ressourcen zu registrieren. Verwandte Ressourcen werden in eine Ressource Group zusammengefasst, die in Abhängigkeit zu anderen WSFC Cluster-Ressourcen gebracht werden kann. Der WSFC Cluster Service kann jetzt die Notwendigkeit zum Neustart der SQL Server Instanz erfassen oder einen automatischen Failover zu einem anderen Server-Knoten im WSFC Cluster auslösen.   Failover Cluster Instances (FCI) Eine SQL Server Failover Cluster Instanz (FCI) ist eine einzelne SQL Server Instanz, die in einem Failover Cluster betrieben wird, der aus mehreren Windows Server Failover Clustering (WSFC) Knoten besteht und so HA (High Availability) auf Ebene der Instanz bietet. Unter Verwendung von Multi-Subnet FCI kann auch Remote DR (Disaster Recovery) unterstützt werden. Eine weitere Option für Remote DR besteht darin, eine unter FCI gehostete Datenbank in einer Availability Group zu betreiben. Hierzu später mehr. FCI und WSFC Basis FCI, das für lokale Hochverfügbarkeit der Instanzen genutzt wird, ähnelt der veralteten Architektur eines kalten Cluster (Aktiv-Passiv). Unter SQL Server 2008 wurde diese Technologie SQL Server 2008 Failover Clustering genannt. Sie nutzte den Windows Server Failover Cluster. In SQL Server 2012 hat Microsoft diese Basistechnologie unter der Bezeichnung AlwaysOn zusammengefasst. Es handelt sich aber nach wie vor um die klassische Aktiv-Passiv-Konfiguration. Der Ablauf im Failover-Fall ist wie folgt: Solange kein Hardware-oder System-Fehler auftritt, werden alle Dirty Pages im Buffer Cache auf Platte geschrieben Alle entsprechenden SQL Server Services (Dienste) in der Ressource Gruppe werden auf dem aktiven Knoten gestoppt Die Ownership der Ressource Gruppe wird auf einen anderen Knoten der FCI transferriert Der neue Owner (Besitzer) der Ressource Gruppe startet seine SQL Server Services (Dienste) Die Connection-Anforderungen einer Client-Applikation werden automatisch auf den neuen aktiven Knoten mit dem selben Virtuellen Network Namen (VNN) umgeleitet Abhängig vom Zeitpunkt des letzten Checkpoints, kann die Anzahl der Dirty Pages im Buffer Cache, die noch auf Platte geschrieben werden müssen, zu unvorhersehbar langen Failover-Zeiten führen. Um diese Anzahl zu drosseln, besitzt der SQL Server 2012 eine neue Fähigkeit, die Indirect Checkpoints genannt wird. Indirect Checkpoints ähnelt dem Fast-Start MTTR Target Feature der Oracle Datenbank, das bereits mit Oracle9i verfügbar war.   SQL Server Multi-Subnet Clustering Ein SQL Server Multi-Subnet Failover Cluster entspricht vom Konzept her einem Oracle RAC Stretch Cluster. Doch dies ist nur auf den ersten Blick der Fall. Im Gegensatz zu RAC ist in einem lokalen SQL Server Failover Cluster jeweils nur ein Knoten aktiv für eine Datenbank. Für die Datenreplikation zwischen geografisch entfernten Sites verlässt sich Microsoft auf 3rd Party Lösungen für das Storage Mirroring.     Die Verbesserung dieses Szenario mit einer SQL Server 2012 Implementierung besteht schlicht darin, dass eine VLAN-Konfiguration (Virtual Local Area Network) nun nicht mehr benötigt wird, so wie dies bisher der Fall war. Das folgende Diagramm stellt dar, wie der Ablauf mit SQL Server 2012 gehandhabt wird. In Site A und Site B wird HA jeweils durch einen lokalen Aktiv-Passiv-Cluster sichergestellt.     Besondere Aufmerksamkeit muss hier der Konfiguration und dem Tuning geschenkt werden, da ansonsten völlig inakzeptable Failover-Zeiten resultieren. Dies liegt darin begründet, weil die Downtime auf Client-Seite nun nicht mehr nur von der reinen Failover-Zeit abhängt, sondern zusätzlich von der Dauer der DNS Replikation zwischen den DNS Servern. (Rufen Sie sich in Erinnerung, dass wir gerade von Multi-Subnet Clustering sprechen). Außerdem ist zu berücksichtigen, wie schnell die Clients die aktualisierten DNS Informationen abfragen. Spezielle Konfigurationen für Node Heartbeat, HostRecordTTL (Host Record Time-to-Live) und Intersite Replication Frequeny für Active Directory Sites und Services werden notwendig. Default TTL für Windows Server 2008 R2: 20 Minuten Empfohlene Einstellung: 1 Minute DNS Update Replication Frequency in Windows Umgebung: 180 Minuten Empfohlene Einstellung: 15 Minuten (minimaler Wert)   Betrachtet man diese Werte, muss man feststellen, dass selbst eine optimale Konfiguration die rigiden SLAs (Service Level Agreements) heutiger geschäftskritischer Anwendungen für HA und DR nicht erfüllen kann. Denn dies impliziert eine auf der Client-Seite erlebte Failover-Zeit von insgesamt 16 Minuten. Hierzu ein Auszug aus der SQL Server 2012 Online Dokumentation: Cons: If a cross-subnet failover occurs, the client recovery time could be 15 minutes or longer, depending on your HostRecordTTL setting and the setting of your cross-site DNS/AD replication schedule.    Wir sind hier an einem Punkt unserer Überlegungen angelangt, an dem sich erklärt, weshalb ich zuvor das "Windows was the God ..." Zitat verwendet habe. Die unbedingte Abhängigkeit zu Windows wird zunehmend zum Problem, da sie die Komplexität einer Microsoft-basierenden Lösung erhöht, anstelle sie zu reduzieren. Und Komplexität ist das Letzte, was sich CIOs heutzutage wünschen.  Zur Ehrenrettung des SQL Server 2012 und AlwaysOn muss man sagen, dass derart lange Failover-Zeiten kein unbedingtes "Muss" darstellen, sondern ein "Kann". Doch auch ein "Kann" kann im unpassenden Moment unvorhersehbare und kostspielige Folgen haben. Die Unabsehbarkeit ist wiederum Ursache vieler an der Implementierung beteiligten Komponenten und deren Abhängigkeiten, wie beispielsweise drei Cluster-Lösungen (zwei von Microsoft, eine 3rd Party Lösung). Wie man die Sache auch dreht und wendet, kommt man an diesem Fakt also nicht vorbei - ganz unabhängig von der Dauer einer Downtime oder Failover-Zeiten. Im Gegensatz zu AlwaysOn und der hier vorgestellten Version eines Stretch-Clusters, vermeidet eine entsprechende Oracle Implementierung eine derartige Komplexität, hervorgerufen duch multiple Abhängigkeiten. Den Unterschied machen Datenbank-integrierte Mechanismen, wie Fast Application Notification (FAN) und Fast Connection Failover (FCF). Für Oracle MAA Konfigurationen (Maximum Availability Architecture) sind Inter-Site Failover-Zeiten im Bereich von Sekunden keine Seltenheit. Wenn Sie dem Link zur Oracle MAA folgen, finden Sie außerdem eine Reihe an Customer Case Studies. Auch dies ist ein wichtiges Unterscheidungsmerkmal zu AlwaysOn, denn die Oracle Technologie hat sich bereits zigfach in höchst kritischen Umgebungen bewährt.   Availability Groups (Verfügbarkeitsgruppen) Die sogenannten Availability Groups (Verfügbarkeitsgruppen) sind - neben FCI - der weitere Baustein von AlwaysOn.   Hinweis: Bevor wir uns näher damit beschäftigen, sollten Sie sich noch einmal ins Gedächtnis rufen, dass eine SQL Server Datenbank nicht die gleiche Bedeutung besitzt, wie eine Oracle Datenbank, sondern eher einem Oracle Schema entspricht. So etwas wie die SQL Server Northwind Datenbank ist vergleichbar mit dem Oracle Scott Schema.   Eine Verfügbarkeitsgruppe setzt sich zusammen aus einem Set mehrerer Benutzer-Datenbanken, die im Falle eines Failover gemeinsam als Gruppe behandelt werden. Eine Verfügbarkeitsgruppe unterstützt ein Set an primären Datenbanken (primäres Replikat) und einem bis vier Sets von entsprechenden sekundären Datenbanken (sekundäre Replikate).       Es können jedoch nicht alle SQL Server Datenbanken einer AlwaysOn Verfügbarkeitsgruppe zugeordnet werden. Der SQL Server Spezialist Michael Otey zählt in seinem SQL Server Pro Artikel folgende Anforderungen auf: Verfügbarkeitsgruppen müssen mit Benutzer-Datenbanken erstellt werden. System-Datenbanken können nicht verwendet werden Die Datenbanken müssen sich im Read-Write Modus befinden. Read-Only Datenbanken werden nicht unterstützt Die Datenbanken in einer Verfügbarkeitsgruppe müssen Multiuser Datenbanken sein Sie dürfen nicht das AUTO_CLOSE Feature verwenden Sie müssen das Full Recovery Modell nutzen und es muss ein vollständiges Backup vorhanden sein Eine gegebene Datenbank kann sich nur in einer einzigen Verfügbarkeitsgruppe befinden und diese Datenbank düerfen nicht für Database Mirroring konfiguriert sein Microsoft empfiehl außerdem, dass der Verzeichnispfad einer Datenbank auf dem primären und sekundären Server identisch sein sollte Wie man sieht, eignen sich Verfügbarkeitsgruppen nicht, um HA und DR vollständig abzubilden. Die Unterscheidung zwischen der Instanzen-Ebene (FCI) und Datenbank-Ebene (Availability Groups) ist von hoher Bedeutung. Vor kurzem wurde mir gesagt, dass man mit den Verfügbarkeitsgruppen auf Shared Storage verzichten könne und dadurch Kosten spart. So weit so gut ... Man kann natürlich eine Installation rein mit Verfügbarkeitsgruppen und ohne FCI durchführen - aber man sollte sich dann darüber bewusst sein, was man dadurch alles nicht abgesichert hat - und dies wiederum für Desaster Recovery (DR) und SLAs (Service Level Agreements) bedeutet. Kurzum, um die Kombination aus beiden AlwaysOn Produkten und der damit verbundene Komplexität kommt man wohl in der Praxis nicht herum.    Availability Groups und WSFC AlwaysOn hängt von Windows Server Failover Clustering (WSFC) ab, um die aktuellen Rollen der Verfügbarkeitsreplikate einer Verfügbarkeitsgruppe zu überwachen und zu verwalten, und darüber zu entscheiden, wie ein Failover-Ereignis die Verfügbarkeitsreplikate betrifft. Das folgende Diagramm zeigt de Beziehung zwischen Verfügbarkeitsgruppen und WSFC:   Der Verfügbarkeitsmodus ist eine Eigenschaft jedes Verfügbarkeitsreplikats. Synychron und Asynchron können also gemischt werden: Availability Modus (Verfügbarkeitsmodus) Asynchroner Commit-Modus Primäres replikat schließt Transaktionen ohne Warten auf Sekundäres Synchroner Commit-Modus Primäres Replikat wartet auf Commit von sekundärem Replikat Failover Typen Automatic Manual Forced (mit möglichem Datenverlust) Synchroner Commit-Modus Geplanter, manueller Failover ohne Datenverlust Automatischer Failover ohne Datenverlust Asynchroner Commit-Modus Nur Forced, manueller Failover mit möglichem Datenverlust   Der SQL Server kennt keinen separaten Switchover Begriff wie in Oracle Data Guard. Für SQL Server werden alle Role Transitions als Failover bezeichnet. Tatsächlich unterstützt der SQL Server keinen Switchover für asynchrone Verbindungen. Es gibt nur die Form des Forced Failover mit möglichem Datenverlust. Eine ähnliche Fähigkeit wie der Switchover unter Oracle Data Guard ist so nicht gegeben.   SQL Sever FCI mit Availability Groups (Verfügbarkeitsgruppen) Neben den Verfügbarkeitsgruppen kann eine zweite Failover-Ebene eingerichtet werden, indem SQL Server FCI (auf Shared Storage) mit WSFC implementiert wird. Ein Verfügbarkeitesreplikat kann dann auf einer Standalone Instanz gehostet werden, oder einer FCI Instanz. Zum Verständnis: Die Verfügbarkeitsgruppen selbst benötigen kein Shared Storage. Diese Kombination kann verwendet werden für lokale HA auf Ebene der Instanz und DR auf Datenbank-Ebene durch Verfügbarkeitsgruppen. Das folgende Diagramm zeigt dieses Szenario:   Achtung! Hier handelt es sich nicht um ein Pendant zu Oracle RAC plus Data Guard, auch wenn das Bild diesen Eindruck vielleicht vermitteln mag - denn alle sekundären Knoten im FCI sind rein passiv. Es existiert außerdem eine weitere und ernsthafte Einschränkung: SQL Server Failover Cluster Instanzen (FCI) unterstützen nicht das automatische AlwaysOn Failover für Verfügbarkeitsgruppen. Jedes unter FCI gehostete Verfügbarkeitsreplikat kann nur für manuelles Failover konfiguriert werden.   Lesbare Sekundäre Replikate Ein oder mehrere Verfügbarkeitsreplikate in einer Verfügbarkeitsgruppe können für den lesenden Zugriff konfiguriert werden, wenn sie als sekundäres Replikat laufen. Dies ähnelt Oracle Active Data Guard, jedoch gibt es Einschränkungen. Alle Abfragen gegen die sekundäre Datenbank werden automatisch auf das Snapshot Isolation Level abgebildet. Es handelt sich dabei um eine Versionierung der Rows. Microsoft versuchte hiermit die Oracle MVRC (Multi Version Read Consistency) nachzustellen. Tatsächlich muss man die SQL Server Snapshot Isolation eher mit Oracle Flashback vergleichen. Bei der Implementierung des Snapshot Isolation Levels handelt sich um ein nachträglich aufgesetztes Feature und nicht um einen inhärenten Teil des Datenbank-Kernels, wie im Falle Oracle. (Ich werde hierzu in Kürze einen weiteren Blogbeitrag verfassen, wenn ich mich mit der neuen SQL Server 2012 Core Lizenzierung beschäftige.) Für die Praxis entstehen aus der Abbildung auf das Snapshot Isolation Level ernsthafte Restriktionen, derer man sich für den Betrieb in der Praxis bereits vorab bewusst sein sollte: Sollte auf der primären Datenbank eine aktive Transaktion zu dem Zeitpunkt existieren, wenn ein lesbares sekundäres Replikat in die Verfügbarkeitsgruppe aufgenommen wird, werden die Row-Versionen auf der korrespondierenden sekundären Datenbank nicht sofort vollständig verfügbar sein. Eine aktive Transaktion auf dem primären Replikat muss zuerst abgeschlossen (Commit oder Rollback) und dieser Transaktions-Record auf dem sekundären Replikat verarbeitet werden. Bis dahin ist das Isolation Level Mapping auf der sekundären Datenbank unvollständig und Abfragen sind temporär geblockt. Microsoft sagt dazu: "This is needed to guarantee that row versions are available on the secondary replica before executing the query under snapshot isolation as all isolation levels are implicitly mapped to snapshot isolation." (SQL Storage Engine Blog: AlwaysOn: I just enabled Readable Secondary but my query is blocked?)  Grundlegend bedeutet dies, dass ein aktives lesbares Replikat nicht in die Verfügbarkeitsgruppe aufgenommen werden kann, ohne das primäre Replikat vorübergehend stillzulegen. Da Leseoperationen auf das Snapshot Isolation Transaction Level abgebildet werden, kann die Bereinigung von Ghost Records auf dem primären Replikat durch Transaktionen auf einem oder mehreren sekundären Replikaten geblockt werden - z.B. durch eine lang laufende Abfrage auf dem sekundären Replikat. Diese Bereinigung wird auch blockiert, wenn die Verbindung zum sekundären Replikat abbricht oder der Datenaustausch unterbrochen wird. Auch die Log Truncation wird in diesem Zustant verhindert. Wenn dieser Zustand längere Zeit anhält, empfiehlt Microsoft das sekundäre Replikat aus der Verfügbarkeitsgruppe herauszunehmen - was ein ernsthaftes Downtime-Problem darstellt. Die Read-Only Workload auf den sekundären Replikaten kann eingehende DDL Änderungen blockieren. Obwohl die Leseoperationen aufgrund der Row-Versionierung keine Shared Locks halten, führen diese Operatioen zu Sch-S Locks (Schemastabilitätssperren). DDL-Änderungen durch Redo-Operationen können dadurch blockiert werden. Falls DDL aufgrund konkurrierender Lese-Workload blockiert wird und der Schwellenwert für 'Recovery Interval' (eine SQL Server Konfigurationsoption) überschritten wird, generiert der SQL Server das Ereignis sqlserver.lock_redo_blocked, welches Microsoft zum Kill der blockierenden Leser empfiehlt. Auf die Verfügbarkeit der Anwendung wird hierbei keinerlei Rücksicht genommen.   Keine dieser Einschränkungen existiert mit Oracle Active Data Guard.   Backups auf sekundären Replikaten  Über die sekundären Replikate können Backups (BACKUP DATABASE via Transact-SQL) nur als copy-only Backups einer vollständigen Datenbank, Dateien und Dateigruppen erstellt werden. Das Erstellen inkrementeller Backups ist nicht unterstützt, was ein ernsthafter Rückstand ist gegenüber der Backup-Unterstützung physikalischer Standbys unter Oracle Data Guard. Hinweis: Ein möglicher Workaround via Snapshots, bleibt ein Workaround. Eine weitere Einschränkung dieses Features gegenüber Oracle Data Guard besteht darin, dass das Backup eines sekundären Replikats nicht ausgeführt werden kann, wenn es nicht mit dem primären Replikat kommunizieren kann. Darüber hinaus muss das sekundäre Replikat synchronisiert sein oder sich in der Synchronisation befinden, um das Beackup auf dem sekundären Replikat erstellen zu können.   Vergleich von Microsoft AlwaysOn mit der Oracle MAA Ich komme wieder zurück auf die Eingangs erwähnte, mehrfach an mich gestellte Frage "Wann denn - und ob überhaupt - Oracle etwas Vergleichbares wie AlwaysOn bieten würde?" und meine damit verbundene (kurze) Irritation. Wenn Sie diesen Blogbeitrag bis hierher gelesen haben, dann kennen Sie jetzt meine darauf gegebene Antwort. Der eine oder andere Punkt traf dabei nicht immer auf Jeden zu, was auch nicht der tiefere Sinn und Zweck meiner Antwort war. Wenn beispielsweise kein Multi-Subnet mit im Spiel ist, sind alle diesbezüglichen Kritikpunkte zunächst obsolet. Was aber nicht bedeutet, dass sie nicht bereits morgen schon wieder zum Thema werden könnten (Sag niemals "Nie"). In manch anderes Fettnäpfchen tritt man wiederum nicht unbedingt in einer Testumgebung, sondern erst im laufenden Betrieb. Erst recht nicht dann, wenn man sich potenzieller Probleme nicht bewusst ist und keine dedizierten Tests startet. Und wer AlwaysOn erfolgreich positionieren möchte, wird auch gar kein Interesse daran haben, auf mögliche Schwachstellen und den besagten Teufel im Detail aufmerksam zu machen. Das ist keine Unterstellung - es ist nur menschlich. Außerdem ist es verständlich, dass man sich in erster Linie darauf konzentriert "was geht" und "was gut läuft", anstelle auf das "was zu Problemen führen kann" oder "nicht funktioniert". Wer will schon der Miesepeter sein? Für mich selbst gesprochen, kann ich nur sagen, dass ich lieber vorab von allen möglichen Einschränkungen wissen möchte, anstelle sie dann nach einer kurzen Zeit der heilen Welt schmerzhaft am eigenen Leib erfahren zu müssen. Ich bin davon überzeugt, dass es Ihnen nicht anders geht. Nachfolgend deshalb eine Zusammenfassung all jener Punkte, die ich im Vergleich zur Oracle MAA (Maximum Availability Architecture) als unbedingt Erwähnenswert betrachte, falls man eine Evaluierung von Microsoft AlwaysOn in Betracht zieht. 1. AlwaysOn ist eine komplexe Technologie Der SQL Server AlwaysOn Stack ist zusammengesetzt aus drei verschiedenen Technlogien: Windows Server Failover Clustering (WSFC) SQL Server Failover Cluster Instances (FCI) SQL Server Availability Groups (Verfügbarkeitsgruppen) Man kann eine derartige Lösung nicht als nahtlos bezeichnen, wofür auch die vielen von Microsoft dargestellten Einschränkungen sprechen. Während sich frühere SQL Server Versionen in Richtung eigener HA/DR Technologien entwickelten (wie Database Mirroring), empfiehlt Microsoft nun die Migration. Doch weshalb dieser Schwenk? Er führt nicht zu einem konsisten und robusten Angebot an HA/DR Technologie für geschäftskritische Umgebungen.  Liegt die Antwort in meiner These begründet, nach der "Windows was the God ..." noch immer gilt und man die Nachteile der allzu engen Kopplung mit Windows nicht sehen möchte? Entscheiden Sie selbst ... 2. Failover Cluster Instanzen - Kein RAC-Pendant Die SQL Server und Windows Server Clustering Technologie basiert noch immer auf dem veralteten Aktiv-Passiv Modell und führt zu einer Verschwendung von Systemressourcen. In einer Betrachtung von lediglich zwei Knoten erschließt sich auf Anhieb noch nicht der volle Mehrwert eines Aktiv-Aktiv Clusters (wie den Real Application Clusters), wie er von Oracle bereits vor zehn Jahren entwickelt wurde. Doch kennt man die Vorzüge der Skalierbarkeit durch einfaches Hinzufügen weiterer Cluster-Knoten, die dann alle gemeinsam als ein einziges logisches System zusammenarbeiten, versteht man was hinter dem Motto "Pay-as-you-Grow" steckt. In einem Aktiv-Aktiv Cluster geht es zwar auch um Hochverfügbarkeit - und ein Failover erfolgt zudem schneller, als in einem Aktiv-Passiv Modell - aber es geht eben nicht nur darum. An dieser Stelle sei darauf hingewiesen, dass die Oracle 11g Standard Edition bereits die Nutzung von Oracle RAC bis zu vier Sockets kostenfrei beinhaltet. Möchten Sie dazu Windows nutzen, benötigen Sie keine Windows Server Enterprise Edition, da Oracle 11g die eigene Clusterware liefert. Sie kommen in den Genuss von Hochverfügbarkeit und Skalierbarkeit und können dazu die günstigere Windows Server Standard Edition nutzen. 3. SQL Server Multi-Subnet Clustering - Abhängigkeit zu 3rd Party Storage Mirroring  Die SQL Server Multi-Subnet Clustering Architektur unterstützt den Aufbau eines Stretch Clusters, basiert dabei aber auf dem Aktiv-Passiv Modell. Das eigentlich Problematische ist jedoch, dass man sich zur Absicherung der Datenbank auf 3rd Party Storage Mirroring Technologie verlässt, ohne Integration zwischen dem Windows Server Failover Clustering (WSFC) und der darunterliegenden Mirroring Technologie. Wenn nun im Cluster ein Failover auf Instanzen-Ebene erfolgt, existiert keine Koordination mit einem möglichen Failover auf Ebene des Storage-Array. 4. Availability Groups (Verfügbarkeitsgruppen) - Vier, oder doch nur Zwei? Ein primäres Replikat erlaubt bis zu vier sekundäre Replikate innerhalb einer Verfügbarkeitsgruppe, jedoch nur zwei im Synchronen Commit Modus. Während dies zwar einen Vorteil gegenüber dem stringenten 1:1 Modell unter Database Mirroring darstellt, fällt der SQL Server 2012 damit immer noch weiter zurück hinter Oracle Data Guard mit bis zu 30 direkten Stanbdy Zielen - und vielen weiteren durch kaskadierende Ziele möglichen. Damit eignet sich Oracle Active Data Guard auch für die Bereitstellung einer Reader-Farm Skalierbarkeit für Internet-basierende Unternehmen. Mit AwaysOn Verfügbarkeitsgruppen ist dies nicht möglich. 5. Availability Groups (Verfügbarkeitsgruppen) - kein asynchrones Switchover  Die Technologie der Verfügbarkeitsgruppen wird auch als geeignetes Mittel für administrative Aufgaben positioniert - wie Upgrades oder Wartungsarbeiten. Man muss sich jedoch einem gravierendem Defizit bewusst sein: Im asynchronen Verfügbarkeitsmodus besteht die einzige Möglichkeit für Role Transition im Forced Failover mit Datenverlust! Um den Verlust von Daten durch geplante Wartungsarbeiten zu vermeiden, muss man den synchronen Verfügbarkeitsmodus konfigurieren, was jedoch ernstzunehmende Auswirkungen auf WAN Deployments nach sich zieht. Spinnt man diesen Gedanken zu Ende, kommt man zu dem Schluss, dass die Technologie der Verfügbarkeitsgruppen für geplante Wartungsarbeiten in einem derartigen Umfeld nicht effektiv genutzt werden kann. 6. Automatisches Failover - Nicht immer möglich Sowohl die SQL Server FCI, als auch Verfügbarkeitsgruppen unterstützen automatisches Failover. Möchte man diese jedoch kombinieren, wird das Ergebnis kein automatisches Failover sein. Denn ihr Zusammentreffen im Failover-Fall führt zu Race Conditions (Wettlaufsituationen), weshalb diese Konfiguration nicht länger das automatische Failover zu einem Replikat in einer Verfügbarkeitsgruppe erlaubt. Auch hier bestätigt sich wieder die tiefere Problematik von AlwaysOn, mit einer Zusammensetzung aus unterschiedlichen Technologien und der Abhängigkeit zu Windows. 7. Problematische RTO (Recovery Time Objective) Microsoft postioniert die SQL Server Multi-Subnet Clustering Architektur als brauchbare HA/DR Architektur. Bedenkt man jedoch die Problematik im Zusammenhang mit DNS Replikation und den möglichen langen Wartezeiten auf Client-Seite von bis zu 16 Minuten, sind strenge RTO Anforderungen (Recovery Time Objectives) nicht erfüllbar. Im Gegensatz zu Oracle besitzt der SQL Server keine Datenbank-integrierten Technologien, wie Oracle Fast Application Notification (FAN) oder Oracle Fast Connection Failover (FCF). 8. Problematische RPO (Recovery Point Objective) SQL Server ermöglicht Forced Failover (erzwungenes Failover), bietet jedoch keine Möglichkeit zur automatischen Übertragung der letzten Datenbits von einem alten zu einem neuen primären Replikat, wenn der Verfügbarkeitsmodus asynchron war. Oracle Data Guard hingegen bietet diese Unterstützung durch das Flush Redo Feature. Dies sichert "Zero Data Loss" und beste RPO auch in erzwungenen Failover-Situationen. 9. Lesbare Sekundäre Replikate mit Einschränkungen Aufgrund des Snapshot Isolation Transaction Level für lesbare sekundäre Replikate, besitzen diese Einschränkungen mit Auswirkung auf die primäre Datenbank. Die Bereinigung von Ghost Records auf der primären Datenbank, wird beeinflusst von lang laufenden Abfragen auf der lesabaren sekundären Datenbank. Die lesbare sekundäre Datenbank kann nicht in die Verfügbarkeitsgruppe aufgenommen werden, wenn es aktive Transaktionen auf der primären Datenbank gibt. Zusätzlich können DLL Änderungen auf der primären Datenbank durch Abfragen auf der sekundären blockiert werden. Und imkrementelle Backups werden hier nicht unterstützt.   Keine dieser Restriktionen existiert unter Oracle Data Guard.

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  • Ubuntu 10.04 & IBM DS3524 with FC multipath, inactive path is [failed][faulty] instead of [active][ghost]

    - by Graeme Donaldson
    OK, this is my setup: FC Switches IBM/Brocade, Switch1 and Switch2, independent fabrics. Server IBM x3650 M2, 2x QLogic QLE2460, 1 connected to each FC Switch. Storage IBM DS3524, 2x controllers with 4x FC ports each, but only 2x connected on each. +-----------------------------------------------------------------------+ | HBA1 Server HBA2 | +-----------------------------------------------------------------------+ | | | | | | +-----------------------------+ +------------------------------+ | Switch1 | | Switch2 | +-----------------------------+ +------------------------------+ | | | | | | | | | | | | | | | | | | | | +-----------------------------------+-----------------------------------+ | Contr A, port 3 | Contr A, port 4 | Contr B, port 3 | Contr B, port 4 | +-----------------------------------+-----------------------------------+ | Storage | +-----------------------------------------------------------------------+ My /etc/multipath.conf is from the IBM redbook for the DS3500, except I use a different setting for prio_callout, IBM uses /sbin/mpath_prio_tpc, but according to http://changelogs.ubuntu.com/changelogs/pool/main/m/multipath-tools/multipath-tools_0.4.8-7ubuntu2/changelog, this was renamed to /sbin/mpath_prio_rdac, which I'm using. devices { device { #ds3500 vendor "IBM" product "1746 FAStT" hardware_handler "1 rdac" path_checker rdac failback 0 path_grouping_policy multibus prio_callout "/sbin/mpath_prio_rdac /dev/%n" } } multipaths { multipath { wwid xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx alias array07 path_grouping_policy multibus path_checker readsector0 path_selector "round-robin 0" failback "5" rr_weight priorities no_path_retry "5" } } The output of multipath -ll with controller A as the preferred path: root@db06:~# multipath -ll sdg: checker msg is "directio checker reports path is down" sdh: checker msg is "directio checker reports path is down" array07 (xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx) dm-2 IBM ,1746 FASt [size=4.9T][features=1 queue_if_no_path][hwhandler=0] \_ round-robin 0 [prio=2][active] \_ 5:0:1:0 sdd 8:48 [active][ready] \_ 5:0:2:0 sde 8:64 [active][ready] \_ 6:0:1:0 sdg 8:96 [failed][faulty] \_ 6:0:2:0 sdh 8:112 [failed][faulty] If I change the preferred path using IBM DS Storage Manager to Controller B, the output swaps accordingly: root@db06:~# multipath -ll sdd: checker msg is "directio checker reports path is down" sde: checker msg is "directio checker reports path is down" array07 (xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx) dm-2 IBM ,1746 FASt [size=4.9T][features=1 queue_if_no_path][hwhandler=0] \_ round-robin 0 [prio=2][active] \_ 5:0:1:0 sdd 8:48 [failed][faulty] \_ 5:0:2:0 sde 8:64 [failed][faulty] \_ 6:0:1:0 sdg 8:96 [active][ready] \_ 6:0:2:0 sdh 8:112 [active][ready] According to IBM, the inactive path should be "[active][ghost]", not "[failed][faulty]". Despite this, I don't seem to have any I/O issues, but my syslog is being spammed with this every 5 seconds: Jun 1 15:30:09 db06 multipathd: sdg: directio checker reports path is down Jun 1 15:30:09 db06 kernel: [ 2350.282065] sd 6:0:2:0: [sdh] Result: hostbyte=DID_OK driverbyte=DRIVER_SENSE Jun 1 15:30:09 db06 kernel: [ 2350.282071] sd 6:0:2:0: [sdh] Sense Key : Illegal Request [current] Jun 1 15:30:09 db06 kernel: [ 2350.282076] sd 6:0:2:0: [sdh] <<vendor>> ASC=0x94 ASCQ=0x1ASC=0x94 ASCQ=0x1 Jun 1 15:30:09 db06 kernel: [ 2350.282083] sd 6:0:2:0: [sdh] CDB: Read(10): 28 00 00 00 00 00 00 00 08 00 Jun 1 15:30:09 db06 kernel: [ 2350.282092] end_request: I/O error, dev sdh, sector 0 Jun 1 15:30:10 db06 multipathd: sdh: directio checker reports path is down Jun 1 15:30:14 db06 kernel: [ 2355.312270] sd 6:0:1:0: [sdg] Result: hostbyte=DID_OK driverbyte=DRIVER_SENSE Jun 1 15:30:14 db06 kernel: [ 2355.312277] sd 6:0:1:0: [sdg] Sense Key : Illegal Request [current] Jun 1 15:30:14 db06 kernel: [ 2355.312282] sd 6:0:1:0: [sdg] <<vendor>> ASC=0x94 ASCQ=0x1ASC=0x94 ASCQ=0x1 Jun 1 15:30:14 db06 kernel: [ 2355.312290] sd 6:0:1:0: [sdg] CDB: Read(10): 28 00 00 00 00 00 00 00 08 00 Jun 1 15:30:14 db06 kernel: [ 2355.312299] end_request: I/O error, dev sdg, sector 0 Does anyone know how I can get the inactive path to show "[active][ghost]" instead of "[failed][faulty]"? I assume that once I can get that right then the spam in my syslog will end as well. One final thing worth mentioning is that the IBM redbook doc targets SLES 11 so I'm assuming there's something a little different under Ubuntu that I just haven't figured out yet. Update: As suggested by Mitch, I've tried removing /etc/multipath.conf, and now the output of multipath -ll looks like this: root@db06:~# multipath -ll sdg: checker msg is "directio checker reports path is down" sdh: checker msg is "directio checker reports path is down" xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxdm-1 IBM ,1746 FASt [size=4.9T][features=0][hwhandler=0] \_ round-robin 0 [prio=1][active] \_ 5:0:2:0 sde 8:64 [active][ready] \_ round-robin 0 [prio=1][enabled] \_ 5:0:1:0 sdd 8:48 [active][ready] \_ round-robin 0 [prio=0][enabled] \_ 6:0:1:0 sdg 8:96 [failed][faulty] \_ round-robin 0 [prio=0][enabled] \_ 6:0:2:0 sdh 8:112 [failed][faulty] So its more or less the same, with the same message in the syslog every 5 minutes as before, but the grouping has changed.

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  • What makes them click ?

    - by Piet
    The other day (well, actually some weeks ago while relaxing at the beach in Kos) I read ‘Neuro Web Design - What makes them click?’ by Susan Weinschenk. (http://neurowebbook.com) The book is a fast and easy read (no unnecessary filler) and a good introduction on how your site’s visitors can be steered in the direction you want them to go. The Obvious The book handles some of the more known/proven techniques, like for example that ratings/testimonials of other people can help sell your product or service. Another well known technique it talks about is inducing a sense of scarcity/urgency in the visitor. Only 2 seats left! Buy now and get 33% off! It’s not because these are known techniques that they stop working. Luckily 2/3rd of the book handles less obvious techniques, otherwise it wouldn’t be worth buying. The Not So Obvious A less known influencing technique is reciprocity. And then I’m not talking about swapping links with another website, but the fact that someone is more likely to do something for you after you did something for them first. The book cites some studies (I always love the facts and figures) and gives some actual examples of how to implement this in your site’s design, which is less obvious when you think about it. Want to know more ? Buy the book! Other interesting sources For a more general introduction to the same principles, I’d suggest ‘Yes! 50 Secrets from the Science of Persuasion’. ‘Yes!…’ cites some of the same studies (it seems there’s a rather limited pool of studies covering this subject), but of course doesn’t show how to implement these techniques in your site’s design. I read ‘Yes!…’ last year, making ‘Neuro Web Design’ just a little bit less interesting. !!!Always make sure you’re able to measure your changes. If you haven’t yet, check out the advanced segmentation in Google Analytics (don’t be afraid because it says ‘beta’, it works just fine) and Google Website Optimizer. Worth Buying? Can I recommend it ? Sure, why not. I think it can be useful for anyone who ever had to think about the design or content of a site. You don’t have to be a marketing guy to want a site you’re involved with to be successful. The content/filler ratio is excellent too: you don’t need to wade through dozens of pages to filter out the interesting bits. (unlike ‘The Design of Sites’, which contains too much useless info and because it’s in dead-tree format, you can’t google it) If you like it, you might also check out ‘Yes! 50 Secrets from the Science of Persuasion’. Tip for people living in Europe: check Amazon UK for your book buying needs. Because of the low UK Pound exchange rate, it’s usually considerably cheaper and faster to get a book delivered to your doorstep by Amazon UK compared to having to order it at the local book store or web-shop.

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  • BizTalk Server Monitoring &ndash; SharePoint Web Part

    - by SURESH GIRIRAJAN
    I have been worked with customers using BizTalk as shared infrastructure in the enterprise, where we have two or more BizTalk apps running on it for different Business groups. Also these customers are not using BizTalk ESB portal even though they are using BizTalk ESB exception framework. So main issue with all these Business groups are they don’t have visibility into the BizTalk apps running in prod, even though they are using SCOM and other monitoring stuff in place. So I am trying to address few issues I am going to list below and how I try to mitigate them, first one on the list is how to get visibility into prod, how to provision those access to the BizTalk resources with minimal activity and how can we take advantage of the resources we have today. So I was working on creating REST data services for BizTalk RFID a year ago and available on codeplex. I thought to extend that idea to take advantage of BizTalk Data Services available in codeplex. I extended the BizTalk data services I will upload the updated service soon. So let me start thru how my solution works, so first step I am using the BizTalk data service (REST service) which expose most of the BizTalk artifacts as resources such as Applications, Orchestrations, Send ports, Receive ports, Host instances and In process instances etc. BizTalk Server Monitoring – SharePoint Web Part I am hosting the BizTalk data service in IIS with application pool configured to run under BizTalk administrator credentials. So with this setup I am making the service to make accessible anonymous. Next step of this solution I have created a SharePoint Visual web part which consumes the BizTalk data service and display all the BizTalk Application and Platform settings in read only mode. Even though BizTalk data services offers to browse resources as well perform actions like starting, stopping Orchestrations, Send ports, Receive locations, Host instances etc. Host Instances BizTalk Applications BizTalk Running / Suspended Instances So having this BizTalk Monitoring SharePoint web part, will be added to the SharePoint. This eliminates the need for granting access to the BizTalk users explicitly, so when you have BizTalk contractor or BizTalk application user need to have access to the BizTalk environment all the need is have access to the SharePoint website. You can configure the web part point to different end point based on your environment. I am making this as read only as part of this to make easier for the users and in terms of provisioning. This removes the dependency of BizTalk admin at least for viewing the BizTalk application status and errors etc. If we need to make any changes to the BizTalk application then its application owner responsibility to co-ordinate with BizTalk admins. There are options like BizTalk ESB portal, BizTalk 360 etc… but this one of the approach to reduce number of steps required to give access to BizTalk application users and also to maximize the resource we have in enterprise today. Also you can expose this data service thru Azure Service Bus and access from other apps like mobile devices or create a web site hosted in Azure etc. One last thing I have tested only with BizTalk Server 2010 on x64 VM only, but it should work on other version. I will try to upload the code shortly with instructions how to setup etc.… I welcome thoughts and suggestions… Hope this helps….

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  • Assign highest priority to my local repository

    - by Anwar Shah
    Original question was : "How to assign highest priority to local repository without using sources.list file" I have setup a local repository with packages I downloaded. I use it to avoid downloading the same packages over the Internet, when I need to reinstall my Ubuntu. It is a basic repository, created with apt-ftparchive packages . > Packages. I made this a trusted repository to avoid "unauthenticated repository" warning. (When you have a untrusted repository, apt or synaptic try to download the same packages over the Internet, 'cause it is trusted). I have been using this local repository for at least 1 years. But I have to always put my local repository line at the top of the sources.list file to use this. But this is annoying, since I must open a terminal and do some typing on it every time I reinstall Ubuntu, though there is a better tool software-properties-gtk. I cannot use this tool since it place the source line at the end of `sources.list. And the real problem is that, the apt or synaptic always download a package from the source which is mentioned earlier, without inspecting whether the packages are already available in the local repository. So, I have no choice but to place the local source at the top of sources.list doing terminal (I actually don't hate terminal, but I need a solution) . I have tried this method. But this does not help me. My preference file is this in /etc/apt/preferences.d/local-pin-900 Package: * Pin: release o=Local,n=ubuntu-local Pin-Priority: 900 My release file is this Origin: Local Label: Local-Ubuntu Description: Local Ubuntu Repository Codename: ubuntu-local MD5Sum: ed43222856d18f389c637ac3d7dd6f85 1043412 Packages d41d8cd98f00b204e9800998ecf8427e 0 Sources When I enable the apt-preference, the apt-cache policy correctly shows the preference, e.g. It shows the local repository has the highest priority. But when I do this sudo apt-get install <package-name>, apt tries to download it from Internet. But when I place my local-repo at the top, it installs from local repository. So, My question is - 'Is it possible to force apt to use local repository when the package is available in local repository, without explicitly placing "the local source" at the top of my repository list (e.g sources.list file) ?' Edit: output of apt-cache policy $package_name is as follows nautilus-wipe: Installed: (none) Candidate: 0.1.1-2 Version table: 0.1.1-2 0 500 http://archive.ubuntu.com/ubuntu/ precise/universe i386 Packages 900 file:/media/Main/Linux-Software/Ubuntu/Precise/ Packages It is showing that my local repository has higher preference, though it is not the one which comes first in sources.list file. Here is the output of apt-get install nautilus-wipe Reading package lists... Done Building dependency tree Reading state information... Done The following NEW packages will be installed: nautilus-wipe 0 upgraded, 1 newly installed, 0 to remove and 131 not upgraded. Need to get 30.7 kB of archives. After this operation, 150 kB of additional disk space will be used. 'http://archive.ubuntu.com/ubuntu/pool/universe/n/nautilus-wipe/nautilus-wipe_0.1.1-2_i386.deb' nautilus-wipe_0.1.1-2_i386.deb 30730 MD5Sum:7d497b8dfcefe1c0b51a45f3b0466994 It is still trying to get the file from Internet, though I think it should be happy with the local one.

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  • Metro: Creating an IndexedDbDataSource for WinJS

    - by Stephen.Walther
    The goal of this blog entry is to describe how you can create custom data sources which you can use with the controls in the WinJS library. In particular, I explain how you can create an IndexedDbDataSource which you can use to store and retrieve data from an IndexedDB database. If you want to skip ahead, and ignore all of the fascinating content in-between, I’ve included the complete code for the IndexedDbDataSource at the very bottom of this blog entry. What is IndexedDB? IndexedDB is a database in the browser. You can use the IndexedDB API with all modern browsers including Firefox, Chrome, and Internet Explorer 10. And, of course, you can use IndexedDB with Metro style apps written with JavaScript. If you need to persist data in a Metro style app written with JavaScript then IndexedDB is a good option. Each Metro app can only interact with its own IndexedDB databases. And, IndexedDB provides you with transactions, indices, and cursors – the elements of any modern database. An IndexedDB database might be different than the type of database that you normally use. An IndexedDB database is an object-oriented database and not a relational database. Instead of storing data in tables, you store data in object stores. You store JavaScript objects in an IndexedDB object store. You create new IndexedDB object stores by handling the upgradeneeded event when you attempt to open a connection to an IndexedDB database. For example, here’s how you would both open a connection to an existing database named TasksDB and create the TasksDB database when it does not already exist: var reqOpen = window.indexedDB.open(“TasksDB”, 2); reqOpen.onupgradeneeded = function (evt) { var newDB = evt.target.result; newDB.createObjectStore("tasks", { keyPath: "id", autoIncrement: true }); }; reqOpen.onsuccess = function () { var db = reqOpen.result; // Do something with db }; When you call window.indexedDB.open(), and the database does not already exist, then the upgradeneeded event is raised. In the code above, the upgradeneeded handler creates a new object store named tasks. The new object store has an auto-increment column named id which acts as the primary key column. If the database already exists with the right version, and you call window.indexedDB.open(), then the success event is raised. At that point, you have an open connection to the existing database and you can start doing something with the database. You use asynchronous methods to interact with an IndexedDB database. For example, the following code illustrates how you would add a new object to the tasks object store: var transaction = db.transaction(“tasks”, “readwrite”); var reqAdd = transaction.objectStore(“tasks”).add({ name: “Feed the dog” }); reqAdd.onsuccess = function() { // Tasks added successfully }; The code above creates a new database transaction, adds a new task to the tasks object store, and handles the success event. If the new task gets added successfully then the success event is raised. Creating a WinJS IndexedDbDataSource The most powerful control in the WinJS library is the ListView control. This is the control that you use to display a collection of items. If you want to display data with a ListView control, you need to bind the control to a data source. The WinJS library includes two objects which you can use as a data source: the List object and the StorageDataSource object. The List object enables you to represent a JavaScript array as a data source and the StorageDataSource enables you to represent the file system as a data source. If you want to bind an IndexedDB database to a ListView then you have a choice. You can either dump the items from the IndexedDB database into a List object or you can create a custom data source. I explored the first approach in a previous blog entry. In this blog entry, I explain how you can create a custom IndexedDB data source. Implementing the IListDataSource Interface You create a custom data source by implementing the IListDataSource interface. This interface contains the contract for the methods which the ListView needs to interact with a data source. The easiest way to implement the IListDataSource interface is to derive a new object from the base VirtualizedDataSource object. The VirtualizedDataSource object requires a data adapter which implements the IListDataAdapter interface. Yes, because of the number of objects involved, this is a little confusing. Your code ends up looking something like this: var IndexedDbDataSource = WinJS.Class.derive( WinJS.UI.VirtualizedDataSource, function (dbName, dbVersion, objectStoreName, upgrade, error) { this._adapter = new IndexedDbDataAdapter(dbName, dbVersion, objectStoreName, upgrade, error); this._baseDataSourceConstructor(this._adapter); }, { nuke: function () { this._adapter.nuke(); }, remove: function (key) { this._adapter.removeInternal(key); } } ); The code above is used to create a new class named IndexedDbDataSource which derives from the base VirtualizedDataSource class. In the constructor for the new class, the base class _baseDataSourceConstructor() method is called. A data adapter is passed to the _baseDataSourceConstructor() method. The code above creates a new method exposed by the IndexedDbDataSource named nuke(). The nuke() method deletes all of the objects from an object store. The code above also overrides a method named remove(). Our derived remove() method accepts any type of key and removes the matching item from the object store. Almost all of the work of creating a custom data source goes into building the data adapter class. The data adapter class implements the IListDataAdapter interface which contains the following methods: · change() · getCount() · insertAfter() · insertAtEnd() · insertAtStart() · insertBefore() · itemsFromDescription() · itemsFromEnd() · itemsFromIndex() · itemsFromKey() · itemsFromStart() · itemSignature() · moveAfter() · moveBefore() · moveToEnd() · moveToStart() · remove() · setNotificationHandler() · compareByIdentity Fortunately, you are not required to implement all of these methods. You only need to implement the methods that you actually need. In the case of the IndexedDbDataSource, I implemented the getCount(), itemsFromIndex(), insertAtEnd(), and remove() methods. If you are creating a read-only data source then you really only need to implement the getCount() and itemsFromIndex() methods. Implementing the getCount() Method The getCount() method returns the total number of items from the data source. So, if you are storing 10,000 items in an object store then this method would return the value 10,000. Here’s how I implemented the getCount() method: getCount: function () { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore().then(function (store) { var reqCount = store.count(); reqCount.onerror = that._error; reqCount.onsuccess = function (evt) { complete(evt.target.result); }; }); }); } The first thing that you should notice is that the getCount() method returns a WinJS promise. This is a requirement. The getCount() method is asynchronous which is a good thing because all of the IndexedDB methods (at least the methods implemented in current browsers) are also asynchronous. The code above retrieves an object store and then uses the IndexedDB count() method to get a count of the items in the object store. The value is returned from the promise by calling complete(). Implementing the itemsFromIndex method When a ListView displays its items, it calls the itemsFromIndex() method. By default, it calls this method multiple times to get different ranges of items. Three parameters are passed to the itemsFromIndex() method: the requestIndex, countBefore, and countAfter parameters. The requestIndex indicates the index of the item from the database to show. The countBefore and countAfter parameters represent hints. These are integer values which represent the number of items before and after the requestIndex to retrieve. Again, these are only hints and you can return as many items before and after the request index as you please. Here’s how I implemented the itemsFromIndex method: itemsFromIndex: function (requestIndex, countBefore, countAfter) { var that = this; return new WinJS.Promise(function (complete, error) { that.getCount().then(function (count) { if (requestIndex >= count) { return WinJS.Promise.wrapError(new WinJS.ErrorFromName(WinJS.UI.FetchError.doesNotExist)); } var startIndex = Math.max(0, requestIndex - countBefore); var endIndex = Math.min(count, requestIndex + countAfter + 1); that._getObjectStore().then(function (store) { var index = 0; var items = []; var req = store.openCursor(); req.onerror = that._error; req.onsuccess = function (evt) { var cursor = evt.target.result; if (index < startIndex) { index = startIndex; cursor.advance(startIndex); return; } if (cursor && index < endIndex) { index++; items.push({ key: cursor.value[store.keyPath].toString(), data: cursor.value }); cursor.continue(); return; } results = { items: items, offset: requestIndex - startIndex, totalCount: count }; complete(results); }; }); }); }); } In the code above, a cursor is used to iterate through the objects in an object store. You fetch the next item in the cursor by calling either the cursor.continue() or cursor.advance() method. The continue() method moves forward by one object and the advance() method moves forward a specified number of objects. Each time you call continue() or advance(), the success event is raised again. If the cursor is null then you know that you have reached the end of the cursor and you can return the results. Some things to be careful about here. First, the return value from the itemsFromIndex() method must implement the IFetchResult interface. In particular, you must return an object which has an items, offset, and totalCount property. Second, each item in the items array must implement the IListItem interface. Each item should have a key and a data property. Implementing the insertAtEnd() Method When creating the IndexedDbDataSource, I wanted to go beyond creating a simple read-only data source and support inserting and deleting objects. If you want to support adding new items with your data source then you need to implement the insertAtEnd() method. Here’s how I implemented the insertAtEnd() method for the IndexedDbDataSource: insertAtEnd:function(unused, data) { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore("readwrite").done(function(store) { var reqAdd = store.add(data); reqAdd.onerror = that._error; reqAdd.onsuccess = function (evt) { var reqGet = store.get(evt.target.result); reqGet.onerror = that._error; reqGet.onsuccess = function (evt) { var newItem = { key:evt.target.result[store.keyPath].toString(), data:evt.target.result } complete(newItem); }; }; }); }); } When implementing the insertAtEnd() method, you need to be careful to return an object which implements the IItem interface. In particular, you should return an object that has a key and a data property. The key must be a string and it uniquely represents the new item added to the data source. The value of the data property represents the new item itself. Implementing the remove() Method Finally, you use the remove() method to remove an item from the data source. You call the remove() method with the key of the item which you want to remove. Implementing the remove() method in the case of the IndexedDbDataSource was a little tricky. The problem is that an IndexedDB object store uses an integer key and the VirtualizedDataSource requires a string key. For that reason, I needed to override the remove() method in the derived IndexedDbDataSource class like this: var IndexedDbDataSource = WinJS.Class.derive( WinJS.UI.VirtualizedDataSource, function (dbName, dbVersion, objectStoreName, upgrade, error) { this._adapter = new IndexedDbDataAdapter(dbName, dbVersion, objectStoreName, upgrade, error); this._baseDataSourceConstructor(this._adapter); }, { nuke: function () { this._adapter.nuke(); }, remove: function (key) { this._adapter.removeInternal(key); } } ); When you call remove(), you end up calling a method of the IndexedDbDataAdapter named removeInternal() . Here’s what the removeInternal() method looks like: setNotificationHandler: function (notificationHandler) { this._notificationHandler = notificationHandler; }, removeInternal: function(key) { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore("readwrite").done(function (store) { var reqDelete = store.delete (key); reqDelete.onerror = that._error; reqDelete.onsuccess = function (evt) { that._notificationHandler.removed(key.toString()); complete(); }; }); }); } The removeInternal() method calls the IndexedDB delete() method to delete an item from the object store. If the item is deleted successfully then the _notificationHandler.remove() method is called. Because we are not implementing the standard IListDataAdapter remove() method, we need to notify the data source (and the ListView control bound to the data source) that an item has been removed. The way that you notify the data source is by calling the _notificationHandler.remove() method. Notice that we get the _notificationHandler in the code above by implementing another method in the IListDataAdapter interface: the setNotificationHandler() method. You can raise the following types of notifications using the _notificationHandler: · beginNotifications() · changed() · endNotifications() · inserted() · invalidateAll() · moved() · removed() · reload() These methods are all part of the IListDataNotificationHandler interface in the WinJS library. Implementing the nuke() Method I wanted to implement a method which would remove all of the items from an object store. Therefore, I created a method named nuke() which calls the IndexedDB clear() method: nuke: function () { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore("readwrite").done(function (store) { var reqClear = store.clear(); reqClear.onerror = that._error; reqClear.onsuccess = function (evt) { that._notificationHandler.reload(); complete(); }; }); }); } Notice that the nuke() method calls the _notificationHandler.reload() method to notify the ListView to reload all of the items from its data source. Because we are implementing a custom method here, we need to use the _notificationHandler to send an update. Using the IndexedDbDataSource To illustrate how you can use the IndexedDbDataSource, I created a simple task list app. You can add new tasks, delete existing tasks, and nuke all of the tasks. You delete an item by selecting an item (swipe or right-click) and clicking the Delete button. Here’s the HTML page which contains the ListView, the form for adding new tasks, and the buttons for deleting and nuking tasks: <!DOCTYPE html> <html> <head> <meta charset="utf-8" /> <title>DataSources</title> <!-- WinJS references --> <link href="//Microsoft.WinJS.1.0.RC/css/ui-dark.css" rel="stylesheet" /> <script src="//Microsoft.WinJS.1.0.RC/js/base.js"></script> <script src="//Microsoft.WinJS.1.0.RC/js/ui.js"></script> <!-- DataSources references --> <link href="indexedDb.css" rel="stylesheet" /> <script type="text/javascript" src="indexedDbDataSource.js"></script> <script src="indexedDb.js"></script> </head> <body> <div id="tmplTask" data-win-control="WinJS.Binding.Template"> <div class="taskItem"> Id: <span data-win-bind="innerText:id"></span> <br /><br /> Name: <span data-win-bind="innerText:name"></span> </div> </div> <div id="lvTasks" data-win-control="WinJS.UI.ListView" data-win-options="{ itemTemplate: select('#tmplTask'), selectionMode: 'single' }"></div> <form id="frmAdd"> <fieldset> <legend>Add Task</legend> <label>New Task</label> <input id="inputTaskName" required /> <button>Add</button> </fieldset> </form> <button id="btnNuke">Nuke</button> <button id="btnDelete">Delete</button> </body> </html> And here is the JavaScript code for the TaskList app: /// <reference path="//Microsoft.WinJS.1.0.RC/js/base.js" /> /// <reference path="//Microsoft.WinJS.1.0.RC/js/ui.js" /> function init() { WinJS.UI.processAll().done(function () { var lvTasks = document.getElementById("lvTasks").winControl; // Bind the ListView to its data source var tasksDataSource = new DataSources.IndexedDbDataSource("TasksDB", 1, "tasks", upgrade); lvTasks.itemDataSource = tasksDataSource; // Wire-up Add, Delete, Nuke buttons document.getElementById("frmAdd").addEventListener("submit", function (evt) { evt.preventDefault(); tasksDataSource.beginEdits(); tasksDataSource.insertAtEnd(null, { name: document.getElementById("inputTaskName").value }).done(function (newItem) { tasksDataSource.endEdits(); document.getElementById("frmAdd").reset(); lvTasks.ensureVisible(newItem.index); }); }); document.getElementById("btnDelete").addEventListener("click", function () { if (lvTasks.selection.count() == 1) { lvTasks.selection.getItems().done(function (items) { tasksDataSource.remove(items[0].data.id); }); } }); document.getElementById("btnNuke").addEventListener("click", function () { tasksDataSource.nuke(); }); // This method is called to initialize the IndexedDb database function upgrade(evt) { var newDB = evt.target.result; newDB.createObjectStore("tasks", { keyPath: "id", autoIncrement: true }); } }); } document.addEventListener("DOMContentLoaded", init); The IndexedDbDataSource is created and bound to the ListView control with the following two lines of code: var tasksDataSource = new DataSources.IndexedDbDataSource("TasksDB", 1, "tasks", upgrade); lvTasks.itemDataSource = tasksDataSource; The IndexedDbDataSource is created with four parameters: the name of the database to create, the version of the database to create, the name of the object store to create, and a function which contains code to initialize the new database. The upgrade function creates a new object store named tasks with an auto-increment property named id: function upgrade(evt) { var newDB = evt.target.result; newDB.createObjectStore("tasks", { keyPath: "id", autoIncrement: true }); } The Complete Code for the IndexedDbDataSource Here’s the complete code for the IndexedDbDataSource: (function () { /************************************************ * The IndexedDBDataAdapter enables you to work * with a HTML5 IndexedDB database. *************************************************/ var IndexedDbDataAdapter = WinJS.Class.define( function (dbName, dbVersion, objectStoreName, upgrade, error) { this._dbName = dbName; // database name this._dbVersion = dbVersion; // database version this._objectStoreName = objectStoreName; // object store name this._upgrade = upgrade; // database upgrade script this._error = error || function (evt) { console.log(evt.message); }; }, { /******************************************* * IListDataAdapter Interface Methods ********************************************/ getCount: function () { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore().then(function (store) { var reqCount = store.count(); reqCount.onerror = that._error; reqCount.onsuccess = function (evt) { complete(evt.target.result); }; }); }); }, itemsFromIndex: function (requestIndex, countBefore, countAfter) { var that = this; return new WinJS.Promise(function (complete, error) { that.getCount().then(function (count) { if (requestIndex >= count) { return WinJS.Promise.wrapError(new WinJS.ErrorFromName(WinJS.UI.FetchError.doesNotExist)); } var startIndex = Math.max(0, requestIndex - countBefore); var endIndex = Math.min(count, requestIndex + countAfter + 1); that._getObjectStore().then(function (store) { var index = 0; var items = []; var req = store.openCursor(); req.onerror = that._error; req.onsuccess = function (evt) { var cursor = evt.target.result; if (index < startIndex) { index = startIndex; cursor.advance(startIndex); return; } if (cursor && index < endIndex) { index++; items.push({ key: cursor.value[store.keyPath].toString(), data: cursor.value }); cursor.continue(); return; } results = { items: items, offset: requestIndex - startIndex, totalCount: count }; complete(results); }; }); }); }); }, insertAtEnd:function(unused, data) { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore("readwrite").done(function(store) { var reqAdd = store.add(data); reqAdd.onerror = that._error; reqAdd.onsuccess = function (evt) { var reqGet = store.get(evt.target.result); reqGet.onerror = that._error; reqGet.onsuccess = function (evt) { var newItem = { key:evt.target.result[store.keyPath].toString(), data:evt.target.result } complete(newItem); }; }; }); }); }, setNotificationHandler: function (notificationHandler) { this._notificationHandler = notificationHandler; }, /***************************************** * IndexedDbDataSource Method ******************************************/ removeInternal: function(key) { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore("readwrite").done(function (store) { var reqDelete = store.delete (key); reqDelete.onerror = that._error; reqDelete.onsuccess = function (evt) { that._notificationHandler.removed(key.toString()); complete(); }; }); }); }, nuke: function () { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore("readwrite").done(function (store) { var reqClear = store.clear(); reqClear.onerror = that._error; reqClear.onsuccess = function (evt) { that._notificationHandler.reload(); complete(); }; }); }); }, /******************************************* * Private Methods ********************************************/ _ensureDbOpen: function () { var that = this; // Try to get cached Db if (that._cachedDb) { return WinJS.Promise.wrap(that._cachedDb); } // Otherwise, open the database return new WinJS.Promise(function (complete, error, progress) { var reqOpen = window.indexedDB.open(that._dbName, that._dbVersion); reqOpen.onerror = function (evt) { error(); }; reqOpen.onupgradeneeded = function (evt) { that._upgrade(evt); that._notificationHandler.invalidateAll(); }; reqOpen.onsuccess = function () { that._cachedDb = reqOpen.result; complete(that._cachedDb); }; }); }, _getObjectStore: function (type) { type = type || "readonly"; var that = this; return new WinJS.Promise(function (complete, error) { that._ensureDbOpen().then(function (db) { var transaction = db.transaction(that._objectStoreName, type); complete(transaction.objectStore(that._objectStoreName)); }); }); }, _get: function (key) { return new WinJS.Promise(function (complete, error) { that._getObjectStore().done(function (store) { var reqGet = store.get(key); reqGet.onerror = that._error; reqGet.onsuccess = function (item) { complete(item); }; }); }); } } ); var IndexedDbDataSource = WinJS.Class.derive( WinJS.UI.VirtualizedDataSource, function (dbName, dbVersion, objectStoreName, upgrade, error) { this._adapter = new IndexedDbDataAdapter(dbName, dbVersion, objectStoreName, upgrade, error); this._baseDataSourceConstructor(this._adapter); }, { nuke: function () { this._adapter.nuke(); }, remove: function (key) { this._adapter.removeInternal(key); } } ); WinJS.Namespace.define("DataSources", { IndexedDbDataSource: IndexedDbDataSource }); })(); Summary In this blog post, I provided an overview of how you can create a new data source which you can use with the WinJS library. I described how you can create an IndexedDbDataSource which you can use to bind a ListView control to an IndexedDB database. While describing how you can create a custom data source, I explained how you can implement the IListDataAdapter interface. You also learned how to raise notifications — such as a removed or invalidateAll notification — by taking advantage of the methods of the IListDataNotificationHandler interface.

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  • Asynchrony in C# 5: Dataflow Async Logger Sample

    - by javarg
    Check out this (very simple) code examples for TPL Dataflow. Suppose you are developing an Async Logger to register application events to different sinks or log writers. The logger architecture would be as follow: Note how blocks can be composed to achieved desired behavior. The BufferBlock<T> is the pool of log entries to be process whereas linked ActionBlock<TInput> represent the log writers or sinks. The previous composition would allows only one ActionBlock to consume entries at a time. Implementation code would be something similar to (add reference to System.Threading.Tasks.Dataflow.dll in %User Documents%\Microsoft Visual Studio Async CTP\Documentation): TPL Dataflow Logger var bufferBlock = new BufferBlock<Tuple<LogLevel, string>>(); ActionBlock<Tuple<LogLevel, string>> infoLogger =     new ActionBlock<Tuple<LogLevel, string>>(         e => Console.WriteLine("Info: {0}", e.Item2)); ActionBlock<Tuple<LogLevel, string>> errorLogger =     new ActionBlock<Tuple<LogLevel, string>>(         e => Console.WriteLine("Error: {0}", e.Item2)); bufferBlock.LinkTo(infoLogger, e => (e.Item1 & LogLevel.Info) != LogLevel.None); bufferBlock.LinkTo(errorLogger, e => (e.Item1 & LogLevel.Error) != LogLevel.None); bufferBlock.Post(new Tuple<LogLevel, string>(LogLevel.Info, "info message")); bufferBlock.Post(new Tuple<LogLevel, string>(LogLevel.Error, "error message")); Note the filter applied to each link (in this case, the Logging Level selects the writer used). We can specify message filters using Predicate functions on each link. Now, the previous sample is useless for a Logger since Logging Level is not exclusive (thus, several writers could be used to process a single message). Let´s use a Broadcast<T> buffer instead of a BufferBlock<T>. Broadcast Logger var bufferBlock = new BroadcastBlock<Tuple<LogLevel, string>>(     e => new Tuple<LogLevel, string>(e.Item1, e.Item2)); ActionBlock<Tuple<LogLevel, string>> infoLogger =     new ActionBlock<Tuple<LogLevel, string>>(         e => Console.WriteLine("Info: {0}", e.Item2)); ActionBlock<Tuple<LogLevel, string>> errorLogger =     new ActionBlock<Tuple<LogLevel, string>>(         e => Console.WriteLine("Error: {0}", e.Item2)); ActionBlock<Tuple<LogLevel, string>> allLogger =     new ActionBlock<Tuple<LogLevel, string>>(     e => Console.WriteLine("All: {0}", e.Item2)); bufferBlock.LinkTo(infoLogger, e => (e.Item1 & LogLevel.Info) != LogLevel.None); bufferBlock.LinkTo(errorLogger, e => (e.Item1 & LogLevel.Error) != LogLevel.None); bufferBlock.LinkTo(allLogger, e => (e.Item1 & LogLevel.All) != LogLevel.None); bufferBlock.Post(new Tuple<LogLevel, string>(LogLevel.Info, "info message")); bufferBlock.Post(new Tuple<LogLevel, string>(LogLevel.Error, "error message")); As this block copies the message to all its outputs, we need to define the copy function in the block constructor. In this case we create a new Tuple, but you can always use the Identity function if passing the same reference to every output. Try both scenarios and compare the results.

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  • July, the 31 Days of SQL Server DMO’s – Day 19 (sys.dm_exec_query_stats)

    - by Tamarick Hill
    The sys.dm_exec_query_stats DMV is one of the most useful DMV’s out there when it comes to performance tuning. If you have been keeping up with this blog series this month, you know that I started out on Day 1 reviewing many of the DMV’s within the ‘exec’ namespace. I’m not sure how I missed this one considering how valuable it is, but hey, they say it’s better late than never right?? On Day 7 and Day 8 we reviewed the sys.dm_exec_procedure_stats and sys.dm_exec_trigger_stats respectively. This sys.dm_exec_query_stats DMV is very similar to these two. As a matter of fact, this DMV will return all of the information you saw in the other two DMV’s, but in addition to that, you can see stats for all queries that have cached execution plans on your server. You can even see stats for statements that are ran Ad-Hoc as long as they are still cached in the buffer pool. To better illustrate this DMV, let have a quick look at it: SELECT * FROM sys.dm_exec_query_stats As you can see, there is a lot of information returned from this DMV. I wont go into detail about each and every one of these columns, but I will touch on a few of them briefly. The first column is the ‘sql_handle’, which if you remember from Day 4 of our blog series, I explained how you can use this column to extract the actual SQL text that was executed. The next columns statement_start_offset and statement_end_offset provide you a way of extracting the exact SQL statement that was executed as part of a batch. The plan_handle column is used to extract the Execution plan that was used, which we talked about during Day 5 of this blog series. Later in the result set, you have columns to identify how many times a particular statement was executed, how much CPU time it used, how many reads/writes it performed, the duration, how many rows were returned, etc. These columns provide you with a solid avenue to begin your performance optimization. The last column I will touch on is the query_plan_hash column. A lot of times when you have Dynamic SQL running on your server, you have similar statements with different parameter values being passed in. Many times these types of statements will get similar execution plans and then a Binary hash value can be generated based on these similar plans. This query plan hash can be used to find the cost of all queries that have similar execution plans and then you can tune based on that plan to improve the performance of all of the individual queries. This is a very powerful way of identifying and tuning Ad-hoc statements that run on your server. As I stated earlier, this sys.dm_exec_query_stats DMV is a very powerful and recommended DMV for performance tuning. You are able to quickly identify statements that are running on your server and analyze their impact on system resources. Using this DMV to track down the biggest performance killers on your server will allow you to make the biggest gains once you focus your tuning efforts on those top offenders. For more information about this DMV, please see the below Books Online link: http://msdn.microsoft.com/en-us/library/ms189741.aspx Follow me on Twitter @PrimeTimeDBA

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  • A quick look at: sys.dm_os_buffer_descriptors

    - by Jonathan Allen
    SQL Server places data into cache as it reads it from disk so as to speed up future queries. This dmv lets you see how much data is cached at any given time and knowing how this changes over time can help you ensure your servers run smoothly and are adequately resourced to run your systems. This dmv gives the number of cached pages in the buffer pool along with the database id that they relate to: USE [tempdb] GO SELECT COUNT(*) AS cached_pages_count , CASE database_id WHEN 32767 THEN 'ResourceDb' ELSE DB_NAME(database_id) END AS Database_name FROM sys.dm_os_buffer_descriptors GROUP BY DB_NAME(database_id) , database_id ORDER BY cached_pages_count DESC; This gives you results which are quite useful, but if you add a new column with the code: …to convert the pages value to show a MB value then they become more relevant and meaningful. To see how your server reacts to queries, start up SSMS and connect to a test server and database – mine is called AdventureWorks2008. Make sure you start from a know position by running: -- Only run this on a test server otherwise your production server's-- performance may drop off a cliff and your phone will start ringing. DBCC DROPCLEANBUFFERS GO Now we can run a query that would normally turn a DBA’s hair white: USE [AdventureWorks2008] go SELECT * FROM [Sales].[SalesOrderDetail] AS sod INNER JOIN [Sales].[SalesOrderHeader] AS soh ON [sod].[SalesOrderID] = [soh].[SalesOrderID] …and then check our cache situation: A nice low figure – not! Almost 2000 pages of data in cache equating to approximately 15MB. Luckily these tables are quite narrow; if this had been on a table with more columns then this could be even more dramatic. So, let’s make our query more efficient. After resetting the cache with the DROPCLEANBUFFERS and FREEPROCCACHE code above, we’ll only select the columns we want and implement a WHERE predicate to limit the rows to a specific customer. SELECT [sod].[OrderQty] , [sod].[ProductID] , [soh].[OrderDate] , [soh].[CustomerID] FROM [Sales].[SalesOrderDetail] AS sod INNER JOIN [Sales].[SalesOrderHeader] AS soh ON [sod].[SalesOrderID] = [soh].[SalesOrderID] WHERE [soh].[CustomerID] = 29722 …and check our effect cache: Now that is more sympathetic to our server and the other systems sharing its resources. I can hear you asking: “What has this got to do with logging, Jonathan?” Well, a smart DBA will keep an eye on this metric on their servers so they know how their hardware is coping and be ready to investigate anomalies so that no ‘disruptive’ code starts to unsettle things. Capturing this information over a period of time can lead you to build a picture of how a database relies on the cache and how it interacts with other databases. This might allow you to decide on appropriate schedules for over night jobs or otherwise balance the work of your server. You could schedule this job to run with a SQL Agent job and store the data in your DBA’s database by creating a table with: IF OBJECT_ID('CachedPages') IS NOT NULL DROP TABLE CachedPages CREATE TABLE CachedPages ( cached_pages_count INT , MB INT , Database_Name VARCHAR(256) , CollectedOn DATETIME DEFAULT GETDATE() ) …and then filling it with: INSERT INTO [dbo].[CachedPages] ( [cached_pages_count] , [MB] , [Database_Name] ) SELECT COUNT(*) AS cached_pages_count , ( COUNT(*) * 8.0 ) / 1024 AS MB , CASE database_id WHEN 32767 THEN 'ResourceDb' ELSE DB_NAME(database_id) END AS Database_name FROM sys.dm_os_buffer_descriptors GROUP BY database_id After this has been left logging your system metrics for a while you can easily see how your databases use the cache over time and may see some spikes that warrant your attention. This sort of logging can be applied to all sorts of server statistics so that you can gather information that will give you baseline data on how your servers are performing. This means that when you get a problem you can see what statistics are out of their normal range and target you efforts to resolve the issue more rapidly.

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  • How do I deal with a third party application that has embedded hints that result in a sub-optimal execution plan in my environment?

    - by Maria Colgan
    I have gotten many variations on this question recently as folks begin to upgrade to Oracle Database 11g and there have been several posts on this blog and on others describing how to use SQL Plan Management (SPM) so that a non-hinted SQL statement can use a plan generated with hints. But what if the hint is supplied in the third party application and is causing performance regressions on your system? You can actually use a very similar technique to the ones shown before but this time capture the un-hinted plan and have the hinted SQL statement use that plan instead. Below is an example that demonstrates the necessary steps. 1. We will begin by running the hinted statement 2. After examining the execution plan we can see it is suboptimal because of a bad join order. 3. In order to use SPM to correct the problem we must create a SQL plan baseline for the statement. In order to create a baseline we will need the SQL_ID for the hinted statement. Easy place to get it is in V$SQL. 4. A SQL plan baseline can be created using a SQL_ID and DBMS_SPM.LOAD_PLANS_FROM_CURSOR_CACHE. This will capture the existing plan for this SQL_ID from the shared pool and store in the SQL plan baseline. 5. We can check the SQL plan baseline got created successfully by querying DBA_SQL_PLAN_BASELINES. 6. When you manually create a SQL plan baseline the first plan added is automatically accepted and enabled. We know that the hinted plan is poorly performing plan so we will disable it using DBMS_SPM.ALTER_SQL_PLAN_BASELINE. Disabling the plan tells the optimizer that this plan not a good plan, however since there is no alternative plan at this point the optimizer will still continue to use this plan until we provide a better one. 7. Now let's run the statement without the hint. 8. Looking at the execution plan we can see that the join order is different. The plan without the hint also has a lower cost (3X lower), which indicates it should perform better. 9. In order to map the un-hinted plan to the hinted SQL statement we need to add the plan to the SQL plan baseline for the hinted statement. We can do this using DBMS_SPM.LOAD_PLANS_FROM_CURSOR_CACHE but we will need the SQL_ID and  PLAN_HASH_VALUE for the non-hinted statement, which we can find in V$SQL. 10. Now we can add the non-hinted plan to the SQL plan baseline of the hinted SQL statement using DBMS_SPM.LOAD_PLANS_FROM_CURSOR_CACHE. This time we need to pass a few more arguments. We will use the SQL_ID and PLAN_HASH_VALUE of the non-hinted statement but the SQL_HANDLE of the hinted statement. 11. The SQL plan baseline for our statement now has two plans. But only the newly added plan (SQL_PLAN_gbpcg3f67pc788a6d8911) is enabled and accepted. This tells the Optimizer that this is the plan it should use for this statement. We can confirm that the correct plan (non-hinted) will be selected for the statement from now on by re-executing the hinted statement and checking its execution plan.

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  • SQL SERVER – Learn SQL Server 2014 Online in a Day – My Latest Pluralsight Course

    - by Pinal Dave
    Click here watch SQL Server 2014 Administration New Features.  SQL Server 2014 was released earlier this year and it has been extremely popular in Microsoft world. Here is the announcement for everyone, who have been asking me to build a tutorial around SQL Server 2014. I have authored latest Pluralsight courses on the subject of SQL Server 2014. This course is 4 hours and 17 minutes long, but the best part is that this course contains all the latest features of SQL Server 2014. I have build this course with the assumption that DBA is familiar with earlier versions of SQL Server and wants to explore and learn new features of SQL Server 2014. The Challenge I Faced The biggest challenge I faced was how to come up with the outline for the course. The reason is that there are so many different features introduced in SQL Server 2014 that is will be difficult to cover each of the features in a single course. I wanted to cover the topics which are the most relevant and useful to developers, but in addition I also wanted to cover the topics which may be useful to develop if they know that they exists in the product. I finally decided to depend on blog readers and few of the SQL Experts. I reached out to selected 20 people via email and gave them a list of the topics which I should be covering in this course. They all work in different organizations and have a good understanding about the need of the DBA and Developers. Based on their feedback, I was able to come up with a very good outline which is currently very popular with Pluralsight library. Lots of people have asked me how was I able to come up with a course content outline so accurately. The credit for the same goes to the developers and DBA, who have voted in the topics and have helped me to build a very solid outline for the course. Outline of the Course Here is a quick outline for the course: Introduction Backup Enhancements Security Enhancements Columnstore Enhancements Online Data Operations Enhancements Enhancements with Microsoft Azure SSD Buffer Pool Extensions Resource Governor IO Miscellaneous Features Online Index Rebuilding Live Plans for Long Running Queries Transaction Durability Cardinality Estimation In Memory OLTP Optimization Well, I had a great fun working on the topics which I have mentioned in the outline. I am very confident that once you start with the course, you will indeed understand how each of the topics builds and presented. I have made sure that each of the topic has a vivid and clear story to begin with. I first explain the story and right after that I explain the concept. Who Should Attend This Course Everyone who has basic knowledge of SQL Server and wants to update themselves with SQL Server 2014. They should attend this course. One thing I have made sure that this course is easy to understand and I have decided complex subject into multiple parts. This way the learning is progressive and anyone with a poor knowledge of the subject can have enough time to understand the presented concept. Screenshot of the Course Here are few of the screenshot of the courses. How to Watch Video Course This course is available at Pluralsight, and you will need a valid login to Pluralsight. If you do not have Pluralsight login, you can quickly sign up for the FREE Trial. Click here watch SQL Server 2014 Administration New Features.  Reference: Pinal Dave (http://blog.SQLAuthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Training, SQLAuthority News, T SQL, Video

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  • Extending Oracle CEP with Predictive Analytics

    - by vikram.shukla(at)oracle.com
    Introduction: OCEP is often used as a business rules engine to execute a set of business logic rules via CQL statements, and take decisions based on the outcome of those rules. There are times where configuring rules manually is sufficient because an application needs to deal with only a small and well-defined set of static rules. However, in many situations customers don't want to pre-define such rules for two reasons. First, they are dealing with events with lots of columns and manually crafting such rules for each column or a set of columns and combinations thereof is almost impossible. Second, they are content with probabilistic outcomes and do not care about 100% precision. The former is the case when a user is dealing with data with high dimensionality, the latter when an application can live with "false" positives as they can be discarded after further inspection, say by a Human Task component in a Business Process Management software. The primary goal of this blog post is to show how this can be achieved by combining OCEP with Oracle Data Mining® and leveraging the latter's rich set of algorithms and functionality to do predictive analytics in real time on streaming events. The secondary goal of this post is also to show how OCEP can be extended to invoke any arbitrary external computation in an RDBMS from within CEP. The extensible facility is known as the JDBC cartridge. The rest of the post describes the steps required to achieve this: We use the dataset available at http://blogs.oracle.com/datamining/2010/01/fraud_and_anomaly_detection_made_simple.html to showcase the capabilities. We use it to show how transaction anomalies or fraud can be detected. Building the model: Follow the self-explanatory steps described at the above URL to build the model.  It is very simple - it uses built-in Oracle Data Mining PL/SQL packages to cleanse, normalize and build the model out of the dataset.  You can also use graphical Oracle Data Miner®  to build the models. To summarize, it involves: Specifying which algorithms to use. In this case we use Support Vector Machines as we're trying to find anomalies in highly dimensional dataset.Build model on the data in the table for the algorithms specified. For this example, the table was populated in the scott/tiger schema with appropriate privileges. Configuring the Data Source: This is the first step in building CEP application using such an integration.  Our datasource looks as follows in the server config file.  It is advisable that you use the Visualizer to add it to the running server dynamically, rather than manually edit the file.    <data-source>         <name>DataMining</name>         <data-source-params>             <jndi-names>                 <element>DataMining</element>             </jndi-names>             <global-transactions-protocol>OnePhaseCommit</global-transactions-protocol>         </data-source-params>         <connection-pool-params>             <credential-mapping-enabled></credential-mapping-enabled>             <test-table-name>SQL SELECT 1 from DUAL</test-table-name>             <initial-capacity>1</initial-capacity>             <max-capacity>15</max-capacity>             <capacity-increment>1</capacity-increment>         </connection-pool-params>         <driver-params>             <use-xa-data-source-interface>true</use-xa-data-source-interface>             <driver-name>oracle.jdbc.OracleDriver</driver-name>             <url>jdbc:oracle:thin:@localhost:1522:orcl</url>             <properties>                 <element>                     <value>scott</value>                     <name>user</name>                 </element>                 <element>                     <value>{Salted-3DES}AzFE5dDbO2g=</value>                     <name>password</name>                 </element>                                 <element>                     <name>com.bea.core.datasource.serviceName</name>                     <value>oracle11.2g</value>                 </element>                 <element>                     <name>com.bea.core.datasource.serviceVersion</name>                     <value>11.2.0</value>                 </element>                 <element>                     <name>com.bea.core.datasource.serviceObjectClass</name>                     <value>java.sql.Driver</value>                 </element>             </properties>         </driver-params>     </data-source>   Designing the EPN: The EPN is very simple in this example. We briefly describe each of the components. The adapter ("DataMiningAdapter") reads data from a .csv file and sends it to the CQL processor downstream. The event payload here is same as that of the table in the database (refer to the attached project or do a "desc table-name" from a SQL*PLUS prompt). While this is for convenience in this example, it need not be the case. One can still omit fields in the streaming events, and need not match all columns in the table on which the model was built. Better yet, it does not even need to have the same name as columns in the table, as long as you alias them in the USING clause of the mining function. (Caveat: they still need to draw values from a similar universe or domain, otherwise it constitutes incorrect usage of the model). There are two things in the CQL processor ("DataMiningProc") that make scoring possible on streaming events. 1.      User defined cartridge function Please refer to the OCEP CQL reference manual to find more details about how to define such functions. We include the function below in its entirety for illustration. <?xml version="1.0" encoding="UTF-8"?> <jdbcctxconfig:config     xmlns:jdbcctxconfig="http://www.bea.com/ns/wlevs/config/application"     xmlns:jc="http://www.oracle.com/ns/ocep/config/jdbc">        <jc:jdbc-ctx>         <name>Oracle11gR2</name>         <data-source>DataMining</data-source>               <function name="prediction2">                                 <param name="CQLMONTH" type="char"/>                      <param name="WEEKOFMONTH" type="int"/>                      <param name="DAYOFWEEK" type="char" />                      <param name="MAKE" type="char" />                      <param name="ACCIDENTAREA"   type="char" />                      <param name="DAYOFWEEKCLAIMED"  type="char" />                      <param name="MONTHCLAIMED" type="char" />                      <param name="WEEKOFMONTHCLAIMED" type="int" />                      <param name="SEX" type="char" />                      <param name="MARITALSTATUS"   type="char" />                      <param name="AGE" type="int" />                      <param name="FAULT" type="char" />                      <param name="POLICYTYPE"   type="char" />                      <param name="VEHICLECATEGORY"  type="char" />                      <param name="VEHICLEPRICE" type="char" />                      <param name="FRAUDFOUND" type="int" />                      <param name="POLICYNUMBER" type="int" />                      <param name="REPNUMBER" type="int" />                      <param name="DEDUCTIBLE"   type="int" />                      <param name="DRIVERRATING"  type="int" />                      <param name="DAYSPOLICYACCIDENT"   type="char" />                      <param name="DAYSPOLICYCLAIM" type="char" />                      <param name="PASTNUMOFCLAIMS" type="char" />                      <param name="AGEOFVEHICLES" type="char" />                      <param name="AGEOFPOLICYHOLDER" type="char" />                      <param name="POLICEREPORTFILED" type="char" />                      <param name="WITNESSPRESNT" type="char" />                      <param name="AGENTTYPE" type="char" />                      <param name="NUMOFSUPP" type="char" />                      <param name="ADDRCHGCLAIM"   type="char" />                      <param name="NUMOFCARS" type="char" />                      <param name="CQLYEAR" type="int" />                      <param name="BASEPOLICY" type="char" />                                     <return-component-type>char</return-component-type>                                                      <sql><![CDATA[             SELECT to_char(PREDICTION_PROBABILITY(CLAIMSMODEL, '0' USING *))               AS probability             FROM (SELECT  :CQLMONTH AS MONTH,                                            :WEEKOFMONTH AS WEEKOFMONTH,                          :DAYOFWEEK AS DAYOFWEEK,                           :MAKE AS MAKE,                           :ACCIDENTAREA AS ACCIDENTAREA,                           :DAYOFWEEKCLAIMED AS DAYOFWEEKCLAIMED,                           :MONTHCLAIMED AS MONTHCLAIMED,                           :WEEKOFMONTHCLAIMED,                             :SEX AS SEX,                           :MARITALSTATUS AS MARITALSTATUS,                            :AGE AS AGE,                           :FAULT AS FAULT,                           :POLICYTYPE AS POLICYTYPE,                            :VEHICLECATEGORY AS VEHICLECATEGORY,                           :VEHICLEPRICE AS VEHICLEPRICE,                           :FRAUDFOUND AS FRAUDFOUND,                           :POLICYNUMBER AS POLICYNUMBER,                           :REPNUMBER AS REPNUMBER,                           :DEDUCTIBLE AS DEDUCTIBLE,                            :DRIVERRATING AS DRIVERRATING,                           :DAYSPOLICYACCIDENT AS DAYSPOLICYACCIDENT,                            :DAYSPOLICYCLAIM AS DAYSPOLICYCLAIM,                           :PASTNUMOFCLAIMS AS PASTNUMOFCLAIMS,                           :AGEOFVEHICLES AS AGEOFVEHICLES,                           :AGEOFPOLICYHOLDER AS AGEOFPOLICYHOLDER,                           :POLICEREPORTFILED AS POLICEREPORTFILED,                           :WITNESSPRESNT AS WITNESSPRESENT,                           :AGENTTYPE AS AGENTTYPE,                           :NUMOFSUPP AS NUMOFSUPP,                           :ADDRCHGCLAIM AS ADDRCHGCLAIM,                            :NUMOFCARS AS NUMOFCARS,                           :CQLYEAR AS YEAR,                           :BASEPOLICY AS BASEPOLICY                 FROM dual)                 ]]>         </sql>        </function>     </jc:jdbc-ctx> </jdbcctxconfig:config> 2.      Invoking the function for each event. Once this function is defined, you can invoke it from CQL as follows: <?xml version="1.0" encoding="UTF-8"?> <wlevs:config xmlns:wlevs="http://www.bea.com/ns/wlevs/config/application">   <processor>     <name>DataMiningProc</name>     <rules>        <query id="q1"><![CDATA[                     ISTREAM(SELECT S.CQLMONTH,                                   S.WEEKOFMONTH,                                   S.DAYOFWEEK, S.MAKE,                                   :                                         S.BASEPOLICY,                                    C.F AS probability                                                 FROM                                 StreamDataChannel [NOW] AS S,                                 TABLE(prediction2@Oracle11gR2(S.CQLMONTH,                                      S.WEEKOFMONTH,                                      S.DAYOFWEEK,                                       S.MAKE, ...,                                      S.BASEPOLICY) AS F of char) AS C)                       ]]></query>                 </rules>               </processor>           </wlevs:config>   Finally, the last stage in the EPN prints out the probability of the event being an anomaly. One can also define a threshold in CQL to filter out events that are normal, i.e., below a certain mark as defined by the analyst or designer. Sample Runs: Now let's see how this behaves when events are streamed through CEP. We use only two events for brevity, one normal and other one not. This is one of the "normal" looking events and the probability of it being anomalous is less than 60%. Event is: eventType=DataMiningOutEvent object=q1  time=2904821976256 S.CQLMONTH=Dec, S.WEEKOFMONTH=5, S.DAYOFWEEK=Wednesday, S.MAKE=Honda, S.ACCIDENTAREA=Urban, S.DAYOFWEEKCLAIMED=Tuesday, S.MONTHCLAIMED=Jan, S.WEEKOFMONTHCLAIMED=1, S.SEX=Female, S.MARITALSTATUS=Single, S.AGE=21, S.FAULT=Policy Holder, S.POLICYTYPE=Sport - Liability, S.VEHICLECATEGORY=Sport, S.VEHICLEPRICE=more than 69000, S.FRAUDFOUND=0, S.POLICYNUMBER=1, S.REPNUMBER=12, S.DEDUCTIBLE=300, S.DRIVERRATING=1, S.DAYSPOLICYACCIDENT=more than 30, S.DAYSPOLICYCLAIM=more than 30, S.PASTNUMOFCLAIMS=none, S.AGEOFVEHICLES=3 years, S.AGEOFPOLICYHOLDER=26 to 30, S.POLICEREPORTFILED=No, S.WITNESSPRESENT=No, S.AGENTTYPE=External, S.NUMOFSUPP=none, S.ADDRCHGCLAIM=1 year, S.NUMOFCARS=3 to 4, S.CQLYEAR=1994, S.BASEPOLICY=Liability, probability=.58931702982118561 isTotalOrderGuarantee=true\nAnamoly probability: .58931702982118561 However, the following event is scored as an anomaly with a very high probability of  89%. So there is likely to be something wrong with it. A close look reveals that the value of "deductible" field (10000) is not "normal". What exactly constitutes normal here?. If you run the query on the database to find ALL distinct values for the "deductible" field, it returns the following set: {300, 400, 500, 700} Event is: eventType=DataMiningOutEvent object=q1  time=2598483773496 S.CQLMONTH=Dec, S.WEEKOFMONTH=5, S.DAYOFWEEK=Wednesday, S.MAKE=Honda, S.ACCIDENTAREA=Urban, S.DAYOFWEEKCLAIMED=Tuesday, S.MONTHCLAIMED=Jan, S.WEEKOFMONTHCLAIMED=1, S.SEX=Female, S.MARITALSTATUS=Single, S.AGE=21, S.FAULT=Policy Holder, S.POLICYTYPE=Sport - Liability, S.VEHICLECATEGORY=Sport, S.VEHICLEPRICE=more than 69000, S.FRAUDFOUND=0, S.POLICYNUMBER=1, S.REPNUMBER=12, S.DEDUCTIBLE=10000, S.DRIVERRATING=1, S.DAYSPOLICYACCIDENT=more than 30, S.DAYSPOLICYCLAIM=more than 30, S.PASTNUMOFCLAIMS=none, S.AGEOFVEHICLES=3 years, S.AGEOFPOLICYHOLDER=26 to 30, S.POLICEREPORTFILED=No, S.WITNESSPRESENT=No, S.AGENTTYPE=External, S.NUMOFSUPP=none, S.ADDRCHGCLAIM=1 year, S.NUMOFCARS=3 to 4, S.CQLYEAR=1994, S.BASEPOLICY=Liability, probability=.89171554529576691 isTotalOrderGuarantee=true\nAnamoly probability: .89171554529576691 Conclusion: By way of this example, we show: real-time scoring of events as they flow through CEP leveraging Oracle Data Mining.how CEP applications can invoke complex arbitrary external computations (function shipping) in an RDBMS.

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  • Red Gate's on the road in 2012 - Will you catch us?

    - by RedAndTheCommunity
    Annabel Bradford, our Communities and Events Manager, tells all about her experience of our 1st SQL Saturday of the year. The first stop this year was SQL Saturday #104 Colorado Springs, back in early January. I made the trip across from the UK just for this SQL Saturday event, and I'm so glad I did. I picked up Max from Red Gate's Pasadena office and we flew into Colorado Springs airport late on Friday evening to be greeted by freezing temperatures, which was quite a shock after the California sunshine. Rising before the sun, we arrived at Mr Biggs, the venue for the event, in the darkness. It was great to see so many smiling attendees so bright and early on a Saturday morning. Everyone was eager to learn more about SQL Server, and hundreds of people came and chatted with us at the table, saw demos and learnt more about Red Gate tools. The event highlights for the attendees were definitely the unlimited lazer quest, bowling and pool available during the break times. For Max, Grant Fritchey and I on the Red Gate table, the highlights have to be meeting customers and getting the opportunity to meet attendees who'd heard of, but wanted to know more about, Red Gate. We were delighted to hear lots of valuable feedback that we took back to share with the team. As a thank you for sharing insights about their work lives and how they use SQL Server and Red Gate tools, attendees are able to take away Red Gate SQL Server books. We aim to have a range of titles available when we exhibit, so that attendees can choose a book that's going to be most interesting to them, and that they can use as a reference back at the office. Every time I meet a Red Gate user or a member of the SQL community, I'm always overwhelmed by the enthusiasm they have for their industry. Everyone who gives up their time to learn more about their job should be rewarded, and at Red Gate we like to do just that. Red Gate has long supported the SQL community through sponsorship to facilitate user group meetings and community events, but it's only though face-to-face contact that we really get a chance to see the impact of our support. I hope we'll have the chance to see you on the road at some point this year. We'll be at a range of events, including free SQL Saturdays, one day free events 'the Red Gate way', two-day Rallys, and full-week conferences. Next stop is SQL Saturday #109 Silicon Valley on March 3rd where you'll meet Jeff and Arneh, two of our US-based SQL team members. Be sure to ask them any questions you've got about the Red Gate tools, as these guys will be delighted to hear your questions, show you the options, and will make a note of your feedback to send through to the development team. Until the next time. Happy learning! Annabel                         Grant, Max and Annabel at SQL Saturday #104 Colorado Springs

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  • A Case for Oracle Fusion Middleware by Lucas Jellema

    - by JuergenKress
    An in-depth look at the interaction of people, processes, and technologies in the transition to a service-oriented architecture. Author's Note This article presents a profile of a fictitious organization, NOPERU. The story of NOPERU as told in this article is actually a collage of the events at some dozen organizations that I have been involved with over the past few years. None of these organizations sport all the characteristics of NOPERU - but all of them have gone through or are going through a similar transition as described here and all aspects of this article were taken from real life at one or usually many of these organizations. Background NOPERU (National Organization for Permits for Emissions and Resource Usage) is a public organization that continues to transform in terms of its business, organization and technology. Changing business requirements; new interaction channels; and increasing demands for more flexibility, faster throughput and lower costs drive these transformations, while technological evolution and new architecture patterns enable the change. NOPERU chose Oracle Fusion Middleware as the technology platform to implement the new architecture and required applications. This article takes a close look at NOPERU's journey from its origins in the early 1990s as a largely paper-based entity with regional databases and client-server Oracle Forms applications. Its upcoming business objectives are introduced: what is required of the organization and what the higher goals behind these requirements are. The architecture roadmap is described at a high level as well as drilled down to a service oriented design. Based on the architecture roadmap and the business requirements and NOPERU went through a technology selection to determine the technology stack with which the future would be realized in terms of IT. The article discusses that selection and details the projects subsequently planned (and executed to date). The new architecture and technology as well as the introduction of an Agile development method have had substantial consequences for the IT organization, the processes and individual staff members. The approach NOPERU has adopted with regard to the people and the organization is portrayed. Finally, the article discusses many conclusions that NOPERU has drawn that may benefit itself and other organizations. Introducing NOPERU NOPERU is a national organization charged with issuing permits for excessive emissions (i.e., carbon dioxide) and disproportionate usage of such resources as energy or water. Anyone-whether a commercial enterprise, government agency or private person--who emits or consumes more than what is considered "fair usage" requires such a permit. When someone builds an outdoor heated swimming pool, for example, or open-air terrace heating, such a permit needs to be obtained. When a company installs new, energy-intensive equipment, such as water boilers or deep freezers, it too needs to get a NOPERU permit. Government-sponsored projects at every level that involve consumption of large quantities of fresh water or production of high volumes of emissions must turn to NOPERU for a permit. Without the required license, any interested party can get a court to immediately put a stop to the disputed activity. Read the full article here. SOA & BPM Partner Community For regular information on Oracle SOA Suite become a member in the SOA & BPM Partner Community for registration please visit www.oracle.com/goto/emea/soa (OPN account required) If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Facebook Wiki Mix Forum Technorati Tags: Lucas Jellema,SOA Community,Oracle SOA,Oracle BPM,Community,OPN,Jürgen Kress

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  • LexisNexis and Oracle Join Forces to Prevent Fraud and Identity Abuse

    - by Tanu Sood
    Author: Mark Karlstrand About the Writer:Mark Karlstrand is a Senior Product Manager at Oracle focused on innovative security for enterprise web and mobile applications. Over the last sixteen years Mark has served as director in a number of tech startups before joining Oracle in 2007. Working with a team of talented architects and engineers Mark developed Oracle Adaptive Access Manager, a best of breed access security solution.The world’s top enterprise software company and the world leader in data driven solutions have teamed up to provide a new integrated security solution to prevent fraud and misuse of identities. LexisNexis Risk Solutions, a Gold level member of Oracle PartnerNetwork (OPN), today announced it has achieved Oracle Validated Integration of its Instant Authenticate product with Oracle Identity Management.Oracle provides the most complete Identity and Access Management platform. The only identity management provider to offer advanced capabilities including device fingerprinting, location intelligence, real-time risk analysis, context-aware authentication and authorization makes the Oracle offering unique in the industry. LexisNexis Risk Solutions provides the industry leading Instant Authenticate dynamic knowledge based authentication (KBA) service which offers customers a secure and cost effective means to authenticate new user or prove authentication for password resets, lockouts and such scenarios. Oracle and LexisNexis now offer an integrated solution that combines the power of the most advanced identity management platform and superior data driven user authentication to stop identity fraud in its tracks and, in turn, offer significant operational cost savings. The solution offers the ability to challenge users with dynamic knowledge based authentication based on the risk of an access request or transaction thereby offering an additional level to other authentication methods such as static challenge questions or one-time password when needed. For example, with Oracle Identity Management self-service, the forgotten password reset workflow utilizes advanced capabilities including device fingerprinting, location intelligence, risk analysis and one-time password (OTP) via short message service (SMS) to secure this sensitive flow. Even when a user has lost or misplaced his/her mobile phone and, therefore, cannot receive the SMS, the new integrated solution eliminates the need to contact the help desk. The Oracle Identity Management platform dynamically switches to use the LexisNexis Instant Authenticate service for authentication if the user is not able to authenticate via OTP. The advanced Oracle and LexisNexis integrated solution, thus, both improves user experience and saves money by avoiding unnecessary help desk calls. Oracle Identity and Access Management secures applications, Juniper SSL VPN and other web resources with a thoroughly modern layered and context-aware platform. Users don't gain access just because they happen to have a valid username and password. An enterprise utilizing the Oracle solution has the ability to predicate access based on the specific context of the current situation. The device, location, temporal data, and any number of other attributes are evaluated in real-time to determine the specific risk at that moment. If the risk is elevated a user can be challenged for additional authentication, refused access or allowed access with limited privileges. The LexisNexis Instant Authenticate dynamic KBA service plugs into the Oracle platform to provide an additional layer of security by validating a user's identity in high risk access or transactions. The large and varied pool of data the LexisNexis solution utilizes to quiz a user makes this challenge mechanism even more robust. This strong combination of Oracle and LexisNexis user authentication capabilities greatly mitigates the risk of exposing sensitive applications and services on the Internet which helps an enterprise grow their business with confidence.Resources:Press release: LexisNexis® Achieves Oracle Validated Integration with Oracle Identity Management Oracle Access Management (HTML)Oracle Adaptive Access Manager (pdf)

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  • Do your filesystems have un-owned files ?

    - by darrenm
    As part of our work for integrated compliance reporting in Solaris we plan to provide a check for determining if the system has "un-owned files", ie those which are owned by a uid that does not exist in our configured nameservice.  Tests such as this already exist in the Solaris CIS Benchmark (9.24 Find Un-owned Files and Directories) and other security benchmarks. The obvious method of doing this would be using find(1) with the -nouser flag.  However that requires we bring into memory the metadata for every single file and directory in every local file system we have mounted.  That is probaby not an acceptable thing to do on a production system that has a large amount of storage and it is potentially going to take a long time. Just as I went to bed last night an idea for a much faster way of listing file systems that have un-owned files came to me. I've now implemented it and I'm happy to report it works very well and peforms many orders of magnatude better than using find(1) ever will.   ZFS (since pool version 15) has per user space accounting and quotas.  We can report very quickly and without actually reading any files at all how much space any given user id is using on a ZFS filesystem.  Using that information we can implement a check to very quickly list which filesystems contain un-owned files. First a few caveats because the output data won't be exactly the same as what you get with find but it answers the same basic question.  This only works for ZFS and it will only tell you which filesystems have files owned by unknown users not the actual files.  If you really want to know what the files are (ie to give them an owner) you still have to run find(1).  However it has the huge advantage that it doesn't use find(1) so it won't be dragging the metadata for every single file and directory on the system into memory. It also has the advantage that it can check filesystems that are not mounted currently (which find(1) can't do). It ran in about 4 seconds on a system with 300 ZFS datasets from 2 pools totalling about 3.2T of allocated space, and that includes the uid lookups and output. #!/bin/sh for fs in $(zfs list -H -o name -t filesystem -r rpool) ; do unknowns="" for uid in $(zfs userspace -Hipn -o name,used $fs | cut -f1); do if [ -z "$(getent passwd $uid)" ]; then unknowns="$unknowns$uid " fi done if [ ! -z "$unknowns" ]; then mountpoint=$(zfs list -H -o mountpoint $fs) mounted=$(zfs list -H -o mounted $fs) echo "ZFS File system $fs mounted ($mounted) on $mountpoint \c" echo "has files owned by unknown user ids: $unknowns"; fi done Sample output: ZFS File system rpool/ROOT/solaris-30/var mounted (no) on /var has files owned by unknown user ids: 6435 33667 101 ZFS File system rpool/ROOT/solaris-32/var mounted (yes) on /var has files owned by unknown user ids: 6435 33667ZFS File system builds/bob mounted (yes) on /builds/bob has files owned by unknown user ids: 101 Note that the above might not actually appear exactly like that in any future Solaris product or feature, it is provided just as an example of what you can do with ZFS user space accounting to answer questions like the above.

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  • MySql Connector/NET 6.7.4 GA has been released

    - by fernando
    MySQL Connector/Net 6.7.4, a new version of the all-managed .NET driver for MySQL has been released.  This is the GA, is feature complete. It is recommended for production environments.  It is appropriate for use with MySQL server versions 5.0-5.7.  It is now available in source and binary form from http://dev.mysql.com/downloads/connector/net/#downloads and mirror sites (note that not all mirror sites may be up to date at this point-if you can't find this version on some mirror, please try again later or choose another download site.) The 6.7 version of MySQL Connector/Net brings the following new features: -  WinRT Connector. -  Load Balancing support. -  Entity Framework 5.0 support. -  Memcached support for Innodb Memcached plugin. -  This version also splits the product in two: from now on, starting version 6.7, Connector/NET will include only the former Connector/NET ADO.NET driver, Entity Framework and ASP.NET providers (Core libraries of MySql.Data, MySql.Data.Entity & MySql.Web). While all the former product Visual Studio integration (Design support, Intellisense, Debugger) are available as part of MySql Windows Installer under the name "MySql for Visual Studio".  WinRT Connector  ------------------------------------------- Now you can write MySql data access apps in Windows Runtime (aka Store Apps) using the familiar API of Connector/NET for .NET.  Load Balancing Support  -------------------------------------------  Now you can setup a Replication or Cluster configuration in the backend, and Connector/NET will balance the load of queries among all servers making up the backend topology.  Entity Framework 5.0  -------------------------------------------  Connector/NET is now compatible with EF 5, including special features of EF 5 like spatial types.  Memcached  -------------------------------------------  Just setup Innodb memcached plugin and use Connector/NET new APIs to establish a client to MySql 5.6 server's memcached daemon.  Bug fixes included in this release: - Fix for Entity Framework when inserts data having Identity columns (Oracle bug #16494585). - Fix for Connector/NET cannot read data from a MySql table using UTF-16/UTF-32 (MySql bug #69169, Oracle bug #16776818). - Fix for Malformed query in Entity Framework when eager loading due to multiple projections (MySql bug #67183, Oracle bug #16872852). - Fix for database objects with 'dbo' prefix when using automatic migrations in Entity Framework 5.0 (Oracle bug #16909439). - Fix for bug IIS application pool reset worker process causes website to crash (Oracle bug #16909237, Mysql Bug #67665). - Fix for bug Error in LINQ to Entities query when using Distinct().Count() (MySql Bug #68513, Oracle bug #16950146). - Fix for occasionally return no data when socket connection is slow, interrupted or delayed (MySql bug #69039, Oracle bug #16950212). - Fix for ConstraintException when filling a datatable (MySql bug #65065, Oracle bug #16952323). - Fix for Data Provider is not found after uninstalling Mysql for visual studio (Oracle bug #16973456). - Fix for nested sql generated for LINQ to Entities query with Take and Order by (MySql bug #65723, Oracle bug #16973939). The documentation is available at http://dev.mysql.com/doc/refman/5.7/en/connector-net.html  Enjoy and thanks for the support!  --  Fernando Gonzalez Sanchez | Software Engineer |  Oracle MySQL Windows Experience Team, Connector/NET  Guadalajara | Jalisco | Mexico 

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  • How to move complete SharePoint Server 2007 from one box to another

    - by DipeshBhanani
    It was time of my first onsite client assignment on SharePoint. Client had one server production environment. They wanted to upgrade the topology with completely new SharePoint Farm of three servers. So, the task was to move whole MOSS 2007 stuff to the new server environment without impacting data. The last three scary words “… without impacting data…” were actually putting pressure on my head. Moreover SSP was required to move because additional information has been added for users apart from AD import.   I thought I had to do only backup and restore. It appeared pretty easy at first thought. Just because of these damn scary words, I thought to check out on internet for guidance related to this scenario. I couldn’t get anything except general guidance of moving server on Microsoft TechNet site. I promised myself for starting blogs with this post if I would be successful in this task. Well, I took long time to write this but finally made it. I hope it will be useful to all guys looking for SharePoint server movement.   Before beginning restoration, make sure that, there is no difference in versions of SharePoint at source and destination server. Also check whether the state of SharePoint Installation at the time of backup and restore is same or not. (E.g. SharePoint related service packs and patches if any)   The main tasks of the server movement are as follow:   Backup all the databases Install and configure SharePoint on new environment Deploy all solution (WSP Files) globally to destination server- for installing features attached to the solutions Install all the custom features Deploy/Copy custom pages/files which are added to the “12Hive” folder later Restore SSP Restore My Site Restore other web application   Tasks 3 to 5 are for making sure that we have configured the environment well enough for the web application to be restored successfully. The main and complex task was restoring SSP. I have started restoring SSP through Central Admin. After a while, the restoration status was updated to “unsuccessful”. “Damn it, what went wrong?” I thought looking at the error detail down the page. I couldn’t remember the error message but I had corrected and restored it again.   Actually once you fail restoring SSP, until and unless you don’t clean all related stuff well, your restoration will be failed again and again. I wanted to find the actual reason. So cleaned, restored, cleaned, restored… I had tried almost 5-6 times and finally, I succeeded. I had realized how pleasant it is, to see the word “Successful” on the screen. Without wasting your much time to read, let me write all the detailed steps of restoring SSP:   Delete the SSP through following STSADM command. stsadm -o deletessp -title <SSP name> -deletedatabases -force e.g.: stsadm -o deletessp -title SharedServices1 -deletedatabases –force Check and delete the web application associated with SSP if it exists. Remove Link from Check and remove “Alternate Access Mapping” associated with SSP if it exists. Check and delete IIS site as well as application pool associated with SSP if it exists. Stop following services: ·         Office SharePoint Server Search ·         Windows SharePoint Services Search ·         Windows SharePoint Services Help Search Delete all the databases associated/related to SSP from SQL Server. Reset IIS. Start again following services: ·         Office SharePoint Server Search ·         Windows SharePoint Services Search ·         Windows SharePoint Services Help Search Restore the new SSP.   After the SSP restoration, all other stuffs had completed very smoothly without any more issues. I did few modifications to sites for change of server name and finally, the new environment was ready.

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  • Some OBI EE Tricks and Tips in the Admin Tool By Gerry Langton

    - by hamsun
    How to set the log level from a Session variable Initialization block As we know it is normal to set the log level non-zero for a particular user when we wish to debug problems. However sometimes it is inconvenient to go into each user’s properties in the Admin tool and update the log level. So I am showing a method which allows the log level to be set for all users via a session initialization block. This is particularly useful for anyone wanting an alternative way to set the log level. The screen shots shown are using the OBIEE 11g SampleApp demo but are applicable to any environment. Open the appropriate rpd in on-line mode and navigate to Manage Variables. Select Session Initialization Blocks, right click in the white space and create a New Initialization Block. I called the Initialization block Set_Loglevel . Now click on ‘Edit Data Source’ to enter the SQL. Chose the ‘Use OBI EE Server’ option for the SQL. This means that the SQL provided must use tables which have been defined in the Physical layer of the RPD, and whilst there is no need to provide a connection pool you must work in On-Line mode. The SQL can access any of the RPD tables and is purely used to return a value of 2. The ‘Test’ button confirms that the SQL is valid. Next, click on the ‘Edit Data Target’ button to add the LOGLEVEL variable to the initialization block. Check the ‘Enable any user to set the value’ option so that this will work for any user. Click OK and the following message will display as LOGLEVEL is a system session variable: Click ‘Yes’. Click ‘OK’ to save the Initialization block. Then check in the On-LIne changes. To test that LOGLEVEL has been set, log in to OBIEE using an administrative login (e.g. weblogic) and reload server metadata, either from the Analysis editor or from Administration > Reload Files and Metadata link. Run a query then navigate to Administration > Manage Sessions and click ‘View Log’ for the query just issued (which should be approximately the last in the list). A log file should exist and with LOGLEVEL set to 2 should include both logical and physical sql. If more diagnostic information is required then set LOGLEVEL to a higher value. If logging is required only for a particular analysis then an alternative method can be used directly from the Analysis editor. Edit the analysis for which debugging is required and click on the Advanced tab. Scroll down to the Advanced SQL clauses section and enter the following in the Prefix box: SET VARIABLE LOGLEVEL = 2; Click the ‘Apply SQL’ button. The SET VARIABLE statement will now prefix the Analysis’s logical SQL. So that any time this analysis is run it will produce a log. You can find information about training for Oracle BI EE products here or in the OU Learning Paths. Please send me an email at [email protected] if you have any further questions. About the Author: Gerry Langton started at Siebel Systems in 1999 working as a technical instructor teaching both Siebel application development and also Siebel Analytics (which subsequently became Oracle BI EE). From 2006 Gerry has worked as Senior Principal Instructor within Oracle University specialising in Oracle BI EE, Oracle BI Publisher and Oracle Data Warehouse development for BI.

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  • Join our Marketing Intelligence Team in Dublin!

    - by jessica.ebbelaar
    Do you want to work with the brightest minds in the industry? Want to be part of a global team that’s changing the way the world does business? Then Oracle is the place for YOU. Join now as a Marketing Intelligence Representative. You will have the opportunity to develop within the role through working alongside the Business Development, Sales and Marketing teams within Oracle. The Marketing Intelligence Group is viewed as a true talent pool for the Business Development and Sales Teams. Oracle offers a structured training programme for Marketing Intelligence Representatives and Business Development Consultants including our approved sales certified training methodology along with regular product training. Miriam started her career as a Marketing Intelligence Representative six years ago, and shares what she has learned and how her career is progressing. My Career Path at Oracle: June 2005 – October 2005: Profiler in the Marketing Intelligence Team November 2005 - October 2006: Team Leader for MIT November 2006 - February 2008: Business Development Consultant Iberia March 2008 - December 2010: Lead Management Specialist Currently: Sales Program Manager for Iberia & Benelux What did you learn from your role in the Market Intelligence Team Being a Profiler helped me to understand how an organisation works, from the beginning to the end. It is like being in University but being paid! The three key things I learnt in this role are: Knowledge of customers: You are on the phone with over 70 customers daily. Not only does this give you an overview of the IT infrastructure of the customers companies but also how to manage their questions and rejections. Essentially you are learning how to convert their pain and complaints into business opportunities. Knowledge of Oracle: As a Profiler you get an excellent overview of how Oracle works internally, from Marketing to Sales, without forgetting the Operations Team. Knowledge about yourself: As a Profiler I learnt how to work outside of my comfort zone, there is a new challenge almost every day but Oracle are there to support you every step of the way. Oracle really invests in developing the MIT Team and as a Profiler you can expect product and sales training on a monthly basis. How did you progress from MIT to Business Development Group (BDG)? I made sure that my manager knew from the very beginning that I was keen to progress at Oracle and I was set very clear objectives to help me reach my goal.  My manager was very supportive and ensured I received all the training I needed. After I became a Team Leader of Profiling, I moved to an Iberia BDG position. How you feel your experience in MI has helped you in your current role? I truly believe that the MI position gives you a great overview of Oracle and this has really helped me in my current position.  I am the Sales Program Manager for IBERIA & Benelux and in my campaigns I need to target the right companies and the right job specs.  My time in the Market Intelligence team really helped me to understand how to focus and target my campaigns so I know I don’t miss any business opportunities! How would you sum up your Oracle experience? Oracle is a big organisation with big opportunities. With the right skills and with the great training programs that Oracle offer, the only limit is you! If you have any questions related to this article feel free to contact [email protected] You can find all our job opportunities via http://campus.oracle.com. Tags van Technorati: Marketing Intelligence,Benelux,Iberia,Profiler,Business Development,Sales Representatives,BDG,Business Development Group,opportunities,Oracle

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  • Expanding the Partner Ecosystem with Third-Party Plug-ins

    - by Joe Diemer
    Oracle Enterprise Manager’s extensibility capabilities are designed to allow customers and partners to adapt Enterprise Manager for management of heterogeneous environments with Plug-ins and Connectors.  Third-party developers continue to take advantage of Oracle Enterprise Manager’s Extensibility Development Kit (EDK) to build plug-ins to Enterprise Manager 12c, such as F5’s BIG IP Plug-in and Entuity’s Eye of the Storm Network Management Plug-In.  Partners can also validate their plug-ins through the Oracle Validated Integration (OVI) program, which assures customers that the plug-in has been tested and is functionally and technically sound, is designed in a reliable and standardized manner, and operates and performs as documented.   Two very recent examples of partners which have beta versions of their plug-ins are Blue Medora's VMware vSphere plug-in and the NetApp Storage plug-in.  VMware vSphere Plug-in by Blue Medora Blue Medora, an Oracle Partner Network (OPN) “Gold” member, which just announced that it is now signing up customers to try a beta version of their new VMware vSphere plug-in for Enterprise Manager 12c.  According to Blue Medora, the vSphere plug-in monitors critical VMware metrics (CPU, Memory, Disk, Network, etc) at the Host, VM, Cluster and Resource Pool levels.  It has minimal performance impact via an “agentless” approach that requires no installation directly on VMware servers.  It has discovery capabilities for VMware Datacenters, ESX Hosts, Clusters, Virtual Machines, and Datastores.  It offers integration of native VMware Events into Enterprise Manager, and it provides over 300 VMware-related health, availability, performance, and configuration metrics.  It comes with more than 30 out-of-the-box pre-defined thresholds and can manage VMware via a series of jobs split between cluster, host and VM target types.The company reports that the Enterprise Manager 12c plug-in supports vSphere versions 4.0, 4.5 and 5.0.  Platforms supported include Linux 64-bit, Windows, AIX and Solaris SPARC and x86.  Information about the plug-in, including how to sign up for the beta, is available at their web site at http://bluemedora.com after selecting the "Products" tab. NetApp Storage Plug-in NetApp believes the combination of storage system monitoring with comprehensive management of Oracle systems with Enterprise Manager will help customers reduce the cost and complexity of managing applications that rely on NetApp storage and Oracle technologies.  So, NetApp built a plug-in and reports that it has comprehensive availability and performance information for NetApp storage systems.  Using the plug-in, Oracle Enterprise Manager customers with NetApp storage solutions can track the association between databases and storage components and thereby respond to faults and IO performance bottlenecks quickly. With the latest configuration management capabilities, one can also perform drift analysis to make sure all storage systems are configured as per established gold standards. The company is also now signing up beta customers, which can be done at the NetApp Communities site at https://communities.netapp.com/groups/netapp-storage-system-plug-in-for-oem12c-beta. Learn More about Enterprise Manager Extensibility More plug-ins from other partners are soon to come, which I'll be reporting on them here.  To learn more about Enterprise Manager and how customers and partners can build plug-ins using the EDK to manage a multi-vendor data center, go to http://oracle.com/enterprisemanager in the Heterogeneous Management solution area.  The site also lists the plug-ins available with information on how to obtain them.  More info about the Oracle Validated Integration program can be found at the OPN Enterprise Manager Knowledge Zone in the "Develop" tab.

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  • Oracle Enterprise Manager Ops Center 12c Update 1 is available now

    - by Anand Akela
    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:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Following the announcement of Oracle Enterprise Manager Ops Center 12c on April 4th, we are happy to announce the release of Oracle Enterprise Manager Ops Center 12c update 1. This is a bundled patch release for Oracle Enterprise Manager Ops Center.  Here are the key features of the Oracle Enterprise Manager Ops Center 12c update 1 : Oracle VM SPARC Server Pool HA Policy  Automatically Upgrade from Ops Center 11g update 3 and Ops Center 12c  Oracle Linux 5.8 and 6.x Support  Oracle VM SPARC IaaS (Virtual Datacenters) WANBoot Improvements with OBP Handling Enhancements SPARC SuperCluster Support Stability fixes This new release contains significant enhancements in the update provisioning, bare metal OS provisioning, shared storage management, cloud/virtual datacenter, and networking management sections of the product.  With this update, customers can achieve better handling of ASR faults, add networks and storage to virtual guests more easily, understand IPMP and VLAN configurations better, get a more robust LDAP integration, get  virtualization aware firmware patching, and observe improved product performance across the board.  Customers can now accelerate Oracle VM SPARC and T4 deployments into production . Oracle Enterprise Manager Ops Center 11g and Ops Center 12c customers will now notice the availability of new product update under the Administration tab within the  Browser User Interface (BUI) .  Upgrade process is explained in detail within the Ops Center Administration Guide under “Chapter 10: Upgrading”.  Please be sure to read over that chapter and the Release Notes before upgrading.  During the week of July 9th,  the full download of the product will be available from the Oracle Enterprise Manager Ops Center download website.  Based on the customer feedback, we have changed the updates to include the entire product. Customers no longer need to install Ops Center 12c and then upgrade to the update 1 release.  The can simply install Ops Center 12c update 1 directly.  Here are some of the resources that can help you learn more about the Oracle Enterprise Manager Ops Center and the new update 1. Oracle Enterprise Manager Ops Center OTN site Bi-Monthly Product Demos Oracle Enterprise Manager Ops Center Forum Oracle Enterprise Manager Ops Center MOS Community Watch the recording of Oracle Enterprise Manager 12c launch webcast by clicking the following banner. Stay Connected: Twitter |  Face book |  You Tube |  Linked in |  Newsletter

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  • Sprinkle Some Magik on that Java Virtual Machine

    - by Jim Connors
    GE Energy, through its Smallworld subsidiary, has been providing geospatial software solutions to the utility and telco markets for over 20 years.  One of the fundamental building blocks of their technology is a dynamically-typed object oriented programming language called Magik.  Like Java, Magik source code is compiled down to bytecodes that run on a virtual machine -- in this case the Magik Virtual Machine. Throughout the years, GE has invested considerable engineering talent in the support and maintenance of this virtual machine.  At the same time vast energy and resources have been invested in the Java Virtual Machine. The question for GE has been whether to continue to make that investment on its own or to leverage massive effort provided by the Java community? Utilizing the Java Virtual Machine instead of maintaining its own virtual machine would give GE more opportunity to focus on application solutions.   At last count, there are dozens, perhaps hundreds of examples of programming languages that have been hosted atop the Java Virtual Machine.  Prior to the release of Java 7, that effort, although certainly possible, was generally less than optimal for languages like Magik because of its dynamic nature.  Java, as a statically typed language had little use for this capability.  In the quest to be a more universal virtual machine, Java 7, via JSR-292, introduced a new bytecode called invokedynamic.  In short, invokedynamic affords a more flexible method call mechanism needed by dynamic languages like Magik. With this new capability GE Energy has succeeded in hosting their Magik environment on top of the Java Virtual Machine.  So you may ask, why would GE wish to do such a thing?  The benefits are many: Competitors to GE Energy claimed that the Magik environment was proprietary.  By utilizing the Java Virtual Machine, that argument gets put to bed.  JVM development is done in open source, where contributions are made world-wide by all types of organizations and individuals. The unprecedented wealth of class libraries and applications written for the Java platform are now opened up to Magik/JVM platform as first class citizens. In addition, the Magik/JVM solution vastly increases the developer pool to include the 9 million Java developers -- the largest developer community on the planet. Applications running on the JVM showed substantial performance gains, in some cases as much as a 5x speed up over the original Magik platform. Legacy Magik applications can still run on the original platform.  They can be seamlessly migrated to run on the JVM by simply recompiling the source code. GE can now leverage the huge Java community.  Undeniably the best virtual machine ever created, hundreds if not thousands of world class developers continually improve, poke, prod and scrutinize all aspects of the Java platform.  As enhancements are made, GE automatically gains access to these. As Magik has little in the way of support for multi-threading, GE will benefit from current and future Java offerings (e.g. lambda expressions) that aim to further facilitate multi-core/multi-threaded application development. As the JVM is available for many more platforms, it broadens the reach of Magik, including the potential to run on a class devices never envisioned just a few short years ago.  For example, Java SE compatible runtime environments are available for popular embedded ARM/Intel/PowerPC configurations that could theoretically host this software too. As compared to other JVM language projects, the Magik integration differs in that it represents a serious commercial entity betting a sizable part of its business on the success of this effort.  Expect to see announcements not only from General Electric, but other organizations as they realize the benefits of utilizing the Java Virtual Machine.

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  • Question on the implementation of my Entity System

    - by miguel.martin
    I am currently creating an Entity System, in C++, it is almost completed (I have all the code there, I just have to add a few things and test it). The only thing is, I can't figure out how to implement some features. This Entity System is based off a bit from the Artemis framework, however it is different. I'm not sure if I'll be able to type this out the way my head processing it. I'm going to basically ask whether I should do something over something else. Okay, now I'll give a little detail on my Entity System itself. Here are the basic classes that my Entity System uses to actually work: Entity - An Id (and some methods to add/remove/get/etc Components) Component - An empty abstract class ComponentManager - Manages ALL components for ALL entities within a Scene EntitySystem - Processes entities with specific components Aspect - The class that is used to help determine what Components an Entity must contain so a specific EntitySystem can process it EntitySystemManager - Manages all EntitySystems within a Scene EntityManager - Manages entities (i.e. holds all Entities, used to determine whether an Entity has been changed, enables/disables them, etc.) EntityFactory - Creates (and destroys) entities and assigns an ID to them Scene - Contains an EntityManager, EntityFactory, EntitySystemManager and ComponentManager. Has functions to update and initialise the scene. Now in order for an EntitySystem to efficiently know when to check if an Entity is valid for processing (so I can add it to a specific EntitySystem), it must recieve a message from the EntityManager (after a call of activate(Entity& e)). Similarly the EntityManager must know when an Entity is destroyed from the EntityFactory in the Scene, and also the ComponentManager must know when an Entity is created AND destroyed. I do have a Listener/Observer pattern implemented at the moment, but with this pattern I may remove a Listener (which is this case is dependent on the method being called). I mainly have this implemented for specific things related to a game, i.e. Teams, Tagging of entities, etc. So... I was thinking maybe I should call a private method (using friend classes) to send out when an Entity has been activated, deleted, etc. i.e. taken from my EntityFactory void EntityFactory::killEntity(Entity& e) { // if the entity doesn't exsist in the entity manager within the scene if(!getScene()->getEntityManager().doesExsist(e)) { return; // go back to the caller! (should throw an exception or something..) } // tell the ComponentManager and the EntityManager that we killed an Entity getScene()->getComponentManager().doOnEntityWillDie(e); getScene()->getEntityManager().doOnEntityWillDie(e); // notify the listners for(Mouth::iterator i = getMouth().begin(); i != getMouth().end(); ++i) { (*i)->onEntityWillDie(*this, e); } _idPool.addId(e.getId()); // add the ID to the pool delete &e; // delete the entity } As you can see on the lines where I am telling the ComponentManager and the EntityManager that an Entity will die, I am calling a method to make sure it handles it appropriately. Now I realise I could do this without calling it explicitly, with the help of that for loop notifying all listener objects connected to the EntityFactory's Mouth (an object used to tell listeners that there's an event), however is this a good idea (good design, or what)? I've gone over the PROS and CONS, I just can't decide what I want to do. Calling Explicitly: PROS Faster? Since these functions are explicitly called, they can't be "removed" CONS Not flexible Bad design? (friend functions) Calling through Listener objects (i.e. ComponentManager/EntityManager inherits from a EntityFactoryListener) PROS More Flexible? Better Design? CONS Slower? (virtual functions) Listeners can be removed, i.e. may be removed and not get called again during the program, which could cause in a crash. P.S. If you wish to view my current source code, I am hosting it on BitBucket.

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