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  • Algorithm for querying linearly through a non-linear list of questions

    - by JoshLeaves
    For a multiplayers trivia game, I need to supply my users with a new quizz in a desired subject (Science, Maths, Litt. and such) at the start of every game. I've generated about 5K quizzes for each subject and filled my database with them. So my 'Quizzes' database looks like this: |ID |Subject |Question +-----+------------+---------------------------------- | 23 |Science | What's water? | 42 |Maths | What's 2+2? | 99 |Litt. | Who wrote "Pride and Prejudice"? | 123 |Litt. | Who wrote "On The Road"? | 146 |Maths | What's 2*2? | 599 |Science | You know what's cool? |1042 |Maths | What's the Fibonacci Sequence? |1056 |Maths | What's 42? And so on... (Much more detailed/complex but I'll keep the exemple simple) As you can see, due to technical constraints (MongoDB), my IDs are not linear but I can use them as an increasing suite. So far, my algorithm to ensure two users get a new quizz when they play together is the following: // Take the last played quizzes by P1 and P2 var q_one = player_one.getLastPlayedQuizz('Maths'); var q_two = player_two.getLastPlayedQuizz('Maths'); // If both of them never played in the subject, return first quizz in the list if ((q_one == NULL) && (q_two == NULL)) return QuizzDB.findOne({subject: 'Maths'}); // If one of them never played, play the next quizz for the other player // This quizz is found by asking for the first quizz in the desired subject where // the ID is greater than the last played quizz's ID (if the last played quizz ID // is 42, this will return 146 following the above example database) if (q_one == NULL) return QuizzDB.findOne({subject: 'Maths', ID > q_two}); if (q_two == NULL) return QuizzDB.findOne({subject: 'Maths', ID > q_one}); // And if both of them have a lastPlayedQuizz, we return the next quizz for the // player whose lastPlayedQuizz got the higher ID if (q_one > q_two) return QuizzDB.findOne({subject: 'Maths', ID > q_one}); else return QuizzDB.findOne({subject: 'Maths', ID > q_two}); Now here comes the real problem: Once I get to the end of my database (let's say, P1's last played quizz in 'Maths' is 1056, P2's is 146 and P3 is 1042), following my algorithm, P1's ID is the highest so I ask for the next question in 'Maths' where ID is superior to 1056. There is nothing, so I roll back to the beginning of my quizz list (with a random skipper to avoid having the first question always show up). P1 and P2's last played will then be 42 and they will start fresh from the beginning of the list. However, if P1 (42) plays against P3 (1042), the resulting ID will be 1056...which P1 already played two games ago. Basically, players who just "rolled back" to the beginning of the list will be brought back to the end of the list by players who still haven't rolled back. The rollback WILL happen in the end, but it'll take time and there'll be a "bottleneck" at the beginning and at the end. Thus my question: What would be the best algorith to avoid this bottleneck and ensure players don't get stuck endlessly on the same quizzes? Also bear in mind that I've got some technical constraints: I can't get a random question in a subject (ie: no "QuizzDB.findOne({subject: 'Maths'}).skip(random());"). It's cool to skip on one to twenty records, but the MongoDB documentation warns against skipping too many documents. I would like to avoid building an array of every quizz played by each player and find the next non-played in the database with a $nin. Thanks for your help

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  • Configuring Multiple Instances of MySQL in Solaris 11

    - by rajeshr
    Recently someone asked me for steps to configure multiple instances of MySQL database in an Operating Platform. Coz of my familiarity with Solaris OE, I prepared some notes on configuring multiple instances of MySQL database on Solaris 11. Maybe it's useful for some: If you want to run Solaris Operating System (or any other OS of your choice) as a virtualized instance in desktop, consider using Virtual Box. To download Solaris Operating System, click here. Once you have your Solaris Operating System (Version 11) up and running and have Internet connectivity to gain access to the Image Packaging System (IPS), please follow the steps as mentioned below to install MySQL and configure multiple instances: 1. Install MySQL Database in Solaris 11 $ sudo pkg install mysql-51 2. Verify if the mysql is installed: $ svcs -a | grep mysql Note: Service FMRI will look similar to the one here: svc:/application/database/mysql:version_51 3. Prepare data file system for MySQL Instance 1 zfs create rpool/mysql zfs create rpool/mysql/data zfs set mountpoint=/mysql/data rpool/mysql/data 4. Prepare data file system for MySQL Instance 2 zfs create rpool/mysql/data2 zfs set mountpoint=/mysql/data rpool/mysql/data2 5. Change the mysql/datadir of the MySQL Service (SMF) to point to /mysql/data $ svcprop mysql:version_51 | grep mysql/data $ svccfg -s mysql:version_51 setprop mysql/data=/mysql/data 6. Create a new instance of MySQL 5.1 (a) Copy the manifest of the default instance to temporary directory: $ sudo cp /lib/svc/manifest/application/database/mysql_51.xml /var/tmp/mysql_51_2.xml (b) Make appropriate modifications on the XML file $ sudo vi /var/tmp/mysql_51_2.xml - Change the "instance name" section to a new value "version_51_2" - Change the value of property name "data" to point to the ZFS file system "/mysql/data2" 7. Import the manifest to the SMF repository: $ sudo svccfg import /var/tmp/mysql_51_2.xml 8. Before starting the service, copy the file /etc/mysql/my.cnf to the data directories /mysql/data & /mysql/data2. $ sudo cp /etc/mysql/my.cnf /mysql/data/ $ sudo cp /etc/mysql/my.cnf /mysql/data2/ 9. Make modifications to the my.cnf in each of the data directories as required: $ sudo vi /mysql/data/my.cnf Under the [client] section port=3306 socket=/tmp/mysql.sock ---- ---- Under the [mysqld] section port=3306 socket=/tmp/mysql.sock datadir=/mysql/data ----- ----- server-id=1 $ sudo vi /mysql/data2/my.cnf Under the [client] section port=3307 socket=/tmp/mysql2.sock ----- ----- Under the [mysqld] section port=3307 socket=/tmp/mysql2.sock datadir=/mysql/data2 ----- ----- server-id=2 10. Make appropriate modification to the startup script of MySQL (managed by SMF) to point to the appropriate my.cnf for each instance: $ sudo vi /lib/svc/method/mysql_51 Note: Search for all occurences of mysqld_safe command and modify it to include the --defaults-file option. An example entry would look as follows: ${MySQLBIN}/mysqld_safe --defaults-file=${MYSQLDATA}/my.cnf --user=mysql --datadir=${MYSQLDATA} --pid=file=${PIDFILE} 11. Start the service: $ sudo svcadm enable mysql:version_51_2 $ sudo svcadm enable mysql:version_51 12. Verify that the two services are running by using: $ svcs mysql 13. Verify the processes: $ ps -ef | grep mysqld 14. Connect to each mysqld instance and verify: $ mysql --defaults-file=/mysql/data/my.cnf -u root -p $ mysql --defaults-file=/mysql/data2/my.cnf -u root -p Some references for Solaris 11 newbies Taking your first steps with Solaris 11 Introducing the basics of Image Packaging System Service Management Facility How To Guide For a detailed list of official educational modules available on Solaris 11, please visit here For MySQL courses from Oracle University access this page.

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  • Today at Oracle OpenWorld 2012

    - by Scott McNeil
    We have another full day of great Oracle OpenWorld keynotes, sessions, demos and customer presentations in the Seen and Be Heard threater. Here's a quick run down of what's happening today with Oracle Enterprise Manager 12c: Download the Oracle Enterprise Manager 12c OpenWorld schedule (PDF) Oracle Enterprise Manager Cloud Control 12c (and Private Cloud) General Session Tues 2 Oct, 2012 Time Title Location 11:45 AM - 12:45 PM General Session: Using Oracle Enterprise Manager to Manage Your Own Private Cloud Moscone South - 103* 1:15 PM - 2:15 PM General Session: Breakthrough Efficiency in Private Cloud Infrastructure Moscone West - 3014 Conference Session Tues 2 Oct, 2012 Time Title Location 10:15 AM - 11:15 AM Oracle Exadata/Oracle Enterprise Manager 12c: Journey into Oracle Database Cloud Moscone West - 3018 10:15 AM - 11:15 AM Bulletproof Your Application Upgrades with Secure Data Masking and Subsetting Moscone West - 3020 10:15 AM - 11:15 AM Oracle Enterprise Manager 12c: Architecture Deep Dive, Tips, and Techniques Moscone South - 303 11:45 AM - 12:45 PM RDBMS Forensics: Troubleshooting with Active Session History Moscone West - 3018 11:45 AM - 12:45 PM Building and Operationalizing Your Data Center Environment with Oracle Exalogic Moscone South - 309 11:45 AM - 12:45 PM Securely Building a National Electronic Health Record: Singapore Case Study Westin San Francisco - Concordia 1:15 PM - 2:15 PM Managing Heterogeneous Environments with Oracle Enterprise Manager Moscone West - 3018 1:15 PM - 2:15 PM Complete Oracle WebLogic Server Management with Oracle Enterprise Manager 12c Moscone South - 309 1:15 PM - 2:15 PM Database Lifecycle Management with Oracle Enterprise Manager 12c Moscone West - 3020 1:15 PM - 2:15 PM Best Practices, Key Features, Tips, Techniques for Oracle Enterprise Manager 12c Upgrade Moscone South - 307 1:15 PM - 2:15 PM Enterprise Cloud with CSC’s Foundation Services for Oracle and Oracle Enterprise Manager 12c Moscone South - 236 5:00 PM - 6:00 PM Deep Dive 3-D on Oracle Exadata Management: From Discovery to Deployment to Diagnostics Moscone West - 3018 5:00 PM - 6:00 PM Everything You Need to Know About Monitoring and Troubleshooting Oracle GoldenGate Moscone West - 3005 5:00 PM - 6:00 PM Oracle Enterprise Manager 12c: The Nerve Center of Oracle Cloud Moscone West - 3020 5:00 PM - 6:00 PM Advanced Management of Oracle E-Business Suite with Oracle Enterprise Manager Moscone West - 2016 5:00 PM - 6:00 PM Oracle Enterprise Manager 12c Cloud Control Performance Pages: Falling in Love Again Moscone West - 3014 Hands-on Labs Tues 2 Oct, 2012 Time Title Location 10:15 AM - 12:45 PM Managing the Cloud with Oracle Enterprise Manager 12c Marriott Marquis - Salon 5/6 1:15 PM - 2:15 PM Database Performance Tuning Hands-on Lab Marriott Marquis - Salon 5/6 Scene and Be Heard Theater Session Tues 2 Oct, 2012 Time Title Location 10:30 AM - 10:50 AM Start Small, Grow Big: Hands-On Oracle Private Cloud—A Step-by-Step Guide Moscone South Exhibition Hall - Booth 2407 12:30 PM - 12:50 PM Blue Medora’s Oracle Enterprise Manager Plug-in for VMware vSphere Monitoring Moscone South Exhibition Hall - Booth 2407 Demos Demo Location Application and Infrastructure Testing Moscone West - W-092 Automatic Application and SQL Tuning Moscone South, Left - S-042 Automatic Fault Diagnostics Moscone South, Left - S-036 Automatic Performance Diagnostics Moscone South, Left - S-033 Complete Care for Oracle Using My Oracle Support Moscone South, Left - S-031 Complete Cloud Lifecycle Management Moscone North, Upper Lobby - N-019 Complete Database Lifecycle Management Moscone South, Left - S-030 Comprehensive Infrastructure as a Service via Oracle Enterprise Manager Moscone South, Left - S-045 Data Masking and Data Subsetting Moscone South, Left - S-034 Database Testing with Oracle Real Application Testing Moscone South, Left - S-041 Identity Management Monitoring with Oracle Enterprise Manager Moscone South, Right - S-212 Mission-Critical, SPARC-Powered Infrastructure as a Service Moscone South, Center - S-157 Oracle E-Business Suite, Siebel, JD Edwards, and PeopleSoft Management Moscone West - W-084 Oracle Enterprise Manager Cloud Control 12c Overview Moscone South, Left - S-039 Oracle Enterprise Manager: Complete Data Center Management Moscone South, Left - S-040 Oracle Exadata Management Moscone South, Center - Oracle Exalogic Management Moscone South, Center - Oracle Fusion Applications Management Moscone West - W-018 Oracle Real User Experience Insight Moscone South, Right - S-226 Oracle WebLogic Server Management and Java Diagnostics Moscone South, Right - S-206 Platform as a Service Using Oracle Enterprise Manager Moscone North, Upper Lobby - N-020 SOA Management Moscone South, Right - S-225 Self-Service Application Testing on Private and Public Clouds Moscone West - W-110 Oracle OpenWorld Music Festival New this year is Oracle’s first annual Oracle OpenWorld Musical Festival, featuring some of today's breakthrough musicians from around the country and the world. It's five nights of back-to-back performances in the heart of San Francisco—free to registered attendees. See the lineup Not Heading to OpenWorld—Watch it Live! Stay Connected: Twitter | Facebook | YouTube | Linkedin | Newsletter Download the Oracle Enterprise Manager Cloud Control12c Mobile app

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  • eSTEP Newsletter November 2012

    - by uwes
    Dear Partners,We would like to inform you that the November '12 issue of our Newsletter is now available.The issue contains information to the following topics: News from CorpOracle Celebrates 25 Years of SPARC Innovation; IDC White Papers Finds Growing Customer Comfort with Oracle Solaris Operating System; Oracle Buys Instantis; Pillar Axiom OpenWorld Highlights; Announcement Oracle Solaris 11.1 Availability (data sheet, new features, FAQ's, corporate pages, internal blog, download links, Oracle shop); Announcing StorageTek VSM 6; Announcement Oracle Solaris Cluster 4.1 Availability (new features, FAQ's, cluster corp page, download site, shop for media); Announcement: Oracle Database Appliance 2.4 patch update becomes available Technical SectionOracle White papers on SPARC SuperCluster; Understanding Parallel Execution; With LTFS, Tape is Gaining Storage Ground with additional link to How to Create Oracle Solaris 11 Zones with Oracle Enterprise Manager Ops Center; Provisioning Capabilities of Oracle Enterprise Ops Center Manager 12c; Maximizing your SPARC T4 Oracle Solaris Application Performance with the following articles: SPARC T4 Servers Set World Record on Siebel CRM 8.1.1.4 Benchmark, SPARC T4-Based Highly Scalable Solutions Posts New World Record on SPECjEnterprise2010 Benchmark, SPARC T4 Server Delivers Outstanding Performance on Oracle Business Intelligence Enterprise Edition 11g; Oracle SUN ZFS Storage Appliance Reference Architecture for VMware vSphere4;  Why 4K? - George Wilson's ZFS Day Talk; Pillar Axiom 600 with connected subjects: Oracle Introduces Pillar Axiom Release 5 Storage System Software, Driving down the high cost of Storage, This Provisioning with Pilar Axiom 600, Pillar Axiom 600- System overview and architecture; Migrate to Oracle;s SPARC Systems; Top 5 Reasons to Migrate to Oracle's SPARC Systems Learning & EventsRecently delivered Techcasts: Learning Paths; Oracle Database 11g: Database Administration (New) - Learning Path; Webcast: Drill Down on Disaster Recovery; What are Oracle Users Doing to Improve Availability and Disaster Recovery; SAP NetWeaver and Oracle Exadata Database Machine ReferencesARTstor Selects Oracle’s Sun ZFS Storage 7420 Appliances To Support Rapidly Growing Digital Image Library, Scottish Widows Cuts Sales Administration 20%, Reduces Time to Prepare Reports by 75%, and Achieves Return on Investment in First Year, Oracle's CRM Cloud Service Powers Innovation: Applications on Demand; Technology on Demand, How toHow to Migrate Your Data to Oracle Solaris 11 Using Shadow Migration; Using svcbundle to Create SMF Manifests and Profiles in Oracle Solaris 11; How to prepare a Sun ZFS Storage Appliance to Serve as a Storage Devise with Oracle Enterprise Manager Ops Center 12c; Command Summary: Basic Operations with the Image Packaging System In Oracle Solaris 11; How to Update to Oracle Solaris 11.1 Using the Image Packaging System, How to Migrate Oracle Database from Oracle Solaris 8 to Oracle Solaris 11;  Setting Up, Configuring, and Using an Oracle WebLogic Server Cluster; Ease the Chaos with Automated Patching: Oracle Enterprise Manager Cloud Control 12c; Book excerpt: Oracle Exalogic Elastic Cloud Handbook You find the Newsletter on our portal under eSTEP News ---> Latest Newsletter. You will need to provide your email address and the pin below to get access. Link to the portal is shown below.URL: http://launch.oracle.com/PIN: eSTEP_2011Previous published Newsletters can be found under the Archived Newsletters section and more useful information under the Events, Download and Links tab. Feel free to explore and any feedback is appreciated to help us improve the service and information we deliver.Thanks and best regards,Partner HW Enablement EMEA

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  • Oracle OpenWorld Update: Demo Pods and Hands-on Labs

    - by Doug Reid
    0 false 18 pt 18 pt 0 0 false false false /* 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-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:12.0pt; font-family:"Times New Roman"; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} Less than one week away until the start of Oracle OpenWorld 2012 and the Data Integration Solutions team is ready to go!  We have an exciting line up for you this year which we have summarized for you in the Oracle OpenWorld Focus on Data Integration Solutions document. In past posts we have discussed session themes and our customer panel, but today I would like to summarize our Hands-on Labs and Demo Pods that we have available for attendees. For Oracle GoldenGate Hands-On Labs we have two labs that we are running this year. Deep Dive into Oracle GoldenGate Thursday October 4th at 11:15AM in the Marriott Marquis Salon 1/2 Oracle GoldenGate provides real-time log-based change data capture and delivery between heterogeneous systems. It enables cost-effective, low-impact, real-time data integration and continuous availability solutions. This session covers Oracle GoldenGate 11g’s internal product architecture and includes a hands-on lab that covers configuration examples for target database instantiation and real-time change data capture and delivery. The participants will configure Oracle GoldenGate to instantiate a secondary database that can be used for disaster recovery or a reporting instance. Come learn how easy it is to use and how this can be a very valuable and easy technology solution for your organization. Introduction to Oracle GoldenGate Veridata Wednesday October 3rd 10:15AM in the Marriott Marquis Sales 1/2 Oracle GoldenGate Veridata compares one set of data with another and identifies data that is out of synchronization. In this hands-on lab, you will be introduced to the key features of this product. Using the Oracle GoldenGate Veridata Web client, you will have the opportunity to configure comparison objects and rules, initiate a comparison, review the status and output of a comparison, and review out-of-sync data. As a bonus this year, we have recorded the labs and made them available on youtube.com/oraclegoldengate. These will be available the day of the labs. Our demo pods are an opportunity for attendees to see our products but more so to meet the product management and development teams. I would like to point out that we have two Oracle GoldenGate 11gR2 demo pods, one in the database camp and the other in the middleware camp. The one in the middleware camp will be focused on all platforms while the one in the database camp will have a focus on the Oracle platform. The other two I would like to point out are the Monitoring Oracle GoldenGate and the Oracle Enterprise Manager demo pods; both of these pods will focus on methods to monitor GoldenGate but the OEM demo pod will have a specific focus on the Oracle GoldenGate Management Pack plug-in for OEM. Below is a list of our demo pods and their locations. Monitoring Oracle GoldenGate for End-to-End Visibility Moscone South, Right - S-241 Oracle Data Integrator and Oracle GoldenGate for Oracle Applications Moscone South, Right - S-240 Oracle GoldenGate 11gR2 New Features Moscone South, Right - S-239 Oracle GoldenGate 11gR2: Real-Time, Transactional Database Replication     Moscone South, Left - S-027 Oracle GoldenGate Veridata and Adapters Moscone South, Right - S-242 Oracle Enterprise Manager Moscone South, Left - S-040 Keep tuned to our blog during the show for news and highlights from the Data Integration Solutions team. See you there.

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  • Exalytics and Oracle Business Intelligence Enterprise Edition (OBIEE) Partner Workshop

    - by mseika
    Workshop Description Oracle Fusion Middleware 11g is the #1 application infrastructure foundation. It enables enterprises to create and run agile and intelligent business applications and maximize IT efficiency by exploiting modern hardware and software architectures. Oracle Exalytics Business Intelligence Machine is the world’s first engineered system specifically designed to deliver high performance analysis, modeling and planning. Built using industry-standard hardware, market-leading business intelligence software and in-memory database technology, Oracle Exalytics is an optimized system that delivers unmatched speed, visualizations and scalability for Business Intelligence and Enterprise Performance Management applications. This FREE hands-on, partner workshop highlights both the hardware and software components that are engineered to work together to deliver Oracle Exalytics - an optimized version of the industry-leading Oracle TimesTen In-Memory Database with analytic extensions, a highly scalable Oracle server designed specifically for in-memory business intelligence, and Oracle’s proven Business Intelligence Foundation with enhanced visualization capabilities and performance optimizations. This workshop will provide hands-on experience with Oracle's latest engineered system. Topics covered will include TimesTen In-Memory Database and the new Summary Advisor for Exalytics, the technical details (including mobile features) of the latest release of visualization enhancements for OBI-EE, and technical updates on Essbase. After taking this course, you will be well prepared to architect, build, demo, and implement an end-to-end Exalytics solution. You will also be able to extend your current analytical and enterprise performance management application implementations with numerous Oracle technologies specifically enhanced to take advantage of the compute capacity and in-memory capabilities of Oracle Exalytics.If you are a BI or Data Warehouse Architect, developer or consultant, you don’t want to miss this 3-day workshop. Register Now! Presentations Exalytics Architectural Overview Upgrade and Lifecycle Management Times Ten for Exalytics Summary Advisor Utility Essbase and EPM System on Exalytics Dashboard and Analysis Interactions OBIEE 11.1.1.6 Features and Advanced Topics Lab OutlineThe labs showcase Oracle Exalytics core components and functionality and provide expertise of Oracle Business Intelligence 11.1.1.6 new features and updates from prior releases. The hands-on activities are based on an Oracle VirtualBox image with software and training samples pre-installed. Lab Environment Setup Creating and Working with Oracle TimesTen In-Memory Database Running Summary Advisor Utility Working with Exalytics Visualization Features – Dashboard and Analysis Interactions Audience Oracle Partners BI and EPM Application Developers and Implementers System Integrators and Solution Consultants Data Warehouse Developers Enterprise Architects Prerequisites Experience and understanding of OBIEE 11g is required Previous attendance of Oracle Business Intelligence Foundation Suite Workshop or BIEE 11gIntroduction Workshop is highly recommended Good understanding of data warehousing and data modeling for reporting and analysis purpose Strong experience with database technologies preferred Equipment RequirementsThis workshop requires attendees to provide their own laptops for this class.Attendee laptops must meet the following minimum hardware/software requirements: Hardware Minimum 8GB RAM 60 GB free space (includes staging) USB 2.0 port (at least one available) It is strongly recommended that you bring a mouse. You will be working in a development environment and using the mouse heavily. Software One of the following operating systems: 64-bit Windows host/laptop OS 64-bit host/laptop OS with a Windows VM (XP, Server, or Win 7, BIC2g, etc.) Internet Explorer 7.x/8.x or Firefox 3.5.x WINRAR or 7ziputility to unzip workshop files: Download-able from http://www.win-rar.com/download.html Download-able from http://www.7zip.com/ Oracle VirtualBox 4.0.2 or higher Downloadable from http://www.virtualbox.org/wiki/Downloads CPU virtualization mode needs to be enabled. We will provide guidance on the day of the workshop. Attendees will be given a VirtualBox image containing a pre-installed Oracle Exalytics environment. Schedule This workshop is 3 days. - Times vary by country!9:00am: Sign-in and technical setup 9:30am: Workshop starts 5:00pm: Workshop ends Oracle Exalytics and Business Intelligence (OBIEE) Workshop December 11-13, 2012: Oracle BVP, Birmingham, UK Register Here. Questions? Send email to: [email protected] Oracle Platform Technologies Enablement Services

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  • Algorithm for tracking progress of controller method running in background

    - by SilentAssassin
    I am using Codeigniter framework for PHP on Windows platform. My problem is I am trying to track progress of a controller method running in background. The controller extracts data from the database(MySQL) then does some processing and then stores the results again in the database. The complete aforesaid process can be considered as a single task. A new task can be assigned while another task is running. The newly assigned task will be added in a queue. So if I can track progress of the controller, I can show status for each of these tasks. Like I can show "Pending" status for tasks in the queue, "In Progress" for tasks running and "Done" for tasks that are completed. Main Issue: Now first thing I need to find is an algorithm to track the progress of how much amount of execution the controller method has completed and that means tracking how much amount of method has completed execution. For instance, this PHP script tracks progress of array being counted. Here the current state and state after total execution are known so it is possible to track its progress. But I am not able to devise anything analogous to it in my case. Maybe what I am trying to achieve is programmtically not possible. If its not possible then suggest me a workaround or a completely new approach. If some details are pending you can mention them. Sorry for my ignorance this is my first post here. I welcome you to point out my mistakes. EDIT: Database outline: The URL(s) and keyword(s) are first entered by user which are stored in a database table called link_master and keyword_master respectively. Then keywords are extracted from all the links present in this table and compared with keywords entered by user and their frequency is calculated which is the final result. And the results are stored in another table called link_result. Now sub-links are extracted from the domain links and stored in a table called sub_link_master. Now again the keywords are extracted from these sub-links and the corresponding results are stored in a table called sub_link_result. The number of records cannot be defined beforehand as the number of links on any web page can be different. Only the cardinality of *link_result* table can be known which will be equal to multiplication of number of keyword(s) and URL(s) . I insert multiple records at a time using this resource. Controller outline: The controller extracts keywords from a web page and also extracts keywords from all the links present on that page. There is a method called crawlLink. I used Rolling Curl to extract keywords and web page content. It has callback function which I used for extracting keywords alongwith generating results and extracting valid sub-links. There is a insertResult method which stores results for links and sub-links in the respective tables. Yes, the processing depends on the number of records. The more the number of records, the more time it takes to execute: Consider this scenario: Number of Domain Links = 1 Number of Keywords = 3 Number of Domain Links Result generated = 3 (3 x 1 as described in the question) Number of Sub Links generated = 41 Number of Sub Links Result = 117 (41 x 3 = 123 but some links are not valid or searchable) Approximate time taken for above process to complete = 55 seconds. The above result is for a single link. I want to track the progress of the above results getting stored in database. When all results are stored, the task is complete. If results are getting stored, the task is In Progress. I am not clear how can I track this progress.

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  • SQL Server IO handling mechanism can be severely affected by high CPU usage

    - by sqlworkshops
    Are you using SSD or SAN / NAS based storage solution and sporadically observe SQL Server experiencing high IO wait times or from time to time your DAS / HDD becomes very slow according to SQL Server statistics? Read on… I need your help to up vote my connect item – https://connect.microsoft.com/SQLServer/feedback/details/744650/sql-server-io-handling-mechanism-can-be-severely-affected-by-high-cpu-usage. Instead of taking few seconds, queries could take minutes/hours to complete when CPU is busy.In SQL Server when a query / request needs to read data that is not in data cache or when the request has to write to disk, like transaction log records, the request / task will queue up the IO operation and wait for it to complete (task in suspended state, this wait time is the resource wait time). When the IO operation is complete, the task will be queued to run on the CPU. If the CPU is busy executing other tasks, this task will wait (task in runnable state) until other tasks in the queue either complete or get suspended due to waits or exhaust their quantum of 4ms (this is the signal wait time, which along with resource wait time will increase the overall wait time). When the CPU becomes free, the task will finally be run on the CPU (task in running state).The signal wait time can be up to 4ms per runnable task, this is by design. So if a CPU has 5 runnable tasks in the queue, then this query after the resource becomes available might wait up to a maximum of 5 X 4ms = 20ms in the runnable state (normally less as other tasks might not use the full quantum).In case the CPU usage is high, let’s say many CPU intensive queries are running on the instance, there is a possibility that the IO operations that are completed at the Hardware and Operating System level are not yet processed by SQL Server, keeping the task in the resource wait state for longer than necessary. In case of an SSD, the IO operation might even complete in less than a millisecond, but it might take SQL Server 100s of milliseconds, for instance, to process the completed IO operation. For example, let’s say you have a user inserting 500 rows in individual transactions. When the transaction log is on an SSD or battery backed up controller that has write cache enabled, all of these inserts will complete in 100 to 200ms. With a CPU intensive parallel query executing across all CPU cores, the same inserts might take minutes to complete. WRITELOG wait time will be very high in this case (both under sys.dm_io_virtual_file_stats and sys.dm_os_wait_stats). In addition you will notice a large number of WAITELOG waits since log records are written by LOG WRITER and hence very high signal_wait_time_ms leading to more query delays. However, Performance Monitor Counter, PhysicalDisk, Avg. Disk sec/Write will report very low latency times.Such delayed IO handling also occurs to read operations with artificially very high PAGEIOLATCH_SH wait time (with number of PAGEIOLATCH_SH waits remaining the same). This problem will manifest more and more as customers start using SSD based storage for SQL Server, since they drive the CPU usage to the limits with faster IOs. We have a few workarounds for specific scenarios, but we think Microsoft should resolve this issue at the product level. We have a connect item open – https://connect.microsoft.com/SQLServer/feedback/details/744650/sql-server-io-handling-mechanism-can-be-severely-affected-by-high-cpu-usage - (with example scripts) to reproduce this behavior, please up vote the item so the issue will be addressed by the SQL Server product team soon.Thanks for your help and best regards,Ramesh MeyyappanHome: www.sqlworkshops.comLinkedIn: http://at.linkedin.com/in/rmeyyappan

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  • SQL Server Optimizer Malfunction?

    - by Tony Davis
    There was a sharp intake of breath from the audience when Adam Machanic declared the SQL Server optimizer to be essentially "stuck in 1997". It was during his fascinating "Query Tuning Mastery: Manhandling Parallelism" session at the recent PASS SQL Summit. Paraphrasing somewhat, Adam (blog | @AdamMachanic) offered a convincing argument that the optimizer often delivers flawed plans based on assumptions that are no longer valid with today’s hardware. In 1997, when Microsoft engineers re-designed the database engine for SQL Server 7.0, SQL Server got its initial implementation of a cost-based optimizer. Up to SQL Server 2000, the developer often had to deploy a steady stream of hints in SQL statements to combat the occasionally wilful plan choices made by the optimizer. However, with each successive release, the optimizer has evolved and improved in its decision-making. It is still prone to the occasional stumble when we tackle difficult problems, join large numbers of tables, perform complex aggregations, and so on, but for most of us, most of the time, the optimizer purrs along efficiently in the background. Adam, however, challenged further any assumption that the current optimizer is competent at providing the most efficient plans for our more complex analytical queries, and in particular of offering up correctly parallelized plans. He painted a picture of a present where complex analytical queries have become ever more prevalent; where disk IO is ever faster so that reads from disk come into buffer cache faster than ever; where the improving RAM-to-data ratio means that we have a better chance of finding our data in cache. Most importantly, we have more CPUs at our disposal than ever before. To get these queries to perform, we not only need to have the right indexes, but also to be able to split the data up into subsets and spread its processing evenly across all these available CPUs. Improvements such as support for ColumnStore indexes are taking things in the right direction, but, unfortunately, deficiencies in the current Optimizer mean that SQL Server is yet to be able to exploit properly all those extra CPUs. Adam’s contention was that the current optimizer uses essentially the same costing model for many of its core operations as it did back in the days of SQL Server 7, based on assumptions that are no longer valid. One example he gave was a "slow disk" bias that may have been valid back in 1997 but certainly is not on modern disk systems. Essentially, the optimizer assesses the relative cost of serial versus parallel plans based on the assumption that there is no IO cost benefit from parallelization, only CPU. It assumes that a single request will saturate the IO channel, and so a query would not run any faster if we parallelized IO because the disk system simply wouldn’t be able to handle the extra pressure. As such, the optimizer often decides that a serial plan is lower cost, often in cases where a parallel plan would improve performance dramatically. It was challenging and thought provoking stuff, as were his techniques for driving parallelism through query logic based on subsets of rows that define the "grain" of the query. I highly recommend you catch the session if you missed it. I’m interested to hear though, when and how often people feel the force of the optimizer’s shortcomings. Barring mistakes, such as stale statistics, how often do you feel the Optimizer fails to find the plan you think it should, and what are the most common causes? Is it fighting to induce it toward parallelism? Combating unexpected plans, arising from table partitioning? Something altogether more prosaic? Cheers, Tony.

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  • The Best Data Integration for Exadata Comes from Oracle

    - by maria costanzo
    Oracle Data Integrator and Oracle GoldenGate offer unique and optimized data integration solutions for Oracle Exadata. For example, customers that choose to feed their data warehouse or reporting database with near real-time throughout the day, can do so without decreasing  performance or availability of source and target systems. And if you ask why real-time, the short answer is: in today’s fast-paced, always-on world, business decisions need to use more relevant, timely data to be able to act fast and seize opportunities. A longer response to "why real-time" question can be found in a related blog post. If we look at the solution architecture, as shown on the diagram below,  Oracle Data Integrator and Oracle GoldenGate are both uniquely designed to take full advantage of the power of the database and to eliminate unnecessary middle-tier components. Oracle Data Integrator (ODI) is the best bulk data loading solution for Exadata. ODI is the only ETL platform that can leverage the full power of Exadata, integrate directly on the Exadata machine without any additional hardware, and by far provides the simplest setup and fastest overall performance on an Exadata system. We regularly see customers achieving a 5-10 times boost when they move their ETL to ODI on Exadata. For  some companies the performance gain is even much higher. For example a large insurance company did a proof of concept comparing ODI vs a traditional ETL tool (one of the market leaders) on Exadata. The same process that was taking 5hrs and 11 minutes to complete using the competing ETL product took 7 minutes and 20 seconds with ODI. Oracle Data Integrator was 42 times faster than the conventional ETL when running on Exadata.This shows that Oracle's own data integration offering helps you to gain the most out of your Exadata investment with a truly optimized solution. GoldenGate is the best solution for streaming data from heterogeneous sources into Exadata in real time. Oracle GoldenGate can also be used together with Data Integrator for hybrid use cases that also demand non-invasive capture, high-speed real time replication. Oracle GoldenGate enables real-time data feeds from heterogeneous sources non-invasively, and delivers to the staging area on the target Exadata system. ODI runs directly on Exadata to use the database engine power to perform in-database transformations. Enterprise Data Quality is integrated with Oracle Data integrator and enables ODI to load trusted data into the data warehouse tables. Only Oracle can offer all these technical benefits wrapped into a single intelligence data warehouse solution that runs on Exadata. Compared to traditional ETL with add-on CDC this solution offers: §  Non-invasive data capture from heterogeneous sources and avoids any performance impact on source §  No mid-tier; set based transformations use database power §  Mini-batches throughout the day –or- bulk processing nightly which means maximum availability for the DW §  Integrated solution with Enterprise Data Quality enables leveraging trusted data in the data warehouse In addition to Starwood Hotels and Resorts, Morrison Supermarkets, United Kingdom’s fourth-largest food retailer, has seen the power of this solution for their new BI platform and shared their story with us. Morrisons needed to analyze data across a large number of manufacturing, warehousing, retail, and financial applications with the goal to achieve single view into operations for improved customer service. The retailer deployed Oracle GoldenGate and Oracle Data Integrator to bring new data into Oracle Exadata in near real-time and replicate the data into reporting structures within the data warehouse—extending visibility into operations. Using Oracle's data integration offering for Exadata, Morrisons produced financial reports in seconds, rather than minutes, and improved staff productivity and agility. You can read more about Morrison’s success story here and hear from Starwood here. From an Irem Radzik article.

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  • Advanced Record-Level Business Intelligence with Inner Queries

    - by gt0084e1
    While business intelligence is generally applied at an aggregate level to large data sets, it's often useful to provide a more streamlined insight into an individual records or to be able to sort and rank them. For instance, a salesperson looking at a specific customer could benefit from basic stats on that account. A marketer trying to define an ideal customer could pull the top entries and look for insights or patterns. Inner queries let you do sophisticated analysis without the overhead of traditional BI or OLAP technologies like Analysis Services. Example - Order History Constancy Let's assume that management has realized that the best thing for our business is to have customers ordering every month. We'll need to identify and rank customers based on how consistently they buy and when their last purchase was so sales & marketing can respond accordingly. Our current application may not be able to provide this and adding an OLAP server like SSAS may be overkill for our needs. Luckily, SQL Server provides the ability to do relatively sophisticated analytics via inner queries. Here's the kind of output we'd like to see. Creating the Queries Before you create a view, you need to create the SQL query that does the calculations. Here we are calculating the total number of orders as well as the number of months since the last order. These fields might be very useful to sort by but may not be available in the app. This approach provides a very streamlined and high performance method of delivering actionable information without radically changing the application. It's also works very well with self-service reporting tools like Izenda. SELECT CustomerID,CompanyName, ( SELECT COUNT(OrderID) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID ) As Orders, DATEDIFF(mm, ( SELECT Max(OrderDate) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID) ,getdate() ) AS MonthsSinceLastOrder FROM Customers Creating Views To turn this or any query into a view, just put CREATE VIEW AS before it. If you want to change it use the statement ALTER VIEW AS. Creating Computed Columns If you'd prefer not to create a view, inner queries can also be applied by using computed columns. Place you SQL in the (Formula) field of the Computed Column Specification or check out this article here. Advanced Scoring and Ranking One of the best uses for this approach is to score leads based on multiple fields. For instance, you may be in a business where customers that don't order every month require more persistent follow up. You could devise a simple formula that shows the continuity of an account. If they ordered every month since their first order, they would be at 100 indicating that they have been ordering 100% of the time. Here's the query that would calculate that. It uses a few SQL tricks to make this happen. We are extracting the count of unique months and then dividing by the months since initial order. This query will give you the following information which can be used to help sales and marketing now where to focus. You could sort by this percentage to know where to start calling or to find patterns describing your best customers. Number of orders First Order Date Last Order Date Percentage of months order was placed since last order. SELECT CustomerID, (SELECT COUNT(OrderID) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID) As Orders, (SELECT Max(OrderDate) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID) AS LastOrder, (SELECT Min(OrderDate) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID) AS FirstOrder, DATEDIFF(mm,(SELECT Min(OrderDate) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID),getdate()) AS MonthsSinceFirstOrder, 100*(SELECT COUNT(DISTINCT 100*DATEPART(yy,OrderDate) + DATEPART(mm,OrderDate)) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID) / DATEDIFF(mm,(SELECT Min(OrderDate) FROM Orders WHERE Orders.CustomerID = Customers.CustomerID),getdate()) As OrderPercent FROM Customers

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  • HERMES Medical Solutions Helps Save Lives with MySQL

    - by Bertrand Matthelié
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Cambria","serif"; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} HERMES Medical Solutions was established in 1976 in Stockholm, Sweden, and is a leading innovator in medical imaging hardware/software products for health care facilities worldwide. HERMES delivers a plethora of different medical imaging solutions to optimize hospital workflow. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Cambria","serif"; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} HERMES advanced algorithms make it possible to detect the smallest changes under therapies important and necessary to optimize different therapeutic methods and doses. Challenges Fighting illness & disease requires state-of-the-art imaging modalities and software in order to diagnose accurately, stage disease appropriately and select the best treatment available. Selecting and implementing a new database platform that would deliver the needed performance, reliability, security and flexibility required by the high-end medical solutions offered by HERMES. Solution Decision to migrate from in-house database to an embedded SQL database powering the HERMES products, delivered either as software, integrated hardware and software solutions, or via the cloud in a software-as-a-service configuration. Evaluation of several databases and selection of MySQL based on its high performance, ease of use and integration, and low Total Cost of Ownership. On average, between 4 and 12 Terabytes of data are stored in MySQL databases underpinning the HERMES solutions. The data generated by each medical study is indeed stored during 10 years or more after the treatment was performed. MySQL-based HERMES systems also allow doctors worldwide to conduct new drug research projects leveraging the large amount of medical data collected. Hospitals and other HERMES customers worldwide highly value the “zero administration” capabilities and reliability of MySQL, enabling them to perform medical analysis without any downtime. Relying on MySQL as their embedded database, the HERMES team has been able to increase their focus on further developing their clinical applications. HERMES Medical Solutions could leverage the Oracle Financing payment plan to spread its investment over time and make the MySQL choice even more valuable. “MySQL has proven to be an excellent database choice for us. We offer high-end medical solutions, and MySQL delivers the reliability, security and performance such solutions require.” Jan Bertling, CEO.

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  • E-Business Suite : Role of CHUNK_SIZE in Oracle Payroll

    - by Giri Mandalika
    Different batch processes in Oracle Payroll flow have the ability to spawn multiple child processes (or threads) to complete the work in hand. The number of child processes to fork is controlled by the THREADS parameter in APPS.PAY_ACTION_PARAMETERS view. THREADS parameter The default value for THREADS parameter is 1, which is fine for a single-processor system but not optimal for the modern multi-core multi-processor systems. Setting the THREADS parameter to a value equal to or less than the total number of [virtual] processors available on the system may improve the performance of payroll processing. However on the down side, since multiple child processes operate against the same set of payroll tables in HR schema, database may experience undesired consequences such as buffer busy waits and index contention, which results in giving up some of the gains achieved by using multiple child processes/threads to process the work. Couple of other action parameters, CHUNK_SIZE and CHUNK_SHUFFLE, help alleviate the database contention. eg., Set a value for THREADS parameter as shown below. CONNECT APPS/APPS_PASSWORD UPDATE PAY_ACTION_PARAMETERS SET PARAMETER_VALUE = DESIRED_VALUE WHERE PARAMETER_NAME = 'THREADS'; COMMIT; (I am not aware of any maximum value for THREADS parameter) CHUNK_SIZE parameter The size of each commit unit for the batch process is controlled by the CHUNK_SIZE action parameter. In other words, chunking is the act of splitting the assignment actions into commit groups of desired size represented by the CHUNK_SIZE parameter. The default value is 20, and each thread processes one chunk at a time -- which means each child process inserts or processes 20 assignment actions at any time. When multiple threads are configured, each thread picks up a chunk to process, completes the assignment actions and then picks up another chunk. This is repeated until all the chunks are exhausted. It is possible to use different chunk sizes in different batch processes. During the initial phase of processing, CHUNK_SIZE number of assignment actions are inserted into relevant table(s). When multiple child processes are inserting data at the same time into the same set of tables, as explained earlier, database may experience contention. The default value of 20 is mostly optimal in such a case. Experiment with different values for the initial phase by +/-10 for CHUNK_SIZE parameter and observe the performance impact. A larger value may make sense during the main processing phase. Again experimentation is the key in finding the suitable value for your environment. Start with a large value such as 2000 for the chunk size, then increment or decrement the size by 500 at a time until an optimal value is found. eg., Set a value for CHUNK_SIZE parameter as shown below. CONNECT APPS/APPS_PASSWORD UPDATE PAY_ACTION_PARAMETERS SET PARAMETER_VALUE = DESIRED_VALUE WHERE PARAMETER_NAME = 'CHUNK_SIZE'; COMMIT; CHUNK_SIZE action parameter accepts a value that is as low as 1 or as high as 16000. CHUNK SHUFFLE parameter By default, chunks of assignment actions are processed sequentially by all threads - which may not be a good thing especially given that all child processes/threads performing similar actions against the same set of tables almost at the same time. By saying not a good thing, I mean to say that the default behavior leads to contention in the database (in data blocks, for example). It is possible to relieve some of that database contention by randomizing the processing order of chunks of assignment actions. This behavior is controlled by the CHUNK SHUFFLE action parameter. Chunk processing is not randomized unless explicitly configured. eg., Set chunk shuffling as shown below. CONNECT APPS/APPS_PASSWORD UPDATE PAY_ACTION_PARAMETERS SET PARAMETER_VALUE = 'Y' WHERE PARAMETER_NAME = 'CHUNK SHUFFLE'; COMMIT; Finally I recommend checking the following document out for additional details and additional pay action tunable parameters that may speed up the processing of Oracle Payroll.     My Oracle Support Doc ID: 226987.1 Oracle 11i & R12 Human Resources (HRMS) & Benefits (BEN) Tuning & System Health Checks Also experiment with different combinations of parameters and values until the right set of action parameters and values are found for your deployment.

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  • eSTEP Newsletter November 2012

    - by mseika
    Dear Partners,We would like to inform you that the November '12 issue of our Newsletter is now available.The issue contains information to the following topics: News from CorpOracle Celebrates 25 Years of SPARC Innovation; IDC White Papers Finds Growing Customer Comfort with Oracle Solaris Operating System; Oracle Buys Instantis; Pillar Axiom OpenWorld Highlights; Announcement Oracle Solaris 11.1 Availability (data sheet, new features, FAQ's, corporate pages, internal blog, download links, Oracle shop); Announcing StorageTek VSM 6; Announcement Oracle Solaris Cluster 4.1 Availability (new features, FAQ's, cluster corp page, download site, shop for media); Announcement: Oracle Database Appliance 2.4 patch update becomes available Technical SectionOracle White papers on SPARC SuperCluster; Understanding Parallel Execution; With LTFS, Tape is Gaining Storage Ground with additional link to How to Create Oracle Solaris 11 Zones with Oracle Enterprise Manager Ops Center; Provisioning Capabilities of Oracle Enterprise Ops Center Manager 12c; Maximizing your SPARC T4 Oracle Solaris Application Performance with the following articles: SPARC T4 Servers Set World Record on Siebel CRM 8.1.1.4 Benchmark, SPARC T4-Based Highly Scalable Solutions Posts New World Record on SPECjEnterprise2010 Benchmark, SPARC T4 Server Delivers Outstanding Performance on Oracle Business Intelligence Enterprise Edition 11g; Oracle SUN ZFS Storage Appliance Reference Architecture for VMware vSphere4; Why 4K? - George Wilson's ZFS Day Talk; Pillar Axiom 600 with connected subjects: Oracle Introduces Pillar Axiom Release 5 Storage System Software, Driving down the high cost of Storage, This Provisioning with Pilar Axiom 600, Pillar Axiom 600- System overview and architecture; Migrate to Oracle;s SPARC Systems; Top 5 Reasons to Migrate to Oracle's SPARC Systems Learning & EventsRecently delivered Techcasts: Learning Paths; Oracle Database 11g: Database Administration (New) - Learning Path; Webcast: Drill Down on Disaster Recovery; What are Oracle Users Doing to Improve Availability and Disaster Recovery; SAP NetWeaver and Oracle Exadata Database Machine ReferencesARTstor Selects Oracle’s Sun ZFS Storage 7420 Appliances To Support Rapidly Growing Digital Image Library, Scottish Widows Cuts Sales Administration 20%, Reduces Time to Prepare Reports by 75%, and Achieves Return on Investment in First Year, Oracle's CRM Cloud Service Powers Innovation: Applications on Demand; Technology on Demand, How toHow to Migrate Your Data to Oracle Solaris 11 Using Shadow Migration; Using svcbundle to Create SMF Manifests and Profiles in Oracle Solaris 11; How to prepare a Sun ZFS Storage Appliance to Serve as a Storage Devise with Oracle Enterprise Manager Ops Center 12c; Command Summary: Basic Operations with the Image Packaging System In Oracle Solaris 11; How to Update to Oracle Solaris 11.1 Using the Image Packaging System, How to Migrate Oracle Database from Oracle Solaris 8 to Oracle Solaris 11; Setting Up, Configuring, and Using an Oracle WebLogic Server Cluster; Ease the Chaos with Automated Patching: Oracle Enterprise Manager Cloud Control 12c; Book excerpt: Oracle Exalogic Elastic Cloud HandbookYou find the Newsletter on our portal under eSTEP News ---> Latest Newsletter. You will need to provide your email address and the pin below to get access. Link to the portal is shown below.URL: http://launch.oracle.com/PIN: eSTEP_2011Previous published Newsletters can be found under the Archived Newsletters section and more useful information under the Events, Download and Links tab. Feel free to explore and any feedback is appreciated to help us improve the service and information we deliver.Thanks and best regards,Partner HW Enablement EMEA

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  • The five steps of business intelligence adoption: where are you?

    - by Red Gate Software BI Tools Team
    When I was in Orlando and New York last month, I spoke to a lot of business intelligence users. What they told me suggested a path of BI adoption. The user’s place on the path depends on the size and sophistication of their organisation. Step 1: A company with a database of customer transactions will often want to examine particular data, like revenue and unit sales over the last period for each product and territory. To do this, they probably use simple SQL queries or stored procedures to produce data on demand. Step 2: The results from step one are saved in an Excel document, so business users can analyse them with filters or pivot tables. Alternatively, SQL Server Reporting Services (SSRS) might be used to generate a report of the SQL query for display on an intranet page. Step 3: If these queries are run frequently, or business users want to explore data from multiple sources more freely, it may become necessary to create a new database structured for analysis rather than CRUD (create, retrieve, update, and delete). For example, data from more than one system — plus external information — may be incorporated into a data warehouse. This can become ‘one source of truth’ for the business’s operational activities. The warehouse will probably have a simple ‘star’ schema, with fact tables representing the measures to be analysed (e.g. unit sales, revenue) and dimension tables defining how this data is aggregated (e.g. by time, region or product). Reports can be generated from the warehouse with Excel, SSRS or other tools. Step 4: Not too long ago, Microsoft introduced an Excel plug-in, PowerPivot, which allows users to bring larger volumes of data into Excel documents and create links between multiple tables.  These BISM Tabular documents can be created by the database owners or other expert Excel users and viewed by anyone with Excel PowerPivot. Sometimes, business users may use PowerPivot to create reports directly from the primary database, bypassing the need for a data warehouse. This can introduce problems when there are misunderstandings of the database structure or no single ‘source of truth’ for key data. Step 5: Steps three or four are often enough to satisfy business intelligence needs, especially if users are sophisticated enough to work with the warehouse in Excel or SSRS. However, sometimes the relationships between data are too complex or the queries which aggregate across periods, regions etc are too slow. In these cases, it can be necessary to formalise how the data is analysed and pre-build some of the aggregations. To do this, a business intelligence professional will typically use SQL Server Analysis Services (SSAS) to create a multidimensional model — or “cube” — that more simply represents key measures and aggregates them across specified dimensions. Step five is where our tool, SSAS Compare, becomes useful, as it helps review and deploy changes from development to production. For us at Red Gate, the primary value of SSAS Compare is to establish a dialog with BI users, so we can develop a portfolio of products that support creation and deployment across a range of report and model types. For example, PowerPivot and the new BISM Tabular model create a potential customer base for tools that extend beyond BI professionals. We’re interested in learning where people are in this story, so we’ve created a six-question survey to find out. Whether you’re at step one or step five, we’d love to know how you use BI so we can decide how to build tools that solve your problems. So if you have a sixty seconds to spare, tell us on the survey!

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  • Patterns for a tree of persistent data with multiple storage options?

    - by Robin Winslow
    I have a real-world problem which I'll try to abstract into an illustrative example. So imagine I have data objects in a tree, where parent objects can access children, and children can access parents: // Interfaces interface IParent<TChild> { List<TChild> Children; } interface IChild<TParent> { TParent Parent; } // Classes class Top : IParent<Middle> {} class Middle : IParent<Bottom>, IChild<Top> {} class Bottom : IChild<Middle> {} // Usage var top = new Top(); var middles = top.Children; // List<Middle> foreach (var middle in middles) { var bottoms = middle.Children; // List<Bottom> foreach (var bottom in bottoms) { var middle = bottom.Parent; // Access the parent var top = middle.Parent; // Access the grandparent } } All three data objects have properties that are persisted in two data stores (e.g. a database and a web service), and they need to reflect and synchronise with the stores. Some objects only request from the web service, some only write to it. Data Mapper My favourite pattern for data access is Data Mapper, because it completely separates the data objects themselves from the communication with the data store: class TopMapper { public Top FetchById(int id) { var top = new Top(DataStore.TopDataById(id)); top.Children = MiddleMapper.FetchForTop(Top); return Top; } } class MiddleMapper { public Middle FetchById(int id) { var middle = new Middle(DataStore.MiddleDataById(id)); middle.Parent = TopMapper.FetchForMiddle(middle); middle.Children = BottomMapper.FetchForMiddle(bottom); return middle; } } This way I can have one mapper per data store, and build the object from the mapper I want, and then save it back using the mapper I want. There is a circular reference here, but I guess that's not a problem because most languages can just store memory references to the objects, so there won't actually be infinite data. The problem with this is that every time I want to construct a new Top, Middle or Bottom, it needs to build the entire object tree within that object's Parent or Children property, with all the data store requests and memory usage that that entails. And in real life my tree is much bigger than the one represented here, so that's a problem. Requests in the object In this the objects request their Parents and Children themselves: class Middle { private List<Bottom> _children = null; // cache public List<Bottom> Children { get { _children = _children ?? BottomMapper.FetchForMiddle(this); return _children; } set { BottomMapper.UpdateForMiddle(this, value); _children = value; } } } I think this is an example of the repository pattern. Is that correct? This solution seems neat - the data only gets requested from the data store when you need it, and thereafter it's stored in the object if you want to request it again, avoiding a further request. However, I have two different data sources. There's a database, but there's also a web service, and I need to be able to create an object from the web service and save it back to the database and then request it again from the database and update the web service. This also makes me uneasy because the data objects themselves are no longer ignorant of the data source. We've introduced a new dependency, not to mention a circular dependency, making it harder to test. And the objects now mask their communication with the database. Other solutions Are there any other solutions which could take care of the multiple stores problem but also mean that I don't need to build / request all the data every time?

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  • When things go awry

    - by Phil Factor
    The moment the Entrepreneur opened his mouth on prime-time national TV, spelled out the URL and waxed big on how exciting ‘his’ new website was, I knew I was in for a busy night. I’d designed and built it. All at once, half a million people tried to log into the website. Although all my stress-testing paid off, I have to admit that the network locked up tight long before there was any danger of a database or website problem. Soon afterwards, the Entrepreneur and the Big Boss were there in the autopsy meeting. We picked through all our systems in detail to see how they’d borne the unexpected strain. Mercifully, in view of the sour mood of the Big Boss, it turned out that the only thing we could have done better was buy a bigger pipe to and from the internet. We’d specified that ‘big pipe’ when designing the system. The Big Boss had then railed at the cost and so we’d subsequently compromised. I felt that my design decisions were vindicated. The Big Boss brooded for a while. Then he made the significant comment: “What really ****** me off is the fact that, for ten minutes, we couldn’t take people’s money.” At that point I stopped feeling smug. Had the internet connection been better, the system would have reached its limit and failed rather precipitously, and that wasn’t what he wanted. Then it occurred to me that what had gummed up the connection was all those images on the site, that had made it so impressive for the visitors. If there had been a way to automatically pare down the site to the bare essentials under stress… Hmm. I began to consider disaster-recovery in the broadest sense – maintaining a service in spite of unusual or unexpected events. What he said makes a lot of sense: sacrifice whatever isn’t essential to keep the core service running when we approach the capacity limits. Maybe in IT we should borrow (or revive) the business concept of the ‘Skeleton service’, maintaining only the priority parts under stress, using a process that is well-prepared and carefully rehearsed. How might this work? Whatever the event we have to prepare for, it is all about understanding the priorities; knowing what one can dispense with when the going gets tough. In the event of database disaster, it’s much faster to deploy a skeletal system with only the essential data than to restore the entire system, though there would have to be a reconciliation process to update the revived database retrospectively, once the emergency was over. It isn’t just the database that could be designed for resilience. One could prepare for unusually high traffic in a website by designing a system that degraded gradually to a ‘skeletal’ site, one that maintained the commercial essentials without fat images, JavaScript libraries and razzmatazz. This is all what the Big Boss scathingly called ‘a mere technicality’. It seems to me that what is needed first is a culture of application and database design which acknowledges that we live in a very imperfect world, and react accordingly when things go awry.

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  • Consumer Oriented Search In Oracle Endeca Information Discovery - Part 2

    - by Bob Zurek
    As discussed in my last blog posting on this topic, Information Discovery, a core capability of the Oracle Endeca Information Discovery solution enables businesses to search, discover and navigate through a wide variety of big data including structured, unstructured and semi-structured data. With search as a core advanced capabilities of our product it is important to understand some of the key differences and capabilities in the underlying data store of Oracle Endeca Information Discovery and that is our Endeca Server. In the last post on this subject, we talked about Exploratory Search capabilities along with support for cascading relevance. Additional search capabilities in the Endeca Server, which differentiate from simple keyword based "search boxes" in other Information Discovery products also include: The Endeca Server Supports Set Search.  The Endeca Server is organized around set retrieval, which means that it looks at groups of results (all the documents that match a search), as well as the relationship of each individual result to the set. Other approaches only compute the relevance of a document by comparing the document to the search query – not by comparing the document to all the others. For example, a search for “U.S.” in another approach might match to the title of a document and get a high ranking. But what if it were a collection of government documents in which “U.S.” appeared in many titles, making that clue less meaningful? A set analysis would reveal this and be used to adjust relevance accordingly. The Endeca Server Supports Second-Order Relvance. Unlike simple search interfaces in traditional BI tools, which provide limited relevance ranking, such as a list of results based on key word matching, Endeca enables users to determine the most salient terms to divide up the result. Determining this second-order relevance is the key to providing effective guidance. Support for Queries and Filters. Search is the most common query type, but hardly complete, and users need to express a wide range of queries. Oracle Endeca Information Discovery also includes navigation, interactive visualizations, analytics, range filters, geospatial filters, and other query types that are more commonly associated with BI tools. Unlike other approaches, these queries operate across structured, semi-structured and unstructured content stored in the Endeca Server. Furthermore, this set is easily extensible because the core engine allows for pluggable features to be added. Like a search engine, queries are answered with a results list, ranked to put the most likely matches first. Unlike “black box” relevance solutions, which generalize one strategy for everyone, we believe that optimal relevance strategies vary across domains. Therefore, it provides line-of-business owners with a set of relevance modules that let them tune the best results based on their content. The Endeca Server query result sets are summarized, which gives users guidance on how to refine and explore further. Summaries include Guided Navigation® (a form of faceted search), maps, charts, graphs, tag clouds, concept clusters, and clarification dialogs. Users don’t explicitly ask for these summaries; Oracle Endeca Information Discovery analytic applications provide the right ones, based on configurable controls and rules. For example, the analytic application might guide a procurement agent filtering for in-stock parts by visualizing the results on a map and calculating their average fulfillment time. Furthermore, the user can interact with summaries and filters without resorting to writing complex SQL queries. The user can simply just click to add filters. Within Oracle Endeca Information Discovery, all parts of the summaries are clickable and searchable. We are living in a search driven society where business users really seem to enjoy entering information into a search box. We do this everyday as consumers and therefore, we have gotten used to looking for that box. However, the key to getting the right results is to guide that user in a way that provides additional Discovery, beyond what they may have anticipated. This is why these important and advanced features of search inside the Endeca Server have been so important. They have helped to guide our great customers to success. 

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  • PCI Encryption Key Management

    - by Unicorn Bob
    (Full disclosure: I'm already an active participant here and at StackOverflow, but for reasons that should hopefully be obvious, I'm choosing to ask this particular question anonymously). I currently work for a small software shop that produces software that's sold commercially to manage small- to mid-size business in a couple of fairly specialized industries. Because these industries are customer-facing, a large portion of the software is related to storing and managing customer information. In particular, the storage (and securing) of customer credit card information. With that, of course, comes PCI compliance. To make a long story short, I'm left with a couple of questions about why certain things were done the way they were, and I'm unfortunately without much of a resource at the moment. This is a very small shop (I report directly to the owner, as does the only other full-time employee), and the owner doesn't have an answer to these questions, and the previous developer is...err...unavailable. Issue 1: Periodic Re-encryption As of now, the software prompts the user to do a wholesale re-encryption of all of the sensitive information in the database (basically credit card numbers and user passwords) if either of these conditions is true: There are any NON-encrypted pieces of sensitive information in the database (added through a manual database statement instead of through the business object, for example). This should not happen during the ordinary use of the software. The current key has been in use for more than a particular period of time. I believe it's 12 months, but I'm not certain of that. The point here is that the key "expires". This is my first foray into commercial solution development that deals with PCI, so I am unfortunately uneducated on the practices involved. Is there some aspect of PCI compliance that mandates (or even just strongly recommends) periodic key updating? This isn't a huge issue for me other than I don't currently have a good explanation to give to end users if they ask why they are being prompted to run it. Question 1: Is the concept of key expiration standard, and, if so, is that simply industry-standard or an element of PCI? Issue 2: Key Storage Here's my real issue...the encryption key is stored in the database, just obfuscated. The key is padded on the left and right with a few garbage bytes and some bits are twiddled, but fundamentally there's nothing stopping an enterprising person from examining our (dotfuscated) code, determining the pattern used to turn the stored key into the real key, then using that key to run amok. This seems like a horrible practice to me, but I want to make sure that this isn't just one of those "grin and bear it" practices that people in this industry have taken to. I have developed an alternative approach that would prevent such an attack, but I'm just looking for a sanity check here. Question 2: Is this method of key storage--namely storing the key in the database using an obfuscation method that exists in client code--normal or crazy? Believe me, I know that free advice is worth every penny that I've paid for it, nobody here is an attorney (or at least isn't offering legal advice), caveat emptor, etc. etc., but I'm looking for any input that you all can provide. Thank you in advance!

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  • Rethinking Oracle Optimizer Statistics for P6 Part 2

    - by Brian Diehl
    In the previous post (Part 1), I tried to draw some key insights about the relationship between P6 and Oracle Optimizer Statistics.  The first is that average cardinality has the greatest impact on query optimization and that the particular queries generated by P6 are more likely to use this average during calculations. The second is that these are statistics that are unlikely to change greatly over the life of the application. Ultimately, our goal is to get the best query optimization possible.  Or is it? Stability No application administrator wants to get the call at 9am that their application users cannot get there work done because everything is running slow. This is a possibility with a regularly scheduled nightly collection of statistics. It may not just be slow performance, but a complete loss of service because one or more queries are optimized poorly. Ideally, this should not be the case. The database optimizer should make better decisions with more up-to-date data. Better statistics may give incremental performance benefit. However, this benefit must be balanced against the potential cost of system down time.  It is stability that we ultimately desire and not absolute optimal performance. We do want the benefit from more accurate statistics and better query plans, but not at the risk of an unusable system. As a result, I've developed the following methodology around managing database statistics for the P6 database.  1. No Automatic Re-Gathering - The daily, weekly, or other interval of statistic gathering is unlikely to be beneficial. Quite the opposite. It is more likely to cause problems. 2. Smart Re-Gathering - The time to collect statistics is when things have changed significantly. For a new installation of P6, this is happening more often because the data is growing from a few rows to thousands and more. But for a mature system, the data is not changing significantly from week-to-week. There are times to collect statistics: New releases of the application Changes in the underlying hardware or software versions (ex. new Oracle RDBMS version) When additional user groups are added. The new groups may use the software in significantly different ways. After significant changes in the data. This may be monthly, quarterly or yearly.  3. Always Test - If you take away one thing from this post, it would be to always have a plan to test after changing statistics. In reality, statistics can be collected as often as you desire provided there are tests in place to verify that performance is the same or better. These might be automated tests or simply a manual script of application functions. 4. Have a Way Out - Never change the statistics without a way to return to the previous set. Think of the statistics as one part of the overall application code that also includes the source code--both application and RDBMS. It would be foolish to change to the new code without a way to get back to the previous version. In the final post, I will talk about the actual script I created for P6 PMDB and possible future direction for managing query performance. 

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  • How to get foreignSecurityPrincipal from group. using DirectorySearcher

    - by kain64b
    What I tested with 0 results: string queryForeignSecurityPrincipal = "(&(objectClass=foreignSecurityPrincipal)(memberof:1.2.840.113556.1.4.1941:={0})(uSNChanged>={1})(uSNChanged<={2}))"; sidsForeign = GetUsersSidsByQuery(groupName, string.Format(queryForeignSecurityPrincipal, groupPrincipal.DistinguishedName, 0, 0)); public IList<SecurityIdentifier> GetUsersSidsByQuery(string groupName, string query) { List<SecurityIdentifier> results = new List<SecurityIdentifier>(); try{ using (var context = new PrincipalContext(ContextType.Domain, DomainName, User, Password)) { using (var groupPrincipal = GroupPrincipal.FindByIdentity(context, IdentityType.SamAccountName, groupName)) { DirectoryEntry directoryEntry = (DirectoryEntry)groupPrincipal.GetUnderlyingObject(); do { directoryEntry = directoryEntry.Parent; } while (directoryEntry.SchemaClassName != "domainDNS"); DirectorySearcher searcher = new DirectorySearcher(directoryEntry){ SearchScope=System.DirectoryServices.SearchScope.Subtree, Filter=query, PageSize=10000, SizeLimit = 15000 }; searcher.PropertiesToLoad.Add("objectSid"); searcher.PropertiesToLoad.Add("distinguishedname"); using (SearchResultCollection result = searcher.FindAll()) { foreach (var obj in result) { if (obj != null) { var valueProp = ((SearchResult)obj).Properties["objectSid"]; foreach (var atributeValue in valueProp) { SecurityIdentifier value = (new SecurityIdentifier((byte[])atributeValue, 0)); results.Add(value); } } } } } } } catch (Exception e) { WriteSystemError(e); } return results; } I tested it on usual users with query: "(&(objectClass=user)(memberof:1.2.840.113556.1.4.1941:={0})(uSNChanged>={1})(uSNChanged<={2}))" and it is work, I test with objectClass=* ... nothing help... But If I call groupPrincipal.GetMembers,I get all foreing user account from group. BUT groupPrincipal.GetMembers HAS MEMORY LEAK. Any Idea how to fix my query????

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  • DataSet does not support System.Nullable<>

    - by a_m0d
    I'm trying to set the DataSource for a Crystal Reports report, but I've run into a few problems. I've been following a guide written by Mohammad Mahdi Ramezanpour, and have managed to get all the way to the last part now (setting the DataSource). However, I have a problem that Mohammad does not seem to have - when I pass the results of my query to the report, I end up with the following exception: DataSet does not support System.Nullable< This is the query I am using: public IQueryable<Part> GetPartsToDisplayOnStockReport() { return from part in db.Parts where part.showOnStockReport == true select part; } and the way I pass it to the Report: public ActionResult ViewStockReport() { StockReport stockReport = new StockReport(); var parts = ordersRepository.GetPartsToDisplayOnStockReport().ToList(); stockReport.SetDataSource(parts); Stream stream = stockReport.ExportToStream(CrystalDecisions.Shared.ExportFormatType.PortableDocFormat); return File(stream, "application/pdf"); } I have also tried changing my query to this code, in the hope that it would fix my problem: return (from part in db.Parts where part.showOnStockReport == true select part) ?? db.Parts.DefaultIfEmpty(); but it still complained about the same problem. How can I pass the results of this query to my report, to use it as a data source? Also, if each of my Parts object contains other objects / collections of other objects, will I be able to reference them in the report with a datasource like this?

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  • Camera Preview App in Android throwing many errors (Nexus 4)

    - by Jagatheesan Jack
    I am trying to develop a camera app that takes a picture and saves it in a SQLite database. I get a lot of errors when executing the application. My code is as below. Any idea? CameraActivity.java private Camera mCamera; private CameraPreview mPreview; private int CAMERA_RETURN_CODE=100; private static final String TAG = "Take_Picture"; public static final int MEDIA_TYPE_IMAGE = 1; public static final int MEDIA_TYPE_VIDEO = 2; private Bitmap cameraBmp; private int MAX_FACES = 1; private Face[] faceList; public RectF[] rects; private Canvas canvas; private Drawable pictureDataDrawable; private MySQLiteHelper database; @Override public void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setContentView(R.layout.camera_activity); //this.requestWindowFeature(Window.FEATURE_NO_TITLE); //Create an instance of Camera mCamera = getCameraInstance(); setCameraDisplayOrientation(this, 0, mCamera); // Create our Preview view and set it as the content of our activity. mPreview = new CameraPreview(this, mCamera); FrameLayout preview = (FrameLayout) findViewById(R.id.camera_preview); preview.addView(mPreview); database = new MySQLiteHelper(getApplicationContext()); Button captureButton = (Button) findViewById(R.id.button_capture); captureButton.setOnClickListener( new View.OnClickListener() { private PictureCallback mPicture; @Override public void onClick(View v) { //mCamera.startPreview(); // get an image from the camera mCamera.takePicture(null, null, mPicture); PictureCallback mPicture = new PictureCallback() { @Override public void onPictureTaken(byte[] data, Camera camera) { try{ if (data != null) database.addEntry(data); //mCamera.startPreview(); } catch(Exception e){ Log.d(TAG, e.getMessage()); } } } ); } /** A safe way to get an instance of the Camera object. */ public static Camera getCameraInstance(){ Camera c = null; try { c = Camera.open(c.getNumberOfCameras()-1); // attempt to get a Camera instance } catch (Exception e){ // Camera is not available (in use or does not exist) } return c; // returns null if camera is unavailable } public static void setCameraDisplayOrientation(Activity activity, int cameraId, android.hardware.Camera camera) { android.hardware.Camera.CameraInfo info = new android.hardware.Camera.CameraInfo(); android.hardware.Camera.getCameraInfo(cameraId, info); int rotation = activity.getWindowManager().getDefaultDisplay() .getRotation(); int degrees = 360; /*switch (rotation) { case Surface.ROTATION_0: degrees = 0; break; case Surface.ROTATION_90: degrees = 90; break; case Surface.ROTATION_180: degrees = 180; break; case Surface.ROTATION_270: degrees = 270; break; }*/ int result; if (info.facing == Camera.CameraInfo.CAMERA_FACING_FRONT) { result = (info.orientation + degrees) % 360; result = (360 - result) % 360; // compensate the mirror } else { // back-facing result = (info.orientation - degrees + 360) % 360; } camera.setDisplayOrientation(result); } @Override protected void onPause() { super.onPause(); //releaseMediaRecorder(); // if you are using MediaRecorder, release it first releaseCamera(); // release the camera immediately on pause event } private void releaseCamera(){ if (mCamera != null){ mCamera.release(); // release the camera for other applications mCamera = null; } } public void startFaceDetection(){ // Try starting Face Detection Camera.Parameters params = mCamera.getParameters(); // start face detection only *after* preview has started if (params.getMaxNumDetectedFaces() > 0){ // camera supports face detection, so can start it: mCamera.startFaceDetection(); } } CameraPreview.java public class CameraPreview extends SurfaceView implements SurfaceHolder.Callback { private SurfaceHolder mHolder; private Camera mCamera; private String TAG; private List<Size> mSupportedPreviewSizes; public CameraPreview(Context context, Camera camera) { super(context); mCamera = camera; // Install a SurfaceHolder.Callback so we get notified when the // underlying surface is created and destroyed. mHolder = getHolder(); mHolder.addCallback(this); // deprecated setting, but required on Android versions prior to 3.0 mHolder.setType(SurfaceHolder.SURFACE_TYPE_PUSH_BUFFERS); } public void surfaceCreated(SurfaceHolder holder) { // The Surface has been created, now tell the camera where to draw the preview. try { mCamera.setPreviewDisplay(holder); mCamera.setDisplayOrientation(90); mCamera.startPreview(); } catch (IOException e) { Log.d(TAG, "Error setting camera preview: " + e.getMessage()); } } public void surfaceDestroyed(SurfaceHolder holder) { // empty. Take care of releasing the Camera preview in your activity. } public void surfaceChanged(SurfaceHolder holder, int format, int w, int h) { // If your preview can change or rotate, take care of those events here. // Make sure to stop the preview before resizing or reformatting it. if (mHolder.getSurface() == null){ // preview surface does not exist return; } // stop preview before making changes try { mCamera.stopPreview(); } catch (Exception e){ // ignore: tried to stop a non-existent preview } try { mCamera.setPreviewDisplay(mHolder); mCamera.startPreview(); } catch (Exception e){ Log.d(TAG, "Error starting camera preview: " + e.getMessage()); } } public void setCamera(Camera camera) { if (mCamera == camera) { return; } mCamera = camera; if (mCamera != null) { List<Size> localSizes = mCamera.getParameters().getSupportedPreviewSizes(); mSupportedPreviewSizes = localSizes; requestLayout(); try { mCamera.setPreviewDisplay(mHolder); } catch (IOException e) { e.printStackTrace(); } /* Important: Call startPreview() to start updating the preview surface. Preview must be started before you can take a picture. */ mCamera.startPreview(); } } MySQLiteHelper.java private static final int count = 0; public static final String TABLE_IMAGE = "images"; public static final String COLUMN_ID = "_id"; public static final String PICTURE_DATA = "picture"; public static final String DATABASE_NAME = "images.db"; public static final int DATABASE_VERSION = 1; public static final String DATABASE_CREATE = "create table " + TABLE_IMAGE + "(" + COLUMN_ID + " integer primary key autoincrement, " + PICTURE_DATA + " blob not null);"; public static SQLiteDatabase database; private static String TAG = "test"; public MySQLiteHelper(Context context) { super(context, DATABASE_NAME, null, DATABASE_VERSION); // TODO Auto-generated constructor stub } public MySQLiteHelper(Context context, String name, CursorFactory factory, int version, DatabaseErrorHandler errorHandler) { super(context, name, factory, version, errorHandler); // TODO Auto-generated constructor stub } @Override public void onCreate(SQLiteDatabase database) { database.execSQL(DATABASE_CREATE); } @Override public void onUpgrade(SQLiteDatabase db, int oldVersion, int newVersion) { Log.w(MySQLiteHelper.class.getName(), "Upgrading database from version " + oldVersion + " to " + newVersion + ", which will destroy all old data"); db.execSQL("DROP TABLE IF EXISTS " + TABLE_IMAGE); onCreate(db); } /** * @param args */ public static void main(String[] args) { // TODO Auto-generated method stub } public void addEntry(byte [] array) throws SQLiteException{ ContentValues cv = new ContentValues(); //cv.put(KEY_NAME, name); cv.put(PICTURE_DATA, array); database.insert( TABLE_IMAGE, null, cv ); Log.w(TAG , "added " +count+ "images"); database.close(); } Errors 11-07 23:28:39.050: E/mm-libcamera2(176): PROFILE HAL: stopPreview(): E: 1383838119.067589459 11-07 23:28:39.050: E/mm-camera(201): config_MSG_ID_STOP_ACK: streamon_mask is not clear. Should not call PP_Release_HW 11-07 23:28:39.090: E/QCameraHWI(176): android::status_t android::QCameraHardwareInterface::setPreviewWindow(preview_stream_ops_t*):Received Setting NULL preview window 11-07 23:28:39.090: E/QCameraHWI(176): android::status_t android::QCameraHardwareInterface::setPreviewWindow(preview_stream_ops_t*): mPreviewWindow = 0x0x0, mStreamDisplay = 0x0xb8a9df90 11-07 23:28:39.090: E/mm-camera(201): config_shutdown_pp Camera not in streaming mode. Returning. 11-07 23:28:39.090: E/mm-camera(201): vfe_ops_deinit: E 11-07 23:28:39.120: E/qcom_sensors_hal(533): hal_process_report_ind: Bad item quality: 11 11-07 23:28:39.310: E/qcom_sensors_hal(533): hal_process_report_ind: Bad item quality: 11 11-07 23:28:39.330: E/mm-camera(201): sensor_load_chromatix: libchromatix_imx119_preview.so: 30 11-07 23:28:39.340: E/mm-camera(201): vfe_ops_init: E 11-07 23:28:39.360: E/mm-camera(201): vfe_legacy_stats_buffer_init: AEC_STATS_BUFNUM 11-07 23:28:39.360: E/mm-camera(201): vfe_legacy_stats_buffer_init: AEC_STATS_BUFNUM 11-07 23:28:39.360: E/mm-camera(201): mctl_init_stats_proc_info: snap_max_line_cnt =25776 11-07 23:28:39.440: E/QCameraHWI(176): android::status_t android::QCameraHardwareInterface::setPreviewWindow(preview_stream_ops_t*): mPreviewWindow = 0x0xb8aa1780, mStreamDisplay = 0x0xb8a9df90 11-07 23:28:39.440: E/mm-camera(201): config_proc_CAMERA_SET_INFORM_STARTPREVIEW 11-07 23:28:39.450: E/mm-camera(201): config_update_stream_info Storing stream parameters for video inst 1 as : width = 640, height 480, format = 1 inst_handle = 810081 cid = 0 11-07 23:28:39.490: E/mm-camera(201): config_update_stream_info Storing stream parameters for video inst 3 as : width = 640, height 480, format = 1 inst_handle = 830083 cid = 0 11-07 23:28:39.490: E/mm-camera(201): config_update_stream_info Storing stream parameters for video inst 4 as : width = 512, height 384, format = 1 inst_handle = 840084 cid = 0 11-07 23:28:39.500: E/mm-camera(201): config_decide_vfe_outputs: Ports Used 3, Op mode 1 11-07 23:28:39.500: E/mm-camera(201): config_decide_vfe_outputs Current mode 0 Full size streaming : Disabled 11-07 23:28:39.500: E/mm-camera(201): config_decide_vfe_outputs: Primary: 640x480, extra_pad: 0x0, Fmt: 1, Type: 1, Path: 1 11-07 23:28:39.500: E/mm-camera(201): config_decide_vfe_outputs: Secondary: 640x480, extra_pad: 0x0, Fmt: 1, Type: 3, Path: 4 11-07 23:28:39.510: E/mm-camera(201): config_update_inst_handles Updated the inst handles as 810081, 830083, 0, 0 11-07 23:28:39.631: E/mm-camera(201): sensor_load_chromatix: libchromatix_imx119_preview.so: 30 11-07 23:28:39.631: E/mm-camera(201): camif_client_set_params: camif has associated with obj mask 0x1 11-07 23:28:39.631: E/mm-camera(201): config_v2_CAMERA_START_common CAMIF_PARAMS_ADD_OBJ_ID failed -1 11-07 23:28:39.641: E/mm-camera(201): vfe_operation_config: format 3 11-07 23:28:39.641: E/mm-camera(201): vfe_operation_config:vfe_op_mode=5 11-07 23:28:39.641: E/mm-camera(201): Invalid ASD Set Params Type 11-07 23:28:39.641: E/mm-camera(201): vfe_set_bestshot: Bestshot mode not changed

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  • IQueryable<> from stored procedure (entity framework)

    - by mmcteam
    I want to get IQueryable<> result when executing stored procedure. Here is peace of code that works fine: IQueryable<SomeEntitiy> someEntities; var globbalyFilteredSomeEntities = from se in m_Entities.SomeEntitiy where se.GlobalFilter == 1234 select se; I can use this to apply global filter, and later use result in such way result = globbalyFilteredSomeEntities .OrderByDescending(se => se.CreationDate) .Skip(500) .Take(10); What I want to do - use some stored procedures in global filter. I tried: Add stored procedure to m_Entities, but it returns IEnumerable<> and executes sp immediately: var globbalyFilteredSomeEntities = from se in m_Entities.SomeEntitiyStoredProcedure(1234); Materialize query using EFExtensions library, but it is IEnumerable<>. If I use AsQueryable() and OrderBy(), Skip(), Take() and after that ToList() to execute that query - I get exception that DataReader is open and I need to close it first(can't paste error - it is in russian). var globbalyFilteredSomeEntities = m_Entities.CreateStoreCommand("exec SomeEntitiyStoredProcedure(1234)") .Materialize<SomeEntitiy>(); //.AsQueryable() //.OrderByDescending(se => se.CreationDate) //.Skip(500) //.Take(10) //.ToList(); Also just skipping .AsQueryable() is not helpful - same exception. When I put ToList() query executes, but it is too expensive to execute query without Skip(), Take().

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