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• Wamp server that works over a network

  - by user28233

  I have 2 computers. Both with w7 as os. I have installed wampserver on one of them. I have mysql database on wampserver. Then I have made a vb.net program to connect to mysql database. I have put the program on both computers. What I want to do is for those two programs to see the same database that is on one computer. For them to be able to add, delete, update that 1 database. How do I do that? How do I network the mysql database? Do I also have to install wampserver on the other computer? What do I do? Please enlighten me.

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• Which would be a better way to load data via ajax

  - by Mike

  I am using google maps and returning html/lat/long from my MySQL database Currently A user picks a business category e.g; "Video Production". an ajax call is sent to a CodeIgniter controller the Controller then queries the db, and returns the following data via JSON Lat/Long of the marker HTML for the popup window this is approximately 34 rows in the database across two tables per business the ajax call receives this data and then plots the marker along with the html onto the map The data that is returned from the controller is one big json object... This is done for all businesses that exist in the Video Production category (currently approx 40 businesses). As you can see, pulling this data for multiple categories (100s of businesses) can get very very taxing on the server. My question is Would it be more beneficial to modify the process flow as such: a user picks a business category e.g; "Video Production". an ajax call is sent to a CodeIgniter controller the controller then queries the database for the location base information lat/long level (used to change marker icon color) This would be a single row per business with several columns the ajax call receives this data and then plots the marker on the map when the user clicks a marker an ajax call is sent to a CodeIgniter Controller the controller queries the database for the HTML and additional data based on business_id and if not, what are some better suggestions to this problem? In summary this means rather than including the HTML and additional data along for each business, only submitting minimal location information and then re-query for that information when each business marker is clicked. Potential Downsides longer load times when a user clicks a marker icon more code?? more queries to the database

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• Adding Column to a SQL Server Table

  - by Dinesh Asanka

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

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• 65536% Autogrowth!

  - by Tara Kizer

  Twice a year, we move our production systems to our disaster recovery site.  Last Saturday night was one of those days.  There are about 50 SQL Server databases to be moved to the DR site, which is done via database mirroring.  It takes only a few seconds to failover, but some databases have a bit more involved work such as setting up replication.  Everything went relatively smooth, but we encountered a weird bug on our most mission critical system.  After everything was successfully failed over to the DR site, it was noticed that mirroring was in a suspended state on one of the databases.  We thought we had run into a SQL Server 2005 bug that we had been encountering and were working with Microsoft on a fix.  Microsoft did fix it in both SQL Server 2005 service pack 3 cumulative update package 13 and service pack 4 cumulative update package 2, however SP3 CU13 and SP4 both recently failed on this system so we were not patched yet with the bug fix.  As the suspended state was causing us issues with replication, we dropped mirroring.  We then noticed we had 10MB of free disk space on the mount point where the principal’s data files are stored.  I knew something went amiss as this system should have at least 150GB free on that mount point.  I immediately checked the main database’s data file and was shocked to see an autgrowth size of 65536%.  The data file autogrew right before mirroring went into the suspended state. 65536%! I didn’t have a lot of time to research if this autgrowth problem was a known SQL Server bug, so I deferred that research to today.  A quick Google search yielded no results but emphasis on “quick”.  I checked our performance system, which was recently restored with a copy of the affected production database, and found the autogrowth setting to be 512MB.  So this autogrowth bug was encountered sometime in the last two weeks.  On February 26th, we had attempted to install SQL 2005 SP4 on production, however it had failed (PSS case open with Microsoft).  I suspected that the SP4 failure was somehow related to this autgrowth bug although that turned out not to be the case. I then tweeted (@TaraKizer) about this problem to see if the SQL Server community (#sqlhelp) had any insights.  It seems several people have either heard of this bug or encountered it.  Aaron Bertrand (blog|twitter) referred me to this Connect item. Our affected database originated on SQL Server 2000 and was upgraded to SQL Server 2005 in 2007.  Back on SQL Server 2000, we were using the default file growth setting which was a percentage.  Sometime after the 2005 upgrade is when we changed it to 512MB.  Our situation seemed to fit the bug Aaron referred to me, so now the question was whether Microsoft had fixed it yet. I received a reply to my tweet from Amit Banerjee (twitter) that it had been fixed in SP3 CU1 (KB958004).  My affected system is SP3 CU8, so I was initially confused why we had encountered the bug.  Because I don’t read things fully, I had missed that there are additional steps you have to follow after applying the bug fix.  Amit set me straight.  Although you can read this information in the KB article, I will also copy it here in case you are as lazy as me and miss the most important section of it (although if you are as lazy as me, you won’t have read this far down my blog post): This hotfix will prevent only future occurrences of this problem. For example, if you restore a database from SQL Server 2000 to a SQL Server 2005 instance that contains this hotfix, this problem will not occur. However, if you already have a database that is affected by this problem, you must follow these steps to resolve this problem manually: Apply this hotfix. Set the file growth settings for the affected files to percentage settings, and then set the settings back to megabyte settings. Take the database offline, and then bring it back online. Verify that the values of the is_percent_growth column are correct in the sys.database_files system table and in the sys.master_files system table.

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• IBM DB2 9.7, DBADM and my Rubik's Cube

  It's a challenge to adapt to change, but the changes in IBM DB2 9.7's Database Administrator authority bring significant database security benefits. Join Rebecca Bond as she shares some twists, some turns, and some clues regarding DB2 9.7's Database Administrator (DBADM) authority.

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• Oracle University Nouveaux cours (Week 14)

  - by swalker

  Parmi les nouveautés d’Oracle Université de ce mois-ci, vous trouverez : Database Oracle Data Modeling and Relational Database Design (4 days) Fusion Middleware Oracle Directory Services 11g: Administration (5 days) Oracle Unified Directory 11g: Services Deployment Essentials (2 days) Oracle GoldenGate 11g Management Pack: Overview (1 day) Business Intelligence & Datawarehousing Oracle Database 11g: Data Mining Techniques (2 days) Oracle Solaris Oracle Solaris 10 System Administration for HP-UX Administrators (5 days) E-Business Suite R12.x Oracle Time and Labor Fundamentals Contacter l’ équipe locale d’ Oracle University pour toute information et dates de cours. Restez connecté à Oracle University : LinkedIn OracleMix Twitter Facebook Google+

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• Error when setting Piwik analytics

  - by bertran

  I've uploaded the latest version of Piwik unto my web server, which is hosted by go daddy.com, on a linux hosting plan. I'm setting it up (accessing it from my browser as instructed) and I have the "Piwikinstallation" page open on step 3 (database set-up ) of 9. I don't know what to imput in the field "database server"... the default is the number 127.0.0.1 When I leave that input as is, and click "Next" leaving the gives the error: "Error when trying to connect to database server: SQLSTATE[HY000] [2013] Lost connection to MySQL server at 'reading initial communication packet', system error: 111" and changing that input to "localhost" gives me another error: "Error when trying to connect to database server:SQLSTATE[HY000] [2002] Can't connect to local MySQL server through socket '/var/lib/mysql/mysql.sock' (2)"

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• Multitenant Design for SQL Azure: White Paper Available

  - by Herve Roggero

  Cloud computing is about scaling out all your application tiers, from web application to the database layer. In fact, the whole promise of Azure is to pay for just what you need. You need more IIS servers? No problemo... just spin another web server. You expect to double your storage needs for Azure Tables? No problemo; you are covered there too... just pay for your storage needs. But what about the database tier, SQL Azure? How do you add new databases easily, and transparently, so that your application simply uses more of SQL Azure if its needs to? Without changing a single line of code? And what if you need to scale back down? Welcome to the world of database scalability. There are many terms that describe database scalability, including data federation, multitenant designs, and even NoSQL depending on the technical solution you are implementing.  Because SQL Azure is a transactional database system, NoSQL is not really an option. However data federation and multitenant designs offer some very interesting scalability options that are worth considering. Data federation, a feature of SQL Azure that will be offered in the future, offers very interesting capabilities available natively on the SQL Azure platform. More to come in a few weeks... Multitenant designs on the other hand are design practices and technologies designed to help you reach flexible scalability options not available otherwise. The first incarnation of such a method was made available on CodePlex as an open source project (http://enzosqlshard.codeplex.com).  This project was an attempt to provide a sharding library for educational purposes.  All that sounds really cool... and really esoteric... almost a form of database "voodoo"... However after being on multiple Azure projects I am starting to see a real need. Customers want to be able to free themselves from the database tier, so that if they have 10 new customers tomorrow, all they need to do is add 2 more SQL Azure instances. It's that simple. How you achieve this, and suggested application design guidelines, are available in a white paper I just published.  The white paper offers two primary sections. The first section describes the business and technical problem at hand, and how to classify it according to specific design patterns. For example, I discuss compressed shards through schema separation. The second section offers a method for addressing the needs of a multitenant design using a new library, the big bother of the codeplex project mentioned previously (that I created earlier this year), complete with management interface and such. A Beta of this platform will be made available within weeks; as soon as the documentation will be ready.   I would like to ask you to drop me a quick email at [email protected] if you are going to download the white paper. It's not required, but it would help me get in touch with you for feedback.  You can download this white paper here:   http://www.bluesyntax.net/files/EnzoFramework.pdf . Thank you, and I am looking for feedback, thoughts and implementation opportunities.

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• Oracle University Nuevos cursos (Week 10)

  - by swalker

  Oracle University ha publicado recientemenete las siguentes formaciones (o versiones) nuevos: Database RAC & Grid Infrastructure for Oracle Solaris System Administration (1 day) Oracle Database 11g: Performance Tuning (Training On Demand) Development Tools Oracle Database: Program with PL/SQL (Training On Demand) MySQL MySQL for Database Administrators (Training On Demand) Fusion Middleware Oracle WebCenter Portal 11g: Build Portals With Spaces (3 days) Oracle WebCenter Content 11g: Site Studio Essentials (5 days) Oracle BPM 11g Modeling (3 days) Business Intelligence & Datawarehousing Oracle BI Applications 7.9.6: Implementation for Oracle EBS (4 days) Oracle BI Applications 7.9.6: Implementation for Siebel CRM (4 days) Oracle BI 11g R1: Build Repositories (Training on Demand) Fusion Applications Fusion Applications: Extend Applications with ADF (5 days) E-Business Suite R12.x Extend Oracle Applications: Building OA Framework Applications (Training On Demand) PeopleSoft PeopleSoft Integration Tools Rel 8.50 (Training On Demand) Póngase en contacto con el equipo local de Oracle University para conocer las fechas y otros detalles de los cursos.

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• Oracle University Nuovi corsi (Week 14)

  - by swalker

  Oracle University ha recentemente rilasciato i seguenti nuovi corsi in inglese: Database Oracle Data Modeling and Relational Database Design (4 days) Fusion Middleware Oracle Directory Services 11g: Administration (5 days) Oracle Unified Directory 11g: Services Deployment Essentials (2 days) Oracle GoldenGate 11g Management Pack: Overview (1 day) Business Intelligence & Datawarehousing Oracle Database 11g: Data Mining Techniques (2 days) Oracle Solaris Oracle Solaris 10 System Administration for HP-UX Administrators (5 days) E-Business Suite R12.x Oracle Time and Labor Fundamentals Per ulteriori informazioni e per conoscere le date dei corsi, contattate il vostro Oracle University team locale. Rimanete in contatto con Oracle University: LinkedIn OracleMix Twitter Facebook Google+

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• Demo on Data Guard Protection From Lost-Write Corruption

  - by Rene Kundersma

  Today I received the news a new demo has been made available on OTN for Data Guard protection from lost-write corruption. Since this is a typical MAA solution and a very nice demo I decided to mention this great feature also in this blog even while it's a recommended best practice for some time. When lost writes occur an I/O subsystem acknowledges the completion of the block write even though the write I/O did not occur in the persistent storage. On a subsequent block read on the primary database, the I/O subsystem returns the stale version of the data block, which might be used to update other blocks of the database, thereby corrupting it.  Lost writes can occur after an OS or storage device driver failure, faulty host bus adapters, disk controller failures and volume manager errors. In the demo a data block lost write occurs when an I/O subsystem acknowledges the completion of the block write, while in fact the write did not occur in the persistent storage. When a primary database lost write corruption is detected by a Data Guard physical standby database, Redo Apply (MRP) will stop and the standby will signal an ORA-752 error to explicitly indicate a primary lost write has occurred (preventing corruption from spreading to the standby database). Links: MOS (1302539.1). "Best Practices for Corruption Detection, Prevention, and Automatic Repair - in a Data Guard Configuration" Demo MAA Best Practices Rene Kundersma

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• SQL Down Under Podcast 50 - Guest Louis Davidson now online

  - by Greg Low

  Hi Folks,I've recorded an interview today with SQL Server MVP Louis Davidson. In it, Louis discusses some of his thoughts on database design and his latest book.You'll find the podcast here: http://www.sqldownunder.com/Resources/Podcast.aspxAnd you'll find his latest book (Pro SQL Server 2012 Relational Database Design and Implementation) here: http://www.amazon.com/Server-Relational-Database-Implementation-Professional/dp/1430236957/ref=sr_1_2?ie=UTF8&qid=1344997477&sr=8-2&keywords=louis+davidsonEnjoy!

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• Oracle University Nuevos cursos (Week 14)

  - by swalker

  Oracle University ha publicado recientemenete las siguentes formaciones (o versiones) nuevos: Database Oracle Data Modeling and Relational Database Design (4 days) Fusion Middleware Oracle Directory Services 11g: Administration (5 days) Oracle Unified Directory 11g: Services Deployment Essentials (2 days) Oracle GoldenGate 11g Management Pack: Overview (1 day) Business Intelligence & Datawarehousing Oracle Database 11g: Data Mining Techniques (2 days) Oracle Solaris Oracle Solaris 10 System Administration for HP-UX Administrators (5 days) E-Business Suite R12.x Oracle Time and Labor Fundamentals Póngase en contacto con el equipo local de Oracle University para conocer las fechas y otros detalles de los cursos. Manténgase conectado a Oracle University: LinkedIn OracleMix Twitter Facebook Google+

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• Big AdventureWorks2012

  - by jamiet

  Last week I launched AdventureWorks on Azure, an initiative to make SQL Azure accessible to anyone, in my blog post AdventureWorks2012 now available for all on SQL Azure. Since then I think its fair to say that the reaction has been lukewarm with 31 insertions into the [dbo].[SqlFamily] table and only 8 donations via PayPal to support it; on the other hand those 8 donators have been incredibly generous and we nearly have enough in the bank to cover a full year’s worth of availability. It was always my intention to try and make this offering more appealing and to that end I have used an adapted version of Adam Machanic’s make_big_adventure.sql script to massively increase the amount of data in the database and give the community more scope to really push SQL Azure and see what it is capable of. There are now two new tables in the database: [dbo].[bigProduct] with 25200 rows [dbo].[bigTransactionHistory] with 7827579 rows The credentials to login and use AdventureWorks on Azure are as they were before: Server mhknbn2kdz.database.windows.net Database AdventureWorks2012 User sqlfamily Password sqlf@m1ly Remember, if you want to support AdventureWorks on Azure simply click here to launch a pre-populated PayPal Send Money form - all you have to do is login, fill in an amount, and click Send. We need more donations to keep this up and running so if you think this is useful and worth supporting, please please donate.   I mentioned that I had to adapt Adam’s script, the main reasons being: Cross-database queries are not yet supported in SQL Azure so I had to create a local copy of [dbo].[spt_values] rather than reference that in [master] SELECT…INTO is not supported in SQL Azure The 1GB limit of SQLAzure web edition meant that there would not be enough space to store all the data generated by Adam’s script so I had to decrease the total number of rows. The amended script is available on my SkyDrive at https://skydrive.live.com/redir.aspx?cid=550f681dad532637&resid=550F681DAD532637!16756&parid=550F681DAD532637!16755 @Jamiet

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• What Are Oracle Users Doing to Improve Availability and Disaster Recovery?

  - by jgelhaus

  What Are Oracle Users Doing to Improve Availability and Disaster Recovery? Download the recent database availability survey report, Enterprise Data and the Cost of Downtime, and watch the Webcast highlighting the results. The survey, conducted by the Independent Oracle Users Group, examined more than 350 data managers and professionals regarding planned and unplanned downtime, database high availability, and disaster recovery solutions. The findings will help you learn about: Leading causes of planned and unplanned downtime of Oracle users Different approaches to database high availability Why a majority of Oracle users commonly deploy Oracle Database with Oracle Real Application Clusters, Oracle Active Data Guard, and Oracle GoldenGate Register now to download the report and watch the Webcast.

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• What the Hekaton?

  - by Tony Davis

  Hekaton, the power behind SQL Server 2014′s In-Memory OLTP technology, is intended to make data operations run orders of magnitude faster on SQL Server. This works its magic partly by serving database workloads entirely from main memory, using memory-optimized table structures. It replaces the relational engine’s standard locking model with an optimistic concurrency model based on time-stamped row versions. Deeper down the Hekaton engine uses new, ‘latch free’ data structures. So far, so good, but performance improvements on this scale require a compromise, and the compromise is that these aren’t tables as we understand them. For the database developer, these differences are painful because they involve sacrificing some very important bits of the relational model. Most importantly, Hekaton tables don’t currently support FOREIGN KEY constraints or CHECK constraints, and you can’t put the checks in triggers because there aren’t any DML triggers either. Constraints allow a relational designer to enforce relational integrity and data integrity. Without them, of course, ‘bad data’ can get into our Hekaton tables. There is no easy way of preventing it. For several classes of database and data, this is a show-stopper. One may regard all these restrictions regretfully, seeing limited opportunity to try out Hekaton with current databases, but perhaps there is also a sudden glow of recognition. Isn’t this how we all originally imagined table variables were going to be, back in SQL 2005? And they have much the same restrictions. Maybe, instead of pretending that a currently-designed database can be ‘Hekatonized’ with a few mouse clicks, we should redesign databases for SQL 2014 to replace table variables with Hekaton tables, exploiting this technology for fast intermediate processing, and for the most part forget, for now, the idea of trying to convert our base relational tables into Hekaton tables. Few database developers would be averse to having their working tables running an order of magnitude faster, as long as it didn’t compromise the integrity of the data in the base tables.

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• Exadata at Oracle Openworld - A guide to sessions

  - by Javier Puerta

  A large number of sessions focusing on Exadata will be taking place during the week of Oracle Openworld in San Francisco. To help you organize your schedule I am including below a list of sessions and events around Exadata that you will find of interest. PARTNER SPECIFIC SESSIONS Date/Time/Location  Session Sunday, Sep 30, 3:30 PM - 4:30 PM - Moscone South - 301 Building a Winning Services Practice with Oracle’s Engineered Systems.- This session kicks off a week-long session on Oracle’s engineered systems, from Oracle Database Appliance to Oracle Exadata, Oracle Exalogic, Oracle Exalytics, Oracle Big Data Appliance, and Oracle SPARC SuperCluster. Hear about what is to come in the week ahead in terms of engineered systems. As an ideal consolidation platform for database workloads, Oracle Exadata generates significant services opportunities. This session reviews the range of partner-led services that support Oracle Exadata deployments.   Monday, October 1st, 2011 at 15:30 - 18:00 PST Grand Hyatt San Francisco 345 Stockton Street, San Francisco (Conference Theater) (It is a 15 minute walk from OOW Moscone Center. See directions here) Exadata & Manageability EMEA Partner Community Forum.- Listen to other partners share their experiences in selling and implementing Exadata and Manageability projects, and have a direct dialogue with some of the Oracle executives that are driving the strategy of the company in these areas. Agenda Welcome - Hans-Peter Kipfer, VP, Engineered Systems Oracle EMEA Next challenges in building and managing clouds - Javier Cabrerizo, VP, Business Development for Exadata, Oracle Corp. Partner Experiences: IT modernization, simplification and cost reduction: The case of a customer in Transportation & Logistics with custom applications and SAP. - Francisco Bermudez, Country Leader Infrastructure Services, Capgemini, Spain Nvision cloud project - Dmitry Krasilov, Head of Oracle Competence Center, Nvision Group, Russia From Exadata Ready to Exadata Optimized: An ISV Experience - Miguel Alves, Product Business Solutions Manager, WeDo Technologies, Portugal To confirm your participation send an email to [email protected]  Wednesday, Oct 3, 11:45 AM - 12:45 PM - Marriott Marquis - Golden Gate B  Building a Practice with Exadata Database Machine.- As an ideal consolidation platform for database workloads, Oracle’s Exadata Database Machine generates significant services opportunities. In this session, learn about the range of partner-led services that support Exadata Database Machine deployments.  Other Engineered Systems sessions for Partners at the Oracle PartnerNetwork Exchange  Click here.-   OOW CUSTOMER SESSIONS   Download the Focus On Exadata guide for a full list of Exadata OOW sessions.  

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• Rule Engine in .net

  - by user641812

  I have to import data from excel to SQL database. Excel data contains various parameters and there value like P1,P1,P4,P5 etc. I have to apply business rules Like if( P1 100 and P1 < 200) then insert the record in database. Similarly in some cases string values are also validated. Can I have any open source rule engine that contains UI to change , add , delete the rules. Am using C# to read the excel and and insert the records One more thing which is best approach: Read excel first and store every record as an object in a collection, then iterate through the collection, apply business rules on every object and then insert record in the database Or Read one record from excel apply business rule and then insert record in the database. Repeat the process for whole excel.

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• Combined Likelihood Models

  - by Lukas Vermeer

  In a series of posts on this blog we have already described a flexible approach to recording events, a technique to create analytical models for reporting, a method that uses the same principles to generate extremely powerful facet based predictions and a waterfall strategy that can be used to blend multiple (possibly facet based) models for increased accuracy. This latest, and also last, addition to this sequence of increasing modeling complexity will illustrate an advanced approach to amalgamate models, taking us to a whole new level of predictive modeling and analytical insights; combination models predicting likelihoods using multiple child models. The method described here is far from trivial. We therefore would not recommend you apply these techniques in an initial implementation of Oracle Real-Time Decisions. In most cases, basic RTD models or the approaches described before will provide more than enough predictive accuracy and analytical insight. The following is intended as an example of how more advanced models could be constructed if implementation results warrant the increased implementation and design effort. Keep implemented statistics simple! Combining likelihoods Because facet based predictions are based on metadata attributes of the choices selected, it is possible to generate such predictions for more than one attribute of a choice. We can predict the likelihood of acceptance for a particular product based on the product category (e.g. ‘toys’), as well as based on the color of the product (e.g. ‘pink’). Of course, these two predictions may be completely different (the customer may well prefer toys, but dislike pink products) and we will have to somehow combine these two separate predictions to determine an overall likelihood of acceptance for the choice. Perhaps the simplest way to combine multiple predicted likelihoods into one is to calculate the average (or perhaps maximum or minimum) likelihood. However, this would completely forgo the fact that some facets may have a far more pronounced effect on the overall likelihood than others (e.g. customers may consider the product category more important than its color). We could opt for calculating some sort of weighted average, but this would require us to specify up front the relative importance of the different facets involved. This approach would also be unresponsive to changing consumer behavior in these preferences (e.g. product price bracket may become more important to consumers as a result of economic shifts). Preferably, we would want Oracle Real-Time Decisions to learn, act upon and tell us about, the correlations between the different facet models and the overall likelihood of acceptance. This additional level of predictive modeling, where a single supermodel (no pun intended) combines the output of several (facet based) models into a single prediction, is what we call a combined likelihood model. Facet Based Scores As an example, we have implemented three different facet based models (as described earlier) in a simple RTD inline service. These models will allow us to generate predictions for likelihood of acceptance for each product based on three different metadata fields: Category, Price Bracket and Product Color. We will use an Analytical Scores entity to store these different scores so we can easily pass them between different functions. A simple function, creatively named Compute Analytical Scores, will compute for each choice the different facet scores and return an Analytical Scores entity that is stored on the choice itself. For each score, a choice attribute referring to this entity is also added to be returned to the client to facilitate testing. One Offer To Predict Them All In order to combine the different facet based predictions into one single likelihood for each product, we will need a supermodel which can predict the likelihood of acceptance, based on the outcomes of the facet models. This model will not need to consider any of the attributes of the session, because they are already represented in the outcomes of the underlying facet models. For the same reason, the supermodel will not need to learn separately for each product, because the specific combination of facets for this product are also already represented in the output of the underlying models. In other words, instead of learning how session attributes influence acceptance of a particular product, we will learn how the outcomes of facet based models for a particular product influence acceptance at a higher level. We will therefore be using a single All Offers choice to represent all offers in our combined likelihood predictions. This choice has no attribute values configured, no scores and not a single eligibility rule; nor is it ever intended to be returned to a client. The All Offers choice is to be used exclusively by the Combined Likelihood Acceptance model to predict the likelihood of acceptance for all choices; based solely on the output of the facet based models defined earlier. The Switcheroo In Oracle Real-Time Decisions, models can only learn based on attributes stored on the session. Therefore, just before generating a combined prediction for a given choice, we will temporarily copy the facet based scores—stored on the choice earlier as an Analytical Scores entity—to the session. The code for the Predict Combined Likelihood Event function is outlined below. // set session attribute to contain facet based scores. // (this is the only input for the combined model) session().setAnalyticalScores(choice.getAnalyticalScores); // predict likelihood of acceptance for All Offers choice. CombinedLikelihoodChoice c = CombinedLikelihood.getChoice("AllOffers"); Double la = CombinedLikelihoodAcceptance.getChoiceEventLikelihoods(c, "Accepted"); // clear session attribute of facet based scores. session().setAnalyticalScores(null); // return likelihood. return la; This sleight of hand will allow the Combined Likelihood Acceptance model to predict the likelihood of acceptance for the All Offers choice using these choice specific scores. After the prediction is made, we will clear the Analytical Scores session attribute to ensure it does not pollute any of the other (facet) models. To guarantee our combined likelihood model will learn based on the facet based scores—and is not distracted by the other session attributes—we will configure the model to exclude any other inputs, save for the instance of the Analytical Scores session attribute, on the model attributes tab. Recording Events In order for the combined likelihood model to learn correctly, we must ensure that the Analytical Scores session attribute is set correctly at the moment RTD records any events related to a particular choice. We apply essentially the same switching technique as before in a Record Combined Likelihood Event function. // set session attribute to contain facet based scores // (this is the only input for the combined model). session().setAnalyticalScores(choice.getAnalyticalScores); // record input event against All Offers choice. CombinedLikelihood.getChoice("AllOffers").recordEvent(event); // force learn at this moment using the Internal Dock entry point. Application.getPredictor().learn(InternalLearn.modelArray, session(), session(), Application.currentTimeMillis()); // clear session attribute of facet based scores. session().setAnalyticalScores(null); In this example, Internal Learn is a special informant configured as the learn location for the combined likelihood model. The informant itself has no particular configuration and does nothing in itself; it is used only to force the model to learn at the exact instant we have set the Analytical Scores session attribute to the correct values. Reporting Results After running a few thousand (artificially skewed) simulated sessions on our ILS, the Decision Center reporting shows some interesting results. In this case, these results reflect perfectly the bias we ourselves had introduced in our tests. In practice, we would obviously use a wider range of customer attributes and expect to see some more unexpected outcomes. The facetted model for categories has clearly picked up on the that fact our simulated youngsters have little interest in purchasing the one red-hot vehicle our ILS had on offer. Also, it would seem that customer age is an excellent predictor for the acceptance of pink products. Looking at the key drivers for the All Offers choice we can see the relative importance of the different facets to the prediction of overall likelihood. The comparative importance of the category facet for overall prediction might, in part, be explained by the clear preference of younger customers for toys over other product types; as evident from the report on the predictiveness of customer age for offer category acceptance. Conclusion Oracle Real-Time Decisions' flexible decisioning framework allows for the construction of exceptionally elaborate prediction models that facilitate powerful targeting, but nonetheless provide insightful reporting. Although few customers will have a direct need for such a sophisticated solution architecture, it is encouraging to see that this lies within the realm of the possible with RTD; and this with limited configuration and customization required. There are obviously numerous other ways in which the predictive and reporting capabilities of Oracle Real-Time Decisions can be expanded upon to tailor to individual customers needs. We will not be able to elaborate on them all on this blog; and finding the right approach for any given problem is often more difficult than implementing the solution. Nevertheless, we hope that these last few posts have given you enough of an understanding of the power of the RTD framework and its models; so that you can take some of these ideas and improve upon your own strategy. As always, if you have any questions about the above—or any Oracle Real-Time Decisions design challenges you might face—please do not hesitate to contact us; via the comments below, social media or directly at Oracle. We are completely multi-channel and would be more than glad to help. :-)

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• Friday Spotlight - October 25, 2013

  - by Chris Kawalek

  Happy Friday, everyone! Our spotlight this week is on a really cool technical tip on the Oracle Technology Network from Yuli Vasiliev called "How to Launch Linux Utilities from Oracle Database". From Yuli's introduction: "By wrapping a Linux utility in a script and using an external database table's preprocessor directive, you can launch the utility from within Oracle Database and have the utility's output be inserted into the external table. This allows you to do things such as query operating system data and then join it with data in Oracle Database." Head on over to OTN to read the full article. -Chris

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• PECL OCI8 2.0 Production Release Announcement

  - by cj

  The PHP OCI8 2.0.6 extension for Oracle Database is now "production" status. The source code is available on PECL. This can be used immediately to update your OCI8 extension in PHP 5.2 and later versions. The extension compiles with Oracle 10.2 or later client libraries. Oracle's standard cross-version database connectivity applies. OCI8 2.0 and PHP 5.5.5 RPMs for Oracle and Red Hat Linux are available from oss.oracle.com. Windows DLLs are available on PECL for PHP 5.3, PHP 5.4 and PHP 5.5. OCI8 2.0 source code will also be automatically included in the next major version of PHP. New Functionality Oracle Database 12c Implicit Result Set support. IRS's make it easy to pass query results back from stored PL/SQL procedures or anonymous PL/SQL blocks. Individual IRS statement resources, each corresponding to a single query, can be obtained with the new function oci_get_implicit_resultset(). These 'child' statement resources can be passed to any oci_fetch_* function. See Using PHP and Oracle Database 12c Implicit Result Sets and the PHP Manual: oci_get_implicit_resultset(). DTrace Dynamic Trace static probes. This well respected DTrace tracing framework is available on a number of platforms, including Oracle Linux. PHP OCI8 static user-space probes can be enabled with PHP's --enable-dtrace configuration option. See Using PHP DTrace on Oracle Linux. Documentation is also available in the PHP Manual OCI8 and DTrace Dynamic Tracing Improved Functionality Using oci_execute($s, OCI_NO_AUTO_COMMIT) for a SELECT no longer unnecessarily initiates an internal ROLLBACK during connection close. This can improve overall scalability by reducing "round trips" between PHP and the database. Changed Functionality PHP OCI8 2.0's minimum pre-requisites are now PHP 5.2 and Oracle client library 10.2. Later versions of both are usable and, in fact, recommended. Use the older PHP OCI8 1.4.10 extension when using PHP 4.3.9 through to PHP 5.1.x, or when only Oracle Database 9.2 client libraries are available. oci_set_*($connection, ...) meta data setting call error handling is fixed so that oci_error($connection) works for these calls. Note: The old, deprecated function aliases like ocilogon still exist but are not recommended for new applications. Phpinfo() Changes Some cosmetic changes were made to the output of php --ri oci8 and the phpinfo() function. The oci8.event and oci8.connection_class values are now shown only when the Oracle client libraries support the respective functionality. Connection statistics are now in a separate phpinfo() table. Temporary LOB and Collection support status lines in phpinfo() output were removed. These two features have always been enabled since 2007. Oci_internal_debug() Changes The oci_internal_debug() function is now a no-op. Use PHP's --enable-dtrace functionality with DTrace or SystemTap instead. References OCI8 Extension source code and Windows DLLs http://pecl.php.net/package/oci8 Oracle Linux RPMs oss.oracle.com PHP Manual for OCI8 OCI8 and DTrace Dynamic Tracing Oracle OpenWorld Conference paper What's New in Oracle Database 12c for PHP

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• EPM 11.1.2.2 Architecture: Financial Performance Management Applications

  - by Marc Schumacher

   Financial Management can be accessed either by a browser based client or by SmartView. Starting from release 11.1.2.2, the Financial Management Windows client does not longer access the Financial Management Consolidation server. All tasks that require an on line connection (e.g. load and extract tasks) can only be done using the web interface. Any client connection initiated by a browser or SmartView is send to the Oracle HTTP server (OHS) first. Based on the path given (e.g. hfmadf, hfmofficeprovider) in the URL, OHS makes a decision to forward this request either to the new Financial Management web application based on the Oracle Application Development Framework (ADF) or to the .NET based application serving SmartView retrievals running on Internet Information Server (IIS). Any requests send to the ADF web interface that need to be processed by the Financial Management application server are send to the IIS using HTTP protocol and will be forwarded further using DCOM to the Financial Management application server. SmartView requests, which are processes by IIS in first row, are forwarded to the Financial Management application server using DCOM as well. The Financial Management Application Server uses OLE DB database connections via native database clients to talk to the Financial Management database schema. Communication between the Financial Management DME Listener, which handles requests from EPMA, and the Financial Management application server is based on DCOM.  Unlike most other components Essbase Analytics Link (EAL) does not have an end user interface. The only user interface is a plug-in for the Essbase Administration Services console, which is used for administration purposes only. End users interact with a Transparent or Replicated Partition that is created in Essbase and populated with data by EAL. The Analytics Link Server deployed on WebLogic communicates through HTTP protocol with the Analytics Link Financial Management Connector that is deployed in IIS on the Financial Management web server. Analytics Link Server interacts with the Data Synchronisation server using the EAL API. The Data Synchronization server acts as a target of a Transparent or Replicated Partition in Essbase and uses a native database client to connect to the Financial Management database. Analytics Link Server uses JDBC to connect to relational repository databases and Essbase JAPI to connect to Essbase.  As most Oracle EPM System products, browser based clients and SmartView can be used to access Planning. The Java based Planning web application is deployed on WebLogic, which is configured behind an Oracle HTTP Server (OHS). Communication between Planning and the Planning RMI Registry Service is done using Java Remote Message Invocation (RMI). Planning uses JDBC to access relational repository databases and talks to Essbase using the CAPI. Be aware of the fact that beside the Planning System database a dedicated database schema is needed for each application that is set up within Planning.  As Planning, Profitability and Cost Management (HPCM) has a pretty simple architecture. Beside the browser based clients and SmartView, a web service consumer can be used as a client too. All clients access the Java based web application deployed on WebLogic through Oracle HHTP Server (OHS). Communication between Profitability and Cost Management and EPMA Web Server is done using HTTP protocol. JDBC is used to access the relational repository databases as well as data sources. Essbase JAPI is utilized to talk to Essbase.  For Strategic Finance, two clients exist, SmartView and a Windows client. While SmartView communicates through the web layer to the Strategic Finance Server, Strategic Finance Windows client makes a direct connection to the Strategic Finance Server using RPC calls. Connections from Strategic Finance Web as well as from Strategic Finance Web Services to the Strategic Finance Server are made using RPC calls too. The Strategic Finance Server uses its own file based data store. JDBC is used to connect to the EPM System Registry from web and application layer.  Disclosure Management has three kinds of clients. While the browser based client and SmartView interact with the Disclosure Management web application directly through Oracle HTTP Server (OHS), Taxonomy Designer does not connect to the Disclosure Management server. Communication to relational repository databases is done via JDBC, to connect to Essbase the Essbase JAPI is utilized.

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• EPM Architecture: Foundation

  - by Marc Schumacher

  This post is the first of a series that is going to describe the EPM System architecture per component. During the following weeks a couple of follow up posts will describe each component. If applicable, the component will have its standard port next to its name in brackets. EPM Foundation is Java based and consists of two web applications, Shared Services and Workspace. Both applications are accessed by browser through Oracle HTTP Server (OHS) or Internet Information Services (IIS). Communication to the backend database is done by JDBC. The file system to store Lifecycle Management (LCM) artifacts can be either local or remote (e.g. NFS, network share). For authentication purposes, the EPM Product Suite can connect to external directories or databases. Interaction with other EPM Suite components like product specific Lifecycle Management connectors or Reporting and Analysis Web happens through HTTP protocol. The next post will cover Reporting and Analysis.

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• Full Portfolio of x86 Systems On Display at Oracle OpenWorld

  - by kgee

  This OpenWorld, Oracle’s x86 hardware team will have two hardware demos, showcasing the new X3 systems, as well as several other x86 solutions such as the ZFS Storage Appliance, Oracle Database Appliance and the Carrier Grade NETRA systems. These two demos are located in the South Hall in Oracle’s booth 1133 and Intel’s booth 1101.  The Intel booth will feature additional demos including 3D demos of each server, a static architectural demo, the Oracle x86 Grand Prix video game and the Intel Theatre featuring several presentations by Intel’s partners. Oracle’s Intel Theatre Schedule and Topics Include:Monday 1. 10:30 a.m. - Engineered to Work Together: Oracle x86 Systems in the Data Center2. 12:30 a.m. - The Oracle NoSQL Database on the Intel Platform.3. 1:30 p.m. - Accelerate Your Path to Cloud with Oracle VM4. 3:30 p.m. - Why Oracle Linux is the Best Linux for Your Intel Based Systems5. 4:30 p.m. - Accelerate Your Path to Cloud with Oracle VMTuesday 1. 10:00 a.m. - Speed of thought” Analytics using In-Memory Analytics2. 1:30 a.m. - A Storage Architecture for Big Data:  "It’s Not JUST Hadoop"3. 2:00 a.m. - Oracle Optimized Solution for Enterprise Cloud Infrastructure.4. 2:30 p.m. - Configuring Storage to Optimize Database Performance and Efficiency.5. 3:30 p.m. - Total Cloud Control for Oracle's x86 SystemsWednesday 1. 10:00 a.m. - Big Data Analysis Using R-Programming Language2. 11:30 a.m. - Extreme Performance Overview, The Oracle Exadata Database Machine3. 1:30 p.m. - Oracle Times Ten In-Memory Database Overview

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• WebCenter Customer Spotlight: Fundação Petrobras de Seguridade Social

  - by me

  Author: Peter Reiser - Social Business Evangelist, Oracle WebCenter Solution Summary Fundação Petrobras de Seguridade Social (PetroS) is a Brazilian nonprofit organization pension fund serving 152 private companies with more then 145,000 plan participants and  managing a portfolio of  US$35.9 billion in equity. PetroS business objective was to implement a robust and flexible online solution to enable the foundation to successfully compete in the pension marketplace. PetroS implemented a robust, flexible and highly available database solution based on Oracle Database 11g, Enterprise Edition and modernized the company’s Web portal using Oracle WebCenter Suite.  The solution enables PetroS to make an average of 5,000 online loans per month to its 110,000 qualifying participants and supports 2,000 online consultations daily. Company ProfileFundação Petrobras de Seguridade Social (Petrobras Social Security Foundation)—better known as PetroS—is a pension fund founded in the 1970s to pay supplementary retirement benefits to Petrobras employees. Later, the foundation expanded its market to include 152 private companies, including Sanasa, Repsol YPF and Alesat. The Foundation, a nonprofit organization, has more than 145,000 plan participants, US$35.9 billion in equity, and a loan portfolio of US$730 million. Business ChallengesPetroS business objectives were to implement a robust and flexible solution to enable the foundation to successfully compete in the pension marketplace without affecting its monthly payments to 60,000 beneficiaries and to extend service delivery through the Web to better serve the fund’s more than 145,000 participants. Solution DeployedPetroS worked with Oracle Consulting to implement a robust, flexible and high available database solution based on Oracle Database 11g, Enterprise Edition and modernized the company’s Web portal using Oracle WebCenter Suite, enabling PetroS to deliver more flexible services to pension plan participants. Business ResultsThe solution enables PetroS to make an average of 5,000 online loans per month to its 110,000 qualifying participants and supports 2,000 online consultations daily. “The combination of Oracle Database 11g and Oracle WebCenter Suite has helped us deliver faster and better service for over 130,000 clients who participate in the 96 supplementary pension plans we currently offer. It has certainly helped to fuel our growth.” Newton Carneiro da Cunha, Diretor Administrativo, Fundação Petrobrás de Seguridade Social           Additional Information PetroS Customer Snapshot Oracle WebCenter Suite Oracle Database 11g, Enterprise Edition Oracle Real Application Clusters Oracle Diagnostics Pack Oracle Tuning Pack Oracle Consulting

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