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  • Support for 15,000 Partitions in SQL Server 2008 SP2 and SQL Server 2008 R2 SP1

    In SQL Server 2008 and SQL Server 2008 R2, the number of partitions on tables and indexes is limited to 1,000. This paper discusses how SQL Server 2008 SP2 and SQL Server 2008 R2 SP1 address this limitation by providing an option to increase the limit to 15,000 partitions. It describes how support for 15,000 partitions can be enabled and disabled on a database. It also talks about performance characteristics, certain limitations associated with this support, known issues, and their workarounds. This support is targeted to enterprise customers and ISVs with large-scale decision support or data warehouse requirements. The Future of SQL Server MonitoringMonitor wherever, whenever with Red Gate's SQL Monitor. See it live in action now.

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  • Oracle Magazine - OWB 11gR2 and Heterogeneous Databases

    - by David Allan
    There's a nice article titled 'Oracle Warehouse Builder 11g Release 2 and Heterogeneous Databases' from Oracle ACE director and cofounder of Rittman Mead Consulting, Mark Rittman in the May/June 2010 Oracle Magazine that covers the heterogeneous database support in OWB 11gR2: http://www.oracle.com/technology/oramag/oracle/10-may/o30bi.html Big thanks to Mark for this write up. There is an Oracle white paper on the support here and for examples of this extensibility you can go to the OWB blog archive where there are quite a few posts. I would recommend the following interesting posts out of the archive architecture overview, bulk file loading, MySQL open connectivity and MySQL bulk extract as interesting posts amongst others.

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  • Kscope 2014 Preview: Data Modeling and Moving Meditation with Kent Graziano

    - by OTN ArchBeat
    Those attending ODTUG's Kscope event in Seattle, June 22-26, will spend several days up to their eyeballs in technical sessions by more than 200 experts in a variety of specialties and Oracle technologies. Oracle ACE Director Kent Graziano is one of those experts, with a focus on business intelligence and data warehouse architecture. But in addition to the two data modeling sessions he'll present, Kent will for the fourth year in a row lead Kscope early risers in daily sessions in Chi Gung, Chinese martial art that Kent describes as "moving mediation." Want to learn more about Kent's Kscope 2014 data modeling sessions and how Chi Gung can help you get a great start on your day? Check out this video interview. Connect with Kent Gaziano Watch more interviews with Kscope 2014 session presenters.

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  • Adatintegrációs rendezvény HOUG tagoknak, DW/BI és Database szakosztály

    - by user645740
    2011. június 29-én szerdán lesz a HOUG szervezet Oracle adatintegrációs rendezvénye. Részvételi feltétel: HOUG tagság! Ha HOUG tag, akkor azért jöjjön, ha Oracle felhasználó és még nem HOUG tag, akkor lépjen be gyorsan a HOUG egyesületbe! Témák: adatintegráció, ELT-ETL, OWB, ODI, GoldenGate, RAC, Active Data Guard, stb. Az Oracle Warehouse Buildernek sok felhasználója van Magyarországon, és nem csupán az adattárházas-BI környezetekben. Az ELT területen Oracle Data Integratorra fókuszál az Oracle, ami heterogén környezetekben kiválóan muködik, azaz nem csak Oracle adatbázisokkal. Katt ide: HOUG szervezet Oracle adatintegrációs rendezvénye.

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  • Geek Deal: Refurbished Kindle Fire for $139; Today Only

    - by Jason Fitzpatrick
    If you’re looking to pick up a Kindle Fire on the cheap, Amazon is offering them–refurbished with a 1-year warranty–for $139. $139 is an even better price than we see on our local Craiglist (where Kindle Fires usually go for $180 or so) and it comes with a 1-year warranty. We’ve purchased several Kindle Keyboard units through Amazon’s refurbished warehouse deals over the last two years and, frankly, we can’t tell them apart from the brand new ones–if you’re looking to pick up a Kindle Fire this is a great deal. Kindle Fire for $139 How to Own Your Own Website (Even If You Can’t Build One) Pt 1 What’s the Difference Between Sleep and Hibernate in Windows? Screenshot Tour: XBMC 11 Eden Rocks Improved iOS Support, AirPlay, and Even a Custom XBMC OS

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  • First Foray&ndash;About timeout

    - by SQLMonger
    It has been quite a while since I signed up for this blog site and high time that something was posted.  I have a list of topics that I will be working through and posting.  Some I am sure will have been posted by others, but I will be sticking to the technical problems and challenges that I’ve recently faced, and the solutions that worked for me.  My motto when learning something new has always been “My kingdom for an example!”, and I plan on delivering useful examples here so others can learn from my efforts, failures and successes.   A bit of background about me… My name is Clayton Groom. I am a founding partner of a consulting firm in St. Louis Missouri, Covenant Technology Partners, LLC and focus on SQL Server Data Warehouse design, Analysis Services and Enterprise Reporting solutions.  I have been working with SQL Server since the early nineties, when it still only ran on OS/2. I love solving puzzles and technical challenges.   Enough about me… On to a real problem… SSIS Connection Time outs versus Command Time outs Last week, I was working on automating the processing for a large Analysis Services cube.  I had reworked an SSIS package and script task originally posted by Vidas Matelis that automates the process of adding new and dropping old partitions to/from an Analysis Services cube.  I had the package working great, tested, and ready for deployment.  It basically performs a query against the source system to determine if there is new data in the warehouse that will require a new partition to be added to the cube, and it checks the cube to see if there are any partitions that are present that are no longer needed in a rolling 60 month window. My client uses Tivoli for running all their production jobs, and not SQL Agent, so I had to build a command line file for Tivoli to use to run the package. Everything was going great. I had tested the command file from my development workstation using an XML configuration file to pass in server-specific parameters into the package when executed using the DTExec utility. With all the pieces ready, I updated the dtsconfig file to point to the UAT environment and started working with the Tivoli developer to test the job.  On the first run, the job failed, and from what I could see in the SSIS log, it had failed because of a timeout. Other errors in the log made me think that perhaps the connection string had not been passed into the package correctly. We bumped the Connection Manager  timeout values from 20 seconds to 120 seconds and tried again. The job still failed. After changing the command line to use the /SET option instead of the /CONFIGFILE option, we tested again, and again failure. After a number more failed attempts, and getting the Teradata DBA involved to monitor and see if we were connecting and failing or just failing to connect, we determined that the job was indeed connecting to the server and then disconnecting itself after 30 seconds.  This seemed odd, as we had the timeout values for the connection manager set to 180 seconds by then.  At this point one of the DBA’s found a post on the Teradata forum that had the clues to the puzzle: There is a separate “CommandTimeout” custom property on the Data source object that may needed to be adjusted for longer running queries.  I opened up the SSIS package, opened the data flow task that generated the partition list table and right-clicked on the data source. from the context menu, I selected “Show Advanced Editor” and found the property. Sure enough, it was set to 30 seconds. The CommandTimeout property can also be edited in the SSIS Properties sheet. In order to determine how long the timeout needed to be, I ran the query from the task in the development environment and received a response in a matter of seconds.  I then tried the same query against the production database and waited several minutes for a response. This did not seem to be a reasonable response time for the query involved, and indeed it wasn’t. The Teradata DBA’s adjusted the query governor settings for the service account I was testing with, and we were able to get the response back down under a minute.  Still, I set the CommandTimeout property to a much higher value in case the job was ever started during a time of high-demand on the production server. With this change in place, the job finally completed successfully.  The lesson learned for me was two-fold: Always compare query execution times between development and production environments, and don’t assume that production will always be faster.  With higher user demands, query governors, and a whole lot more data, the execution time of even what might seem to be simple queries can vary greatly. SSIS Connection time out settings do not affect command time outs.  Connection timeouts control how long the package will wait for a response from the server before assuming the server is not available or is not responding. Command time outs control how long a task will wait for results to start being returned before deciding that the server is not responding. Both lessons seem pretty straight forward, and I felt pretty sheepish once I finally figured out what the issue was.  To be fair though, In the 5+ years that I have been working with SSIS, I could only recall one other time where I had to set the CommandTimeout property, and that memory only resurfaced while I was penning this post.

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  • Aktuell: Oracle Enterprise Manager 12c Release 4 ist da

    - by Ralf Durben (DBA Community)
    Ein neues Release für Oracle Enterprise Manager Cloud Control ist verfügbar. Es ist das Release 4, oder genauer die Version 12.1.0.4. Der Download steht für alle unterstützten Plattformen seit dem 03.06.2014 auf OTN zur Verfügung.Natürlich gibt es viele Neuerungen, daher können hier nur wenige aufgezählt werden: - Als Repository Datenbank wird jetzt auch die Datenbankversion 12c (als Non-CDB) unterstützt - Das Sicherheitsmodell für zusammengefasste Zieltypen (z.B. Gruppen) wurde geändert. Jetzt kann man Rechte auf die Member einer Grupper vergeben, ohne dass das gleiche Recht auf die Gruppe selbst vergeben werden müsste - Default Preferred Credentials stellen sicher, dass neue EM Benutzer auch ohne weitere Konfiguration arbeiten können - Der Bereich Cloud Management, also der Betrieb einer eigenen Cloud wurde stark weiterentwickelt. - Im Datenbankbereich können die AWR Daten der einzelnen Zieldatenbanken jetzt in ein zentrales AWR Warehouse übertragen und somit besser für längere Zeit gespeichert werden. Details zum neuen Release werden in Kürze hier in dieser Community besprochen.

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  • Hints to properly design UML class diagram

    - by mic4ael
    Here is the problem. I have just started learning UML and that is why I would like to ask for a few cues from experienced users how I could improve my diagram because I do know it lacks a lot of details, it has mistakes for sure etc. Renovation company hires workers. Each employee has some kind of profession, which is required to work on a particular position. Workers work in groups consisting of at most 15 members - so called production units, which specializes in a specified kind of work. Each production unit is managed by a foreman. Every worker in order to be able to perform job tasks needs proper accessories. There are two kind of tools - light and heavy. To use heavy tools, a worker must have proper privileges. A worker can have at most 3 light tools taken from the warehouse.

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  • Taking the Mystique out of the Remote Diagnostics Agent (RDA)

    - by Robert Schweighardt
    Ever wondered why you were asked for the RDA? When you open an SR with support you may be asked to upload the RDA.   We realize that this might take you some time, however the RDA contains a lot of diagnostic information about your environment which may help us resolve the SR faster. The following document goes through all the key stages involved in collating the RDA :- Get Proactive with Fusion Middleware : Resolve SRs Faster! Use Remote Diagnostic Agent [ID 1498376.1]  Click on the Tabs within the document to have all your questions answered. Further Information for specific Data Integration Products can be found in the following Notes:- How To Run RDA for Oracle Data Integrator 11g (Note 1457914.1)  Using OCM (Oracle Configuration Manager) and RDA (Remote Diagnostic Agent) For Troubleshooting ODI (Note 1398483.1)  How To Run RDA for Oracle Warehouse Builder [ID 1098485.1] Always ensure you have the latest RDA this can be downloaded from:- Remote Diagnostic Agent (RDA) 4 - Getting Started [ID 314422.1] 

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  • New Exadata public references

    - by Javier Puerta
    The following customers are now public references for Exadata. Show your customers how other companies in their industries are leveraging Exadata to achieve their business objectives. MIGROS BANK - Financial Services - Switzerland Oracle EXADATA Database Machine + OBIEE 11gMigros Bank AG Makes Systems More Available and Improves Operational Insight and Analytics with a Scalable, Integrated Data Warehouse Success Story (English)Success Story(German) - Professional Services - United Arab Emirates Oracle EXADATA Database MachineTech Access Drives Compelling Proof-of-Concept Evaluations for Hardware Sales in Regions Largest Solutions CenterSuccess Story   - Saudi Arabia - Wholesale Distribution Oracle EXADATA Database Machine + OBIEE 11g Balubaid Group of Companies Reduces Help-Desk Complaints by 75%, Improves Business Continuity and System Response Success Story   - Nigeria - Communications Oracle EXADATA Database Machine Etisalat Accelerates Data Retrieval and Analysis by 99 Percent with Oracle Communications Data Model Running on Oracle Exadata Database Machine Oracle Press Release   ETISALAT BALUBAID GROUP TECH ACCESS

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  • SAP ouvre sa plateforme In Memory aux Startups et organise une série d'événements pour construire un écosystème autour d'HANA

    SAP ouvre sa plateforme In Memory aux Startups et organise une série d'événements pour construire un écosystème fiable autour d'HANA SAP organise une série d'événements pour aider les développeurs et startups qui utilisent la plateforme In Memory HANA à tirer parti de celle-ci. SAP HANA (High-Performance Analytic Appliance) permet de produire des environnements de Data Warehouse dopés, qui fournissent des données clients en temps réel. Elle permet également d'animer un réseau en ligne et offre une plateforme ouverte aux développeurs. La société souhaite qu'un écosystème fiable soit construit autour de sa plateforme grâce à son programme de soutien aux startups du monde en...

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  • Recomendation for Webshop with API

    - by m.sr
    I'm searching for a webshop. The problem with my search is, that the webshop-software of my choice needs to have a useabel API or some interface for external applications. E.g. i need to place orders by an external application or need to get product descriptions or warehouse stock from the external application. I somehow would like to have a webshop wehere the webinterface is just one way to interact with the whole system. There are some other requirments, which have to be fullfilled, but i guess they are kind of common: running on linux MySQL (we already have MySQL-replication and backup in place) i like open source but i'm willing to pay for it, if it's worth it I found some webshops on the net - but perhaps you can tell me, if theres any hope for a webshop with a good API before i go and test all of them, on the first look i didn't find any docs about any interface to external applications for any of my search results. Thank you!

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  • Introducing Next-Generation Enterprise Auditing and Database Firewall Platform Webcast, 12/12/12

    - by Troy Kitch
    Join us, December 12 at 10am PT/1pm ET, to hear about a new Oracle product that monitors Oracle and non-Oracle database traffic, detects unauthorized activity including SQL injection attacks, and blocks internal and external threats from reaching the database. In addition, this new product collects and consolidates audit data from databases, operating systems, directories, and any custom template-defined source into a centralized, secure warehouse. This new enterprise security monitoring and auditing platform allows organizations to quickly detect and respond to threats with powerful real-time policy analysis, alerting and reporting capabilities. Based on proven SQL grammar analysis that ensures accuracy, performance, and scalability, organizations can deploy with confidence in any mode. You will also hear how organizations such as TransUnion Interactive and SquareTwo Financial rely on Oracle today to monitor and secure their Oracle and non-Oracle database environments. Register for the webcast here.

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  • Partner case - ISE (Germany) - IDS brings light into Investment Controlling with Exadata

    - by Javier Puerta
    (Original post in German: IDS bringt mit Exadata Licht ins Investmentcontrolling) "The amount of data that IDS GmbH (Analysis and Reporting Services) has to cope with daily, is enormous: at the subsidiary of Allianz SE all the services are around Investment Controlling.The company needed an extensible data warehouse solution in which all the data could be merged together, harmonized and enriched. Finally IDS decided for Exadata to be as optimal solution, specifically the Oracle Exadata Database Machine. The implementation was carried out jointly with the Oracle Platinum Partner ISE, who took over the technical and advisory support part and will be IDS´ preffered consultant in any further Exadata development. See how Exadata is used and why this investment has paid off for IDS, by watching watching the following video (in German)"

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  • Fixing Gatekeeper Row Cardinality Estimate Issues

    The Query Optimiser needs a good estimate of the number of rows likely to be returned by each physical operator in order to select the best query plan from the most likely alternatives. Sometimes these estimates can go so wildly wrong as to result in a very slow query. Joe Sack shows how it can happen with SQL Queries on a data warehouse with a star schema. Make working with SQL a breezeSQL Prompt 5.3 is the effortless way to write, edit, and explore SQL. It's packed with features such as code completion, script summaries, and SQL reformatting, that make working with SQL a breeze. Try it now.

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  • The Advancement of Technology That Lead to Websites Being One of the Most Important Business Assets

    Twenty years ago the world was a very different place. Most companies were still using paper based filing systems and people saw computers as being complicated and expensive. Businesses had storage rooms and large filing cabinets full of alphabetically and chronologically ordered documents and letters. Due to the efforts of large corporations, technology has advanced in a way that most people would have never imagined. What would have taken up a full warehouse worth of space can now be stored digitally in a device that is smaller than a book and it can be searched through in a matter of seconds.

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  • Exception opening TAdoDataset: Arguments are of the wrong type, are out of acceptable range, or are

    - by Dave Falkner
    I've been trying to debug the following problem for several weeks now - this method is called from several places within the same datamodule, but this exception (from the subject line of this post) only occurs when integers for a certain purpose (pickup orders vs. orders that we ship through a carrier) are used - and don't ask me how the application can tell the difference between one integer's purpose and another! Furthermore, I cannot duplicate this issue on my machine - the error occurs on a warehouse machine but not my own development machine, even when working with the same production database. I have suspected an MDAC version conflict between the two machines, but have run a version checker and confirmed that both machines are running 2.8, and additionally have confirmed this by logging the TAdoDataset's .Version property at runtime. function TdmESShip.SecondaryID(const PrimaryID : Integer ): String; begin try with qESPackage2 do begin if Active then Close; LogMessage('-----------------------------------'); LogMessage('Version: ' + FConnection.Version); LogMessage('DB Info: ' + FConnection.Properties['Initial Catalog'].Value + ' ' + FConnection.Properties['Data Source'].Value); LogMessage('Setting the parameter.'); Parameters.ParamByName('ParameterName').Value := PrimaryID; LogMessage('Done setting the parameter.'); Open; Ninety-nine times out of 100 this logging code logs a successful operation as follows: Version: 2.8 DB Info: (database name and instance) Setting the parameter. Done setting the parameter. Opened the dataset. But then whenever a "pickup" order is processed, this exception gets thrown whenever the dataset is opened: Version: 2.8 DB Info: (database name and instance) Setting the parameter. Done setting the parameter. GetESPackageID() threw an exception. Type: EOleException, Message: Arguments are of the wrong type, are out of acceptable range, or are in conflict with one another Error: Arguments are of the wrong type, are out of acceptable range, or are in conflict with one another for packageID 10813711 I've tried eliminating the parameter and have built the commandtext for this dataset programmatically, suspecting that some part of the TParameter's configuration might be out of whack, but the same error occurs under the same circumstances. I've tried every combination of TParameter properties that I can think of - this is the millionth TParameter I've created for my millionth dataset, and I've never encountered this error. I've even created a second dataset from scratch and removed all references to the original dataset in case some property of the original dataset in the .dfm might be corrupted, but the same error occurs under the same circumstances. The commandtext for this dataset is a simple select ValueA from TableName where ValueB = @ParameterB I'm about ready to do something extreme, such as writing a web service to look these values up - it feels right now as though I could destroy my machine, rebuild it, rewrite this entire application from scratch, and the application would still know to throw an exception whenever I try to look up a secondary value from a primary value, but only for pickup orders, and only from the one machine in the warehouse, but I'm probably missing something simple. So, any help anyone could provide would be greatly appreciated.

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  • IsAuthenticated is false! weird behaviour + review question

    - by Naor
    This is the login function (after I validate user name and password, I load user data into "user" variable and call Login function: public static void Login(IUser user) { HttpResponse Response = HttpContext.Current.Response; HttpRequest Request = HttpContext.Current.Request; FormsAuthenticationTicket ticket = new FormsAuthenticationTicket(1, user.UserId.ToString(), DateTime.Now, DateTime.Now.AddHours(12), false, UserResolver.Serialize(user)); HttpCookie cookie = new HttpCookie(FormsAuthentication.FormsCookieName, FormsAuthentication.Encrypt(ticket)); cookie.Path = FormsAuthentication.FormsCookiePath; Response.Cookies.Add(cookie); string redirectUrl = user.HomePage; Response.Redirect(redirectUrl, true); } UserResolver is the following class: public class UserResolver { public static IUser Current { get { IUser user = null; if (HttpContext.Current.User.Identity.IsAuthenticated) { FormsIdentity id = (FormsIdentity)HttpContext.Current.User.Identity; FormsAuthenticationTicket ticket = id.Ticket; user = Desrialize(ticket.UserData); } return user; } } public static string Serialize(IUser user) { StringBuilder data = new StringBuilder(); StringWriter w = new StringWriter(data); string type = user.GetType().ToString(); //w.Write(type.Length); w.WriteLine(user.GetType().ToString()); StringBuilder userData = new StringBuilder(); XmlSerializer serializer = new XmlSerializer(user.GetType()); serializer.Serialize(new StringWriter(userData), user); w.Write(userData.ToString()); w.Close(); return data.ToString(); } public static IUser Desrialize(string data) { StringReader r = new StringReader(data); string typeStr = r.ReadLine(); Type type=Type.GetType(typeStr); string userData = r.ReadToEnd(); XmlSerializer serializer = new XmlSerializer(type); return (IUser)serializer.Deserialize(new StringReader(userData)); } } And the global.asax implements the following: void Application_PostAuthenticateRequest(Object sender, EventArgs e) { IPrincipal p = HttpContext.Current.User; if (p.Identity.IsAuthenticated) { IUser user = UserResolver.Current; Role[] roles = user.GetUserRoles(); HttpContext.Current.User = Thread.CurrentPrincipal = new GenericPrincipal(p.Identity, Role.ToString(roles)); } } First question: Am I do it right? Second question - weird thing! The user variable I pass to Login has 4 members: UserName, Password, Name, Id. When UserResolver.Current executed, I got the user instance. I descided to change the user structure - I add an array of Warehouse object. Since that time, when UserResolver.Current executed (after Login), HttpContext.Current.User.Identity.IsAuthenticated was false and I couldn't get the user data. When I removed the Warehouse[] from user structure, it starts to be ok again and HttpContext.Current.User.Identity.IsAuthenticated become true after I Login. What is the reason to this weird behaviour?

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  • Avoid writing SQL queries altogether in SSIS

    - by Jonn
    Working on a Data Warehouse project, the guy that gave us the tutorial advised that we stick to using SQL queries over defining a lot of data flow transformations, citing points like it'll consume a lot of memory on the ETL box so we'd rather leave the processing to the DB box. Is this really advisable? Where's the balance between relying on GUI tools over executing a bunch of SQL scripts on your Integration package? And honestly, I'd like to avoid writing SQL queries as much as I can.

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  • Can I add a delay to sql server transactional replication ?

    - by Brann
    I've got transactional replication configured from a database called DBProd to another database called DBWarehouse ; everything works fine, and transaction are usually replicated instantaneously to the warehouse .... which is my problem. I'd like to add a slight delay to the replication (something like 10 minutes), so that the replicated database can be used to access a previous version of the database (in case a bug occurs for example) Is there a simple way to achieve this ?

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  • Start a Mapping or Process Flow from OWB Browser

    - by Dong Ruirong
    Basically, we start a Mapping or Process Flow from Oracle Warehouse Builder (OWB) Design Client. But actually we can also start a Mapping or Process Flow from OWB Browser. This paper will introduce the Start Report first and then introduce how to start/rerun a Mapping or Process Flow from OWB Browser. Start Report Start Report is used to start an execution of a Mapping or Process Flow. So there are two kinds of Start Report: Mapping Start Report (See Figure 1) and Process Flow Start Report (See Figure 2). Start Report shows the Mapping or Process Flow identification properties, including latest deployment and latest execution, lists all execution parameters for the Mapping or Process Flow, which were specified by the latest deployment, and assigns parameter default values from the latest deployment specification. You can do a couple of things from Start Report: Sort execution parameters on name, category. Table 1 lists all parameters of a Mapping. Table 2 lists all parameters of a Process Flow. Change values of any input parameter where permitted. For some parameters, selection lists are provided. For example, Mapping’s parameter Audit Level has a selection list. Reset all parameter settings to their default values. Apply basic validation to parameter values before starting an execution. Start the Mapping or Process Flow, which means it is executed immediately. Navigate to Deployment Report for latest deployment details of the Mapping or Process Flow. Navigate to Execution Job Report for latest execution of current Mapping or Process Flow Link to on-link help Warehouse Report Page, Deployment Report, Execution Report, Execution Schedule Report and Execution Summary Report. Figure 1 Mapping Start Report Table 1 Execution Parameters and default values for a Mapping Category Name Mode Input Value System Audit Level In Error Details System Bulk Size In 1000 System Commit Frequency In 1000 System EXECUTE_RESUME_TASK In FALSE System FORCE_RESUME_OPTION In FALSE System Max No of Errors In 50 System NUMBER_OF_TIMES_TO_RETRY In 2 System Operating Mode In Set Based Fail Over to Row Based System PARALLEL_LEVEL In 0 System Procedure Name In main System Purge Group In WB Figure 2 Process Flow Start Report Table 2 Execution Parameters and default values for a Process Flow Category Name Mode Input Value System EVAL_LOCATION In   System Item Key In-Out   System Item Type In PFPKG_1 Start a Mapping or Process Flow To navigate to Start Report, it’s better to login OWB Browser with Control Center option; if not, after logging in OWB Browser, go to Control Center first. Then you can follow the ways introduced in this section to navigate to Start Report. One more thing you need to pay attention to is that you are not allowed to deploy any Mappings and Process Flows from OWB Browser as it’s not supported. So it’s necessary to deploy the Mappings and Process Flows first before starting them from OWB Browser. If you have deployed a Mapping or Process Flow but have not started it, please navigate from Object Summary Report or Deployment Schedule Report to Start Report. 1. Navigating from Object Summary Report to Start Report Open the Object Summary Report to see all deployed Mappings and Process Flows. Click the Mapping Name or Process Flow Name link to see its Deployment Report. Select the Start link in the Available Reports tab for the given Mapping or Process Flow to display a Start Report for the Mapping or Process Flow. The execution parameters have the default deployment-time settings. Change any of the input parameter values as required. Click Start Execution button to execute the Mapping or Process Flow. 2. Navigating from Deployment Schedule Report to Start Report Open the Deployment Schedule Report to see deployment details of Mapping and Process Flow. Expand the project trees to find the deployed Mappings and Process Flows. Click the Mapping Name or Process Flow Name link to see its Deployment Report. Select the Start link in the Available Reports tab for the given Mapping or Process Flow to display a Start Report for the Mapping or Process Flow. The execution parameters have the default deployment-time settings. Change any of the input parameter values as required. Click Start Execution button to execute the Mapping or Process Flow. Re-run a Mapping or Process Flow If you have executed a Mapping or Process Flow, you can navigate from Object Summary Report, Deployment Schedule Report, Execution Summary Report or Execution Schedule Report to Start Report. 1. Navigating from the Execution Summary Report to Start Report Open the Execution Summary Report to see all execution jobs including Mapping jobs and Process Flow jobs. Click on the Mapping Name or Process Flow Name to see its Execution Report. Select the Start link in the Available Reports tab for the given Mapping or Process Flow to display a Start Report for the Mapping or Process Flow. The execution parameters have the default deployment-time settings. Change any of the input parameter values as required. Click Start Execution button to execute the Mapping or Process Flow. 2. Navigating from the Execution Schedule Report to Start Report Open the Execution Schedule Report to see list of all executions of Mapping and Process Flow. Click on the Mapping Name or Process Flow Name to see its Execution Report. Select the Start link in the Available Reports tab for the given Mapping or Process Flow to display a Start Report for the Mapping or Process Flow. The execution parameters have the default deployment-time settings. Change any of the input parameter values as required. Click Start Execution button to execute the Mapping or Process Flow. If the execution of a Mapping or Process Flow is successful, you will see this message from the Start Report: Start Execution request successful. (See Figure 3) Figure 3 Execution Result You can also confirm the execution of the Mapping or Process Flow by referring to Execution Report of the current Mapping or Process Flow by clicking the link in the Available Reports tab for the given Mapping or Process Flow. One new record of execution job details is added to Execution Report of the Mapping or Process Flow which shows the details of the execution such as Start Time, Elapsed Time, Status, the number of records selected, inserted, updated, deleted etc.

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  • Big Data&rsquo;s Killer App&hellip;

    - by jean-pierre.dijcks
    Recently Keith spent  some time talking about the cloud on this blog and I will spare you my thoughts on the whole thing. What I do want to write down is something about the Big Data movement and what I think is the killer app for Big Data... Where is this coming from, ok, I confess... I spent 3 days in cloud land at the Cloud Connect conference in Santa Clara and it was quite a lot of fun. One of the nice things at Cloud Connect was that there was a track dedicated to Big Data, which prompted me to some extend to write this post. What is Big Data anyways? The most valuable point made in the Big Data track was that Big Data in itself is not very cool. Doing something with Big Data is what makes all of this cool and interesting to a business user! The other good insight I got was that a lot of people think Big Data means a single gigantic monolithic system holding gazillions of bytes or documents or log files. Well turns out that most people in the Big Data track are talking about a lot of collections of smaller data sets. So rather than thinking "big = monolithic" you should be thinking "big = many data sets". This is more than just theoretical, it is actually relevant when thinking about big data and how to process it. It is important because it means that the platform that stores data will most likely consist out of multiple solutions. You may be storing logs on something like HDFS, you may store your customer information in Oracle and you may store distilled clickstream information in some distilled form in MySQL. The big question you will need to solve is not what lives where, but how to get it all together and get some value out of all that data. NoSQL and MapReduce Nope, sorry, this is not the killer app... and no I'm not saying this because my business card says Oracle and I'm therefore biased. I think language is important, but as with storage I think pragmatic is better. In other words, some questions can be answered with SQL very efficiently, others can be answered with PERL or TCL others with MR. History should teach us that anyone trying to solve a problem will use any and all tools around. For example, most data warehouses (Big Data 1.0?) get a lot of data in flat files. Everyone then runs a bunch of shell scripts to massage or verify those files and then shoves those files into the database. We've even built shell script support into external tables to allow for this. I think the Big Data projects will do the same. Some people will use MapReduce, although I would argue that things like Cascading are more interesting, some people will use Java. Some data is stored on HDFS making Cascading the way to go, some data is stored in Oracle and SQL does do a good job there. As with storage and with history, be pragmatic and use what fits and neither NoSQL nor MR will be the one and only. Also, a language, while important, does in itself not deliver business value. So while cool it is not a killer app... Vertical Behavioral Analytics This is the killer app! And you are now thinking: "what does that mean?" Let's decompose that heading. First of all, analytics. I would think you had guessed by now that this is really what I'm after, and of course you are right. But not just analytics, which has a very large scope and means many things to many people. I'm not just after Business Intelligence (analytics 1.0?) or data mining (analytics 2.0?) but I'm after something more interesting that you can only do after collecting large volumes of specific data. That all important data is about behavior. What do my customers do? More importantly why do they behave like that? If you can figure that out, you can tailor web sites, stores, products etc. to that behavior and figure out how to be successful. Today's behavior that is somewhat easily tracked is web site clicks, search patterns and all of those things that a web site or web server tracks. that is where the Big Data lives and where these patters are now emerging. Other examples however are emerging, and one of the examples used at the conference was about prediction churn for a telco based on the social network its members are a part of. That social network is not about LinkedIn or Facebook, but about who calls whom. I call you a lot, you switch provider, and I might/will switch too. And that just naturally brings me to the next word, vertical. Vertical in this context means per industry, e.g. communications or retail or government or any other vertical. The reason for being more specific than just behavioral analytics is that each industry has its own data sources, has its own quirky logic and has its own demands and priorities. Of course, the methods and some of the software will be common and some will have both retail and service industry analytics in place (your corner coffee store for example). But the gist of it all is that analytics that can predict customer behavior for a specific focused group of people in a specific industry is what makes Big Data interesting. Building a Vertical Behavioral Analysis System Well, that is going to be interesting. I have not seen much going on in that space and if I had to have some criticism on the cloud connect conference it would be the lack of concrete user cases on big data. The telco example, while a step into the vertical behavioral part is not really on big data. It used a sample of data from the customers' data warehouse. One thing I do think, and this is where I think parts of the NoSQL stuff come from, is that we will be doing this analysis where the data is. Over the past 10 years we at Oracle have called this in-database analytics. I guess we were (too) early? Now the entire market is going there including companies like SAS. In-place btw does not mean "no data movement at all", what it means that you will do this on data's permanent home. For SAS that is kind of the current problem. Most of the inputs live in a data warehouse. So why move it into SAS and back? That all worked with 1 TB data warehouses, but when we are looking at 100TB to 500 TB of distilled data... Comments? As it is still early days with these systems, I'm very interested in seeing reactions and thoughts to some of these thoughts...

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  • SPARC T4-4 Beats 8-CPU IBM POWER7 on TPC-H @3000GB Benchmark

    - by Brian
    Oracle's SPARC T4-4 server delivered a world record TPC-H @3000GB benchmark result for systems with four processors. This result beats eight processor results from IBM (POWER7) and HP (x86). The SPARC T4-4 server also delivered better performance per core than these eight processor systems from IBM and HP. Comparisons below are based upon system to system comparisons, highlighting Oracle's complete software and hardware solution. This database world record result used Oracle's Sun Storage 2540-M2 arrays (rotating disk) connected to a SPARC T4-4 server running Oracle Solaris 11 and Oracle Database 11g Release 2 demonstrating the power of Oracle's integrated hardware and software solution. The SPARC T4-4 server based configuration achieved a TPC-H scale factor 3000 world record for four processor systems of 205,792 QphH@3000GB with price/performance of $4.10/QphH@3000GB. The SPARC T4-4 server with four SPARC T4 processors (total of 32 cores) is 7% faster than the IBM Power 780 server with eight POWER7 processors (total of 32 cores) on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 36% better in price performance compared to the IBM Power 780 server on the TPC-H @3000GB Benchmark. The SPARC T4-4 server is 29% faster than the IBM Power 780 for data loading. The SPARC T4-4 server is up to 3.4 times faster than the IBM Power 780 server for the Refresh Function. The SPARC T4-4 server with four SPARC T4 processors is 27% faster than the HP ProLiant DL980 G7 server with eight x86 processors on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 52% faster than the HP ProLiant DL980 G7 server for data loading. The SPARC T4-4 server is up to 3.2 times faster than the HP ProLiant DL980 G7 for the Refresh Function. The SPARC T4-4 server achieved a peak IO rate from the Oracle database of 17 GB/sec. This rate was independent of the storage used, as demonstrated by the TPC-H @3000TB benchmark which used twelve Sun Storage 2540-M2 arrays (rotating disk) and the TPC-H @1000TB benchmark which used four Sun Storage F5100 Flash Array devices (flash storage). [*] The SPARC T4-4 server showed linear scaling from TPC-H @1000GB to TPC-H @3000GB. This demonstrates that the SPARC T4-4 server can handle the increasingly larger databases required of DSS systems. [*] The SPARC T4-4 server benchmark results demonstrate a complete solution of building Decision Support Systems including data loading, business questions and refreshing data. Each phase usually has a time constraint and the SPARC T4-4 server shows superior performance during each phase. [*] The TPC believes that comparisons of results published with different scale factors are misleading and discourages such comparisons. Performance Landscape The table lists the leading TPC-H @3000GB results for non-clustered systems. TPC-H @3000GB, Non-Clustered Systems System Processor P/C/T – Memory Composite(QphH) $/perf($/QphH) Power(QppH) Throughput(QthH) Database Available SPARC Enterprise M9000 3.0 GHz SPARC64 VII+ 64/256/256 – 1024 GB 386,478.3 $18.19 316,835.8 471,428.6 Oracle 11g R2 09/22/11 SPARC T4-4 3.0 GHz SPARC T4 4/32/256 – 1024 GB 205,792.0 $4.10 190,325.1 222,515.9 Oracle 11g R2 05/31/12 SPARC Enterprise M9000 2.88 GHz SPARC64 VII 32/128/256 – 512 GB 198,907.5 $15.27 182,350.7 216,967.7 Oracle 11g R2 12/09/10 IBM Power 780 4.1 GHz POWER7 8/32/128 – 1024 GB 192,001.1 $6.37 210,368.4 175,237.4 Sybase 15.4 11/30/11 HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 8/64/128 – 512 GB 162,601.7 $2.68 185,297.7 142,685.6 SQL Server 2008 10/13/10 P/C/T = Processors, Cores, Threads QphH = the Composite Metric (bigger is better) $/QphH = the Price/Performance metric in USD (smaller is better) QppH = the Power Numerical Quantity QthH = the Throughput Numerical Quantity The following table lists data load times and refresh function times during the power run. TPC-H @3000GB, Non-Clustered Systems Database Load & Database Refresh System Processor Data Loading(h:m:s) T4Advan RF1(sec) T4Advan RF2(sec) T4Advan SPARC T4-4 3.0 GHz SPARC T4 04:08:29 1.0x 67.1 1.0x 39.5 1.0x IBM Power 780 4.1 GHz POWER7 05:51:50 1.5x 147.3 2.2x 133.2 3.4x HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 08:35:17 2.1x 173.0 2.6x 126.3 3.2x Data Loading = database load time RF1 = power test first refresh transaction RF2 = power test second refresh transaction T4 Advan = the ratio of time to T4 time Complete benchmark results found at the TPC benchmark website http://www.tpc.org. Configuration Summary and Results Hardware Configuration: SPARC T4-4 server 4 x SPARC T4 3.0 GHz processors (total of 32 cores, 128 threads) 1024 GB memory 8 x internal SAS (8 x 300 GB) disk drives External Storage: 12 x Sun Storage 2540-M2 array storage, each with 12 x 15K RPM 300 GB drives, 2 controllers, 2 GB cache Software Configuration: Oracle Solaris 11 11/11 Oracle Database 11g Release 2 Enterprise Edition Audited Results: Database Size: 3000 GB (Scale Factor 3000) TPC-H Composite: 205,792.0 QphH@3000GB Price/performance: $4.10/QphH@3000GB Available: 05/31/2012 Total 3 year Cost: $843,656 TPC-H Power: 190,325.1 TPC-H Throughput: 222,515.9 Database Load Time: 4:08:29 Benchmark Description The TPC-H benchmark is a performance benchmark established by the Transaction Processing Council (TPC) to demonstrate Data Warehousing/Decision Support Systems (DSS). TPC-H measurements are produced for customers to evaluate the performance of various DSS systems. These queries and updates are executed against a standard database under controlled conditions. Performance projections and comparisons between different TPC-H Database sizes (100GB, 300GB, 1000GB, 3000GB, 10000GB, 30000GB and 100000GB) are not allowed by the TPC. TPC-H is a data warehousing-oriented, non-industry-specific benchmark that consists of a large number of complex queries typical of decision support applications. It also includes some insert and delete activity that is intended to simulate loading and purging data from a warehouse. TPC-H measures the combined performance of a particular database manager on a specific computer system. The main performance metric reported by TPC-H is called the TPC-H Composite Query-per-Hour Performance Metric (QphH@SF, where SF is the number of GB of raw data, referred to as the scale factor). QphH@SF is intended to summarize the ability of the system to process queries in both single and multiple user modes. The benchmark requires reporting of price/performance, which is the ratio of the total HW/SW cost plus 3 years maintenance to the QphH. A secondary metric is the storage efficiency, which is the ratio of total configured disk space in GB to the scale factor. Key Points and Best Practices Twelve Sun Storage 2540-M2 arrays were used for the benchmark. Each Sun Storage 2540-M2 array contains 12 15K RPM drives and is connected to a single dual port 8Gb FC HBA using 2 ports. Each Sun Storage 2540-M2 array showed 1.5 GB/sec for sequential read operations and showed linear scaling, achieving 18 GB/sec with twelve Sun Storage 2540-M2 arrays. These were stand alone IO tests. The peak IO rate measured from the Oracle database was 17 GB/sec. Oracle Solaris 11 11/11 required very little system tuning. Some vendors try to make the point that storage ratios are of customer concern. However, storage ratio size has more to do with disk layout and the increasing capacities of disks – so this is not an important metric in which to compare systems. The SPARC T4-4 server and Oracle Solaris efficiently managed the system load of over one thousand Oracle Database parallel processes. Six Sun Storage 2540-M2 arrays were mirrored to another six Sun Storage 2540-M2 arrays on which all of the Oracle database files were placed. IO performance was high and balanced across all the arrays. The TPC-H Refresh Function (RF) simulates periodical refresh portion of Data Warehouse by adding new sales and deleting old sales data. Parallel DML (parallel insert and delete in this case) and database log performance are a key for this function and the SPARC T4-4 server outperformed both the IBM POWER7 server and HP ProLiant DL980 G7 server. (See the RF columns above.) See Also Transaction Processing Performance Council (TPC) Home Page Ideas International Benchmark Page SPARC T4-4 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Sun Storage 2540-M2 Array oracle.com OTN Disclosure Statement TPC-H, QphH, $/QphH are trademarks of Transaction Processing Performance Council (TPC). For more information, see www.tpc.org. SPARC T4-4 205,792.0 QphH@3000GB, $4.10/QphH@3000GB, available 5/31/12, 4 processors, 32 cores, 256 threads; IBM Power 780 QphH@3000GB, 192,001.1 QphH@3000GB, $6.37/QphH@3000GB, available 11/30/11, 8 processors, 32 cores, 128 threads; HP ProLiant DL980 G7 162,601.7 QphH@3000GB, $2.68/QphH@3000GB available 10/13/10, 8 processors, 64 cores, 128 threads.

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  • Oracle Database 12 c New Partition Maintenance Features by Gwen Lazenby

    - by hamsun
    One of my favourite new features in Oracle Database 12c is the ability to perform partition maintenance operations on multiple partitions. This means we can now add, drop, truncate and merge multiple partitions in one operation, and can split a single partition into more than two partitions also in just one command. This would certainly have made my life slightly easier had it been available when I administered a data warehouse at Oracle 9i. To demonstrate this new functionality and syntax, I am going to create two tables, ORDERS and ORDERS_ITEMS which have a parent-child relationship. ORDERS is to be partitioned using range partitioning on the ORDER_DATE column, and ORDER_ITEMS is going to partitioned using reference partitioning and its foreign key relationship with the ORDERS table. This form of partitioning was a new feature in 11g and means that any partition maintenance operations performed on the ORDERS table will also take place on the ORDER_ITEMS table as well. First create the ORDERS table - SQL CREATE TABLE orders ( order_id NUMBER(12), order_date TIMESTAMP, order_mode VARCHAR2(8), customer_id NUMBER(6), order_status NUMBER(2), order_total NUMBER(8,2), sales_rep_id NUMBER(6), promotion_id NUMBER(6), CONSTRAINT orders_pk PRIMARY KEY(order_id) ) PARTITION BY RANGE(order_date) (PARTITION Q1_2007 VALUES LESS THAN (TO_DATE('01-APR-2007','DD-MON-YYYY')), PARTITION Q2_2007 VALUES LESS THAN (TO_DATE('01-JUL-2007','DD-MON-YYYY')), PARTITION Q3_2007 VALUES LESS THAN (TO_DATE('01-OCT-2007','DD-MON-YYYY')), PARTITION Q4_2007 VALUES LESS THAN (TO_DATE('01-JAN-2008','DD-MON-YYYY')) ); Table created. Now the ORDER_ITEMS table SQL CREATE TABLE order_items ( order_id NUMBER(12) NOT NULL, line_item_id NUMBER(3) NOT NULL, product_id NUMBER(6) NOT NULL, unit_price NUMBER(8,2), quantity NUMBER(8), CONSTRAINT order_items_fk FOREIGN KEY(order_id) REFERENCES orders(order_id) on delete cascade) PARTITION BY REFERENCE(order_items_fk) tablespace example; Table created. Now look at DBA_TAB_PARTITIONS to get details of what partitions we have in the two tables – SQL select table_name,partition_name, partition_position position, high_value from dba_tab_partitions where table_owner='SH' and table_name like 'ORDER_%' order by partition_position, table_name; TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 Just as an aside it is also now possible in 12c to use interval partitioning on reference partitioned tables. In 11g it was not possible to combine these two new partitioning features. For our first example of the new 12cfunctionality, let us add all the partitions necessary for 2008 to the tables using one command. Notice that the partition specification part of the add command is identical in format to the partition specification part of the create command as shown above - SQL alter table orders add PARTITION Q1_2008 VALUES LESS THAN (TO_DATE('01-APR-2008','DD-MON-YYYY')), PARTITION Q2_2008 VALUES LESS THAN (TO_DATE('01-JUL-2008','DD-MON-YYYY')), PARTITION Q3_2008 VALUES LESS THAN (TO_DATE('01-OCT-2008','DD-MON-YYYY')), PARTITION Q4_2008 VALUES LESS THAN (TO_DATE('01-JAN-2009','DD-MON-YYYY')); Table altered. Now look at DBA_TAB_PARTITIONS and we can see that the 4 new partitions have been added to both tables – SQL select table_name,partition_name, partition_position position, high_value from dba_tab_partitions where table_owner='SH' and table_name like 'ORDER_%' order by partition_position, table_name; TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 ORDERS Q1_2008 5 TIMESTAMP' 2008-04-01 00:00:00' ORDER_ITEMS Q1_2008 5 ORDERS Q2_2008 6 TIMESTAMP' 2008-07-01 00:00:00' ORDER_ITEM Q2_2008 6 ORDERS Q3_2008 7 TIMESTAMP' 2008-10-01 00:00:00' ORDER_ITEMS Q3_2008 7 ORDERS Q4_2008 8 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 8 Next, we can drop or truncate multiple partitions by giving a comma separated list in the alter table command. Note the use of the plural ‘partitions’ in the command as opposed to the singular ‘partition’ prior to 12c– SQL alter table orders drop partitions Q3_2008,Q2_2008,Q1_2008; Table altered. Now look at DBA_TAB_PARTITIONS and we can see that the 3 partitions have been dropped in both the two tables – TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 ORDERS Q4_2008 5 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 5 Now let us merge all the 2007 partitions together to form one single partition – SQL alter table orders merge partitions Q1_2005, Q2_2005, Q3_2005, Q4_2005 into partition Y_2007; Table altered. TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Y_2007 1 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Y_2007 1 ORDERS Q4_2008 2 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 2 Splitting partitions is a slightly more involved. In the case of range partitioning one of the new partitions must have no high value defined, and in list partitioning one of the new partitions must have no list of values defined. I call these partitions the ‘everything else’ partitions, and will contain any rows contained in the original partition that are not contained in the any of the other new partitions. For example, let us split the Y_2007 partition back into 4 quarterly partitions – SQL alter table orders split partition Y_2007 into (PARTITION Q1_2007 VALUES LESS THAN (TO_DATE('01-APR-2007','DD-MON-YYYY')), PARTITION Q2_2007 VALUES LESS THAN (TO_DATE('01-JUL-2007','DD-MON-YYYY')), PARTITION Q3_2007 VALUES LESS THAN (TO_DATE('01-OCT-2007','DD-MON-YYYY')), PARTITION Q4_2007); Now look at DBA_TAB_PARTITIONS to get details of the new partitions – TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 ORDERS Q4_2008 5 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 5 Partition Q4_2007 has a high value equal to the high value of the original Y_2007 partition, and so has inherited its upper boundary from the partition that was split. As for a list partitioning example let look at the following another table, SALES_PAR_LIST, which has 2 partitions, Americas and Europe and a partitioning key of country_name. SQL select table_name,partition_name, high_value from dba_tab_partitions where table_owner='SH' and table_name = 'SALES_PAR_LIST'; TABLE_NAME PARTITION_NAME HIGH_VALUE -------------- --------------- ----------------------------- SALES_PAR_LIST AMERICAS 'Argentina', 'Canada', 'Peru', 'USA', 'Honduras', 'Brazil', 'Nicaragua' SALES_PAR_LIST EUROPE 'France', 'Spain', 'Ireland', 'Germany', 'Belgium', 'Portugal', 'Denmark' Now split the Americas partition into 3 partitions – SQL alter table sales_par_list split partition americas into (partition south_america values ('Argentina','Peru','Brazil'), partition north_america values('Canada','USA'), partition central_america); Table altered. Note that no list of values was given for the ‘Central America’ partition. However it should have inherited any values in the original ‘Americas’ partition that were not assigned to either the ‘North America’ or ‘South America’ partitions. We can confirm this by looking at the DBA_TAB_PARTITIONS view. SQL select table_name,partition_name, high_value from dba_tab_partitions where table_owner='SH' and table_name = 'SALES_PAR_LIST'; TABLE_NAME PARTITION_NAME HIGH_VALUE --------------- --------------- -------------------------------- SALES_PAR_LIST SOUTH_AMERICA 'Argentina', 'Peru', 'Brazil' SALES_PAR_LIST NORTH_AMERICA 'Canada', 'USA' SALES_PAR_LIST CENTRAL_AMERICA 'Honduras', 'Nicaragua' SALES_PAR_LIST EUROPE 'France', 'Spain', 'Ireland', 'Germany', 'Belgium', 'Portugal', 'Denmark' In conclusion, I hope that DBA’s whose work involves maintaining partitions will find the operations a bit more straight forward to carry out once they have upgraded to Oracle Database 12c. Gwen Lazenby is a Principal Training Consultant at Oracle. She is part of Oracle University's Core Technology delivery team based in the UK, teaching Database Administration and Linux courses. Her specialist topics include using Oracle Partitioning and Parallelism in Data Warehouse environments, as well as Oracle Spatial and RMAN.

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