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  • Oracle E-Business Suite Partners Get Plugged In - Oracle Enterprise Manager 12c

    - by Get_Specialized!
      Oracle E-Business Suite Plug-in, an integral part of Application Management Suite for Oracle E-Business Suite, is Generally Available. More information may be found in note 1434392.1 on MyOracle Support. Oracle E-Business Suite Plug-in can be accessed a few ways: Fresh install Enterprise Manager Store Oracle Software Delivery Cloud   Upgrade Oracle Technology Network Please refer to the Application Management Pack for Oracle E-Business Suite Guide for further details. If you are a partner and have not yet joined the Oracle PartnerNetwork Enterprise Manager KnowledgeZone, be sure and sign up today to learn more about Oracle Application Management and how it can aid your customers and business.

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  • Oracle's Vision for the Social-Enabled Enterprise

    - by Peggy Chen
    Register Now Join us for the Webcast. Mon., Sept. 10, 2012 10 a.m. PT / 1 p.m. ET Join the conversation: #oracle and #socbiz Mark Hurd President, Oracle Thomas Kurian Executive Vice President, Product Development, Oracle Reggie Bradford Senior Vice President, Product Development, Oracle Dear Colleague, Smart companies are developing social media strategies to engage customers, gain brand insights, and transform employee collaboration and recruitment. Oracle is powering this transformation with the most comprehensive enterprise social platform that lets you: Monitor and engage in social conversations Collect and analyze social data Build and grow brands through social media Integrate enterprisewide social functionality into a single system Create rich social applications Join Oracle President Mark Hurd and senior Oracle executives to learn more about Oracle’s vision for the social-enabled enterprise. Register now for this Webcast. Copyright © 2012, Oracle and/or its affiliates. All rights reserved. Contact Us | Legal Notices and Terms of Use | Privacy Statement

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  • MySQL Enterprise Backup 3.8.2 - Overview

    - by Priya Jayakumar
      MySQL Enterprise Backup (MEB) is the ideal solution for backing up MySQL databases. MEB 3.8.2 is released in June 2013. MySQL Enterprise Backup 3.8.2 release’s main goal is to improve usability. With this release, users can know the progress of backup completed both in terms of size and as a percentage of the total. This release also offers options to be able to manage the behavior of MEB in case the space on the secondary storage is completely exhausted during backup. The progress indicator is a (short) string that indicates how far the execution of a time-consuming MEB command has progressed. It consists of one or more "meters" that measures the progress of the command. There are two options introduced to control the progress reporting function of mysqlbackup command (1) –show-progress (2) –progress-interval. The user can control the progress indicator by using “--show-progress” option in any of the MEB operations. This option instructs MEB to output periodically short reports on the progress of time-consuming commands. The argument of this option instructs where the output could be sent. For example it could be stderr, stdout, file, fifo and table. With the “--show-progress” option both the total size of the backup to be copied and the size that’s already copied will be shown. Along with this, the state of the operation for example data or meta-data being copied or tables being locked and other such operations will also be reported. This gives more clear information to the DBA on the progress of the backup that’s happening. Interval between progress report in seconds is controlled by “--progress-interval” option. For more information on this please refer progress-report-options. MEB can also be accessed through GUI from MySQL WorkBench’s next version. This can be used as the front end interface for MEB users to perform backup operations at the click of a button. This feature was highly requested by DBAs and will be very useful. Refer http://insidemysql.com/mysql-workbench-6-0-a-sneak-preview/ for WorkBench upcoming release info. Along with the progress report feature some of the important issues like below are also addressed in MEB 3.8.2. In MEB 3.8.2 a new command line option “--on-disk-full” is introduced to abort or warn the user when a backup process encounters a full disk condition. When no option is given, by default it would abort. A few issues related to “incremental-backup” are also addressed in this release. Please refer 3.8.2 documentation for more details. It would be good for MEB users to move to 3.8.2 to take incremental backups. Overall the added usability and the important defects fixed in this release makes MySQL Enterprise Backup 3.8.2 a promising release.  

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  • Adjusting the Score on Oracle Text search results

    - by Kyle Hatlestad
    When you sort the results of a search by Score using OracleTextSearch as the search engine in WebCenter Content, the results coming back are based on the relevancy on the document.  In theory, the more relevant the search term is to the document, the higher ranked Score it should receive.  But in practice, the relevancy score can seem somewhat of a mystery.  It's not entirely clear how it ranks the importance of some documents over others based on the search term.  And often times, once a word appears a certain number of times within a document, the Score simply maxes out at 100 and the top results can be difficult to discern from one another.  Take for example the search for 'vacation' on this set of documents: Out of 7 results, 6 of them have a Score of '100' which means they are basically ranked the same.  This doesn't make the sort by Score very meaningful.   Besides sorting by relevance, you can also tell Oracle Text to sort by occurrence.  In that case, it is a much more predictable result in how they would be ranked. And for many cases provide a more meaningful sorting of results then relevance. To change this takes a small component change to the SearchOperatorMap resource.  By default, the query used for full-text searching looks like: <td>(ORACLETEXTSEARCH)fullText</td> <td>DEFINESCORE((%V), RELEVANCE * .1)</td> <td>text</td> Overriding this resource and changing it to: <td>(ORACLETEXTSEARCH)fullText</td> <td>DEFINESCORE((%V), OCCURRENCE * .01)</td>  <td>text</td> will force it to now use occurrence (note the change in scale to .01 as well).  So running the same search and sort options as the example above, the results come out quite a bit differently: In this case, there is a clear understanding of how the items rank.   And generally, if the search term appears 3 times more in one document then another, it's got a better chance of being a document I'm interested in.  You may or may not feel the relevance ranking is better then the search term occurrence, but this provides the opportunity to try an alternate method that might work better for your results.  A pre-built component is available for download here. There is one caveat in using this method.  The occurrence ranking also maxes out at 100, so if a search term is in the document more then that, the Score result will stay at 100.

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  • Save the date For AutoVue Enterprise Visualization at Oracle OpenWorld 2013

    - by Gerald Fauteux
    Planning to attend Oracle OpenWorld 2013 (September 22–26, 2013)?  If so, be sure to check out the various Enterprise Visualization activities that you can take advantage of while in San Francisco. Enterprise Visualization Sessions: CON8992 - Qualcomm Streamlines Its Design and Manufacturing Process with AutoVue/Agile Products. Click here for full session description. Customer Speakers: Mary Legaspi - Staff Systems Administrator and Ravi Sankaran - Sr. Staff Systems Analyst, Qualcomm CON8741 - Visual Information Navigator: Next-Generation Interaction Paradigm. Click here for full session description. Speakers: Rozita Naghshin - Sr. Principal Product Manager-Visual Information Navigator and Thierry Bonfante - Senior Director Product Development, Oracle Other Activities  There will be an “Oracle’s AutoVue & Visual Information Navigator" pod in the exhibit hall Come and meet Oracle’s Visualization experts at the SCM product lounge, and have exclusive 1 on 1 or group conversations with development and strategy experts.     Check back shortly for the dates and times of these activities

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  • DB Enterprise User Security Integration With Directory Services

    - by Etienne Remillon
    Gain a better understanding of how to integrate Enterprise User Security (EUS) with various Directories by attending this 1 hour Advisor Webcast!  When: July 11, 2012 at 16:00 UK / 17:00 CET / 08:00 am Pacific / 9:00 am Mountain / 11:00 am Eastern Enterprise User Security (EUS) is a DB feature to externalize, and centrally manage DB users in a directory server. The webcast will briefly introduce EUS, followed by a detailed discussion about the various directory options that are supported, including integration with Microsoft Active Directory. We'll conclude how to avoid common pitfalls deploying EUS with directory services. TOPICS WILL INCLUDE: - Understand EUS basics - Understand EUS and directory integration options - Avoid common EUS deployment mistakes Make sure to register and mark this date on your calendar! - Details and registration.

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  • Solving Big Problems with Oracle R Enterprise, Part I

    - by dbayard
    Abstract: This blog post will show how we used Oracle R Enterprise to tackle a customer’s big calculation problem across a big data set. Overview: Databases are great for managing large amounts of data in a central place with rigorous enterprise-level controls.  R is great for doing advanced computations.  Sometimes you need to do advanced computations on large amounts of data, subject to rigorous enterprise-level concerns.  This blog post shows how Oracle R Enterprise enables R plus the Oracle Database enabled us to do some pretty sophisticated calculations across 1 million accounts (each with many detailed records) in minutes. The problem: A financial services customer of mine has a need to calculate the historical internal rate of return (IRR) for its customers’ portfolios.  This information is needed for customer statements and the online web application.  In the past, they had solved this with a home-grown application that pulled trade and account data out of their data warehouse and ran the calculations.  But this home-grown application was not able to do this fast enough, plus it was a challenge for them to write and maintain the code that did the IRR calculation. IRR – a problem that R is good at solving: Internal Rate of Return is an interesting calculation in that in most real-world scenarios it is impractical to calculate exactly.  Rather, IRR is a calculation where approximation techniques need to be used.  In this blog post, we will discuss calculating the “money weighted rate of return” but in the actual customer proof of concept we used R to calculate both money weighted rate of returns and time weighted rate of returns.  You can learn more about the money weighted rate of returns here: http://www.wikinvest.com/wiki/Money-weighted_return First Steps- Calculating IRR in R We will start with calculating the IRR in standalone/desktop R.  In our second post, we will show how to take this desktop R function, deploy it to an Oracle Database, and make it work at real-world scale.  The first step we did was to get some sample data.  For a historical IRR calculation, you have a balances and cash flows.  In our case, the customer provided us with several accounts worth of sample data in Microsoft Excel.      The above figure shows part of the spreadsheet of sample data.  The data provides balances and cash flows for a sample account (BMV=beginning market value. FLOW=cash flow in/out of account. EMV=ending market value). Once we had the sample spreadsheet, the next step we did was to read the Excel data into R.  This is something that R does well.  R offers multiple ways to work with spreadsheet data.  For instance, one could save the spreadsheet as a .csv file.  In our case, the customer provided a spreadsheet file containing multiple sheets where each sheet provided data for a different sample account.  To handle this easily, we took advantage of the RODBC package which allowed us to read the Excel data sheet-by-sheet without having to create individual .csv files.  We wrote ourselves a little helper function called getsheet() around the RODBC package.  Then we loaded all of the sample accounts into a data.frame called SimpleMWRRData. Writing the IRR function At this point, it was time to write the money weighted rate of return (MWRR) function itself.  The definition of MWRR is easily found on the internet or if you are old school you can look in an investment performance text book.  In the customer proof, we based our calculations off the ones defined in the The Handbook of Investment Performance: A User’s Guide by David Spaulding since this is the reference book used by the customer.  (One of the nice things we found during the course of this proof-of-concept is that by using R to write our IRR functions we could easily incorporate the specific variations and business rules of the customer into the calculation.) The key thing with calculating IRR is the need to solve a complex equation with a numerical approximation technique.  For IRR, you need to find the value of the rate of return (r) that sets the Net Present Value of all the flows in and out of the account to zero.  With R, we solve this by defining our NPV function: where bmv is the beginning market value, cf is a vector of cash flows, t is a vector of time (relative to the beginning), emv is the ending market value, and tend is the ending time. Since solving for r is a one-dimensional optimization problem, we decided to take advantage of R’s optimize method (http://stat.ethz.ch/R-manual/R-patched/library/stats/html/optimize.html). The optimize method can be used to find a minimum or maximum; to find the value of r where our npv function is closest to zero, we wrapped our npv function inside the abs function and asked optimize to find the minimum.  Here is an example of using optimize: where low and high are scalars that indicate the range to search for an answer.   To test this out, we need to set values for bmv, cf, t, emv, tend, low, and high.  We will set low and high to some reasonable defaults. For example, this account had a negative 2.2% money weighted rate of return. Enhancing and Packaging the IRR function With numerical approximation methods like optimize, sometimes you will not be able to find an answer with your initial set of inputs.  To account for this, our approach was to first try to find an answer for r within a narrow range, then if we did not find an answer, try calling optimize() again with a broader range.  See the R help page on optimize()  for more details about the search range and its algorithm. At this point, we can now write a simplified version of our MWRR function.  (Our real-world version is  more sophisticated in that it calculates rate of returns for 5 different time periods [since inception, last quarter, year-to-date, last year, year before last year] in a single invocation.  In our actual customer proof, we also defined time-weighted rate of return calculations.  The beauty of R is that it was very easy to add these enhancements and additional calculations to our IRR package.)To simplify code deployment, we then created a new package of our IRR functions and sample data.  For this blog post, we only need to include our SimpleMWRR function and our SimpleMWRRData sample data.  We created the shell of the package by calling: To turn this package skeleton into something usable, at a minimum you need to edit the SimpleMWRR.Rd and SimpleMWRRData.Rd files in the \man subdirectory.  In those files, you need to at least provide a value for the “title” section. Once that is done, you can change directory to the IRR directory and type at the command-line: The myIRR package for this blog post (which has both SimpleMWRR source and SimpleMWRRData sample data) is downloadable from here: myIRR package Testing the myIRR package Here is an example of testing our IRR function once it was converted to an installable package: Calculating IRR for All the Accounts So far, we have shown how to calculate IRR for a single account.  The real-world issue is how do you calculate IRR for all of the accounts?This is the kind of situation where we can leverage the “Split-Apply-Combine” approach (see http://www.cscs.umich.edu/~crshalizi/weblog/815.html).  Given that our sample data can fit in memory, one easy approach is to use R’s “by” function.  (Other approaches to Split-Apply-Combine such as plyr can also be used.  See http://4dpiecharts.com/2011/12/16/a-quick-primer-on-split-apply-combine-problems/). Here is an example showing the use of “by” to calculate the money weighted rate of return for each account in our sample data set.  Recap and Next Steps At this point, you’ve seen the power of R being used to calculate IRR.  There were several good things: R could easily work with the spreadsheets of sample data we were given R’s optimize() function provided a nice way to solve for IRR- it was both fast and allowed us to avoid having to code our own iterative approximation algorithm R was a convenient language to express the customer-specific variations, business-rules, and exceptions that often occur in real-world calculations- these could be easily added to our IRR functions The Split-Apply-Combine technique can be used to perform calculations of IRR for multiple accounts at once. However, there are several challenges yet to be conquered at this point in our story: The actual data that needs to be used lives in a database, not in a spreadsheet The actual data is much, much bigger- too big to fit into the normal R memory space and too big to want to move across the network The overall process needs to run fast- much faster than a single processor The actual data needs to be kept secured- another reason to not want to move it from the database and across the network And the process of calculating the IRR needs to be integrated together with other database ETL activities, so that IRR’s can be calculated as part of the data warehouse refresh processes In our next blog post in this series, we will show you how Oracle R Enterprise solved these challenges.

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  • Oracle Enterprise Manager Cloud Control 12c: Die Verwendung von Gruppen

    - by Ralf Durben (DBA Community)
    Mit Oracle Enterprise Manager Cloud Control 12c können Sie eine Vielzahl von Zielsystemen verwalten, sowohl was die Vielfältigkeit als auch die pure Anzahl betrifft. Eine große Anzahl von Zielsystemen wirft die Frage auf, wie diese Menge effizient verwaltet werden kann. Dazu gehören die Kontrolle des Zugriffs, die möglichst automatische Einstellung des Monitorings und die Bildung von benutzerorientieren Sichten. Zu diesem Zweck gibt es das Konzept der Gruppen, in denen Zielsysteme (Targets) zusammengefasst werden können. In Oracle Enterprise Manager Cloud Control 12c gibt es drei verschiedene Typen von Gruppen, die im aktuellen Tipp erklärt und voneinander abgegrenzt werden.

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  • All About Search Engine Position Optimization

    Search engine optimization or SEO is a method increasing the amount of traffic or hits to your website, which results in making your website rank high in search engine results. These results are produced whenever an individual types in a keyword or a set of keywords in a search query in search engines like Yahoo!, Google and the like. Being high on the list of search results matters a lot because it makes you more visible to the general public, especially to your target market. This differentiates you from your competitors who may rank low in the search results, or may not even appear in the results lists at all.

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  • Why Executives Need Enterprise Project Portfolio Management: 3 Key Considerations to Drive Value Across the Organization

    - by Melissa Centurio Lopes
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Cambria","serif";} By: Guy Barlow, Oracle Primavera Industry Strategy Director Over the last few years there has been a tremendous shift – some would say tectonic in nature – that has brought project management to the forefront of executive attention. Many factors have been driving this growing awareness, most notably, the global financial crisis, heightened regulatory environments and a need to more effectively operationalize corporate strategy. Executives in India are no exception. In fact, given the phenomenal rate of progress of the country, top of mind for all executives (whether in finance, operations, IT, etc.) is the need to build capacity, ramp-up production and ensure that the right resources are in place to capture growth opportunities. This applies across all industries from asset-intensive – like oil & gas, utilities and mining – to traditional manufacturing and the public sector, including services-based sectors such as the financial, telecom and life sciences segments are also part of the mix. However, compounding matters is a complex, interplay between projects – big and small, complex and simple – as companies expand and grow both domestically and internationally. So, having a standardized, enterprise wide solution for project portfolio management is natural. Failing to do so is akin to having two ERP systems, one to manage “large” invoices and one to manage “small” invoices. It makes no sense and provides no enterprise wide visibility. Therefore, it is imperative for executives to understand the full range of their business commitments, the benefit to the company, current performance and associated course corrections if needed. Irrespective of industry and regardless of the use case (e.g., building a power plant, launching a new financial service or developing a new automobile) company leaders need to approach the value of enterprise project portfolio management via 3 critical areas: Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Cambria","serif";} 1. Greater Financial Discipline – Improve financial rigor and results through better governance and control is an imperative given today’s financial uncertainty and greater investment scrutiny. For example, as India plans a US$1 trillion investment in the country’s infrastructure how do companies ensure costs are managed? How do you control cash flow? Can you easily report this to stakeholders? 2. Improved Operational Excellence – Increase efficiency and reduce costs through robust collaboration and integration. Upwards of 66% of cost variances are driven by poor supplier collaboration. As you execute initiatives do you have visibility into the performance of your supply base? How are they integrated into the broader program plan? 3. Enhanced Risk Mitigation – Manage and react to uncertainty through improved transparency and contingency planning. What happens if you’re faced with a skills shortage? How do you plan and account for geo-political or weather related events? In summary, projects are not just the delivery of a product or service to a customer inside a predetermined schedule; they often form a contractual and even moral obligation to shareholders and stakeholders alike. Hence the intimate connection between executives and projects, with the latter providing executives with the platform to demonstrate that their organization has the capabilities and competencies needed to meet and, whenever possible, exceed their customer commitments. Effectively developing and operationalizing corporate strategy is the hallmark of successful executives and enterprise project and portfolio management allows them to achieve this goal. Article was first published for Manage India, an e-newsletter, PMI India.

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  • R Statistical Analytics with Faster Performance for Enterprise Database Access and Big Data

    - by Mike.Hallett(at)Oracle-BI&EPM
    Further demonstrating commitment to the open source community, Oracle has just released enhanced support of the R statistical programming language for Oracle Solaris and AIX in addition to Linux and Windows, connectivity to Oracle TimesTen In-Memory Database in addition to Oracle Database, and integration of hardware-specific Math libraries for faster performance.  Oracle’s Open Source distribution of R is available with the Oracle Big Data Appliance and available for download now. Oracle also offers Oracle R Enterprise, a component of Oracle Advanced Analytics that enables R processing on Oracle Database servers.   This all goes to make big data analytics more accessible in the enterprise and improving data scientist productivity with faster performance Since its introduction in 1995, R has attracted more than two million users and is widely used today for developing statistical applications that analyze big data. Analyst Report: Oracle Advances its Advanced Analytics Strategy  

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  • Partners - Steer Clear of the Unknown with Oracle Enterprise Manager12c and Plug-in Extensibility

    - by Get_Specialized!
    Imagine if you just purchased a new car and as you entered the vehicle to drive it home and you found there was no steering wheel. And upon asking the dealer you were told that it was an option and you had a choice now or later of a variety of aftermarket steering wheels that fit a wide variety of automobiles. If you expected the car to already have a steering wheel designed to manage your transportation solution, you might wonder why someone would offer an application solution where its management is not offered as an option or come as part of the solution... Using management designed to support the underlying technology and that can provide management and support  for your own Oracle technology based solution can benefit your business  a variety of ways: increased customer satisfaction, reduction of support calls, margin and revenue growth. Sometimes when something is not included or recommended , customers take their own path which may not be optimal when using your solution and has later impact on the customers satisfaction or worse a negative impact on their business. As an Oracle Partner, you can reduce your research, certification, and time to market by selecting and offering management designed, developed, and supported for Oracle product technology by Oracle with Oracle Enterprise Manager 12c. For partners with solution specific management needs or seeking to differentiate themselves in the market, Enterprise Manager 12c is extensible and provides partners the opportunity to create their own plug-ins as well as a validation program for them.  Today a number of examples by partners are available and Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-family:"Calibri","sans-serif"; mso-ascii- mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi- mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} more on the way from such partners as NetApp for NetApp storage and Blue Medora for VMware vSphere. To review and consider further for applicability to your solution, visit  the Oracle PartnerNetwork KnowledgeZone for Enterprise Manager under the Develop Tab http://www.oracle.com/partners/goto/enterprisemanager

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  • Quadratic Programming with Oracle R Enterprise

    - by Jeff Taylor-Oracle
         I wanted to use quadprog with ORE on a server running Oracle Solaris 11.2 on a Oracle SPARC T-4 server For background, see: Oracle SPARC T4-2 http://docs.oracle.com/cd/E23075_01/ Oracle Solaris 11.2 http://www.oracle.com/technetwork/server-storage/solaris11/overview/index.html quadprog: Functions to solve Quadratic Programming Problems http://cran.r-project.org/web/packages/quadprog/index.html Oracle R Enterprise 1.4 ("ORE") 1.4 http://www.oracle.com/technetwork/database/options/advanced-analytics/r-enterprise/ore-downloads-1502823.html Problem: path to Solaris Studio doesn't match my installation: $ ORE CMD INSTALL quadprog_1.5-5.tar.gz * installing to library \u2018/u01/app/oracle/product/12.1.0/dbhome_1/R/library\u2019 * installing *source* package \u2018quadprog\u2019 ... ** package \u2018quadprog\u2019 successfully unpacked and MD5 sums checked ** libs /opt/SunProd/studio12u3/solarisstudio12.3/bin/f95 -m64   -PIC  -g  -c aind.f -o aind.o bash: /opt/SunProd/studio12u3/solarisstudio12.3/bin/f95: No such file or directory *** Error code 1 make: Fatal error: Command failed for target `aind.o' ERROR: compilation failed for package \u2018quadprog\u2019 * removing \u2018/u01/app/oracle/product/12.1.0/dbhome_1/R/library/quadprog\u2019 $ ls -l /opt/solarisstudio12.3/bin/f95 lrwxrwxrwx   1 root     root          15 Aug 19 17:36 /opt/solarisstudio12.3/bin/f95 -> ../prod/bin/f90 Solution: a symbolic link: $ sudo mkdir -p /opt/SunProd/studio12u3 $ sudo ln -s /opt/solarisstudio12.3 /opt/SunProd/studio12u3/ Now, it is all good: $ ORE CMD INSTALL quadprog_1.5-5.tar.gz * installing to library \u2018/u01/app/oracle/product/12.1.0/dbhome_1/R/library\u2019 * installing *source* package \u2018quadprog\u2019 ... ** package \u2018quadprog\u2019 successfully unpacked and MD5 sums checked ** libs /opt/SunProd/studio12u3/solarisstudio12.3/bin/f95 -m64   -PIC  -g  -c aind.f -o aind.o /opt/SunProd/studio12u3/solarisstudio12.3/bin/ cc -xc99 -m64 -I/usr/lib/64/R/include -DNDEBUG -KPIC  -xlibmieee  -c init.c -o init.o /opt/SunProd/studio12u3/solarisstudio12.3/bin/f95 -m64  -PIC -g  -c -o solve.QP.compact.o solve.QP.compact.f /opt/SunProd/studio12u3/solarisstudio12.3/bin/f95 -m64  -PIC -g  -c -o solve.QP.o solve.QP.f /opt/SunProd/studio12u3/solarisstudio12.3/bin/f95 -m64   -PIC  -g  -c util.f -o util.o /opt/SunProd/studio12u3/solarisstudio12.3/bin/ cc -xc99 -m64 -G -o quadprog.so aind.o init.o solve.QP.compact.o solve.QP.o util.o -xlic_lib=sunperf -lsunmath -lifai -lsunimath -lfai -lfai2 -lfsumai -lfprodai -lfminlai -lfmaxlai -lfminvai -lfmaxvai -lfui -lfsu -lsunmath -lmtsk -lm -lifai -lsunimath -lfai -lfai2 -lfsumai -lfprodai -lfminlai -lfmaxlai -lfminvai -lfmaxvai -lfui -lfsu -lsunmath -lmtsk -lm -L/usr/lib/64/R/lib -lR installing to /u01/app/oracle/product/12.1.0/dbhome_1/R/library/quadprog/libs ** R ** preparing package for lazy loading ** help *** installing help indices   converting help for package \u2018quadprog\u2019     finding HTML links ... done     solve.QP                                html      solve.QP.compact                        html  ** building package indices ** testing if installed package can be loaded * DONE (quadprog) ====== Here is an example from http://cran.r-project.org/web/packages/quadprog/quadprog.pdf > require(quadprog) > Dmat <- matrix(0,3,3) > diag(Dmat) <- 1 > dvec <- c(0,5,0) > Amat <- matrix(c(-4,-3,0,2,1,0,0,-2,1),3,3) > bvec <- c(-8,2,0) > solve.QP(Dmat,dvec,Amat,bvec=bvec) $solution [1] 0.4761905 1.0476190 2.0952381 $value [1] -2.380952 $unconstrained.solution [1] 0 5 0 $iterations [1] 3 0 $Lagrangian [1] 0.0000000 0.2380952 2.0952381 $iact [1] 3 2 Here, the standard example is modified to work with Oracle R Enterprise require(ORE) ore.connect("my-name", "my-sid", "my-host", "my-pass", 1521) ore.doEval(   function () {     require(quadprog)   } ) ore.doEval(   function () {     Dmat <- matrix(0,3,3)     diag(Dmat) <- 1     dvec <- c(0,5,0)     Amat <- matrix(c(-4,-3,0,2,1,0,0,-2,1),3,3)     bvec <- c(-8,2,0)    solve.QP(Dmat,dvec,Amat,bvec=bvec)   } ) $solution [1] 0.4761905 1.0476190 2.0952381 $value [1] -2.380952 $unconstrained.solution [1] 0 5 0 $iterations [1] 3 0 $Lagrangian [1] 0.0000000 0.2380952 2.0952381 $iact [1] 3 2 Now I can combine the quadprog compute algorithms with the Oracle R Enterprise Database engine functionality: Scale to large datasets Access to tables, views, and external tables in the database, as well as those accessible through database links Use SQL query parallel execution Use in-database statistical and data mining functionality

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  • Windows 7 Enterprise : Microsoft sort une version d'évaluation gratuite de l'édition "réservée aux professionnels de l'informatique"

    Microsoft propose une version d'évaluation gratuite de Windows 7 Enterprise Que pensez-vous de cette édition spécialement dédiée aux professionnels de l'informatique Le 8 avril 2014, Windows XP sera de l'histoire ancienne pour Microsoft. Plus aucune mise à jour et plus aucun support ne seront proposés pour le système d'exploitation n°1 dans le monde. Vista a suivi mais a déboussolé tant d'utilisateurs que pour beaucoup de professionnels IT, le vrai successeur de Windows XP est en fait Windows 7. Et plus exactement Windows 7 Enterprise. Au moment où Microsoft vient de lancer une offre spéciale de 90 jours d'essai gratuit pour cette édition spéciale (justement en rapport avec...

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