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  • Big Data – Operational Databases Supporting Big Data – Key-Value Pair Databases and Document Databases – Day 13 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the Relational Database and NoSQL database in the Big Data Story. In this article we will understand the role of Key-Value Pair Databases and Document Databases Supporting Big Data Story. Now we will see a few of the examples of the operational databases. Relational Databases (Yesterday’s post) NoSQL Databases (Yesterday’s post) Key-Value Pair Databases (This post) Document Databases (This post) Columnar Databases (Tomorrow’s post) Graph Databases (Tomorrow’s post) Spatial Databases (Tomorrow’s post) Key Value Pair Databases Key Value Pair Databases are also known as KVP databases. A key is a field name and attribute, an identifier. The content of that field is its value, the data that is being identified and stored. They have a very simple implementation of NoSQL database concepts. They do not have schema hence they are very flexible as well as scalable. The disadvantages of Key Value Pair (KVP) database are that they do not follow ACID (Atomicity, Consistency, Isolation, Durability) properties. Additionally, it will require data architects to plan for data placement, replication as well as high availability. In KVP databases the data is stored as strings. Here is a simple example of how Key Value Database will look like: Key Value Name Pinal Dave Color Blue Twitter @pinaldave Name Nupur Dave Movie The Hero As the number of users grow in Key Value Pair databases it starts getting difficult to manage the entire database. As there is no specific schema or rules associated with the database, there are chances that database grows exponentially as well. It is very crucial to select the right Key Value Pair Database which offers an additional set of tools to manage the data and provides finer control over various business aspects of the same. Riak Rick is one of the most popular Key Value Database. It is known for its scalability and performance in high volume and velocity database. Additionally, it implements a mechanism for collection key and values which further helps to build manageable system. We will further discuss Riak in future blog posts. Key Value Databases are a good choice for social media, communities, caching layers for connecting other databases. In simpler words, whenever we required flexibility of the data storage keeping scalability in mind – KVP databases are good options to consider. Document Database There are two different kinds of document databases. 1) Full document Content (web pages, word docs etc) and 2) Storing Document Components for storage. The second types of the document database we are talking about over here. They use Javascript Object Notation (JSON) and Binary JSON for the structure of the documents. JSON is very easy to understand language and it is very easy to write for applications. There are two major structures of JSON used for Document Database – 1) Name Value Pairs and 2) Ordered List. MongoDB and CouchDB are two of the most popular Open Source NonRelational Document Database. MongoDB MongoDB databases are called collections. Each collection is build of documents and each document is composed of fields. MongoDB collections can be indexed for optimal performance. MongoDB ecosystem is highly available, supports query services as well as MapReduce. It is often used in high volume content management system. CouchDB CouchDB databases are composed of documents which consists fields and attachments (known as description). It supports ACID properties. The main attraction points of CouchDB are that it will continue to operate even though network connectivity is sketchy. Due to this nature CouchDB prefers local data storage. Document Database is a good choice of the database when users have to generate dynamic reports from elements which are changing very frequently. A good example of document usages is in real time analytics in social networking or content management system. Tomorrow In tomorrow’s blog post we will discuss about various other Operational Databases supporting Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • The EXECUTE permission was denied on the object 'bam_Metadata_GetConfigurationXml'

    - by Andy Morrison
    We were seeing this exception on two servers when we tried to access the BAM Portal... after having to reconfigure the BAM Portal and Tools for reasons unrelated to the error: --- Log Name:      Application Source:        Bam Web Service Date:          2/18/2011 10:24:07 AM Event ID:      1534 Task Category: None Level:         Error Keywords:      Classic User:          N/A Computer:      yyyyyyyyyyyyyyyyyyyy Description: Current User: yy\yyyyyyyy EXCEPTION: Microsoft.BizTalk.Bam.Management.BamManagerException: Encountered error while executing command on SQL Server "yyyyyyyyyyyyyyy". ---> System.Data.SqlClient.SqlException: The EXECUTE permission was denied on the object 'bam_Metadata_GetConfigurationXml', database 'BAMPrimaryImport', schema 'dbo'.    at System.Data.SqlClient.SqlConnection.OnError(SqlException exception, Boolean breakConnection)    at System.Data.SqlClient.SqlInternalConnection.OnError(SqlException exception, Boolean breakConnection)    at System.Data.SqlClient.TdsParser.ThrowExceptionAndWarning(TdsParserStateObject stateObj)    at System.Data.SqlClient.TdsParser.Run(RunBehavior runBehavior, SqlCommand cmdHandler, SqlDataReader dataStream, BulkCopySimpleResultSet bulkCopyHandler, TdsParserStateObject stateObj)    at System.Data.SqlClient.SqlDataReader.ConsumeMetaData()    at System.Data.SqlClient.SqlDataReader.get_MetaData()    at System.Data.SqlClient.SqlCommand.FinishExecuteReader(SqlDataReader ds, RunBehavior runBehavior, String resetOptionsString)    at System.Data.SqlClient.SqlCommand.RunExecuteReaderTds(CommandBehavior cmdBehavior, RunBehavior runBehavior, Boolean returnStream, Boolean async)    at System.Data.SqlClient.SqlCommand.RunExecuteReader(CommandBehavior cmdBehavior, RunBehavior runBehavior, Boolean returnStream, String method, DbAsyncResult result)    at System.Data.SqlClient.SqlCommand.RunExecuteReader(CommandBehavior cmdBehavior, RunBehavior runBehavior, Boolean returnStream, String method)    at System.Data.SqlClient.SqlCommand.ExecuteReader(CommandBehavior behavior, String method)    at System.Data.SqlClient.SqlCommand.ExecuteReader(CommandBehavior behavior)    at Microsoft.BizTalk.Bam.Management.SqlHelper.ExecuteQuery(String cmdText, CommandType cmdType, Transaction transaction)    --- End of inner exception stack trace ---    at Microsoft.BizTalk.Bam.Management.SqlHelper.ExecuteQuery(String cmdText, CommandType cmdType, Transaction transaction)    at Microsoft.BizTalk.Bam.Management.BamConfigurationManager.GetConfigurationXmlFromPrimaryImportDb()    at Microsoft.BizTalk.Bam.Management.BamConfigurationManager..ctor(String piServer, String piDatabase, Int32 sqlHelperCmdTimeout, Boolean validateServerNames)    at Microsoft.BizTalk.Bam.Management.BamManager..ctor(String primaryImportServer, String primaryImportDatabase, Int32 sqlCmdTimeout, Boolean validateServerNames)    at Microsoft.BizTalk.Bam.Management.BamManager..ctor(String primaryImportServer, String primaryImportDatabase)    at Microsoft.BizTalk.Bam.WebServices.Utilities.FetchBamManager()    at Microsoft.BizTalk.Bam.WebServices.Management.BamManagementService.GetViewSummaryForCurrentUser() EXCEPTION: Microsoft.BizTalk.Bam.Management.BamManagerException: Encountered error while executing command on SQL Server "yyyyyyyyyyyyyyyyyy". ---&gt; System.Data.SqlClient.SqlException: The EXECUTE permission was denied on the object 'bam_Metadata_GetConfigurationXml', database 'BAMPrimaryImport', schema 'dbo'.    at System.Data.SqlClient.SqlConnection.OnError(SqlException exception, Boolean breakConnection)    at System.Data.SqlClient.SqlInternalConnection.OnError(SqlException exception, Boolean breakConnection)    at System.Data.SqlClient.TdsParser.ThrowExceptionAndWarning(TdsParserStateObject stateObj)    at System.Data.SqlClient.TdsParser.Run(RunBehavior runBehavior, SqlCommand cmdHandler, SqlDataReader dataStream, BulkCopySimpleResultSet bulkCopyHandler, TdsParserStateObject stateObj)    at System.Data.SqlClient.SqlDataReader.ConsumeMetaData()    at System.Data.SqlClient.SqlDataReader.get_MetaData()    at System.Data.SqlClient.SqlCommand.FinishExecuteReader(SqlDataReader ds, RunBehavior runBehavior, String resetOptionsString)    at System.Data.SqlClient.SqlCommand.RunExecuteReaderTds(CommandBehavior cmdBehavior, RunBehavior runBehavior, Boolean returnStream, Boolean async)    at System.Data.SqlClient.SqlCommand.RunExecuteReader(CommandBehavior cmdBehavior, RunBehavior runBehavior, Boolean returnStream, String method, DbAsyncResult result)    at System.Data.SqlClient.SqlCommand.RunExecuteReader(CommandBehavior cmdBehavior, RunBehavior runBehavior, Boolean returnStream, String method)    at System.Data.SqlClient.SqlCommand.ExecuteReader(CommandBehavior behavior, String method)    at System.Data.SqlClient.SqlCommand.ExecuteReader(CommandBehavior behavior)    at Microsoft.BizTalk.Bam.Management.SqlHelper.ExecuteQuery(String cmdText, CommandType cmdType, Transaction transaction)    --- End of inner exception stack trace ---    at Microsoft.BizTalk.Bam.Management.SqlHelper.ExecuteQuery(String cmdText, CommandType cmdType, Transaction transaction)    at Microsoft.BizTalk.Bam.Management.BamConfigurationManager.GetConfigurationXmlFromPrimaryImportDb()    at Microsoft.BizTalk.Bam.Management.BamConfigurationManager..ctor(String piServer, String piDatabase, Int32 sqlHelperCmdTimeout, Boolean validateServerNames)    at Microsoft.BizTalk.Bam.Management.BamManager..ctor(String primaryImportServer, String primaryImportDatabase, Int32 sqlCmdTimeout, Boolean validateServerNames)    at Microsoft.BizTalk.Bam.Management.BamManager..ctor(String primaryImportServer, String primaryImportDatabase)    at Microsoft.BizTalk.Bam.WebServices.Utilities.FetchBamManager()    at Microsoft.BizTalk.Bam.WebServices.Management.BamManagementService.GetViewSummaryForCurrentUser() --- We reconfigured the BAM Portal and Tools multiple times, trying to fix this issue, but kept getting the exception.  The fix was to add the BizTalk Server Administrators and BizTalk Application Users to the BAM_ManagementWS role in the BAMPrimaryImport database.  (Note that these two groups do not appear to be added to this role in a "clean" configuration. Thanks go to Ed at http://talentedmonkeys.wordpress.com/ for figuring out a solution.

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  • Bitmask data insertions in SSDT Post-Deployment scripts

    - by jamiet
    On my current project we are using SQL Server Data Tools (SSDT) to manage our database schema and one of the tasks we need to do often is insert data into that schema once deployed; the typical method employed to do this is to leverage Post-Deployment scripts and that is exactly what we are doing. Our requirement is a little different though, our data is split up into various buckets that we need to selectively deploy on a case-by-case basis. I was going to use a SQLCMD variable for each bucket (defaulted to some value other than “Yes”) to define whether it should be deployed or not so we could use something like this in our Post-Deployment script: IF ($(DeployBucket1Flag) = 'Yes')BEGIN   :r .\Bucket1.data.sqlENDIF ($(DeployBucket2Flag) = 'Yes')BEGIN   :r .\Bucket2.data.sqlENDIF ($(DeployBucket3Flag) = 'Yes')BEGIN   :r .\Bucket3.data.sqlEND That works fine and is, I’m sure, a very common technique for doing this. It is however slightly ugly because we have to litter our deployment with various SQLCMD variables. My colleague James Rowland-Jones (whom I’m sure many of you know) suggested another technique – bitmasks. I won’t go into detail about how this works (James has already done that at Using a Bitmask - a practical example) but I’ll summarise by saying that you can deploy different combinations of the buckets simply by supplying a different numerical value for a single SQLCMD variable. Each bit of that value’s binary representation signifies whether a particular bucket should be deployed or not. This is better demonstrated using the following simple script (which can be easily leveraged inside your Post-Deployment scripts): /* $(DeployData) is a SQLCMD variable that would, if you were using this in SSDT, be declared in the SQLCMD variables section of your project file. It should contain a numerical value, defaulted to 0. In this example I have declared it using a :setvar statement. Test the affect of different values by changing the :setvar statement accordingly. Examples: :setvar DeployData 1 will deploy bucket 1 :setvar DeployData 2 will deploy bucket 2 :setvar DeployData 3   will deploy buckets 1 & 2 :setvar DeployData 6   will deploy buckets 2 & 3 :setvar DeployData 31  will deploy buckets 1, 2, 3, 4 & 5 */ :setvar DeployData 0 DECLARE  @bitmask VARBINARY(MAX) = CONVERT(VARBINARY,$(DeployData)); IF (@bitmask & 1 = 1) BEGIN     PRINT 'Bucket 1 insertions'; END IF (@bitmask & 2 = 2) BEGIN     PRINT 'Bucket 2 insertions'; END IF (@bitmask & 4 = 4) BEGIN     PRINT 'Bucket 3 insertions'; END IF (@bitmask & 8 = 8) BEGIN     PRINT 'Bucket 4 insertions'; END IF (@bitmask & 16 = 16) BEGIN     PRINT 'Bucket 5 insertions'; END An example of running this using DeployData=6 The binary representation of 6 is 110. The second and third significant bits of that binary number are set to 1 and hence buckets 2 and 3 are “activated”. Hope that makes sense and is useful to some of you! @Jamiet P.S. I used the awesome HTML Copy feature of Visual Studio’s Productivity Power Tools in order to format the T-SQL code above for this blog post.

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  • Evaluating Oracle Data Mining Has Never Been Easier - Evaluation "Kit" Available

    - by chberger
    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-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Now you can quickly and easily get set up to starting using Oracle Data Mining for evaluation purposes. Just go to the Oracle Technology Network (OTN) and follow these simple steps. Oracle Data Mining Evaluation "Kit" Instructions Step 1: Download and Install the Oracle Database 11g Release 2 Anyone can download and install the Oracle Database for free for evaluation purposes. Read OTN web site for details. 11.2.0.1.0 DB is the minimum, 11.2.0.2 is better and naturally 11.2.0.3 is best if you are a current customer and on active support. Either 32-bit or 64-bit is fine. 4GB of RAM or more works fine for SQL Developer and the Oracle Data Miner GUI extension. Downloading the database and installing it should take just about an hour or so, depending on your network and computer. For more instructions on setting up Oracle Data Mining see: http://www.oracle.com/technetwork/database/options/odm/dataminerworkflow-168677.html When you install the Oracle Database, the Sample Examples data should also be installed e.g.:Release 2 Examples win32_11gR2_examples.zip (565,154,740 bytes). Contains examples of how to use the Oracle Database. Download if you are new to Oracle and want to try some of the examples presented in the Documentation Step 2: Install SQL Developer 3.1 (the Oracle Data Mining Extension installs automatically) Step 3. Follow the four free step-by-step Oracle-by-Examples e-training lessons: Setting Up Oracle Data Miner 11g Release 2 This tutorial covers the process of setting up Oracle Data Miner 11g Release 2 for use within Oracle SQL Developer 3.0. Using Oracle Data Miner 11g Release 2 This tutorial covers the use of Oracle Data Miner to perform data mining against Oracle Database 11g Release 2. In this lesson, you examine and solve a data mining business problem by using the Oracle Data Miner graphical user interface (GUI). Star Schema Mining Using Oracle Data Miner This tutorial covers the use of Oracle Data Miner to perform star schema mining against Oracle Database 11g Release 2. Text Mining Using Oracle Data Miner This tutorial covers the use of Oracle Data Miner to perform text mining against Oracle Database 11g Release 2. That’s it! Easy, fun and the fastest way to get started evaluating Oracle Data Mining. Enjoy! Charlie

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  • Unit Testing Framework for XQuery

    - by Knut Vatsendvik
    This posting provides a unit testing framework for XQuery using Oracle Service Bus. It allows you to write a test case to run your XQuery transformations in an automated fashion. When the test case is run, the framework returns any differences found in the response. The complete code sample with install instructions can be downloaded from here. Writing a Unit Test You start a new Test Case by creating a Proxy Service from Workshop that comes with Oracle Service Bus. In the General Configuration page select Service Type to be Messaging Service           In the Message Type Configuration page link both the Request & Response Message Type to the TestCase element of the UnitTest.xsd schema                 The TestCase element consists of the following child elements The ID and optional Name element is simply used for reference. The Transformation element is the XQuery resource to be executed. The Input elements represents the input to run the XQuery with. The Output element represents the expected output. These XML documents are “also” represented as an XQuery resource where the XQuery function takes no arguments and returns the XML document. Why not pass the test data with the TestCase? Passing an XML structure in another XML structure is not very easy or at least not very human readable. Therefore it was chosen to represent the test data as an loadable resource in the OSB. However you are free to go ahead with another approach on this if wanted. The XMLDiff elements represents any differences found. A sample on input is shown here. Modeling the Message Flow Then the next step is to model the message flow of the Proxy Service. In the Request Pipeline create a stage node that loads the test case input data.      For this, specify a dynamic XQuery expression that evaluates at runtime to the name of a pre-registered XQuery resource. The expression is of course set by the input data from the test case.           Add a Run stage node. Assign the result of the XQuery, that is to be run, to a context variable. Define a mapping for each of the input variables added in previous stage.     Add a Compare stage. Like with the input data, load the expected output data. Do a compare using XMLDiff XQuery provided where the first argument is the loaded output test data, and the second argument the result from the Run stage. Any differences found is replaced back into the test case XMLDiff element. In case of any unexpected failure while processing, add an Error Handler to the Pipeline to capture the fault. To pass back the result add the following Insert action In the Response Pipeline. A sample on output is shown here.

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  • What Counts For a DBA – Decisions

    - by Louis Davidson
    It’s Friday afternoon, and the lead DBA, a very talented guy, is getting ready to head out for two well-earned weeks of vacation, with his family, when this error message pops up in his inbox: Msg 211, Level 23, State 51, Line 1. Possible schema corruption. Run DBCC CHECKCATALOG. His heart sinks. It’s ten…no eight…minutes till it’s time to walk out the door. He glances around at his coworkers, competent to handle many problems, but probably not up to the challenge of fixing possible database corruption. What does he do? After a few agonizing moments of indecision, he clicks shut his laptop. He’ll just wait and see. It was unlikely to come to anything; after all, it did say “possible” schema corruption, not definite. In that moment, his fate was sealed. The start of the solution to the problem (run DBCC CHECKCATALOG) had been right there in the error message. Had he done this, or at least took two of those eight minutes to delegate the task to a coworker, then he wouldn’t have ended up spending two-thirds of an idyllic vacation (for the rest of the family, at least) dealing with a problem that got consistently worse as the weekend progressed until the entire system was down. When I told this story to a friend of mine, an opera fan, he smiled and said it described the basic plotline of almost every opera or ‘Greek Tragedy’ ever written. The particular joy in opera, he told me, isn’t the warbly voiced leading ladies, or the plump middle-aged romantic leads, or even the music. No, what packs the opera houses in Italy is the drama of characters who, by the very nature of their life-experiences and emotional baggage, make all sorts of bad choices when faced with ordinary decisions, and so move inexorably to their fate. The audience is gripped by the spectacle of exotic characters doomed by their inability to see the obvious. I confess, my personal experience with opera is limited to Bugs Bunny in “What’s Opera, Doc?” (Elmer Fudd is a great example of a bad decision maker, if ever one existed), but I was struck by my friend’s analogy. If all the DBA cubicles were a stage, I think we would hear many similarly tragic tales, played out to music: “Error handling? We write our code to never experience errors, so nah…“ “Backups failed today, but it’s okay, we’ll back up tomorrow (we’ll back up tomorrow)“ And similarly, they would leave their audience gasping, not necessarily at the beauty of the music, or poetry of the lyrics, but at the inevitable, grisly fate of the protagonists. If you choose not to use proper error handling, or if you choose to skip a backup because, hey, you haven’t had a server crash in 10 years, then inevitably, in that moment you expected to be enjoying a vacation, or a football game, with your family and friends, you will instead be sitting in front of a computer screen, paying for your poor choices. Tragedies are very much part of IT. Most of a DBA’s day to day work has limited potential to wreak havoc; paperwork, timesheets, random anonymous threats to developers, routine maintenance and whatnot. However, just occasionally, you, as a DBA, will face one of those decisions that really matter, and which has the possibility to greatly affect your future and the future of your user’s data. Make those decisions count, and you’ll avoid the tragic fate of many an operatic hero or villain.

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  • AppKata - Enter the next level of programming exercises

    - by Ralf Westphal
    Doing CodeKatas is all the rage lately. That´s great since widely accepted exercises are important to further the art. They provide a means of communication across platforms and allow to compare results which is part of any deliberate practice. But CodeKatas suffer from their size. They are intentionally small, so they can be done again and again. Repetition helps to build habit and to dig deeper. Over time ever new nuances of the problem or one´s approach become visible. On the other hand, though, their small size limits the methods, techniques, technologies that can be applied. To improve your TDD skills doing CodeKatas might be enough. But what about other skills? Developing on a software in a team, designing larger pieces of software, iteratively releasing software… all this and more is kinda hard to train using the tiny CodeKata problems. That´s why I´d like to present here another kind of kata I call Application Kata (or just AppKata). AppKatas are larger programming problems. They require the development of “whole” applications, i.e. not just one class or method, but bunches of classes accessible through a user interface. Also AppKata problems always are split into iterations. To get the most out of them, just look at the requirements of one iteration at a time. This way you´re closer to reality where requirements evolve in unexpected ways. So if you´re looking for more of a challenge for your software development skills, check out these AppKatas – or invent your own. AppKatas are platform independent like CodeKatas. Use whatever programming language and IDE you like. Also use whatever approach to software development you like. Just be sensitive to how easy it is to evolve your code across iterations. Reflect on what went well and what not. Compare your solutions with others. Or – for even more challenge – go for the “Coding Carousel” (see below). CSV Viewer An application to view CSV files. Sounds easy, but watch out! Requirements sometimes drastically change if the customer is happy with what you delivered. Iteration 1 Iteration 2 Iteration 3 Iteration 4 Iteration 5 (to come) Questionnaire If you like GUI programming, this AppKata might be for you. It´s about an app to let people fill out questionnaires. Also this problem might be interestin for you, if you´re into DDD. Iteration 1 Iteration 2 (to come) Iteration 3 (to come) Iteration 4 (to come) Tic Tac Toe For developers who like game programming. Although Tic Tac Toe is a trivial game, this AppKata poses some interesting infrastructure challenges. The GUI, however, stays simple; leave any 3D ambitions at home ;-) Iteration 1 Iteration 2 (to come) Iteration 3 (to come) Iteration 4 (to come) Iteration 5 (to come) Coding Carousel There are many ways you can do AppKatas. Work on them alone or in a team, pitch several devs against each other in an AppKata contest – or go around in a Coding Carousel. For the Coding Carousel you need at least 3 dev teams (regardless of size). All teams work on the same iteration at the same time. But here´s the trick: After each iteration the teams swap their code. Whatever they did for iteration n will be the basis for changes another team has to apply in iteration n+1. The code is going around the teams like in a carousel. I promise you, that´s gonna be fun! :-)

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  • Hey Retailers, Are You Ready For The Holiday Season?

    - by Jeri Kelley
    With online holiday spending reaching $35.3 billion in 2011 and American shoppers spending just under $750 on average on their holiday purchases this year, how ready is your business for the 2012 holiday season?   ?? Today’s shoppers do not take their purchases lightly.  They are more connected, interact with more resources to make decisions, diligently compare products and services, seek out the best deals, and ask for input from friends and family.   This holiday season, as consumers browse for apparel, tablets, toys, and much more, they will be bombarded with retailer communication - from emails and commercials to countless search engine results and social recommendations.  With a flurry of activity coming at consumers from every channel and competitor, your success this year will rely on communicating a consistent, personalized message no matter where your customers are shopping.  Here are a few ideas to help with your commerce strategy this holiday season: CONSISTENCY COUNTS FOR MULTICHANNEL SHOPPERS??According to a November 2011 study commissioned by Oracle, “Channel Commerce 2011: The Consumer View,” 54% of consumers in the U.S. and Canada regularly employ two or more channels before they make a purchase.  While each channel has its own unique benefit, user profile, and purpose, it’s critical that your shoppers have a consistent core experience wherever they’re looking for information or making a purchase.  Be sure consumers can consistently search and browse the same product information and receive the same promotions online, on their mobile devices, and in-store.? USE YOUR CUSTOMER’S CONTEXT TO SURFACE RELEVANT CONTENTYour Web site is likely the hub of your holiday activity.  According to a Monetate infographic, 39% of shoppers will visit your Web site directly to find out about the best holiday deals.   Use everything you know about your customers from past purchase data to browsing history to provide a relevant experience at every click, and assemble content in a context that entices shoppers to buy online, or influences an offline purchase.? TAKE ADVANTAGE OF MOBILE BEHAVIOR?Having a mobile program is no longer a choice.   Armed with smartphones and tablets, consumers now have access to more and more product information and can compare products and prices from anywhere.  In fact, approximately 52% of smartphone users will use their device to research products, redeem coupons and use apps to assist in their holiday gift purchase.  At a minimum, be sure your mobile environment has store information, consistent pricing and promotions, and simple checkout capabilities. ARM IN-STORE ASSOCIATES WITH TABLETS?According to RISNews.com, 31% of retailers plan to begin testing tablets in stores in 2012, 22% have already begun such testing and 6% had fully deployed tablets within stores.   Take advantage of this compelling sales tool to get shoppers interacting with videos, user reviews, how-to guides, side-by-side product comparisons, and specs.  Automatically trigger upsell and cross sell suggestions for store associates to recommend for each product or category, build in alerts for promotions, and allow associates to place orders and check inventory from their tablet.  ? WISDOM OF THE CROWDS IS GOOD, BUT WISDOM FROM FRIENDS IS BETTER?Shoppers who grapple with options are looking for recommendations; they’d rather get advice from friends, and they’re more likely to spend more while doing so.    In fact, according to an infographic by Mr. Youth, 66% of social media users made a purchase on Black Friday or Cyber Monday as a direct result of social media interactions with brands or family.   This holiday season, be sure you are leveraging your social channels from Facebook to Pinterest to drive consistent promotions and help your brand to become part of the conversation. So, are you ready for the holidays this year?  

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  • EPM 11.1.2.2 Architecture: Financial Performance Management Applications

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

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  • Exploring TCP throughput with DTrace

    - by user12820842
    One key measure to use when assessing TCP throughput is assessing the amount of unacknowledged data in the pipe. This is sometimes termed the Bandwidth Delay Product (BDP) (note that BDP is often used more generally as the product of the link capacity and the end-to-end delay). In DTrace terms, the amount of unacknowledged data in bytes for the connection is the different between the next sequence number to send and the lowest unacknoweldged sequence number (tcps_snxt - tcps_suna). According to the theory, when the number of unacknowledged bytes for the connection is less than the receive window of the peer, the path bandwidth is the limiting factor for throughput. In other words, if we can fill the pipe without the peer TCP complaining (by virtue of its window size reaching 0), we are purely bandwidth-limited. If the peer's receive window is too small however, the sending TCP has to wait for acknowledgements before it can send more data. In this case the round-trip time (RTT) limits throughput. In such cases the effective throughput limit is the window size divided by the RTT, e.g. if the window size is 64K and the RTT is 0.5sec, the throughput is 128K/s. So a neat way to visually determine if the receive window of clients may be too small should be to compare the distribution of BDP values for the server versus the client's advertised receive window. If the BDP distribution overlaps the send window distribution such that it is to the right (or lower down in DTrace since quantizations are displayed vertically), it indicates that the amount of unacknowledged data regularly exceeds the client's receive window, so that it is possible that the sender may have more data to send but is blocked by a zero-window on the client side. In the following example, we compare the distribution of BDP values to the receive window advertised by the receiver (10.175.96.92) for a large file download via http. # dtrace -s tcp_tput.d ^C BDP(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count -1 | 0 0 | 6 1 | 0 2 | 0 4 | 0 8 | 0 16 | 0 32 | 0 64 | 0 128 | 0 256 | 3 512 | 0 1024 | 0 2048 | 9 4096 | 14 8192 | 27 16384 | 67 32768 |@@ 1464 65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 32396 131072 | 0 SWND(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count 16384 | 0 32768 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 17067 65536 | 0 Here we have a puzzle. We can see that the receiver's advertised window is in the 32768-65535 range, while the amount of unacknowledged data in the pipe is largely in the 65536-131071 range. What's going on here? Surely in a case like this we should see zero-window events, since the amount of data in the pipe regularly exceeds the window size of the receiver. We can see that we don't see any zero-window events since the SWND distribution displays no 0 values - it stays within the 32768-65535 range. The explanation is straightforward enough. TCP Window scaling is in operation for this connection - the Window Scale TCP option is used on connection setup to allow a connection to advertise (and have advertised to it) a window greater than 65536 bytes. In this case the scaling shift is 1, so this explains why the SWND values are clustered in the 32768-65535 range rather than the 65536-131071 range - the SWND value needs to be multiplied by two since the reciever is also scaling its window by a shift factor of 1. Here's the simple script that compares BDP and SWND distributions, fixed to take account of window scaling. #!/usr/sbin/dtrace -s #pragma D option quiet tcp:::send / (args[4]-tcp_flags & (TH_SYN|TH_RST|TH_FIN)) == 0 / { @bdp["BDP(bytes)", args[2]-ip_daddr, args[4]-tcp_sport] = quantize(args[3]-tcps_snxt - args[3]-tcps_suna); } tcp:::receive / (args[4]-tcp_flags & (TH_SYN|TH_RST|TH_FIN)) == 0 / { @swnd["SWND(bytes)", args[2]-ip_saddr, args[4]-tcp_dport] = quantize((args[4]-tcp_window)*(1 tcps_snd_ws)); } And here's the fixed output. # dtrace -s tcp_tput_scaled.d ^C BDP(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count -1 | 0 0 | 39 1 | 0 2 | 0 4 | 0 8 | 0 16 | 0 32 | 0 64 | 0 128 | 0 256 | 3 512 | 0 1024 | 0 2048 | 4 4096 | 9 8192 | 22 16384 | 37 32768 |@ 99 65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 3858 131072 | 0 SWND(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count 512 | 0 1024 | 1 2048 | 0 4096 | 2 8192 | 4 16384 | 7 32768 | 14 65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 1956 131072 | 0

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  • Design pattern for logging changes in parent/child objects saved to database

    - by andrew
    I’ve got a 2 database tables in parent/child relationship as one-many. I’ve got three classes representing the data in these two tables: Parent Class { Public int ID {get; set;} .. other properties } Child Class { Public int ID {get;set;} Public int ParentID {get; set;} .. other properties } TogetherClass { Public Parent Parent; Public List<Child> ChildList; } Lastly I’ve got a client and server application – I’m in control of both ends so can make changes to both programs as I need to. Client makes a request for ParentID and receives a Together Class for the matching parent, and all of the child records. The client app may make changes to the children – add new children, remove or modify existing ones. Client app then sends the Together Class back to the server app. Server app needs to update the parent and child records in the database. In addition I would like to be able to log the changes – I’m doing this by having 2 separate tables one for Parent, one for child; each containing the same columns as the original plus date time modified, by whom and a list of the changes. I’m unsure as to the best approach to detect the changes in records – new records, records to be deleted, records with no fields changed, records with some fields changed. I figure I need to read the parent & children records and compare those to the ones in the Together Class. Strategy A: If Together class’s child record has an ID of say 0, that indicates a new record; insert. Any deleted child records are no longer in the Together Class; see if any of the comparison child records are not found in the Together class and delete if not found (Compare using ID). Check each child record for changes and if changed log. Strategy B: Make a new Updated TogetherClass UpdatedClass { Public Parent Parent {get; set} Public List<Child> ListNewChild {get;set;} Public List<Child> DeletedChild {get;set;} Public List<Child> ExistingChild {get;set;} // used for no changes and modified rows } And then process as per the list. The reason why I’m asking for ideas is that both of these solutions don’t seem optimal to me and I suspect this problem has been solved already – some kind of design pattern ? I am aware of one potential problem in this general approach – that where Client App A requests a record; App B requests same record; A then saves changes; B then saves changes which may overwrite changes A made. This is a separate locking issue which I’ll raise a separate question for if I’ve got trouble implementing. The actual implementation is c#, SQL Server and WCF between client and server - sharing a library containing the class implementations. Apologies if this is a duplicate post – I tried searching various terms without finding a match though.

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  • Oracle Fusion Supply Chain Management (SCM) Designs May Improve End User Productivity

    - by Applications User Experience
    By Applications User Experience on March 10, 2011 Michele Molnar, Senior Usability Engineer, Applications User Experience The Challenge: The SCM User Experience team, in close collaboration with product management and strategy, completely redesigned the user experience for Oracle Fusion applications. One of the goals of this redesign was to increase end user productivity by applying design patterns and guidelines and incorporating findings from extensive usability research. But a question remained: How do we know that the Oracle Fusion designs will actually increase end user productivity? The Test: To answer this question, the SCM Usability Engineers compared Oracle Fusion designs to their corresponding existing Oracle applications using the workflow time analysis method. The workflow time analysis method breaks tasks into a sequence of operators. By applying standard time estimates for all of the operators in the task, an estimate of the overall task time can be calculated. The workflow time analysis method has been recently adopted by the Applications User Experience group for use in predicting end user productivity. Using this method, a design can be tested and refined as needed to improve productivity even before the design is coded. For the study, we selected some of our recent designs for Oracle Fusion Product Information Management (PIM). The designs encompassed tasks performed by Product Managers to create, manage, and define products for their organization. (See Figure 1 for an example.) In applying this method, the SCM Usability Engineers collaborated with Product Management to compare the new Oracle Fusion Applications designs against Oracle’s existing applications. Together, we performed the following activities: Identified the five most frequently performed tasks Created detailed task scenarios that provided the context for each task Conducted task walkthroughs Analyzed and documented the steps and flow required to complete each task Applied standard time estimates to the operators in each task to estimate the overall task completion time Figure 1. The interactions on each Oracle Fusion Product Information Management screen were documented, as indicated by the red highlighting. The task scenario and script provided the context for each task.  The Results: The workflow time analysis method predicted that the Oracle Fusion Applications designs would result in productivity gains in each task, ranging from 8% to 62%, with an overall productivity gain of 43%. All other factors being equal, the new designs should enable these tasks to be completed in about half the time it takes with existing Oracle Applications. Further analysis revealed that these performance gains would be achieved by reducing the number of clicks and screens needed to complete the tasks. Conclusions: Using the workflow time analysis method, we can expect the Oracle Fusion Applications redesign to succeed in improving end user productivity. The workflow time analysis method appears to be an effective and efficient tool for testing, refining, and retesting designs to optimize productivity. The workflow time analysis method does not replace usability testing with end users, but it can be used as an early predictor of design productivity even before designs are coded. We are planning to conduct usability tests later in the development cycle to compare actual end user data with the workflow time analysis results. Such results can potentially be used to validate the productivity improvement predictions. Used together, the workflow time analysis method and usability testing will enable us to continue creating, evaluating, and delivering Oracle Fusion designs that exceed the expectations of our end users, both in the quality of the user experience and in productivity. (For more information about studying productivity, refer to the Measuring User Productivity blog.)

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  • Crime Scene Investigation: SQL Server

    - by Rodney Landrum
    “The packages are running slower in Prod than they are in Dev” My week began with this simple declaration from one of our lead BI developers, quickly followed by an emailed spreadsheet demonstrating that, over 5 executions, an extensive ETL process was running average 630 seconds faster on Dev than on Prod. The situation needed some scientific investigation to determine why the same code, the same data, the same schema would yield consistently slower results on a more powerful server. Prod had yet to be officially christened with a “Go Live” date so I had the time, and having recently been binge watching CSI: New York, I also had the inclination. An inspection of the two systems, Prod and Dev, revealed the first surprise: although Prod was indeed a “bigger” system, with double the amount of RAM of Dev, the latter actually had twice as many processor cores. On neither system did I see much sign of resources being heavily taxed, while the ETL process was running. Without any real supporting evidence, I jumped to a conclusion that my years of performance tuning should have helped me avoid, and that was that the hardware differences explained the better performance on Dev. We spent time setting up a Test system, similarly scoped to Prod except with 4 times the cores, and ported everything across. The results of our careful benchmarks left us truly bemused; the ETL process on the new server was slower than on both other systems. We burned more time tweaking server configurations, monitoring IO and network latency, several times believing we’d uncovered the smoking gun, until the results of subsequent test runs pitched us back into confusion. Finally, I decided, enough was enough. Hadn’t I learned very early in my DBA career that almost all bottlenecks were caused by code and database design, not hardware? It was time to get back to basics. With over 100 SSIS packages and hundreds of queries, each handling specific tasks such as file loads, bulk inserts, transforms, logging, and so on, the task seemed formidable. And yet, after barely an hour spent with Profiler, Extended Events, and wait statistics DMVs, I had a lead in the shape of a query that joined three tables, containing millions of rows, returned 3279 results, but performed 239K logical reads. As soon as I looked at the execution plans for the query in Dev and Test I saw the culprit, an implicit conversion warning on a join predicate field that was numeric in one table and a varchar(50) in another! I turned this information over to the BI developers who quickly resolved the data type mismatches and found and fixed “several” others as well. After the schema changes the same query with the same databases ran in under 1 second on all systems and reduced the logical reads down to fewer than 300. The analysis also revealed that on Dev, the ETL task was pulling data across a LAN, whereas Prod and Test were connected across slower WAN, in large part explaining why the same process ran slower on the latter two systems. Loading the data locally on Prod delivered a further 20% gain in performance. As we progress through our DBA careers we learn valuable lessons. Sometimes, with a project deadline looming and pressure mounting, we choose to forget them. I was close to giving into the temptation to throw more hardware at the problem. I’m pleased at least that I resisted, though I still kick myself for not looking at the code on day one. It can seem a daunting prospect to return to the fundamentals of the code so close to roll out, but with the right tools, and surprisingly little time, you can collect the evidence that reveals the true problem. It is a lesson I trust I will remember for my next 20 years as a DBA, if I’m ever again tempted to bypass the evidence.

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  • Where Have All the Ugly Forms Gone? Users and ADF Took Care Of It

    - by ultan o'broin
    Sometimes I hear that our application demos are a bit too "cutsey" and that we never talk about with any user roles that have lots of data entry as a requirement. Some (no names) consider those old clunker forms, with the myriad rows of fields, to be super-productive for data clerks. We do have such roles covered in Oracle Fusion Applications for sure. But consider what is really the issue here: productivity. Check out how the Oracle Fusion Financials Applications User Experience team went about designing for productivity when receiving and entering invoice data, for example. See how Fusion Financials caters so well for input and control of data? Central to all this is knowing the users and how they work: what tasks do they need to perform, and when. Read more about Fusion Financials productivity in the white paper, Get It Done Fast, Get It Done Right: The Oracle Fusion Financials User Experience. Now and then, I see forms that weren't designed for end user activity at all. Instead, they were designed by developers or by the IT department around the database schema. Forms with literally dozens of fields on the same page, sometimes. Forms that give the impression there was only task involved, when there may have been several. At times, completing one of these huge forms accurately became so tedious that, under pressure, it made more sense for the user to complete it quickly as possible and then let somebody else check it for accuracy and fill in the gaps from data emailed along in spreadsheet form. Data accuracy is critical in our business. Not good. Not efficient. Not productive. So here are a few basics on forms design for data entry-type user roles. A great place for developers to start exploring what is possible with forms layout is the Rich Client User Experience (RCUX) guidance on Form Layout, using ADF components. User-Centered Forms Design Considerations The starting point--something you must always keep in mind with your own design--is design for the end user. Find a representative end user, and keep that user engaged throughout the design, deployment, and test process. Consider these points in user testing those forms: Are there automated or technical solutions to entering the data that avoid manual input in the first place? For example, imports, uploads, OCR, whatever. Some day we will be able to tell Siri to do it, but leave that for now. Design your form to reflect the task involved (i.e., the business process) and not the database schema. On the form, group like fields together, logically. Eliminate duplicate data entry or prepopulate from previous data entry. Allow users to complete fields in the order they wish (i.e., no interdependency). Allow for tabbing between fields (keyboard is faster than mouse), so know how the browser supports this (see that RCUX guideline). Allow for final validation at the page level not at field-level entry. Way better for heads-down users. For example, ADF messages allow you to see a list of all validation errors on a page on a final submit or navigation action and to easily navigate to the point of error. Better still, be error tolerant. Allow users to enter data in formats they comfortable with. Bind any relevant user preference setting to the input format allowed (for example, the locale date format). Explore what data entry conversion can do for you automatically too (see the ADF converter demos, convenience patterns can also be written). Only ask for data input when it's needed. Get rid of, or hide optional fields. Cut down on the number of mandatory fields, and mark them clearly (use a *). Clearly label the fields in plain language. I am sure you may have a few more tips on forms design for data entry users. Remember the user before finding the comments.

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  • how to write the code for this program specially in mathematica? [closed]

    - by asd
    I implemented a solution to the problem below in Mathematica, but it takes a very long time (hours) to compute f of kis or the set B for large numbers. Somebody suggested that implementing this in C++ resulted in a solution in less than 10 minutes. Would C++ be a good language to learn to solve these problems, or can my Mathematica code be improved to fix the performance issues? I don't know anything about C or C++ and it should be difficult to start to learn this languages. I prefer to improve or write new code in mathematica. Problem Description Let $f$ be an arithmetic function and A={k1,k2,...,kn} are integers in increasing order. Now I want to start with k1 and compare f(ki) with f(k1). If f(ki)f(k1), put ki as k1. Now start with ki, and compare f(kj) with f(ki), for ji. If f(kj)f(ki), put kj as ki, and repeat this procedure. At the end we will have a sub sequence B={L1,...,Lm} of A by this property: f(L(i+1))f(L(i)), for any 1<=i<=m-1 For example, let f is the divisor function of integers. Here I put some part of my code and this is just a sample and the question in my program could be more larger than these: «««««««««««««««««««««««««««««««««««« f[n_] := DivisorSigma[0, n]; g[n_] := Product[Prime[i], {i, 1, PrimePi[n]}]; k1 = g[67757] g[353] g[59] g[19] g[11] g[7] g[5]^2 6^3 2^7; k2 = g[67757] g[353] g[59] g[19] g[11] g[7] g[5] 6^5 2^7; k3 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5] 6^4 2^7; k4 = g[67759] g[349] g[53] g[19] g[11] g[7] g[5] 6^5 2^6; k5 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5] 6^4 2^8; k6 = g[67759] g[349] g[53] g[19] g[11] g[7] g[5]^2 6^3 2^7; k7 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5] 6^5 2^6; k8 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5] 6^4 2^9; k9 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5]^2 6^3 2^7; k10 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5] 6^5 2^7; k11 = g[67759] g[349] g[53] g[19] g[11] g[7] g[5]^2 6^4 2^6; k12 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5]^2 6^3 2^8; k13 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5]^2 6^4 2^6; k14 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5]^2 6^3 2^9; k15 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5]^2 6^4 2^7; k16 = g[67757] g[359] g[53] g[23] g[11] g[7] g[5] 6^4 2^8; k17 = g[67757] g[359] g[59] g[19] g[11] g[7] g[5] 6^4 2^7; k18 = g[67757] g[359] g[53] g[23] g[11] g[7] g[5] 6^4 2^9; k19 = g[67759] g[353] g[53] g[19] g[11] g[7] g[5] 6^4 2^6; k20 = g[67763] g[347] g[53] g[19] g[11] g[7] g[5] 6^4 2^7; k = Table[k1, k2, k3, k4, k5, k6, k7, k8, k9, k10, k11, k12, k13, k14, k15, k16, k17, k18, k19, k20]; i = 1; count = 0; For[j = i, j <= 20, j++, If[f[k[[j]]] - f[k[[i]]] > 0, i = j; Print["k",i]; count = count + 1]]; Print["count= ", count] ««««««««««««««««««««««««««««««««««««

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  • NHibernate Pitfalls: Custom Types and Detecting Changes

    - by Ricardo Peres
    This is part of a series of posts about NHibernate Pitfalls. See the entire collection here. NHibernate supports the declaration of properties of user-defined types, that is, not entities, collections or primitive types. These are used for mapping a database columns, of any type, into a different type, which may not even be an entity; think, for example, of a custom user type that converts a BLOB column into an Image. User types must implement interface NHibernate.UserTypes.IUserType. This interface specifies an Equals method that is used for comparing two instances of the user type. If this method returns false, the entity is marked as dirty, and, when the session is flushed, will trigger an UPDATE. So, in your custom user type, you must implement this carefully so that it is not mistakenly considered changed. For example, you can cache the original column value inside of it, and compare it with the one in the other instance. Let’s see an example implementation of a custom user type that converts a Byte[] from a BLOB column into an Image: 1: [Serializable] 2: public sealed class ImageUserType : IUserType 3: { 4: private Byte[] data = null; 5: 6: public ImageUserType() 7: { 8: this.ImageFormat = ImageFormat.Png; 9: } 10: 11: public ImageFormat ImageFormat 12: { 13: get; 14: set; 15: } 16: 17: public Boolean IsMutable 18: { 19: get 20: { 21: return (true); 22: } 23: } 24: 25: public Object Assemble(Object cached, Object owner) 26: { 27: return (cached); 28: } 29: 30: public Object DeepCopy(Object value) 31: { 32: return (value); 33: } 34: 35: public Object Disassemble(Object value) 36: { 37: return (value); 38: } 39: 40: public new Boolean Equals(Object x, Object y) 41: { 42: return (Object.Equals(x, y)); 43: } 44: 45: public Int32 GetHashCode(Object x) 46: { 47: return ((x != null) ? x.GetHashCode() : 0); 48: } 49: 50: public override Int32 GetHashCode() 51: { 52: return ((this.data != null) ? this.data.GetHashCode() : 0); 53: } 54: 55: public override Boolean Equals(Object obj) 56: { 57: ImageUserType other = obj as ImageUserType; 58: 59: if (other == null) 60: { 61: return (false); 62: } 63: 64: if (Object.ReferenceEquals(this, other) == true) 65: { 66: return (true); 67: } 68: 69: return (this.data.SequenceEqual(other.data)); 70: } 71: 72: public Object NullSafeGet(IDataReader rs, String[] names, Object owner) 73: { 74: Int32 index = rs.GetOrdinal(names[0]); 75: Byte[] data = rs.GetValue(index) as Byte[]; 76: 77: this.data = data as Byte[]; 78: 79: if (data == null) 80: { 81: return (null); 82: } 83: 84: using (MemoryStream stream = new MemoryStream(this.data ?? new Byte[0])) 85: { 86: return (Image.FromStream(stream)); 87: } 88: } 89: 90: public void NullSafeSet(IDbCommand cmd, Object value, Int32 index) 91: { 92: if (value != null) 93: { 94: Image data = value as Image; 95: 96: using (MemoryStream stream = new MemoryStream()) 97: { 98: data.Save(stream, this.ImageFormat); 99: value = stream.ToArray(); 100: } 101: } 102: 103: (cmd.Parameters[index] as DbParameter).Value = value ?? DBNull.Value; 104: } 105: 106: public Object Replace(Object original, Object target, Object owner) 107: { 108: return (original); 109: } 110: 111: public Type ReturnedType 112: { 113: get 114: { 115: return (typeof(Image)); 116: } 117: } 118: 119: public SqlType[] SqlTypes 120: { 121: get 122: { 123: return (new SqlType[] { new SqlType(DbType.Binary) }); 124: } 125: } 126: } In this case, we need to cache the original Byte[] data because it’s not easy to compare two Image instances, unless, of course, they are the same.

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  • How much is a subscriber worth?

    - by Tom Lewin
    This year at Red Gate, we’ve started providing a way to back up SQL Azure databases and Azure storage. We decided to sell this as a service, instead of a product, which means customers only pay for what they use. Unfortunately for us, it makes figuring out revenue much trickier. With a product like SQL Compare, a customer pays for it, and it’s theirs for good. Sure, we offer support and upgrades, but, fundamentally, the sale is a simple, upfront transaction: we’ve made this product, you need this product, we swap product for money and everyone is happy. With software as a service, it isn’t that easy. The money and product don’t change hands up front. Instead, we provide a service in exchange for a recurring fee. We know someone buying SQL Compare will pay us $X, but we don’t know how long service customers will stay with us, or how much they will spend. How do we find this out? We use lifetime value analysis. What is lifetime value? Lifetime value, or LTV, is how much a customer is worth to the business. For Entrepreneurs has a brilliant write up that we followed to conduct our analysis. Basically, it all boils down to this equation: LTV = ARPU x ALC To make it a bit less of an alphabet-soup and a bit more understandable, we can write it out in full: The lifetime value of a customer equals the average revenue per customer per month, times the average time a customer spends with the service Simple, right? A customer is worth the average spend times the average stay. If customers pay on average $50/month, and stay on average for ten months, then a new customer will, on average, bring in $500 over the time they are a customer! Average spend is easy to work out; it’s revenue divided by customers. The problem comes when we realise that we don’t know exactly how long a customer will stay with us. How can we figure out the average lifetime of a customer, if we only have six months’ worth of data? The answer lies in the fact that: Average Lifetime of a Customer = 1 / Churn Rate The churn rate is the percentage of customers that cancel in a month. If half of your customers cancel each month, then your average customer lifetime is two months. The problem we faced was that we didn’t have enough data to make an estimate of one month’s cancellations reliable (because barely anybody cancels)! To deal with this data problem, we can take data from the last three months instead. This means we have more data to play with. We can still use the equation above, we just need to multiply the final result by three (as we worked out how many three month periods customers stay for, and we want our answer to be in months). Now these estimates are likely to be fairly unreliable; when there’s not a lot of data it pays to be cautious with inference. That said, the numbers we have look fairly consistent, and it’s super easy to revise our estimates when new data comes in. At the very least, these numbers give us a vague idea of whether a subscription business is viable. As far as Cloud Services goes, the business looks very viable indeed, and the low cancellation rates are much more than just data points in LTV equations; they show that the product is working out great for our customers, which is exactly what we’re looking for!

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  • We have our standards, and we need them

    - by Tony Davis
    The presenter suddenly broke off. He was midway through his section on how to apply to the relational database the Continuous Delivery techniques that allowed for rapid-fire rounds of development and refactoring, while always retaining a “production-ready” state. He sighed deeply and then launched into an astonishing diatribe against Database Administrators, much of his frustration directed toward Oracle DBAs, in particular. In broad strokes, he painted the picture of a brave new deployment philosophy being frustratingly shackled by the relational database, and by especially by the attitudes of the guardians of these databases. DBAs, he said, shunned change and “still favored tools I’d have been embarrassed to use in the ’80′s“. DBAs, Oracle DBAs especially, were more attached to their vendor than to their employer, since the former was the primary source of their career longevity and spectacular remuneration. He contended that someone could produce the best IDE or tool in the world for Oracle DBAs and yet none of them would give a stuff, unless it happened to come from the “mother ship”. I sat blinking in astonishment at the speaker’s vehemence, and glanced around nervously. Nobody in the audience disagreed, and a few nodded in assent. Although the primary target of the outburst was the Oracle DBA, it made me wonder. Are we who work with SQL Server, database professionals or merely SQL Server fanbois? Do DBAs, in general, have an image problem? Is it a good career-move to be seen to be holding onto a particular product by the whites of our knuckles, to the exclusion of all else? If we seek a broad, open-minded, knowledge of our chosen technology, the database, and are blessed with merely mortal powers of learning, then we like standards. Vendors of RDBMSs generally don’t conform to standards by instinct, but by customer demand. Microsoft has made great strides to adopt the international SQL Standards, where possible, thanks to considerable lobbying by the community. The implementation of Window functions is a great example. There is still work to do, though. SQL Server, for example, has an unusable version of the Information Schema. One cast-iron rule of any RDBMS is that we must be able to query the metadata using the same language that we use to query the data, i.e. SQL, and we do this by running queries against the INFORMATION_SCHEMA views. Developers who’ve attempted to apply a standard query that works on MySQL, or some other database, but doesn’t produce the expected results on SQL Server are advised to shun the Standards-based approach in favor of the vendor-specific one, using the catalog views. The argument behind this is sound and well-documented, and of course we all use those catalog views, out of necessity. And yet, as database professionals, committed to supporting the best databases for the business, whatever they are now and in the future, surely our heart should sink somewhat when we advocate a vendor specific approach, to a developer struggling with something as simple as writing a guard clause. And when we read messages on the Microsoft documentation informing us that we shouldn’t rely on INFORMATION_SCHEMA to identify reliably the schema of an object, in SQL Server!

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  • Security Access Control With Solaris Virtualization

    - by Thierry Manfe-Oracle
    Numerous Solaris customers consolidate multiple applications or servers on a single platform. The resulting configuration consists of many environments hosted on a single infrastructure and security constraints sometimes exist between these environments. Recently, a customer consolidated many virtual machines belonging to both their Intranet and Extranet on a pair of SPARC Solaris servers interconnected through Infiniband. Virtual Machines were mapped to Solaris Zones and one security constraint was to prevent SSH connections between the Intranet and the Extranet. This case study gives us the opportunity to understand how the Oracle Solaris Network Virtualization Technology —a.k.a. Project Crossbow— can be used to control outbound traffic from Solaris Zones. Solaris Zones from both the Intranet and Extranet use an Infiniband network to access a ZFS Storage Appliance that exports NFS shares. Solaris global zones on both SPARC servers mount iSCSI LU exported by the Storage Appliance.  Non-global zones are installed on these iSCSI LU. With no security hardening, if an Extranet zone gets compromised, the attacker could try to use the Storage Appliance as a gateway to the Intranet zones, or even worse, to the global zones as all the zones are reachable from this node. One solution consists in using Solaris Network Virtualization Technology to stop outbound SSH traffic from the Solaris Zones. The virtualized network stack provides per-network link flows. A flow classifies network traffic on a specific link. As an example, on the network link used by a Solaris Zone to connect to the Infiniband, a flow can be created for TCP traffic on port 22, thereby a flow for the ssh traffic. A bandwidth can be specified for that flow and, if set to zero, the traffic is blocked. Last but not least, flows are created from the global zone, which means that even with root privileges in a Solaris zone an attacker cannot disable or delete a flow. With the flow approach, the outbound traffic of a Solaris zone is controlled from outside the zone. Schema 1 describes the new network setting once the security has been put in place. Here are the instructions to create a Crossbow flow as used in Schema 1 : (GZ)# zoneadm -z zonename halt ...halts the Solaris Zone. (GZ)# flowadm add-flow -l iblink -a transport=TCP,remote_port=22 -p maxbw=0 sshFilter  ...creates a flow on the IB partition "iblink" used by the zone to connect to the Infiniband.  This IB partition can be identified by intersecting the output of the commands 'zonecfg -z zonename info net' and 'dladm show-part'.  The flow is created on port 22, for the TCP traffic with a zero maximum bandwidth.  The name given to the flow is "sshFilter". (GZ)# zoneadm -z zonename boot  ...restarts the Solaris zone now that the flow is in place.Solaris Zones and Solaris Network Virtualization enable SSH access control on Infiniband (and on Ethernet) without the extra cost of a firewall. With this approach, no change is required on the Infiniband switch. All the security enforcements are put in place at the Solaris level, minimizing the impact on the overall infrastructure. The Crossbow flows come in addition to many other security controls available with Oracle Solaris such as IPFilter and Role Based Access Control, and that can be used to tackle security challenges.

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  • MySQL for Excel new features (1.2.0): Save and restore Edit sessions

    - by Javier Rivera
    Today we are going to talk about another new feature included in the latest MySQL for Excel release to date (1.2.0) which can be Installed directly from our MySQL Installer downloads page.Since the first release you were allowed to open a session to directly edit data from a MySQL table at Excel on a worksheet and see those changes reflected immediately on the database. You were also capable of opening multiple sessions to work with different tables at the same time (when they belong to the same schema). The problem was that if for any reason you were forced to close Excel or the Workbook you were working on, you had no way to save the state of those open sessions and to continue where you left off you needed to reopen them one by one. Well, that's no longer a problem since we are now introducing a new feature to save and restore active Edit sessions. All you need to do is in click the options button from the main MySQL for Excel panel:  And make sure the Edit Session Options (highlighted in yellow) are set correctly, specially that Restore saved Edit sessions is checked: Then just begin an Edit session like you would normally do, select the connection and schema on the main panel and then select table you want to edit data from and click over Edit MySQL Data. and just import the MySQL data into Excel:You can edit data like you always did with the previous version. To test the save and restore saved sessions functionality, first we need to save the workbook while at least one Edit session is opened and close the file.Then reopen the workbook. Depending on your version of Excel is where the next steps are going to differ:Excel 2013 extra step (first): In Excel 2013 you first need to open the workbook with saved edit sessions, then click the MySQL for Excel Icon on the the Data menu (notice how in this version, every time you open or create a new file the MySQL for Excel panel is closed in the new window). Please note that if you work on Excel 2013 with several workbooks with open edit sessions each at the same time, you'll need to repeat this step each time you open one of them: Following steps:  In Excel 2010 or previous, you just need to make sure the MySQL for Excel panel is already open at this point, if its not, please do the previous step specified above (Excel 2013 extra step). For Excel 2010 or older versions you will only need to do this previous step once.  When saved sessions are detected, you will be prompted what to do with those sessions, you can click Restore to continue working where you left off, click Discard to delete the saved sessions (All edit session information for this file will be deleted from your computer, so you will no longer be prompted the next time you open this same file) or click Nothing to continue without opening saved sessions (This will keep the saved edit sessions intact, to be prompted again about them the next time you open this workbook): And there you have it, now you will be able to save your Edit sessions, close your workbook or turn off your computer and you will still be able to reopen them in the future, to continue working right where you were. Today we talked about how you can save your active Edit sessions and restore them later, this is another feature included in the latest MySQL for Excel release (1.2.0). Please remember you can try this product and many others for free downloading the installer directly from our MySQL Installer downloads page.Happy editing !

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  • Consolidation in a Database Cloud

    - by B R Clouse
    Consolidation of multiple databases onto a shared infrastructure is the next step after Standardization.  The potential consolidation density is a function of the extent to which the infrastructure is shared.  The three models provide increasing degrees of sharing: Server: each database is deployed in a dedicated VM. Hardware is shared, but most of the software infrastructure is not. Standardization is often applied incompletely since operating environments can be moved as-is onto the shared platform. The potential for VM sprawl is an additional downside. Database: multiple database instances are deployed on a shared software / hardware infrastructure. This model is very efficient and easily implemented with the features in the Oracle Database and supporting products. Many customers have moved to this model and achieved significant, measurable benefits. Schema: multiple schemas are deployed within a single database instance. The most efficient model, it places constraints on the environment. Usually this model will be implemented only by customers deploying their own applications.  (Note that a single deployment can combine Database and Schema consolidations.) Customer value: lower costs, better system utilization In this phase of the maturity model, under-utilized hardware can be used to host more workloads, or retired and those workloads migrated to consolidation platforms. Customers benefit from higher utilization of the hardware resources, resulting in reduced data center floor space, and lower power and cooling costs. And, the OpEx savings from Standardization are multiplied, since there are fewer physical components (both hardware and software) to manage. Customer value: higher productivity The OpEx benefits from Standardization are compounded since not only are there fewer types of things to manage, now there are fewer entities to manage. In this phase, customers discover that their IT staff has time to move away from "day-to-day" tasks and start investing in higher value activities. Database users benefit from consolidating onto shared infrastructures by relieving themselves of the requirement to maintain their own dedicated servers. Also, if the shared infrastructure offers capabilities such as High Availability / Disaster Recovery, which are often beyond the budget and skillset of a standalone database environment, then moving to the consolidation platform can provide access to those capabilities, resulting in less downtime. Capabilities / Characteristics In this phase, customers will typically deploy fixed-size clusters and consolidate on a cluster until that cluster is deemed "full," at which point a new cluster is built. Customers will define one or a few cluster architectures that are used wherever possible; occasionally there may be deployments which must be handled as exceptions. The "full" policy may be based on number of databases deployed on the cluster, or observed peak workload, etc. IT will own the provisioning of new databases on a cluster, making the decision of when and where to place new workloads. Resources may be managed dynamically, e.g., as a priority workload increases, it may be given more CPU and memory to handle the spike. Users will be charged at a fixed, relatively coarse level; or in some cases, no charging will be applied. Activities / Tasks Oracle offers several tools to plan a successful consolidation. Real Application Testing (RAT) has a feature to help plan and validate database consolidations. Enterprise Manager 12c's Cloud Management Pack for Database includes a planning module. Looking ahead, customers should start planning for the Services phase by defining the Service Catalog that will be made available for database services.

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

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

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  • Multitenancy in SQL Azure

    - by cibrax
    If you are building a SaaS application in Windows Azure that relies on SQL Azure, it’s probably that you will need to support multiple tenants at database level. This is short overview of the different approaches you can use for support that scenario, A different database per tenant A new database is created and assigned when a tenant is provisioned. Pros Complete isolation between tenants. All the data for a tenant lives in a database only he can access. Cons It’s not cost effective. SQL Azure databases are not cheap, and the minimum size for a database is 1GB.  You might be paying for storage that you don’t really use. A different connection pool is required per database. Updates must be replicated across all the databases You need multiple backup strategies across all the databases Multiple schemas in a database shared by all the tenants A single database is shared among all the tenants, but every tenant is assigned to a different schema and database user. Pros You only pay for a single database. Data is isolated at database level. If the credentials for one tenant is compromised, the rest of the data for the other tenants is not. Cons You need to replicate all the database objects in every schema, so the number of objects can increase indefinitely. Updates must be replicated across all the schemas. The connection pool for the database must maintain a different connection per tenant (or set of credentials) A different user is required per tenant, which is stored at server level. You have to backup that user independently. Centralizing the database access with store procedures in a database shared by all the tenants A single database is shared among all the tenants, but nobody can read the data directly from the tables. All the data operations are performed through store procedures that centralize the access to the tenant data. The store procedures contain some logic to map the database user to an specific tenant. Pros You only pay for a single database. You only have a set of objects to maintain and backup. Cons There is no real isolation. All the data for the different tenants is shared in the same tables. You can not use traditional ORM like EF code first for consuming the data. A different user is required per tenant, which is stored at server level. You have to backup that user independently. SQL Federations A single database is shared among all the tenants, but a different federation is used per tenant. A federation in few words, it’s a mechanism for horizontal scaling in SQL Azure, which basically uses the idea of logical partitions to distribute data based on certain criteria. Pros You only have a single database with multiple federations. You can use filtering in the connections to pick the right federation, so any ORM could be used to consume the data. Cons There is no real isolation at that database level. The isolation is enforced programmatically with federations.

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  • SPException: Catastrophic failure (Exception from HRESULT: 0x8000FFF (E_UNEXPECTED) in Sharepoint

    - by BeraCim
    I've been trying to programmatically copy custom content type and its custom columns from one web to another for some time now, and I always get different errors or exceptions every time. After yet more tries, I received more strange and cryptic exception from Sharepoint after clicking onto a newly copied custom column in a custom content type. I checked the logs, and this is what I got: Unknown SPRequest erorr occurred. More information: 0x80070002 Unable to locate the xml-definition for FieldName with FieldId 'guid without braces', exception: Microsoft.SharePoint.SPException: Catastrophic failure (Exception from HRESULT: 0x8000FFF (E_UNEXPECTED)) ---> System.Runtime.InteropServices.COMException... ... at Microsoft.SharePoint.Library.SPRequestInternalClass.GetGlobalContentTypeXml(String bstrUrl, Int32 type, UInt 32 lcid, Object varIdBytes... Failed to find the content type schema for ct-1033-0x1000blahblahblahcontenttypeId while caching feature data. Unknown SPRequest error occurred. More informationL 0x8000ffff Unable to locate the xml-definition for CType with SPContentTypeId '0x0100MorecontenttypeId', exception: Microsoft.SharePoint.SPException: Catastrophic failure(Exception from HRESULT: 0x8000FFFF (E_UNEXPECTED)) ---> System.Runtime.InteropServices.COMException (0x8000FFFF): Catastrophic failure... ... at Microsoft.SharePoint.Library.SPRequestInternalClass.GetGlobalContentTypeXml(String bstrUrl, Int32 type, UInt 32 lcid, Object varIdBytes... It failed to find quite a few content type schema. I'm confused with what Sharepoint is trying to do here, and why a simple process of copying a custom content type from one web to another just wouldn't work in contrast to the information found on the web e.g. this. Appreciate any help to get over this problem. Thanks.

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  • Subsonic : Can’t decide which property to consider the Key? foreign key issue.

    - by AJ
    Hi I am trying to select count of rows from a table which has foreign keys of two tables. The C# code threw the error mentioned below. So, I added a primary key column to the table (schema as follows) and regenerated the code. But still the same error is coming. Error : Can't decide which property to consider the Key - you can create one called 'ID' or mark one with SubSonicPrimaryKey attribute sqLite Table schema CREATE TABLE "AlbumDocuments" ("Id" INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL , "AlbumId" INTEGER NOT NULL CONSTRAINT fk_AlbumId REFERENCES Albums(Id) , "DocumentId" INTEGER NOT NULL CONSTRAINT fk_DocumentId REFERENCES Documents(Id)) C# code int selectAlbumDocumentsCount = new SubSonic.Query.Select() .From<DocSafeDB.DataLayer.AlbumDocumentsTable>() .Where(DocSafeDB.DataLayer.AlbumDocumentsTable.AlbumIdColumn).In(request.AlbumId) .Execute(); Not sure what I should be doing next as I can't do where against primary key because I don;t have that info. So my questions are: How do I select count of rows against foreign key column? Is primary key required in this scenario? I have several things but not sure why its not working. To me it looks like a very normal use case. Please advise. Thanks AJ

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