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  • dictionary/map/key-value pairs data structure in C

    - by morgancodes
    How does one construct and access a set of key-value pairs in C? To use a silly simple example, let's say I want to create a table which translates between an integer and its square root. If I were writing javascript, I could just do this: var squareRoots = { 4: 2, 9: 3, 16: 4, 25: 5 } and then access them like: var squareRootOf25 = squareRoots[5] What's the prettiest way to do this in C? What if I want to use one type of enum as the key and another type of enum as the value?

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  • Sesame Data Browser: filtering, sorting, selecting and linking

    - by Fabrice Marguerie
    I have deferred the post about how Sesame is built in favor of publishing a new update.This new release offers major features such as the ability to quickly filter and sort data, select columns, and create hyperlinks to OData. Filtering, sorting, selecting In order to filter data, you just have to use the filter row, which becomes available when you click on the funnel button: You can then type some text and select an operator: The data grid will be refreshed immediately after you apply a filter. It works in the same way for sorting. Clicking on a column will immediately update the query and refresh the grid.Note that multi-column sorting is possible by using SHIFT-click: Viewing data is not enough. You can also view and copy the query string that returns that data: One more thing you can to shape data is to select which columns are displayed. Simply use the Column Chooser and you'll be done: Again, this will update the data and query string in real time: Linking to Sesame, linking to OData The other main feature of this release is the ability to create hyperlinks to Sesame. That's right, you can ask Sesame to give you a link you can display on a webpage, send in an email, or type in a chat session. You can get a link to a connection: or to a query: You'll note that you can also decide to embed Sesame in a webpage... Here are some sample links created via Sesame: Netflix movies with high ratings, sorted by release year Netflix horror movies from the 21st century Northwind discontinued products with remaining stock Netflix empty connection I'll give more examples in a post to follow. There are many more minor improvements in this release, but I'll let you find out about them by yourself :-)Please try Sesame Data Browser now and let me know what you think! PS: if you use Sesame from the desktop, please use the "Remove this application" command in the context menu of the destkop app and then "Install on desktop" again in your web browser. I'll activate automatic updates with the next release.

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  • Webinar: NoSQL - Data Center Centric Application Enablement

    - by Charles Lamb
    NoSQL - Data Center Centric Application Enablement AUGUST 6 WEBINAR About the Webinar The growth of Datacenter infrastructure is trending out of bounds, along with the pace in user activity and data generation in this digital era. However, the nature of the typical application deployment within the data center is changing to accommodate new business needs. Those changes introduce complexities in application deployment architecture and design, which cascade into requirements for a new generation of database technology (NoSQL) destined to ease that complexity. This webcast will discuss the modern data centers data centric application, the complexities that must be dealt with and common architectures found to describe and prescribe new data center aware services. Well look at the practical issues in implementation and overview current state of art in NoSQL database technology solving the problems of data center awareness in application development. REGISTER NOW>> MORE INFORMATION >> NOTE! All attendees will be entered to win a guest pass to the NoSQL Now! 2013 Conference & Expo. About the Speaker Robert Greene, Oracle NoSQL Product Management Robert GreeneRobert Greene is a principle product manager / strategist for Oracle’s NoSQL Database technology. Prior to Oracle he was the V.P. Technology for a NoSQL Database company, Versant Corporation, where he set the strategy for alignment with Big Data technology trends resulting in the acquisition of the company by Actian Corp in 2012. Robert has been an active member of both commercial and open source initiatives in the NoSQL and Object Relational Mapping spaces for the past 18 years, developing software, leading project teams, authoring articles and presenting at major conferences on these topics. In his previous life, Robert was an electronic engineer developing first generation wireless, spread spectrum based security systems.

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  • Internal Data Masking

    - by ACShorten
    By default, the data in the product is unmasked for authorized users. If particular data within the object is considered a candidate for data masking then the masking capabilities with the product can be used to mask the data in an appropriate fashion. The inbuilt Data Masking capabilities of the Oracle Utilities Application Framework uses a number of configuration elements: An algorithm, of type F1-MASK, is specified to configure the elements of the data masking including the masking character, number of suffix characters left unmasked, characters to ignore in the string, the application service, security type and authorization levels applicable to the mask. A Data Masking Feature Configuration is created to define where the algorithm applies. The specification of the feature allows you to define the fields to encrypt using the configured algorithm. The algorithm can be attached to a schema field, table field, characteristic, search field and even a child record (such as an identifier). The appropriate user groups are then connected to the application services with the appropriate service types and level to indicate whether the masking applies to the user group or not. For example, say there is a field called CCNBR in the product which holds the credit card details. I would create an algorithm, say CCformatCC, to mask the credit card number with the last few digits as unmasked (as the standard in most systems dictate). I would specify on the Field Mask the following: field="CCNBR", alg="CMformatCC" On the algorithm CMfomatCC, I would specify the mask, application service, security type and the authorization level which users would see the credit card unmasked. To finish the configuration off and to implemention I would connect the appropriate user groups to the application service I specified with the security type and appropriate authorization level for that group. Whenever a user accesses the CCNBR field on any of the maintenance screens, searches and other screens that use the CCNBR meta data definition would then be masked according to the user group that the user was a member of. Refer to the documentation supplied with F1-MASK algorithm type entry for more examples of what is possible.

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  • Cross-Platform Migration using Heterogeneous Data Guard

    - by Roy F. Swonger
    Most people think of Data Guard as a disaster recovery solution, and it certainly excels in that role. However, did you know that you can also use Data Guard for platform migration under some conditions? While you would normally have your primary and standby Data Guard systems running on the same OS and hardware platform, there are some heterogeneous combinations of primary and stanby system that are supported by Data Guard Physical Standby. One example of heterogenous Data Guard support is the ability to go between Linux and Windows on many processor architectures. Another is the support for environments that are running HP-UX on both PA-RIsC and Itanium hardware. Brand new in 11.2.0.2 is the ability to have both SPARC Solaris and IBM AIX on Power Systems in the same Data Guard environment. See My Oracle Support note 413484.1 for all the details about supported platform combinations. So, why mention this in an upgrade blog? Simple: much of the time required for a platform migration is usually spent copying files from one system to another. If you are moving between systems that are supported by heterogenous Data Guard, then you can reduce that migration downtime to a matter of minutes. This can be a big win when downtime is at a premium (and isn't downtime always at a premium? In addition, you get the benefit of being able to keep the old and new environments synchronized until you are sure the migration is successful! A great case study of using Data Guard for a technology refresh is located on this OTN page. The case study showing CERN's methodology isn't highlighted as a link on the overview page, but it is clickable. As always, make sure you are fully versed on the details and restrictions by reading the available documentation and MOS notes. Happy migrating!

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  • SFTP permission denied on files owned by www-data

    - by Charles Roper
    I have a pretty standard server set up running Apache and PHP. An app I am running creates files and these are owned by the Apache user www-data. Files that I upload via SFTP are owned by my own user charlesr. All files are part of the www-data group. My problem is that I cannot modify or overwrite any of the files via SFTP which are owned by www-data, even though charlesr is part of the www-data group. I can modify the files no problem via a SSH session. So I'm not sure what to do. How do I give my SFTP session permissions to modify www-data owned files? For a bit of background, these are the notes I wrote for myself when setting-up the server: Now set up permissions on `/var/www` where your files are served from by default: $ sudo adduser $USER www-data $ sudo chgrp -R www-data /var/www $ sudo chmod -R g+rw /var/www $ sudo chmod -R g+s /var/www Now log out and log in again to make the changes take hold. The previous set of commands does the following: 1. adds the current user ($USER) to the `www-data` group; 2. changes `/var/www` to belong to the `www-data` group; 3. adds read/write permissions to the group that `/var/www` belongs to; 4. sets the SGID bit on `/var/www`; this final point bears some explaining. And then I go on to explain to myself what setting the SGID bit means (i.e. all files created in /var/www become part of the www-data group automatically). Btw, nothing feels sweeter than going back and reading your own detailed notes on the what, how and why of your own server set up when trying to troubleshoot like this - I recommend it highly to all beginners like myself :-)

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  • How do I find the JavaScript that is invoked when I click on a button or a link in a web-page (part of a data mining project)?

    - by aste123
    I tried to use the 'inspect element' of the firebug addon for Firefox but it doesn't give me any link to the javascript. For example I got this from the firebug addon: < a href="javascript:" text of the link < /a But there is no link to the actual javascript or anything that I can use to directly go to the said link. How do I accomplish this? I need this as part of a personal data mining project that I am doing.

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  • Spreading incoming batched data into a real-time stream

    - by pr1001
    I would like to display some events in 'real-time'. However, I must fetch the data from another source. I can request the last X minutes, though the source is updated approximately every 5 minutes. This means that there will be a delay between the most recent data retrieved and the point in time that I make the request. Second, because I will be receiving a batch of data, I don't want to just fire out all the events down a socket once my fetcher has retrieved it: I would like to spread out the events so that they are both accurately spaced amongst each other and in sync with their original occurrences (e.g. an event is always displayed 6 minutes after it actually happened). My thought is to fetch the data every 5 minutes from the source, knowing that I won't get the very latest data. The original data would be then queued to be sent down the socket 7.5 minutes from its original timestamp – that is, at least ~2.5 minutes from when its batch was fetched and at most 7.5 minutes since then. My question is this: is this the best way to approach the problem? Does this problem have any standard approaches or associated literature related to implementation best-practices and edge cases? I am a bit worried that the frequency of my fetches and the frequency in which the source is updated will get out of sync, leading to points where no data will be retrieved from the source. However, since my socket delay is greater than my fetch frequency, the subsequent fetch should retrieve newer data before the socket queue is empty. Is that correct? Am I missing something? Thanks!

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  • Using R on your Oracle Data Warehouse

    - by jean-pierre.dijcks
    Since it is Predictive Analytics World in our backyard (or are we San Francisco’s backyard…?) I figured it is well worth the time to dust of some old but important news. With big data (should we start calling it “any data analytics” instead?) being the buzz word and analytics the key operative goal, not moving data around is becoming more and more critical to the business users. Why? Because instead of spending time on moving data around into your next analytics server you should be running analytics on those CPUs. You could always do this with Oracle Data Mining within the Oracle Database. But a lot of folks want to leverage R as their main tool. Well, this article describes how you can do this, since 2010… As Casimir Saternos concludes in the article; “There is a growing awareness of the need to effectively analyze astronomical amounts of data, much of which is stored in Oracle databases. Statistics and modeling techniques are used to improve a wide variety of business functions. ODM accessed using the R language increases the value of your data by uncovering additional information. RODM is a powerful tool to enable your organization to make predictions, classify data, and create visualizations that maximize effectiveness and efficiencies.” Happy Analysis!

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  • What is a Relational Database Management System (RDBMS)?

    A Relational Database Management System (RDBMS)  can also be called a traditional database that uses a Structured Query Language (SQL) to provide access to stored data while insuring the integrity of the data. The data is stored in a collection of tables that is defined by relationships between data items. In addition, data permitted to be joined in new relationships. Traditional databases primarily process data through transactions called transaction processing. Transaction processing is the methodology of grouping related business operations based predefined business events. An example of this can be seen when a person attempts to purchase an item from an online e-tailor. The business must execute specific operations for a related  business event. In this case, a business must store the following information: Customer Info, Order Info, Order Item Info, Customer Payment Data, Payment Results, and Current Order Status. Example: Pseudo SQL Operations needed for processing an online e-tailor sale. Insert Customer into Customers Insert New Order into Orders Insert Each New Order Item into OrderItems Insert Customer Payment Info into PaymentInfo Insert Payment Processing Result into PaymentDetails Update Customer for Current Order Status Common Relational Database Management System Microsoft SQL Server Microsoft Access Oracle MySQL DB2 It is important to note that no current RDBMS has fully implemented all of the Relational Principles. Common RDBMS Traits Volatile Data Supports Transaction Processing Optimized for Updates and Simple Queries 

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  • Olympics data available for all on Windows Azure SQL Database and Power View

    - by jamiet
    Are you looking around for some decent test data for your BI demos? Well, if so, Microsoft have provided some data about all medals won at the Olympics Games (1900 to 2008) at OlympicsData workbook - Excel, SSIS, Azure sample; it provides analysis over athletes, countries, medal type, sport, discipline and various other dimensions. The data has been provided in an Excel workbook along with instructions on how to load the data into a Windows Azure SQL Database using SQL Server Integration Services (SSIS). Frankly though, the rigmarole of standing up your own Windows Azure SQL Database ok, SQL Azure database, is both costly (SQL Azure isn’t free) and time consuming (the provided instructions aren’t exactly an idiot’s guide and getting SSIS to work properly with Excel isn’t a barrel of laughs either). To ease the pain for all you BI folks out there that simply want to party on the data I have loaded it all into the SQL Azure database that I use for hosting AdventureWorks on Azure. You can read more about AdventureWorks on Azure below however I’ll summarise here by saying it is a SQL Azure database provided for the use of the SQL Server community and which is supported by voluntary donations. To view the data the credentials you need are: Server mhknbn2kdz.database.windows.net  Database AdventureWorks2012 User sqlfamily Password sqlf@m1ly Type those into SSMS and away you go, the data is provided in four tables [olympics].[Sport], [olympics].[Discipline], [olympics].[Event] & [olympics].[Medalist]: I figured this would be a good candidate for a Power View report so I fired up Excel 2013 and built such a report to slice’n’dice through the data – here are some screenshots that should give you a flavour of what is available: A view of all the available data Where do all the gymastics medals go? Which countries do top ten all-time medal winners come from? You get the idea. There is masses of information here and if you have Excel 2013 handy Power View provides a quick and easy way of surfing through it. To save you the bother of setting up the Power View report yourself you can have the one that I took these screenshots from, it is available on my SkyDrive at OlympicsAnalysis.xlsx so just hit the link and download to play to your heart’s content. Party on, people! As I said above the data is hosted on a SQL Azure database that I use for hosting “AdventureWorks on Azure” which I first announced in March 2013 at AdventureWorks2012 now available for all on SQL Azure. I’ll repeat the pertinent parts of that blog post here: I am pleased to announce that as of today … [AdventureWorks2012] now resides on SQL Azure and is available for anyone, absolutely anyone, to connect to and use for their own means. This database is free for you to use but SQL Azure is of course not free so before I give you the credentials please lend me your ears eyes for a short while longer. AdventureWorks on Azure is being provided for the SQL Server community to use and so I am hoping that that same community will rally around to support this effort by making a voluntary donation to support the upkeep which, going on current pricing, is going to be $119.88 per year. If you would like to contribute to keep AdventureWorks on Azure up and running for that full year please donate via PayPal to [email protected] Any amount, no matter how small, will help. If those 50+ people that retweeted me beforehand all contributed $2 then that would just about be enough to keep this up for a year. If the community contributes more than we need then there are a number of additional things that could be done: Host additional databases (Northwind anyone??) Host in more datacentres (this first one is in Western Europe) Make a charitable donation That last one, a charitable donation, is something I would really like to do. The SQL Community have proved before that they can make a significant contribution to charitable orgnisations through purchasing the SQL Server MVP Deep Dives book and I harbour hopes that AdventureWorks on Azure can continue in that vein. So please, if you think AdventureWorks on Azure is something that is worth supporting please make a contribution. I’d like to emphasize that last point. If my hosting this Olympics data is useful to you please support this initiative by donating. Thanks in advance. @Jamiet

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  • Making user input/math on data fast, unlike excel type programs

    - by proGrammar
    I'm creating a research platform solely for myself to do some research on data. Programs like excel are terribly slow for me so I'm trying to come up with another solution. Originally I used excel. A1 was the cell that contained the data and all other cells in use calculated something on A1, or on other cells, that all could be in the end traced to A1. A1 was like an element of an array, I then I incremented it to go through all my data. This was way too slow. So the only other option I found originally was to hand code in c# the calculations inside a loop. Then I simply recompiled each time I changed my math. This was terribly slow to do and I had to order everything correctly so things would update correctly (dependencies). I could have also used events, but hand coding events for each cell like calculation would also be very slow. Next I created an application to read Excel and to perfectly imitate it. Which is what I now use. Basically I write formulas onto a fraction of my data to get live results inside excel. Then my program reads excel, writes another c# program, compiles it, and runs that program which runs my excel created formulas through a lot more data a whole lot faster. The advantage being my application dependency sorts everything (or I could use events) so I don't have to (like excel does) And of course the speed. But now its not a single application anymore. Instead its 2 applications, one which only reads my formulas and writes another program. The other one being the result which only lives for a short while before I do other runs through my data with different formulas / settings. So I can't see multiple results at one time without introducing even more programs like a database or at least having the 2 applications talking to each other. My idea was to have a dll that would be written, compiled, loaded, and unloaded again and again. So a self-updating program, sort of. But apparently that's not possible without another appdomain which means data has to be marshaled to be moved between the appdomains. Which would slow things down, not for summaries, but for other stuff I need to do with all my data. I'm also forgetting to mention a huge problem with restarting an application again and again which is having to reload ALL my data into memory again and again. But its still a whole lot faster than excel. I'm really super puzzled as to what people do when they want to research data fast. I'm completely unable to have a program accept user input and having it fast. My understanding is that it would have to do things like excel which is to evaluate strings again and again. So my only option is to repeatedly compile applications. Do I have a correct understanding on computer science? I've only just began programming, and didn't think I would have to learn much to do some simple math on data. My understanding is its either compiling my user defined stuff to a program or evaluating them from a string or something stupid again and again. And my only option is to probably switch operating systems or something to be able to have a program compile and run itself without stopping (writing/compiling dll, loading dll to program, unloading, and repeating). Can someone give me some idea on how computers work? Is anything better possible? Like a running program, that can accept user input and compile it and then unload it later? I mean heck operating systems dont need to be RESTARTED with every change to user input. What is this the cave man days? Sorry, it's just so super frustrating not knowing what one can do, and can't do. If only I could understand and learn this stuff fast enough.

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  • Java Cloud Service Integration using Web Service Data Control

    - by Jani Rautiainen
    Java Cloud Service (JCS) provides a platform to develop and deploy business applications in the cloud. In Fusion Applications Cloud deployments customers do not have the option to deploy custom applications developed with JDeveloper to ensure the integrity and supportability of the hosted application service. Instead the custom applications can be deployed to the JCS and integrated to the Fusion Application Cloud instance.This series of articles will go through the features of JCS, provide end-to-end examples on how to develop and deploy applications on JCS and how to integrate them with the Fusion Applications instance.In this article a custom application integrating with Fusion Application using Web Service Data Control will be implemented. v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} 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:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif";} Pre-requisites Access to Cloud instance In order to deploy the application access to a JCS instance is needed, a free trial JCS instance can be obtained from Oracle Cloud site. To register you will need a credit card even if the credit card will not be charged. To register simply click "Try it" and choose the "Java" option. The confirmation email will contain the connection details. See this video for example of the registration. Once the request is processed you will be assigned 2 service instances; Java and Database. Applications deployed to the JCS must use Oracle Database Cloud Service as their underlying database. So when JCS instance is created a database instance is associated with it using a JDBC data source. The cloud services can be monitored and managed through the web UI. For details refer to Getting Started with Oracle Cloud. JDeveloper JDeveloper contains Cloud specific features related to e.g. connection and deployment. To use these features download the JDeveloper from JDeveloper download site by clicking the “Download JDeveloper 11.1.1.7.1 for ADF deployment on Oracle Cloud” link, this version of JDeveloper will have the JCS integration features that will be used in this article. For versions that do not include the Cloud integration features the Oracle Java Cloud Service SDK or the JCS Java Console can be used for deployment. For details on installing and configuring the JDeveloper refer to the installation guide. For details on SDK refer to Using the Command-Line Interface to Monitor Oracle Java Cloud Service and Using the Command-Line Interface to Manage Oracle Java Cloud Service. Create Application In this example the “JcsWsDemo” application created in the “Java Cloud Service Integration using Web Service Proxy” article is used as the base. Create Web Service Data Control In this example we will use a Web Service Data Control to integrate with Credit Rule Service in Fusion Applications. The data control will be used to query data from Fusion Applications using a web service call and present the data in a table. To generate the data control choose the “Model” project and navigate to "New -> All Technologies -> Business Tier -> Data Controls -> Web Service Data Control" and enter following: Name: CreditRuleServiceDC URL: https://ic-[POD].oracleoutsourcing.com/icCnSetupCreditRulesPublicService/CreditRuleService?WSDL Service: {{http://xmlns.oracle.com/apps/incentiveCompensation/cn/creditSetup/creditRule/creditRuleService/}CreditRuleService On step 2 select the “findRule” operation: Skip step 3 and on step 4 define the credentials to access the service. Do note that in this example these credentials are only used if testing locally, for JCS deployment credentials need to be manually updated on the EAR file: Click “Finish” and the proxy generation is done. Creating UI In order to use the data control we will need to populate complex objects FindCriteria and FindControl. For simplicity in this example we will create logic in a managed bean that populates the objects. Open “JcsWsDemoBean.java” and add the following logic: Map findCriteria; Map findControl; public void setFindCriteria(Map findCriteria) { this.findCriteria = findCriteria; } public Map getFindCriteria() { findCriteria = new HashMap(); findCriteria.put("fetchSize",10); findCriteria.put("fetchStart",0); return findCriteria; } public void setFindControl(Map findControl) { this.findControl = findControl; } public Map getFindControl() { findControl = new HashMap(); return findControl; } Open “JcsWsDemo.jspx”, navigate to “Data Controls -> CreditRuleServiceDC -> findRule(Object, Object) -> result” and drag and drop the “result” node into the “af:form” element in the page: On the “Edit Table Columns” remove all columns except “RuleId” and “Name”: On the “Edit Action Binding” window displayed enter reference to the java class created above by selecting “#{JcsWsDemoBean.findCriteria}”: Also define the value for the “findControl” by selecting “#{JcsWsDemoBean.findControl}”. Deploy to JCS For WS DC the authentication details need to be updated on the connection details before deploying. Open “connections.xml” by navigating “Application Resources -> Descriptors -> ADF META-INF -> connections.xml”: Change the user name and password entry from: <soap username="transportUserName" password="transportPassword" To match the access details for the target environment. Follow the same steps as documented in previous article ”Java Cloud Service ADF Web Application”. Once deployed the application can be accessed with URL: https://java-[identity domain].java.[data center].oraclecloudapps.com/JcsWsDemo-ViewController-context-root/faces/JcsWsDemo.jspx When accessed the first 10 rules in the system are displayed: Summary In this article we learned how to integrate with Fusion Applications using a Web Service Data Control in JCS. In future articles various other integration techniques will be covered. 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:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif";}

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  • The Sensemaking Spectrum for Business Analytics: Translating from Data to Business Through Analysis

    - by Joe Lamantia
    One of the most compelling outcomes of our strategic research efforts over the past several years is a growing vocabulary that articulates our cumulative understanding of the deep structure of the domains of discovery and business analytics. Modes are one example of the deep structure we’ve found.  After looking at discovery activities across a very wide range of industries, question types, business needs, and problem solving approaches, we've identified distinct and recurring kinds of sensemaking activity, independent of context.  We label these activities Modes: Explore, compare, and comprehend are three of the nine recognizable modes.  Modes describe *how* people go about realizing insights.  (Read more about the programmatic research and formal academic grounding and discussion of the modes here: https://www.researchgate.net/publication/235971352_A_Taxonomy_of_Enterprise_Search_and_Discovery) By analogy to languages, modes are the 'verbs' of discovery activity.  When applied to the practical questions of product strategy and development, the modes of discovery allow one to identify what kinds of analytical activity a product, platform, or solution needs to support across a spread of usage scenarios, and then make concrete and well-informed decisions about every aspect of the solution, from high-level capabilities, to which specific types of information visualizations better enable these scenarios for the types of data users will analyze. The modes are a powerful generative tool for product making, but if you've spent time with young children, or had a really bad hangover (or both at the same time...), you understand the difficult of communicating using only verbs.  So I'm happy to share that we've found traction on another facet of the deep structure of discovery and business analytics.  Continuing the language analogy, we've identified some of the ‘nouns’ in the language of discovery: specifically, the consistently recurring aspects of a business that people are looking for insight into.  We call these discovery Subjects, since they identify *what* people focus on during discovery efforts, rather than *how* they go about discovery as with the Modes. Defining the collection of Subjects people repeatedly focus on allows us to understand and articulate sense making needs and activity in more specific, consistent, and complete fashion.  In combination with the Modes, we can use Subjects to concretely identify and define scenarios that describe people’s analytical needs and goals.  For example, a scenario such as ‘Explore [a Mode] the attrition rates [a Measure, one type of Subject] of our largest customers [Entities, another type of Subject] clearly captures the nature of the activity — exploration of trends vs. deep analysis of underlying factors — and the central focus — attrition rates for customers above a certain set of size criteria — from which follow many of the specifics needed to address this scenario in terms of data, analytical tools, and methods. We can also use Subjects to translate effectively between the different perspectives that shape discovery efforts, reducing ambiguity and increasing impact on both sides the perspective divide.  For example, from the language of business, which often motivates analytical work by asking questions in business terms, to the perspective of analysis.  The question posed to a Data Scientist or analyst may be something like “Why are sales of our new kinds of potato chips to our largest customers fluctuating unexpectedly this year?” or “Where can innovate, by expanding our product portfolio to meet unmet needs?”.  Analysts translate questions and beliefs like these into one or more empirical discovery efforts that more formally and granularly indicate the plan, methods, tools, and desired outcomes of analysis.  From the perspective of analysis this second question might become, “Which customer needs of type ‘A', identified and measured in terms of ‘B’, that are not directly or indirectly addressed by any of our current products, offer 'X' potential for ‘Y' positive return on the investment ‘Z' required to launch a new offering, in time frame ‘W’?  And how do these compare to each other?”.  Translation also happens from the perspective of analysis to the perspective of data; in terms of availability, quality, completeness, format, volume, etc. By implication, we are proposing that most working organizations — small and large, for profit and non-profit, domestic and international, and in the majority of industries — can be described for analytical purposes using this collection of Subjects.  This is a bold claim, but simplified articulation of complexity is one of the primary goals of sensemaking frameworks such as this one.  (And, yes, this is in fact a framework for making sense of sensemaking as a category of activity - but we’re not considering the recursive aspects of this exercise at the moment.) Compellingly, we can place the collection of subjects on a single continuum — we call it the Sensemaking Spectrum — that simply and coherently illustrates some of the most important relationships between the different types of Subjects, and also illuminates several of the fundamental dynamics shaping business analytics as a domain.  As a corollary, the Sensemaking Spectrum also suggests innovation opportunities for products and services related to business analytics. The first illustration below shows Subjects arrayed along the Sensemaking Spectrum; the second illustration presents examples of each kind of Subject.  Subjects appear in colors ranging from blue to reddish-orange, reflecting their place along the Spectrum, which indicates whether a Subject addresses more the viewpoint of systems and data (Data centric and blue), or people (User centric and orange).  This axis is shown explicitly above the Spectrum.  Annotations suggest how Subjects align with the three significant perspectives of Data, Analysis, and Business that shape business analytics activity.  This rendering makes explicit the translation and bridging function of Analysts as a role, and analysis as an activity. Subjects are best understood as fuzzy categories [http://georgelakoff.files.wordpress.com/2011/01/hedges-a-study-in-meaning-criteria-and-the-logic-of-fuzzy-concepts-journal-of-philosophical-logic-2-lakoff-19731.pdf], rather than tightly defined buckets.  For each Subject, we suggest some of the most common examples: Entities may be physical things such as named products, or locations (a building, or a city); they could be Concepts, such as satisfaction; or they could be Relationships between entities, such as the variety of possible connections that define linkage in social networks.  Likewise, Events may indicate a time and place in the dictionary sense; or they may be Transactions involving named entities; or take the form of Signals, such as ‘some Measure had some value at some time’ - what many enterprises understand as alerts.   The central story of the Spectrum is that though consumers of analytical insights (represented here by the Business perspective) need to work in terms of Subjects that are directly meaningful to their perspective — such as Themes, Plans, and Goals — the working realities of data (condition, structure, availability, completeness, cost) and the changing nature of most discovery efforts make direct engagement with source data in this fashion impossible.  Accordingly, business analytics as a domain is structured around the fundamental assumption that sense making depends on analytical transformation of data.  Analytical activity incrementally synthesizes more complex and larger scope Subjects from data in its starting condition, accumulating insight (and value) by moving through a progression of stages in which increasingly meaningful Subjects are iteratively synthesized from the data, and recombined with other Subjects.  The end goal of  ‘laddering’ successive transformations is to enable sense making from the business perspective, rather than the analytical perspective.Synthesis through laddering is typically accomplished by specialized Analysts using dedicated tools and methods. Beginning with some motivating question such as seeking opportunities to increase the efficiency (a Theme) of fulfillment processes to reach some level of profitability by the end of the year (Plan), Analysts will iteratively wrangle and transform source data Records, Values and Attributes into recognizable Entities, such as Products, that can be combined with Measures or other data into the Events (shipment of orders) that indicate the workings of the business.  More complex Subjects (to the right of the Spectrum) are composed of or make reference to less complex Subjects: a business Process such as Fulfillment will include Activities such as confirming, packing, and then shipping orders.  These Activities occur within or are conducted by organizational units such as teams of staff or partner firms (Networks), composed of Entities which are structured via Relationships, such as supplier and buyer.  The fulfillment process will involve other types of Entities, such as the products or services the business provides.  The success of the fulfillment process overall may be judged according to a sophisticated operating efficiency Model, which includes tiered Measures of business activity and health for the transactions and activities included.  All of this may be interpreted through an understanding of the operational domain of the businesses supply chain (a Domain).   We'll discuss the Spectrum in more depth in succeeding posts.

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  • Using jQuery to POST Form Data to an ASP.NET ASMX AJAX Web Service

    - by Rick Strahl
    The other day I got a question about how to call an ASP.NET ASMX Web Service or PageMethods with the POST data from a Web Form (or any HTML form for that matter). The idea is that you should be able to call an endpoint URL, send it regular urlencoded POST data and then use Request.Form[] to retrieve the posted data as needed. My first reaction was that you can’t do it, because ASP.NET ASMX AJAX services (as well as Page Methods and WCF REST AJAX Services) require that the content POSTed to the server is posted as JSON and sent with an application/json or application/x-javascript content type. IOW, you can’t directly call an ASP.NET AJAX service with regular urlencoded data. Note that there are other ways to accomplish this. You can use ASP.NET MVC and a custom route, an HTTP Handler or separate ASPX page, or even a WCF REST service that’s configured to use non-JSON inputs. However if you want to use an ASP.NET AJAX service (or Page Methods) with a little bit of setup work it’s actually quite easy to capture all the form variables on the client and ship them up to the server. The basic steps needed to make this happen are: Capture form variables into an array on the client with jQuery’s .serializeArray() function Use $.ajax() or my ServiceProxy class to make an AJAX call to the server to send this array On the server create a custom type that matches the .serializeArray() name/value structure Create extension methods on NameValue[] to easily extract form variables Create a [WebMethod] that accepts this name/value type as an array (NameValue[]) This seems like a lot of work but realize that steps 3 and 4 are a one time setup step that can be reused in your entire site or multiple applications. Let’s look at a short example that looks like this as a base form of fields to ship to the server: The HTML for this form looks something like this: <div id="divMessage" class="errordisplay" style="display: none"> </div> <div> <div class="label">Name:</div> <div><asp:TextBox runat="server" ID="txtName" /></div> </div> <div> <div class="label">Company:</div> <div><asp:TextBox runat="server" ID="txtCompany"/></div> </div> <div> <div class="label" ></div> <div> <asp:DropDownList runat="server" ID="lstAttending"> <asp:ListItem Text="Attending" Value="Attending"/> <asp:ListItem Text="Not Attending" Value="NotAttending" /> <asp:ListItem Text="Maybe Attending" Value="MaybeAttending" /> <asp:ListItem Text="Not Sure Yet" Value="NotSureYet" /> </asp:DropDownList> </div> </div> <div> <div class="label">Special Needs:<br /> <small>(check all that apply)</small></div> <div> <asp:ListBox runat="server" ID="lstSpecialNeeds" SelectionMode="Multiple"> <asp:ListItem Text="Vegitarian" Value="Vegitarian" /> <asp:ListItem Text="Vegan" Value="Vegan" /> <asp:ListItem Text="Kosher" Value="Kosher" /> <asp:ListItem Text="Special Access" Value="SpecialAccess" /> <asp:ListItem Text="No Binder" Value="NoBinder" /> </asp:ListBox> </div> </div> <div> <div class="label"></div> <div> <asp:CheckBox ID="chkAdditionalGuests" Text="Additional Guests" runat="server" /> </div> </div> <hr /> <input type="button" id="btnSubmit" value="Send Registration" /> The form includes a few different kinds of form fields including a multi-selection listbox to demonstrate retrieving multiple values. Setting up the Server Side [WebMethod] The [WebMethod] on the server we’re going to call is going to be very simple and just capture the content of these values and echo then back as a formatted HTML string. Obviously this is overly simplistic but it serves to demonstrate the simple point of capturing the POST data on the server in an AJAX callback. public class PageMethodsService : System.Web.Services.WebService { [WebMethod] public string SendRegistration(NameValue[] formVars) { StringBuilder sb = new StringBuilder(); sb.AppendFormat("Thank you {0}, <br/><br/>", HttpUtility.HtmlEncode(formVars.Form("txtName"))); sb.AppendLine("You've entered the following: <hr/>"); foreach (NameValue nv in formVars) { // strip out ASP.NET form vars like _ViewState/_EventValidation if (!nv.name.StartsWith("__")) { if (nv.name.StartsWith("txt") || nv.name.StartsWith("lst") || nv.name.StartsWith("chk")) sb.Append(nv.name.Substring(3)); else sb.Append(nv.name); sb.AppendLine(": " + HttpUtility.HtmlEncode(nv.value) + "<br/>"); } } sb.AppendLine("<hr/>"); string[] needs = formVars.FormMultiple("lstSpecialNeeds"); if (needs == null) sb.AppendLine("No Special Needs"); else { sb.AppendLine("Special Needs: <br/>"); foreach (string need in needs) { sb.AppendLine("&nbsp;&nbsp;" + need + "<br/>"); } } return sb.ToString(); } } The key feature of this method is that it receives a custom type called NameValue[] which is an array of NameValue objects that map the structure that the jQuery .serializeArray() function generates. There are two custom types involved in this: The actual NameValue type and a NameValueExtensions class that defines a couple of extension methods for the NameValue[] array type to allow for single (.Form()) and multiple (.FormMultiple()) value retrieval by name. The NameValue class is as simple as this and simply maps the structure of the array elements of .serializeArray(): public class NameValue { public string name { get; set; } public string value { get; set; } } The extension method class defines the .Form() and .FormMultiple() methods to allow easy retrieval of form variables from the returned array: /// <summary> /// Simple NameValue class that maps name and value /// properties that can be used with jQuery's /// $.serializeArray() function and JSON requests /// </summary> public static class NameValueExtensionMethods { /// <summary> /// Retrieves a single form variable from the list of /// form variables stored /// </summary> /// <param name="formVars"></param> /// <param name="name">formvar to retrieve</param> /// <returns>value or string.Empty if not found</returns> public static string Form(this NameValue[] formVars, string name) { var matches = formVars.Where(nv => nv.name.ToLower() == name.ToLower()).FirstOrDefault(); if (matches != null) return matches.value; return string.Empty; } /// <summary> /// Retrieves multiple selection form variables from the list of /// form variables stored. /// </summary> /// <param name="formVars"></param> /// <param name="name">The name of the form var to retrieve</param> /// <returns>values as string[] or null if no match is found</returns> public static string[] FormMultiple(this NameValue[] formVars, string name) { var matches = formVars.Where(nv => nv.name.ToLower() == name.ToLower()).Select(nv => nv.value).ToArray(); if (matches.Length == 0) return null; return matches; } } Using these extension methods it’s easy to retrieve individual values from the array: string name = formVars.Form("txtName"); or multiple values: string[] needs = formVars.FormMultiple("lstSpecialNeeds"); if (needs != null) { // do something with matches } Using these functions in the SendRegistration method it’s easy to retrieve a few form variables directly (txtName and the multiple selections of lstSpecialNeeds) or to iterate over the whole list of values. Of course this is an overly simple example – in typical app you’d probably want to validate the input data and save it to the database and then return some sort of confirmation or possibly an updated data list back to the client. Since this is a full AJAX service callback realize that you don’t have to return simple string values – you can return any of the supported result types (which are most serializable types) including complex hierarchical objects and arrays that make sense to your client code. POSTing Form Variables from the Client to the AJAX Service To call the AJAX service method on the client is straight forward and requires only use of little native jQuery plus JSON serialization functionality. To start add jQuery and the json2.js library to your page: <script src="Scripts/jquery.min.js" type="text/javascript"></script> <script src="Scripts/json2.js" type="text/javascript"></script> json2.js can be found here (be sure to remove the first line from the file): http://www.json.org/json2.js It’s required to handle JSON serialization for those browsers that don’t support it natively. With those script references in the document let’s hookup the button click handler and call the service: $(document).ready(function () { $("#btnSubmit").click(sendRegistration); }); function sendRegistration() { var arForm = $("#form1").serializeArray(); $.ajax({ url: "PageMethodsService.asmx/SendRegistration", type: "POST", contentType: "application/json", data: JSON.stringify({ formVars: arForm }), dataType: "json", success: function (result) { var jEl = $("#divMessage"); jEl.html(result.d).fadeIn(1000); setTimeout(function () { jEl.fadeOut(1000) }, 5000); }, error: function (xhr, status) { alert("An error occurred: " + status); } }); } The key feature in this code is the $("#form1").serializeArray();  call which serializes all the form fields of form1 into an array. Each form var is represented as an object with a name/value property. This array is then serialized into JSON with: JSON.stringify({ formVars: arForm }) The format for the parameter list in AJAX service calls is an object with one property for each parameter of the method. In this case its a single parameter called formVars and we’re assigning the array of form variables to it. The URL to call on the server is the name of the Service (or ASPX Page for Page Methods) plus the name of the method to call. On return the success callback receives the result from the AJAX callback which in this case is the formatted string which is simply assigned to an element in the form and displayed. Remember the result type is whatever the method returns – it doesn’t have to be a string. Note that ASP.NET AJAX and WCF REST return JSON data as a wrapped object so the result has a ‘d’ property that holds the actual response: jEl.html(result.d).fadeIn(1000); Slightly simpler: Using ServiceProxy.js If you want things slightly cleaner you can use the ServiceProxy.js class I’ve mentioned here before. The ServiceProxy class handles a few things for calling ASP.NET and WCF services more cleanly: Automatic JSON encoding Automatic fix up of ‘d’ wrapper property Automatic Date conversion on the client Simplified error handling Reusable and abstracted To add the service proxy add: <script src="Scripts/ServiceProxy.js" type="text/javascript"></script> and then change the code to this slightly simpler version: <script type="text/javascript"> proxy = new ServiceProxy("PageMethodsService.asmx/"); $(document).ready(function () { $("#btnSubmit").click(sendRegistration); }); function sendRegistration() { var arForm = $("#form1").serializeArray(); proxy.invoke("SendRegistration", { formVars: arForm }, function (result) { var jEl = $("#divMessage"); jEl.html(result).fadeIn(1000); setTimeout(function () { jEl.fadeOut(1000) }, 5000); }, function (error) { alert(error.message); } ); } The code is not very different but it makes the call as simple as specifying the method to call, the parameters to pass and the actions to take on success and error. No more remembering which content type and data types to use and manually serializing to JSON. This code also removes the “d” property processing in the response and provides more consistent error handling in that the call always returns an error object regardless of a server error or a communication error unlike the native $.ajax() call. Either approach works and both are pretty easy. The ServiceProxy really pays off if you use lots of service calls and especially if you need to deal with date values returned from the server  on the client. Summary Making Web Service calls and getting POST data to the server is not always the best option – ASP.NET and WCF AJAX services are meant to work with data in objects. However, in some situations it’s simply easier to POST all the captured form data to the server instead of mapping all properties from the input fields to some sort of message object first. For this approach the above POST mechanism is useful as it puts the parsing of the data on the server and leaves the client code lean and mean. It’s even easy to build a custom model binder on the server that can map the array values to properties on an object generically with some relatively simple Reflection code and without having to manually map form vars to properties and do string conversions. Keep in mind though that other approaches also abound. ASP.NET MVC makes it pretty easy to create custom routes to data and the built in model binder makes it very easy to deal with inbound form POST data in its original urlencoded format. The West Wind West Wind Web Toolkit also includes functionality for AJAX callbacks using plain POST values. All that’s needed is a Method parameter to query/form value to specify the method to be called on the server. After that the content type is completely optional and up to the consumer. It’d be nice if the ASP.NET AJAX Service and WCF AJAX Services weren’t so tightly bound to the content type so that you could more easily create open access service endpoints that can take advantage of urlencoded data that is everywhere in existing pages. It would make it much easier to create basic REST endpoints without complicated service configuration. Ah one can dream! In the meantime I hope this article has given you some ideas on how you can transfer POST data from the client to the server using JSON – it might be useful in other scenarios beyond ASP.NET AJAX services as well. Additional Resources ServiceProxy.js A small JavaScript library that wraps $.ajax() to call ASP.NET AJAX and WCF AJAX Services. Includes date parsing extensions to the JSON object, a global dataFilter for processing dates on all jQuery JSON requests, provides cleanup for the .NET wrapped message format and handles errors in a consistent fashion. Making jQuery Calls to WCF/ASMX with a ServiceProxy Client More information on calling ASMX and WCF AJAX services with jQuery and some more background on ServiceProxy.js. Note the implementation has slightly changed since the article was written. ww.jquery.js The West Wind West Wind Web Toolkit also includes ServiceProxy.js in the West Wind jQuery extension library. This version is slightly different and includes embedded json encoding/decoding based on json2.js.© Rick Strahl, West Wind Technologies, 2005-2010Posted in jQuery  ASP.NET  AJAX  

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  • SQLAuthority News – Download Whitepaper Using SharePoint List Data in PowerPivot

    - by pinaldave
    One of the many features of Microsoft SQL Server PowerPivot is the range of data sources that can be used to import data. Anything, from Microsoft SQL Server relational databases, Oracle databases, and Microsoft Access databases, to text documents, can be used as data sources in PowerPivot. In this paper, I explain one of the new and upcoming data sources that people are excited about – SharePoint list data in the form of Atom feeds. This white paper goes on to explain the different ways you can import SharePoint list data into PowerPivot, what types of lists are supported, various components that need to be installed to use this feature, and where to get those components. Download and read this whitepaper. Note: Abstract is taken from MSDN Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, SQL White Papers, SQLAuthority News, T SQL, Technology

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  • Visualising data a different way with Pivot collections

    - by Rob Farley
    Roger’s been doing a great job extending PivotViewer recently, and you can find the list of LobsterPot pivots at http://pivot.lobsterpot.com.au Many months back, the TED Talk that Gary Flake did about Pivot caught my imagination, and I did some research into it. At the time, most of what we did with Pivot was geared towards what we could do for clients, including making Pivot collections based on students at a school, and using it to browse PDF invoices by their various properties. We had actual commercial work based on Pivot collections back then, and it was all kinds of fun. Later, we made some collections for events that were happening, and even got featured in the TechEd Australia keynote. But I’m getting ahead of myself... let me explain the concept. A Pivot collection is an XML file (with .cxml extension) which lists Items, each linking to an image that’s stored in a Deep Zoom format (this means that it contains tiles like Bing Maps, so that the browser can request only the ones of interest according to the zoom level). This collection can be shown in a Silverlight application that uses the PivotViewer control, or in the Pivot Browser that’s available from getpivot.com. Filtering and sorting the items according to their facets (attributes, such as size, age, category, etc), the PivotViewer rearranges the way that these are shown in a very dynamic way. To quote Gary Flake, this lets us “see patterns which are otherwise hidden”. This browsing mechanism is very suited to a number of different methods, because it’s just that – browsing. It’s not searching, it’s more akin to window-shopping than doing an internet search. When we decided to put something together for the conferences such as TechEd Australia 2010 and the PASS Summit 2010, we did some screen-scraping to provide a different view of data that was already available online. Nick Hodge and Michael Kordahi from Microsoft liked the idea a lot, and after a bit of tweaking, we produced one that Michael used in the TechEd Australia keynote to show the variety of talks on offer. It’s interesting to see a pattern in this data: The Office track has the most sessions, but if the Interactive Sessions and Instructor-Led Labs are removed, it drops down to only the sixth most popular track, with Cloud Computing taking over. This is something which just isn’t obvious when you look an ordinary search tool. You get a much better feel for the data when moving around it like this. The more observant amongst you will have noticed some difference in the collection that Michael is demonstrating in the picture above with the screenshots I’ve shown. That’s because it’s been extended some more. At the SQLBits conference in the UK this year, I had some interesting discussions with the guys from Xpert360, particularly Phil Carter, who I’d met in 2009 at an earlier SQLBits conference. They had got around to producing a Pivot collection based on the SQLBits data, which we had been planning to do but ran out of time. We discussed some of ways that Pivot could be used, including the ways that my old friend Howard Dierking had extended it for the MSDN Magazine. I’m not suggesting I influenced Xpert360 at all, but they certainly inspired us with some of their posts on the matter So with LobsterPot guys David Gardiner and Roger Noble both having dabbled in Pivot collections (and Dave doing some for clients), I set Roger to work on extending it some more. He’s used various events and so on to be able to make an environment that allows us to do quick deployment of new collections, as well as showing the data in a grid view which behaves as if it were simply a third view of the data (the other two being the array of images and the ‘histogram’ view). I see PivotViewer as being a significant step in data visualisation – so much so that I feature it when I deliver talks on Spatial Data Visualisation methods. Any time when there is information that can be conveyed through an image, you have to ask yourself how best to show that image, and whether that image is the focal point. For Spatial data, the image is most often a map, and the map becomes the central mode for navigation. I show Pivot with postcode areas, since I can browse the postcodes based on their data, and many of the images are recognisable (to locals of South Australia). Naturally, the images could link through to the map itself, and so on, but generally people think of Spatial data in terms of navigating a map, which doesn’t always gel with the information you’re trying to extract. Roger’s even looking into ways to hook PivotViewer into the Bing Maps API, in a similar way to the Deep Earth project, displaying different levels of map detail according to how ‘zoomed in’ the images are. Some of the work that Dave did with one of the schools was generating the Deep Zoom tiles “on the fly”, based on images stored in a database, and Roger has produced a collection which uses images from flickr, that lets you move from one search term to another. Pulling the images down from flickr.com isn’t particularly ideal from a performance aspect, and flickr doesn’t store images in a small-enough format to really lend itself to this use, but you might agree that it’s an interesting concept which compares nicely to using Maps. I’m looking forward to future versions of the PivotViewer control, and hope they provide many more events that can be used, and even more hooks into it. Naturally, LobsterPot could help provide your business with a PivotViewer experience, but you can probably do a lot of it yourself too. There’s a thorough guide at getpivot.com, which is how we got into it. For some examples of what we’ve done, have a look at http://pivot.lobsterpot.com.au. I’d like to see PivotViewer really catch on a data visualisation tool.

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  • Oracle Unbreakable Enterprise Kernel and Emulex HBA Eliminate Silent Data Corruption

    - by sergio.leunissen
    Yesterday, Emulex announced that it has added support for T10 Protection Information (T10-PI), formerly called T10-DIF, to a number of its HBAs. When used with Oracle's Unbreakable Enterprise Kernel, this will prevent silent data corruption and help ensure the integrity and regulatory compliance of user data as it is transferred from the application to the SAN From the press release: Traditionally, protecting the integrity of customers' data has been done with multiple discrete solutions, including Error Correcting Code (ECC) and Cyclic Redundancy Check (CRC), but there have been coverage gaps across the I/O path from the operating system to the storage. The implementation of the T10-PI standard via Emulex's BlockGuard feature, in conjunction with other industry player's implementations, ensures that data is validated as it moves through the data path, from the application, to the HBA, to storage, enabling seamless end-to-end integrity. Read the white paper and don't miss the live webcast on eliminating silent data corruption on December 16th!

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  • Storing large data in HTTP Session (Java Application)

    - by Umesh Awasthi
    I am asking this question in continuation with http-session-or-database-approach. I am planning to follow this approach. When user add product to cart, create a Cart Model, add items to cart and save to DB. Convert Cart model to cart data and save it to HTTP session. Any update/ edit update underlying cart in DB and update data snap shot in Session. When user click on view cart page, just pick cart data from Session and display to customer. I have following queries regarding HTTP Session How good is it to store large data (Shopping Cart) in Session? How scalable this approach can be ? (With respect to Session) Won't my application going to eat and demand a lot of memory? Is my approach is fine or do i need to consider other points while designing this? Though, we can control what all cart data should be stored in the Session, but still we need to have certain information in cart data being stored in session?

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  • Google I/O 2012 - OAuth 2.0 for Identity and Data Access

    Google I/O 2012 - OAuth 2.0 for Identity and Data Access Ryan Boyd Users like to keep their data in one place on the web where it's easily accessible. Whether it's YouTube videos, Google Drive files, Google contacts or one of many other types of data, users need a way to securely grant applications access to their data. OAuth is the key web standard for delegated data access and OAuth 2.0 is the next-generation version with additional security features. This session will cover the latest advances in how OAuth can be used for data access, but will also dive into how you can lower the barrier to entry for your application by allowing users to login using their Google accounts. You will learn, through an example written in Python, how to use OAuth 2.0 to incorporate user identity into your web application. Best practices for desktop applications, mobile applications and server-to-server use cases will also be discussed. From: GoogleDevelopers Views: 11 1 ratings Time: 58:56 More in Science & Technology

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  • Aggregating cache data from OCEP in CQL

    - by Manju James
    There are several use cases where OCEP applications need to join stream data with external data, such as data available in a Coherence cache. OCEP’s streaming language, CQL, supports simple cache-key based joins of stream data with data in Coherence (more complex queries will be supported in a future release). However, there are instances where you may need to aggregate the data in Coherence based on input data from a stream. This blog describes a sample that does just that. For our sample, we will use a simplified credit card fraud detection use case. The input to this sample application is a stream of credit card transaction data. The input stream contains information like the credit card ID, transaction time and transaction amount. The purpose of this application is to detect suspicious transactions and send out a warning event. For the sake of simplicity, we will assume that all transactions with amounts greater than $1000 are suspicious. The transaction history is available in a Coherence distributed cache. For every suspicious transaction detected, a warning event must be sent with maximum amount, total amount and total number of transactions over the past 30 days, as shown in the diagram below. Application Input Stream input to the EPN contains events of type CCTransactionEvent. This input has to be joined with the cache with all credit card transactions. The cache is configured in the EPN as shown below: <wlevs:caching-system id="CohCacheSystem" provider="coherence"/> <wlevs:cache id="CCTransactionsCache" value-type="CCTransactionEvent" key-properties="cardID, transactionTime" caching-system="CohCacheSystem"> </wlevs:cache> Application Output The output that must be produced by the application is a fraud warning event. This event is configured in the spring file as shown below. Source for cardHistory property can be seen here. <wlevs:event-type type-name="FraudWarningEvent"> <wlevs:properties type="tuple"> <wlevs:property name="cardID" type="CHAR"/> <wlevs:property name="transactionTime" type="BIGINT"/> <wlevs:property name="transactionAmount" type="DOUBLE"/> <wlevs:property name="cardHistory" type="OBJECT"/> </wlevs:properties </wlevs:event-type> Cache Data Aggregation using Java Cartridge In the output warning event, cardHistory property contains data from the cache aggregated over the past 30 days. To get this information, we use a java cartridge method. This method uses Coherence’s query API on credit card transactions cache to get the required information. Therefore, the java cartridge method requires a reference to the cache. This may be set up by configuring it in the spring context file as shown below: <bean class="com.oracle.cep.ccfraud.CCTransactionsAggregator"> <property name="cache" ref="CCTransactionsCache"/> </bean> This is used by the java class to set a static property: public void setCache(Map cache) { s_cache = (NamedCache) cache; } The code snippet below shows how the total of all the transaction amounts in the past 30 days is computed. Rest of the information required by CardHistory object is calculated in a similar manner. Complete source of this class can be found here. To find out more information about using Coherence's API to query a cache, please refer Coherence Developer’s Guide. public static CreditHistoryData(String cardID) { … Filter filter = QueryHelper.createFilter("cardID = :cardID and transactionTime :transactionTime", map); CardHistoryData history = new CardHistoryData(); Double sum = (Double) s_cache.aggregate(filter, new DoubleSum("getTransactionAmount")); history.setTotalAmount(sum); … return history; } The java cartridge method is used from CQL as seen below: select cardID, transactionTime, transactionAmount, CCTransactionsAggregator.execute(cardID) as cardHistory from inputChannel where transactionAmount1000 This produces a warning event, with history data, for every credit card transaction over $1000. That is all there is to it. The complete source for the sample application, along with the configuration files, is available here. In the sample, I use a simple java bean to load the cache with initial transaction history data. An input adapter is used to create and send transaction events for the input stream.

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  • Logical and Physical Modeling for Analytical Applications

    - by Dejan Sarka
    I am proud to announce that my first course for Pluralsight is released. The course title is Logical and Physical Modeling for Analytical Applications. Here is the description of the course. A bad data model leads to an application that does not perform well. Therefore, when developing an application, you should create a good data model from the start. However, even the best logical model can’t help when the physical implementation is bad. It is also important to know how SQL Server stores and accesses data, and how to optimize the data access. Database optimization starts by splitting transactional and analytical applications. In this course, you learn how to support analytical applications with logical design, get understanding of the problems with data access for queries that deal with large amounts of data, and learn about SQL Server optimizations that help solving these problems. Enjoy the course!

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  • Telerik Releases the Data Service Wizard

    After a great beta cycle, Telerik is proud to announce today the commercial availability of the OpenAccess Data Service Wizard. You can download it and install it with Telerik OpenAccess Q1 2010 for both Visual Studio 2008 and 2010 RTM. If you are new to the Data Service Wizard, it is a great tool that will allow you to point a wizard at your OpenAccess generated data access classes and automatically build an WCF, Astoria (WCF Data Services), REST or ATOMPub collection endpoint, complete with the CRUD methods if applicable. If you are familiar with the Data Service Wizard already, there will be two new surprises in the release version. If you generated a domain model with the new OpenAccess Visual Entity Designer, you have only one file added to your project, mydomainmodel.rlinq for example. The first surprise of the new Data Service Wizard is that if you right click on the domain model in Visual Studio, ...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • MSSQL: Copying data from one database to another

    - by DigiMortal
    I have database that has data imported from another server using import and export wizard of SQL Server Management Studio. There is also empty database with same tables but it also has primary keys, foreign keys and indexes. How to get data from first database to another? Here is the description of my crusade. And believe me – it is not nice one. Bugs in import and export wizard There is some awful bugs in import and export wizard that makes data imports and exports possible only on very limited manner: wizard is not able to analyze foreign keys, wizard wants to create tables always, whatever you say in settings. The result is faulty and useless package. Now let’s go step by step and make things work in our scenario. Database There are two databases. Let’s name them like this: PLAIN – contains data imported from remote server (no indexes, no keys, no nothing, just plain dumb data) CORRECT – empty database with same structure as remote database (indexes, keys and everything else but no data) Our goal is to get data from PLAIN to CORRECT. 1. Create import and export package In this point we will create faulty SSIS package using SQL Server Management Studio. Run import and export wizard and let it create SSIS package that reads data from CORRECT and writes it to, let’s say, CORRECT-2. Make sure you enable identity insert. Make sure there are no views selected. Make sure you don’t let package to create tables (you can miss this step because it wants to create tables anyway). Save package to SSIS. 2. Modify import and export package Now let’s clean up the package and remove all faulty crap. Connect SQL Server Management Studio to SSIS instance. Select the package you just saved and export it to your hard disc. Run Business Intelligence Studio. Create new SSIS project (DON’T MISS THIS STEP). Add package from disc as existing item to project and open it. Move to Control Flow page do one of following: Remove all preparation SQL-tasks and connect Data Flow tasks. Modify all preparation SQL-tasks so the existence of tables is checked before table is created (yes, you have to do it manually). Add new Execute-SQL task as first task in control flow: Open task properties. Assign destination connection as connection to use. Insert the following SQL as command:   EXEC sp_MSForEachTable 'ALTER TABLE ? NOCHECK CONSTRAINT ALL' GO   EXEC sp_MSForEachTable 'DELETE FROM ?' GO   Save task. Add new Execute-SQL task as last task in control flow: Open task properties. Assign destination connection as connection to use. Insert the following SQL as command:   EXEC sp_MSForEachTable 'ALTER TABLE ? CHECK CONSTRAINT ALL' GO   Save task Now connect first Execute-SQL task with first Data Flow task and last Data Flow task with second Execute-SQL task. Now move to Package Explorer tab and change connections under Connection Managers folder. Make source connection to use database PLAIN. Make destination connection to use database CORRECT. Save package and rebuilt the project. Update package using SQL Server Management Studio. Some hints: Make sure you take the package from solution folder because it is saved there now. Don’t overwrite existing package. Use numeric suffix and let Management Studio to create a new version of package. Now you are done with your package. Run it to test it and clean out all the errors you find. TRUNCATE vs DELETE You can see that I used DELETE FROM instead of TRUNCATE. Why? Because TRUNCATE has some nasty limits (taken from MSDN): “You cannot use TRUNCATE TABLE on a table referenced by a FOREIGN KEY constraint; instead, use DELETE statement without a WHERE clause. Because TRUNCATE TABLE is not logged, it cannot activate a trigger. TRUNCATE TABLE may not be used on tables participating in an indexed view.” As I am not sure what tables you have and how they are used I provided here the solution that should work for all scenarios. If you need better performance then in some cases you can use TRUNCATE table instead of DELETE. Conclusion My conclusion is bitter this time although I am very positive guy. It is A.D. 2010 and still we have to write stupid hacks for simple things. Simple tools that existed before are long gone and we have to live mysterious bloatware that is our only choice when using default tools. If you take a look at the length of this posting and the count of steps I had to do for one easy thing you should treat it as a signal that something has went wrong in last years. Although I got my job done I would be still more happy if out of box tools are more intelligent one day. References T-SQL Trick for Deleting All Data in Your Database (Mauro Cardarelli) TRUNCATE TABLE (MSDN Library) Error Handling in SQL 2000 – a Background (Erland Sommarskog) Disable/Enable Foreign Key and Check constraints in SQL Server (Decipher)

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  • Enterprise MDM: Rationalizing Reference Data in a Fast Changing Environment

    - by Mala Narasimharajan
    By Rahul Kamath Enterprises must move at a rapid pace to establish and retain global market leadership by continuously focusing on operational efficiency, customer intimacy and relentless execution. Reference Data Management    As multi-national companies with a presence in multiple industry categories, market segments, and geographies, their ability to proactively manage changes and harness them to align their front office with back-office operations and performance management initiatives is critical to make the proverbial elephant dance. Managing reference data including types and codes, business taxonomies, complex relationships as well as mappings represent a key component of the broader agenda for enabling flexibility and agility, without sacrificing enterprise-level consistency, regulatory compliance and control. Financial Transformation  Periodically, companies find that processes implemented a decade or more ago no longer mirror the way of doing business and seek to proactively transform how they operate their business and underlying processes. Financial transformation often begins with the redesign of one’s chart of accounts. The ability to model and redesign one’s chart of accounts collaboratively, quickly validate against historical transaction bases and secure business buy-in across multiple line of business stakeholders, while continuing to manage changes within the legacy general ledger systems and downstream analytical applications while piloting the in-flight transformation can mean the difference between controlled success and project failure. Attend the session titled CON8275 - Oracle Hyperion Data Relationship Management: Enabling Enterprise Transformation at Oracle Openworld on Monday, October 1, 2012 at 4:45pm in Ballroom A of the InterContinental Hotel to learn how Oracle’s Data Relationship Management solution can help you stay ahead of the competition and proactively harness master (and reference) data changes to transform your enterprise. Hear in-depth customer testimonials from GE Healthcare and Old Mutual South Africa to learn how others have harnessed this technology effectively to build enduring competitive advantage through business process innovation and investments in master data governance. Hear GE Healthcare discuss how DRM has enabled financial transformation, ERP consolidation, mergers and acquisitions, and the alignment reference data across financial and management reporting applications. Also, learn how Old Mutual SA has upgraded to EBS R12 Financials and is transforming the management of chart of accounts for corporate reporting. Separately, an esteemed panel of DRM customers including Cisco Systems, Nationwide Insurance, Ralcorp Holdings and Mentor Graphics will discuss their perspectives on how DRM has helped them address business challenges associated with enterprise MDM including major change management initiatives including financial transformations, corporate restructuring, mergers & acquisitions, and the rationalization of financial and analytical master reference data to support alternate business perspectives for the alignment of EPM/BI initiatives. Attend the session titled CON9377 - Customer Showcase: Success with Oracle Hyperion Data Relationship Management at Openworld on Thursday, October 4, 2012 at 12:45pm in Ballroom of the InterContinental Hotel to interact with our esteemed speakers first hand.

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