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  • New .NET Library for Accessing the Survey Monkey API

    - by Ben Emmett
    I’ve used Survey Monkey’s API for a while, and though it’s pretty powerful, there’s a lot of boilerplate each time it’s used in a new project, and the json it returns needs a bunch of processing to be able to use the raw information. So I’ve finally got around to releasing a .NET library you can use to consume the API more easily. The main advantages are: Only ever deal with strongly-typed .NET objects, making everything much more robust and a lot faster to get going Automatically handles things like rate-limiting and paging through results Uses combinations of endpoints to get all relevant data for you, and processes raw response data to map responses to questions To start, either install it using NuGet with PM> Install-Package SurveyMonkeyApi (easier option), or grab the source from https://github.com/bcemmett/SurveyMonkeyApi if you prefer to build it yourself. You’ll also need to have signed up for a developer account with Survey Monkey, and have both your API key and an OAuth token. A simple usage would be something like: string apiKey = "KEY"; string token = "TOKEN"; var sm = new SurveyMonkeyApi(apiKey, token); List<Survey> surveys = sm.GetSurveyList(); The surveys object is now a list of surveys with all the information available from the /surveys/get_survey_list API endpoint, including the title, id, date it was created and last modified, language, number of questions / responses, and relevant urls. If there are more than 1000 surveys in your account, the library pages through the results for you, making multiple requests to get a complete list of surveys. All the filtering available in the API can be controlled using .NET objects. For example you might only want surveys created in the last year and containing “pineapple” in the title: var settings = new GetSurveyListSettings { Title = "pineapple", StartDate = DateTime.Now.AddYears(-1) }; List<Survey> surveys = sm.GetSurveyList(settings); By default, whenever optional fields can be requested with a response, they will all be fetched for you. You can change this behaviour if for some reason you explicitly don’t want the information, using var settings = new GetSurveyListSettings { OptionalData = new GetSurveyListSettingsOptionalData { DateCreated = false, AnalysisUrl = false } }; Survey Monkey’s 7 read-only endpoints are supported, and the other 4 which make modifications to data might be supported in the future. The endpoints are: Endpoint Method Object returned /surveys/get_survey_list GetSurveyList() List<Survey> /surveys/get_survey_details GetSurveyDetails() Survey /surveys/get_collector_list GetCollectorList() List<Collector> /surveys/get_respondent_list GetRespondentList() List<Respondent> /surveys/get_responses GetResponses() List<Response> /surveys/get_response_counts GetResponseCounts() Collector /user/get_user_details GetUserDetails() UserDetails /batch/create_flow Not supported Not supported /batch/send_flow Not supported Not supported /templates/get_template_list Not supported Not supported /collectors/create_collector Not supported Not supported The hierarchy of objects the library can return is Survey List<Page> List<Question> QuestionType List<Answer> List<Item> List<Collector> List<Response> Respondent List<ResponseQuestion> List<ResponseAnswer> Each of these classes has properties which map directly to the names of properties returned by the API itself (though using PascalCasing which is more natural for .NET, rather than the snake_casing used by SurveyMonkey). For most users, Survey Monkey imposes a rate limit of 2 requests per second, so by default the library leaves at least 500ms between requests. You can request higher limits from them, so if you want to change the delay between requests just use a different constructor: var sm = new SurveyMonkeyApi(apiKey, token, 200); //200ms delay = 5 reqs per sec There’s a separate cap of 1000 requests per day for each API key, which the library doesn’t currently enforce, so if you think you’ll be in danger of exceeding that you’ll need to handle it yourself for now.  To help, you can see how many requests the current instance of the SurveyMonkeyApi object has made by reading its RequestsMade property. If the library encounters any errors, including communicating with the API, it will throw a SurveyMonkeyException, so be sure to handle that sensibly any time you use it to make calls. Finally, if you have a survey (or list of surveys) obtained using GetSurveyList(), the library can automatically fill in all available information using sm.FillMissingSurveyInformation(surveys); For each survey in the list, it uses the other endpoints to fill in the missing information about the survey’s question structure, respondents, and responses. This results in at least 5 API calls being made per survey, so be careful before passing it a large list. It also joins up the raw response information to the survey’s question structure, so that for each question in a respondent’s set of replies, you can access a ProcessedAnswer object. For example, a response to a dropdown question (from the /surveys/get_responses endpoint) might be represented in json as { "answers": [ { "row": "9384627365", } ], "question_id": "615487516" } Separately, the question’s structure (from the /surveys/get_survey_details endpoint) might have several possible answers, one of which might look like { "text": "Fourth item in dropdown list", "visible": true, "position": 4, "type": "row", "answer_id": "9384627365" } The library understands how this mapping works, and uses that to give you the following ProcessedAnswer object, which first describes the family and type of question, and secondly gives you the respondent’s answers as they relate to the question. Survey Monkey has many different question types, with 11 distinct data structures, each of which are supported by the library. If you have suggestions or spot any bugs, let me know in the comments, or even better submit a pull request .

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  • Book Review: Oracle ADF Real World Developer’s Guide

    - by Frank Nimphius
    Recently PACKT Publishing published "Oracle ADF Real World Developer’s Guide" by Jobinesh Purushothaman, a product manager in our team. Though already the sixth book dedicated to Oracle ADF, it has a lot of great information in it that none of the previous books covered, making it a safe buy even for those who own the other books published by Oracle Press (McGrwHill) and PACKT Publishing. More than the half of the "Oracle ADF Real World Developer’s Guide" book is dedicated to Oracle ADF Business Components in a depth and clarity that allows you to feel the expertise that Jobinesh gained in this area. If you enjoy Jobinesh blog (http://jobinesh.blogspot.co.uk/) about Oracle ADF, then, no matter what expert you are in Oracle ADF, this book makes you happy as it provides you with detail information you always wished to have. If you are new to Oracle ADF, then this book alone doesn't get you flying, but, if you have some Java background, accelerates your learning big, big, big times. Chapter 1 is an introduction to Oracle ADF and not only explains the layers but also how it compares to plain Java EE solutions (page 13). If you are new to Oracle JDeveloper and ADF, then at the end of this chapter you know how to start JDeveloper and begin your ADF development Chapter 2 starts with what Jobinesh really is good at: ADF Business Components. In this chapter you learn about the architecture ingredients of ADF Business Components: View Objects, View Links, Associations, Entities, Row Sets, Query Collections and Application Modules. This chapter also provides a introduction to ADFBC SDO services, as well as sequence diagrams for what happens when you execute queries or commit updates. Chapter 3 is dedicated to entity objects and  is one of many chapters in this book you will enjoy and never want to miss. Jobinesh explains the artifacts that make up an entity object, how to work with entities and resource bundles, and many advanced topics, including inheritance, change history tracking, custom properties, validation and cursor handling.  Chapter 4 - you guessed it - is all about View objects. Comparable to entities, you learn about the XM files and classes that make a view object, as well as how to define and work with queries. List-of-values, inheritance, polymorphism, bind variables and data filtering are interesting - and important topics that follow. Again the chapter provides helpful sequence diagrams for you to understand what happens internally within a view object. Chapter 5 focuses on advanced view object and entity object topics, like lifecycle callback methods and when you want to override them. This chapter is a good digest of Jobinesh's blog entries (which most ADF developers have in their bookmark list). Really worth reading ! Chapter 6 then is bout Application Modules. Beside of what application modules are, this chapter covers important topics like properties, passivation, activation, application module pooling, how and where to write custom logic. In addition you learn about the AM lifecycle and request sequence. Chapter 7 is about the ADF binding layer. If you are new to Oracle ADF and got lost in the more advanced ADF Business Components chapters, then this chapter is where you get back into the game. In very easy terms, Jobinesh explains what the ADF binding is, how it fits into the JSF request lifecycle and what are the metadata file involved. Chapter 8 then goes into building data bound web user interfaces. In this chapter you get the basics of JavaServer Faces (e.g. managed beans) and learn about the interaction between the JSF UI and the ADF binding layer. Later this chapter provides advanced solutions for working with tree components and list of values. Chapter 9 introduces bounded task flows and ADF controller. This is a chapter you want to read if you are new to ADF of have started. Experts don't find anything new here, which doesn't mean that it is not worth reading it (I for example, enjoyed the controller talk very much) Chapter 10 is an advanced coverage of bounded task flow and talks about contextual events  Chapter 11 is another highlight and explains error handling, trains, transactions and more. I can only recommend you read this chapter. I am aware of many documents that cover exception handling in Oracle ADF (and my Oracle Magazine article for January/February 2013 does the same), but none that covers it in such a great depth. Chapter 12 covers ADF best practices, which is a great round-up of all the tips provided in this book (without Jobinesh to repeat himself). Its all cool stuff that helps you with your ADF projects. In summary, "Oracle ADF Real World Developer’s Guide" by Jobinesh Purushothaman is a great book and addition for all Oracle ADF developers and those who want to become one. Frank

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  • Markus Zirn, "Big Data with CEP and SOA" @ SOA, Cloud &amp; Service Technology Symposium 2012

    - by JuergenKress
    ORACLE PROMOTIONAL DISCOUNT FOR EXCLUSIVE ORACLE DISCOUNT, ENTER PROMO CODE: DJMXZ370 Early-Bird Registration is Now Open with Special Pricing! Register before July 1, 2012 to qualify for discounts. Visit the Registration page for details. The International SOA, Cloud + Service Technology Symposium is a yearly event that features the top experts and authors from around the world, providing a series of keynotes, talks, demonstrations, and panels, as well as training and certification workshops - all dedicated to empowering IT professionals to realize modern service technologies and practices in the real world. Click here for a two-page printable conference overview (PDF). Big Data with CEP and SOA - September 25, 2012 - 14:15 Speaker: Markus Zirn, Oracle and Baz Kuthi, Avocent The "Big Data" trend is driving new kinds of IT projects that process machine-generated data. Such projects store and mine using Hadoop/ Map Reduce, but they also analyze streaming data via event-driven patterns, which can be called "Fast Data" complementary to "Big Data". This session highlights how "Big Data" and "Fast Data" design patterns can be combined with SOA design principles into modern, event-driven architectures. We will describe specific architectures that combines CEP, Distributed Caching, Event-driven Network, SOA Composites, Application Development Framework, as well as Hadoop. Architecture patterns include pre-processing and filtering event streams as close as possible to the event source, in memory master data for event pattern matching, event-driven user interfaces as well as distributed event processing. Focus is on how "Fast Data" requirements are elegantly integrated into a traditional SOA architecture. Markus Zirn is Vice President of Product Management covering Oracle SOA Suite, SOA Governance, Application Integration Architecture, BPM, BPM Solutions, Complex Event Processing and UPK, an end user learning solution. He is the author of “The BPEL Cookbook” (rated best book on Services Oriented Architecture in 2007) as well as “Fusion Middleware Patterns”. Previously, he was a management consultant with Booz Allen & Hamilton’s High Tech practice in Duesseldorf as well as San Francisco and Vice President of Product Marketing at QUIQ. Mr. Zirn holds a Masters of Electrical Engineering from the University of Karlsruhe and is an alumnus of the Tripartite program, a joint European degree from the University of Karlsruhe, Germany, the University of Southampton, UK, and ESIEE, France. KEYNOTES & SPEAKERS More than 80 international subject matter experts will be speaking at the Symposium. Below are confirmed keynotes and speakers so far. Over 50% of the agenda has not yet been finalized. Many more speakers to come. View the partial program calendars on the Conference Agenda page. CONFERENCE THEMES & TRACKS Cloud Computing Architecture & Patterns New SOA & Service-Orientation Practices & Models Emerging Service Technology Innovation Service Modeling & Analysis Techniques Service Infrastructure & Virtualization Cloud-based Enterprise Architecture Business Planning for Cloud Computing Projects Real World Case Studies Semantic Web Technologies (with & without the Cloud) Governance Frameworks for SOA and/or Cloud Computing Projects Service Engineering & Service Programming Techniques Interactive Services & the Human Factor New REST & Web Services Tools & Techniques Oracle Specialized SOA & BPM Partners Oracle Specialized partners have proven their skills by certifications and customer references. To find a local Specialized partner please visit http://solutions.oracle.com SOA & BPM Partner Community For regular information on Oracle SOA Suite become a member in the SOA & BPM Partner Community for registration please visit  www.oracle.com/goto/emea/soa (OPN account required) If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Mix Forum Technorati Tags: Markus Zirn,SOA Symposium,Thomas Erl,SOA Community,Oracle SOA,Oracle BPM,BPM Community,OPN,Jürgen Kress

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  • Windows Azure Use Case: Web Applications

    - by BuckWoody
    This is one in a series of posts on when and where to use a distributed architecture design in your organization's computing needs. You can find the main post here: http://blogs.msdn.com/b/buckwoody/archive/2011/01/18/windows-azure-and-sql-azure-use-cases.aspx  Description: Many applications have a requirement to be located outside of the organization’s internal infrastructure control. For instance, the company website for a brick-and-mortar retail company may want to post not only static but interactive content to be available to their external customers, and not want the customers to have access inside the organization’s firewall. There are also cases of pure web applications used for a great many of the internal functions of the business. This allows for remote workers, shared customer/employee workloads and data and other advantages. Some firms choose to host these web servers internally, others choose to contract out the infrastructure to an “ASP” (Application Service Provider) or an Infrastructure as a Service (IaaS) company. In any case, the design of these applications often resembles the following: In this design, a server (or perhaps more than one) hosts the presentation function (http or https) access to the application, and this same system may hold the computational aspects of the program. Authorization and Access is controlled programmatically, or is more open if this is a customer-facing application. Storage is either placed on the same or other servers, hosted within an RDBMS or NoSQL database, or a combination of the options, all coded into the application. High-Availability within this scenario is often the responsibility of the architects of the application, and by purchasing more hosting resources which must be built, licensed and configured, and manually added as demand requires, although some IaaS providers have a partially automatic method to add nodes for scale-out, if the architecture of the application supports it. Disaster Recovery is the responsibility of the system architect as well. Implementation: In a Windows Azure Platform as a Service (PaaS) environment, many of these architectural considerations are designed into the system. The Azure “Fabric” (not to be confused with the Azure implementation of Application Fabric - more on that in a moment) is designed to provide scalability. Compute resources can be added and removed programmatically based on any number of factors. Balancers at the request-level of the Fabric automatically route http and https requests. The fabric also provides High-Availability for storage and other components. Disaster recovery is a shared responsibility between the facilities (which have the ability to restore in case of catastrophic failure) and your code, which should build in recovery. In a Windows Azure-based web application, you have the ability to separate out the various functions and components. Presentation can be coded for multiple platforms like smart phones, tablets and PC’s, while the computation can be a single entity shared between them. This makes the applications more resilient and more object-oriented, and lends itself to a SOA or Distributed Computing architecture. It is true that you could code up a similar set of functionality in a traditional web-farm, but the difference here is that the components are built into the very design of the architecture. The API’s and DLL’s you call in a Windows Azure code base contains components as first-class citizens. For instance, if you need storage, it is simply called within the application as an object.  Computation has multiple options and the ability to scale linearly. You also gain another component that you would either have to write or bolt-in to a typical web-farm: the Application Fabric. This Windows Azure component provides communication between applications or even to on-premise systems. It provides authorization in either person-based or claims-based perspectives. SQL Azure provides relational storage as another option, and can also be used or accessed from on-premise systems. It should be noted that you can use all or some of these components individually. Resources: Design Strategies for Scalable Active Server Applications - http://msdn.microsoft.com/en-us/library/ms972349.aspx  Physical Tiers and Deployment  - http://msdn.microsoft.com/en-us/library/ee658120.aspx

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  • value types in the vm

    - by john.rose
    value types in the vm p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times} p.p2 {margin: 0.0px 0.0px 14.0px 0.0px; font: 14.0px Times} p.p3 {margin: 0.0px 0.0px 12.0px 0.0px; font: 14.0px Times} p.p4 {margin: 0.0px 0.0px 15.0px 0.0px; font: 14.0px Times} p.p5 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Courier} p.p6 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Courier; min-height: 17.0px} p.p7 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times; min-height: 18.0px} p.p8 {margin: 0.0px 0.0px 0.0px 36.0px; text-indent: -36.0px; font: 14.0px Times; min-height: 18.0px} p.p9 {margin: 0.0px 0.0px 12.0px 0.0px; font: 14.0px Times; min-height: 18.0px} p.p10 {margin: 0.0px 0.0px 12.0px 0.0px; font: 14.0px Times; color: #000000} li.li1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times} li.li7 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times; min-height: 18.0px} span.s1 {font: 14.0px Courier} span.s2 {color: #000000} span.s3 {font: 14.0px Courier; color: #000000} ol.ol1 {list-style-type: decimal} Or, enduring values for a changing world. Introduction A value type is a data type which, generally speaking, is designed for being passed by value in and out of methods, and stored by value in data structures. The only value types which the Java language directly supports are the eight primitive types. Java indirectly and approximately supports value types, if they are implemented in terms of classes. For example, both Integer and String may be viewed as value types, especially if their usage is restricted to avoid operations appropriate to Object. In this note, we propose a definition of value types in terms of a design pattern for Java classes, accompanied by a set of usage restrictions. We also sketch the relation of such value types to tuple types (which are a JVM-level notion), and point out JVM optimizations that can apply to value types. This note is a thought experiment to extend the JVM’s performance model in support of value types. The demonstration has two phases.  Initially the extension can simply use design patterns, within the current bytecode architecture, and in today’s Java language. But if the performance model is to be realized in practice, it will probably require new JVM bytecode features, changes to the Java language, or both.  We will look at a few possibilities for these new features. An Axiom of Value In the context of the JVM, a value type is a data type equipped with construction, assignment, and equality operations, and a set of typed components, such that, whenever two variables of the value type produce equal corresponding values for their components, the values of the two variables cannot be distinguished by any JVM operation. Here are some corollaries: A value type is immutable, since otherwise a copy could be constructed and the original could be modified in one of its components, allowing the copies to be distinguished. Changing the component of a value type requires construction of a new value. The equals and hashCode operations are strictly component-wise. If a value type is represented by a JVM reference, that reference cannot be successfully synchronized on, and cannot be usefully compared for reference equality. A value type can be viewed in terms of what it doesn’t do. We can say that a value type omits all value-unsafe operations, which could violate the constraints on value types.  These operations, which are ordinarily allowed for Java object types, are pointer equality comparison (the acmp instruction), synchronization (the monitor instructions), all the wait and notify methods of class Object, and non-trivial finalize methods. The clone method is also value-unsafe, although for value types it could be treated as the identity function. Finally, and most importantly, any side effect on an object (however visible) also counts as an value-unsafe operation. A value type may have methods, but such methods must not change the components of the value. It is reasonable and useful to define methods like toString, equals, and hashCode on value types, and also methods which are specifically valuable to users of the value type. Representations of Value Value types have two natural representations in the JVM, unboxed and boxed. An unboxed value consists of the components, as simple variables. For example, the complex number x=(1+2i), in rectangular coordinate form, may be represented in unboxed form by the following pair of variables: /*Complex x = Complex.valueOf(1.0, 2.0):*/ double x_re = 1.0, x_im = 2.0; These variables might be locals, parameters, or fields. Their association as components of a single value is not defined to the JVM. Here is a sample computation which computes the norm of the difference between two complex numbers: double distance(/*Complex x:*/ double x_re, double x_im,         /*Complex y:*/ double y_re, double y_im) {     /*Complex z = x.minus(y):*/     double z_re = x_re - y_re, z_im = x_im - y_im;     /*return z.abs():*/     return Math.sqrt(z_re*z_re + z_im*z_im); } A boxed representation groups component values under a single object reference. The reference is to a ‘wrapper class’ that carries the component values in its fields. (A primitive type can naturally be equated with a trivial value type with just one component of that type. In that view, the wrapper class Integer can serve as a boxed representation of value type int.) The unboxed representation of complex numbers is practical for many uses, but it fails to cover several major use cases: return values, array elements, and generic APIs. The two components of a complex number cannot be directly returned from a Java function, since Java does not support multiple return values. The same story applies to array elements: Java has no ’array of structs’ feature. (Double-length arrays are a possible workaround for complex numbers, but not for value types with heterogeneous components.) By generic APIs I mean both those which use generic types, like Arrays.asList and those which have special case support for primitive types, like String.valueOf and PrintStream.println. Those APIs do not support unboxed values, and offer some problems to boxed values. Any ’real’ JVM type should have a story for returns, arrays, and API interoperability. The basic problem here is that value types fall between primitive types and object types. Value types are clearly more complex than primitive types, and object types are slightly too complicated. Objects are a little bit dangerous to use as value carriers, since object references can be compared for pointer equality, and can be synchronized on. Also, as many Java programmers have observed, there is often a performance cost to using wrapper objects, even on modern JVMs. Even so, wrapper classes are a good starting point for talking about value types. If there were a set of structural rules and restrictions which would prevent value-unsafe operations on value types, wrapper classes would provide a good notation for defining value types. This note attempts to define such rules and restrictions. Let’s Start Coding Now it is time to look at some real code. Here is a definition, written in Java, of a complex number value type. @ValueSafe public final class Complex implements java.io.Serializable {     // immutable component structure:     public final double re, im;     private Complex(double re, double im) {         this.re = re; this.im = im;     }     // interoperability methods:     public String toString() { return "Complex("+re+","+im+")"; }     public List<Double> asList() { return Arrays.asList(re, im); }     public boolean equals(Complex c) {         return re == c.re && im == c.im;     }     public boolean equals(@ValueSafe Object x) {         return x instanceof Complex && equals((Complex) x);     }     public int hashCode() {         return 31*Double.valueOf(re).hashCode()                 + Double.valueOf(im).hashCode();     }     // factory methods:     public static Complex valueOf(double re, double im) {         return new Complex(re, im);     }     public Complex changeRe(double re2) { return valueOf(re2, im); }     public Complex changeIm(double im2) { return valueOf(re, im2); }     public static Complex cast(@ValueSafe Object x) {         return x == null ? ZERO : (Complex) x;     }     // utility methods and constants:     public Complex plus(Complex c)  { return new Complex(re+c.re, im+c.im); }     public Complex minus(Complex c) { return new Complex(re-c.re, im-c.im); }     public double abs() { return Math.sqrt(re*re + im*im); }     public static final Complex PI = valueOf(Math.PI, 0.0);     public static final Complex ZERO = valueOf(0.0, 0.0); } This is not a minimal definition, because it includes some utility methods and other optional parts.  The essential elements are as follows: The class is marked as a value type with an annotation. The class is final, because it does not make sense to create subclasses of value types. The fields of the class are all non-private and final.  (I.e., the type is immutable and structurally transparent.) From the supertype Object, all public non-final methods are overridden. The constructor is private. Beyond these bare essentials, we can observe the following features in this example, which are likely to be typical of all value types: One or more factory methods are responsible for value creation, including a component-wise valueOf method. There are utility methods for complex arithmetic and instance creation, such as plus and changeIm. There are static utility constants, such as PI. The type is serializable, using the default mechanisms. There are methods for converting to and from dynamically typed references, such as asList and cast. The Rules In order to use value types properly, the programmer must avoid value-unsafe operations.  A helpful Java compiler should issue errors (or at least warnings) for code which provably applies value-unsafe operations, and should issue warnings for code which might be correct but does not provably avoid value-unsafe operations.  No such compilers exist today, but to simplify our account here, we will pretend that they do exist. A value-safe type is any class, interface, or type parameter marked with the @ValueSafe annotation, or any subtype of a value-safe type.  If a value-safe class is marked final, it is in fact a value type.  All other value-safe classes must be abstract.  The non-static fields of a value class must be non-public and final, and all its constructors must be private. Under the above rules, a standard interface could be helpful to define value types like Complex.  Here is an example: @ValueSafe public interface ValueType extends java.io.Serializable {     // All methods listed here must get redefined.     // Definitions must be value-safe, which means     // they may depend on component values only.     List<? extends Object> asList();     int hashCode();     boolean equals(@ValueSafe Object c);     String toString(); } //@ValueSafe inherited from supertype: public final class Complex implements ValueType { … The main advantage of such a conventional interface is that (unlike an annotation) it is reified in the runtime type system.  It could appear as an element type or parameter bound, for facilities which are designed to work on value types only.  More broadly, it might assist the JVM to perform dynamic enforcement of the rules for value types. Besides types, the annotation @ValueSafe can mark fields, parameters, local variables, and methods.  (This is redundant when the type is also value-safe, but may be useful when the type is Object or another supertype of a value type.)  Working forward from these annotations, an expression E is defined as value-safe if it satisfies one or more of the following: The type of E is a value-safe type. E names a field, parameter, or local variable whose declaration is marked @ValueSafe. E is a call to a method whose declaration is marked @ValueSafe. E is an assignment to a value-safe variable, field reference, or array reference. E is a cast to a value-safe type from a value-safe expression. E is a conditional expression E0 ? E1 : E2, and both E1 and E2 are value-safe. Assignments to value-safe expressions and initializations of value-safe names must take their values from value-safe expressions. A value-safe expression may not be the subject of a value-unsafe operation.  In particular, it cannot be synchronized on, nor can it be compared with the “==” operator, not even with a null or with another value-safe type. In a program where all of these rules are followed, no value-type value will be subject to a value-unsafe operation.  Thus, the prime axiom of value types will be satisfied, that no two value type will be distinguishable as long as their component values are equal. More Code To illustrate these rules, here are some usage examples for Complex: Complex pi = Complex.valueOf(Math.PI, 0); Complex zero = pi.changeRe(0);  //zero = pi; zero.re = 0; ValueType vtype = pi; @SuppressWarnings("value-unsafe")   Object obj = pi; @ValueSafe Object obj2 = pi; obj2 = new Object();  // ok List<Complex> clist = new ArrayList<Complex>(); clist.add(pi);  // (ok assuming List.add param is @ValueSafe) List<ValueType> vlist = new ArrayList<ValueType>(); vlist.add(pi);  // (ok) List<Object> olist = new ArrayList<Object>(); olist.add(pi);  // warning: "value-unsafe" boolean z = pi.equals(zero); boolean z1 = (pi == zero);  // error: reference comparison on value type boolean z2 = (pi == null);  // error: reference comparison on value type boolean z3 = (pi == obj2);  // error: reference comparison on value type synchronized (pi) { }  // error: synch of value, unpredictable result synchronized (obj2) { }  // unpredictable result Complex qq = pi; qq = null;  // possible NPE; warning: “null-unsafe" qq = (Complex) obj;  // warning: “null-unsafe" qq = Complex.cast(obj);  // OK @SuppressWarnings("null-unsafe")   Complex empty = null;  // possible NPE qq = empty;  // possible NPE (null pollution) The Payoffs It follows from this that either the JVM or the java compiler can replace boxed value-type values with unboxed ones, without affecting normal computations.  Fields and variables of value types can be split into their unboxed components.  Non-static methods on value types can be transformed into static methods which take the components as value parameters. Some common questions arise around this point in any discussion of value types. Why burden the programmer with all these extra rules?  Why not detect programs automagically and perform unboxing transparently?  The answer is that it is easy to break the rules accidently unless they are agreed to by the programmer and enforced.  Automatic unboxing optimizations are tantalizing but (so far) unreachable ideal.  In the current state of the art, it is possible exhibit benchmarks in which automatic unboxing provides the desired effects, but it is not possible to provide a JVM with a performance model that assures the programmer when unboxing will occur.  This is why I’m writing this note, to enlist help from, and provide assurances to, the programmer.  Basically, I’m shooting for a good set of user-supplied “pragmas” to frame the desired optimization. Again, the important thing is that the unboxing must be done reliably, or else programmers will have no reason to work with the extra complexity of the value-safety rules.  There must be a reasonably stable performance model, wherein using a value type has approximately the same performance characteristics as writing the unboxed components as separate Java variables. There are some rough corners to the present scheme.  Since Java fields and array elements are initialized to null, value-type computations which incorporate uninitialized variables can produce null pointer exceptions.  One workaround for this is to require such variables to be null-tested, and the result replaced with a suitable all-zero value of the value type.  That is what the “cast” method does above. Generically typed APIs like List<T> will continue to manipulate boxed values always, at least until we figure out how to do reification of generic type instances.  Use of such APIs will elicit warnings until their type parameters (and/or relevant members) are annotated or typed as value-safe.  Retrofitting List<T> is likely to expose flaws in the present scheme, which we will need to engineer around.  Here are a couple of first approaches: public interface java.util.List<@ValueSafe T> extends Collection<T> { … public interface java.util.List<T extends Object|ValueType> extends Collection<T> { … (The second approach would require disjunctive types, in which value-safety is “contagious” from the constituent types.) With more transformations, the return value types of methods can also be unboxed.  This may require significant bytecode-level transformations, and would work best in the presence of a bytecode representation for multiple value groups, which I have proposed elsewhere under the title “Tuples in the VM”. But for starters, the JVM can apply this transformation under the covers, to internally compiled methods.  This would give a way to express multiple return values and structured return values, which is a significant pain-point for Java programmers, especially those who work with low-level structure types favored by modern vector and graphics processors.  The lack of multiple return values has a strong distorting effect on many Java APIs. Even if the JVM fails to unbox a value, there is still potential benefit to the value type.  Clustered computing systems something have copy operations (serialization or something similar) which apply implicitly to command operands.  When copying JVM objects, it is extremely helpful to know when an object’s identity is important or not.  If an object reference is a copied operand, the system may have to create a proxy handle which points back to the original object, so that side effects are visible.  Proxies must be managed carefully, and this can be expensive.  On the other hand, value types are exactly those types which a JVM can “copy and forget” with no downside. Array types are crucial to bulk data interfaces.  (As data sizes and rates increase, bulk data becomes more important than scalar data, so arrays are definitely accompanying us into the future of computing.)  Value types are very helpful for adding structure to bulk data, so a successful value type mechanism will make it easier for us to express richer forms of bulk data. Unboxing arrays (i.e., arrays containing unboxed values) will provide better cache and memory density, and more direct data movement within clustered or heterogeneous computing systems.  They require the deepest transformations, relative to today’s JVM.  There is an impedance mismatch between value-type arrays and Java’s covariant array typing, so compromises will need to be struck with existing Java semantics.  It is probably worth the effort, since arrays of unboxed value types are inherently more memory-efficient than standard Java arrays, which rely on dependent pointer chains. It may be sufficient to extend the “value-safe” concept to array declarations, and allow low-level transformations to change value-safe array declarations from the standard boxed form into an unboxed tuple-based form.  Such value-safe arrays would not be convertible to Object[] arrays.  Certain connection points, such as Arrays.copyOf and System.arraycopy might need additional input/output combinations, to allow smooth conversion between arrays with boxed and unboxed elements. Alternatively, the correct solution may have to wait until we have enough reification of generic types, and enough operator overloading, to enable an overhaul of Java arrays. Implicit Method Definitions The example of class Complex above may be unattractively complex.  I believe most or all of the elements of the example class are required by the logic of value types. If this is true, a programmer who writes a value type will have to write lots of error-prone boilerplate code.  On the other hand, I think nearly all of the code (except for the domain-specific parts like plus and minus) can be implicitly generated. Java has a rule for implicitly defining a class’s constructor, if no it defines no constructors explicitly.  Likewise, there are rules for providing default access modifiers for interface members.  Because of the highly regular structure of value types, it might be reasonable to perform similar implicit transformations on value types.  Here’s an example of a “highly implicit” definition of a complex number type: public class Complex implements ValueType {  // implicitly final     public double re, im;  // implicitly public final     //implicit methods are defined elementwise from te fields:     //  toString, asList, equals(2), hashCode, valueOf, cast     //optionally, explicit methods (plus, abs, etc.) would go here } In other words, with the right defaults, a simple value type definition can be a one-liner.  The observant reader will have noticed the similarities (and suitable differences) between the explicit methods above and the corresponding methods for List<T>. Another way to abbreviate such a class would be to make an annotation the primary trigger of the functionality, and to add the interface(s) implicitly: public @ValueType class Complex { … // implicitly final, implements ValueType (But to me it seems better to communicate the “magic” via an interface, even if it is rooted in an annotation.) Implicitly Defined Value Types So far we have been working with nominal value types, which is to say that the sequence of typed components is associated with a name and additional methods that convey the intention of the programmer.  A simple ordered pair of floating point numbers can be variously interpreted as (to name a few possibilities) a rectangular or polar complex number or Cartesian point.  The name and the methods convey the intended meaning. But what if we need a truly simple ordered pair of floating point numbers, without any further conceptual baggage?  Perhaps we are writing a method (like “divideAndRemainder”) which naturally returns a pair of numbers instead of a single number.  Wrapping the pair of numbers in a nominal type (like “QuotientAndRemainder”) makes as little sense as wrapping a single return value in a nominal type (like “Quotient”).  What we need here are structural value types commonly known as tuples. For the present discussion, let us assign a conventional, JVM-friendly name to tuples, roughly as follows: public class java.lang.tuple.$DD extends java.lang.tuple.Tuple {      double $1, $2; } Here the component names are fixed and all the required methods are defined implicitly.  The supertype is an abstract class which has suitable shared declarations.  The name itself mentions a JVM-style method parameter descriptor, which may be “cracked” to determine the number and types of the component fields. The odd thing about such a tuple type (and structural types in general) is it must be instantiated lazily, in response to linkage requests from one or more classes that need it.  The JVM and/or its class loaders must be prepared to spin a tuple type on demand, given a simple name reference, $xyz, where the xyz is cracked into a series of component types.  (Specifics of naming and name mangling need some tasteful engineering.) Tuples also seem to demand, even more than nominal types, some support from the language.  (This is probably because notations for non-nominal types work best as combinations of punctuation and type names, rather than named constructors like Function3 or Tuple2.)  At a minimum, languages with tuples usually (I think) have some sort of simple bracket notation for creating tuples, and a corresponding pattern-matching syntax (or “destructuring bind”) for taking tuples apart, at least when they are parameter lists.  Designing such a syntax is no simple thing, because it ought to play well with nominal value types, and also with pre-existing Java features, such as method parameter lists, implicit conversions, generic types, and reflection.  That is a task for another day. Other Use Cases Besides complex numbers and simple tuples there are many use cases for value types.  Many tuple-like types have natural value-type representations. These include rational numbers, point locations and pixel colors, and various kinds of dates and addresses. Other types have a variable-length ‘tail’ of internal values. The most common example of this is String, which is (mathematically) a sequence of UTF-16 character values. Similarly, bit vectors, multiple-precision numbers, and polynomials are composed of sequences of values. Such types include, in their representation, a reference to a variable-sized data structure (often an array) which (somehow) represents the sequence of values. The value type may also include ’header’ information. Variable-sized values often have a length distribution which favors short lengths. In that case, the design of the value type can make the first few values in the sequence be direct ’header’ fields of the value type. In the common case where the header is enough to represent the whole value, the tail can be a shared null value, or even just a null reference. Note that the tail need not be an immutable object, as long as the header type encapsulates it well enough. This is the case with String, where the tail is a mutable (but never mutated) character array. Field types and their order must be a globally visible part of the API.  The structure of the value type must be transparent enough to have a globally consistent unboxed representation, so that all callers and callees agree about the type and order of components  that appear as parameters, return types, and array elements.  This is a trade-off between efficiency and encapsulation, which is forced on us when we remove an indirection enjoyed by boxed representations.  A JVM-only transformation would not care about such visibility, but a bytecode transformation would need to take care that (say) the components of complex numbers would not get swapped after a redefinition of Complex and a partial recompile.  Perhaps constant pool references to value types need to declare the field order as assumed by each API user. This brings up the delicate status of private fields in a value type.  It must always be possible to load, store, and copy value types as coordinated groups, and the JVM performs those movements by moving individual scalar values between locals and stack.  If a component field is not public, what is to prevent hostile code from plucking it out of the tuple using a rogue aload or astore instruction?  Nothing but the verifier, so we may need to give it more smarts, so that it treats value types as inseparable groups of stack slots or locals (something like long or double). My initial thought was to make the fields always public, which would make the security problem moot.  But public is not always the right answer; consider the case of String, where the underlying mutable character array must be encapsulated to prevent security holes.  I believe we can win back both sides of the tradeoff, by training the verifier never to split up the components in an unboxed value.  Just as the verifier encapsulates the two halves of a 64-bit primitive, it can encapsulate the the header and body of an unboxed String, so that no code other than that of class String itself can take apart the values. Similar to String, we could build an efficient multi-precision decimal type along these lines: public final class DecimalValue extends ValueType {     protected final long header;     protected private final BigInteger digits;     public DecimalValue valueOf(int value, int scale) {         assert(scale >= 0);         return new DecimalValue(((long)value << 32) + scale, null);     }     public DecimalValue valueOf(long value, int scale) {         if (value == (int) value)             return valueOf((int)value, scale);         return new DecimalValue(-scale, new BigInteger(value));     } } Values of this type would be passed between methods as two machine words. Small values (those with a significand which fits into 32 bits) would be represented without any heap data at all, unless the DecimalValue itself were boxed. (Note the tension between encapsulation and unboxing in this case.  It would be better if the header and digits fields were private, but depending on where the unboxing information must “leak”, it is probably safer to make a public revelation of the internal structure.) Note that, although an array of Complex can be faked with a double-length array of double, there is no easy way to fake an array of unboxed DecimalValues.  (Either an array of boxed values or a transposed pair of homogeneous arrays would be reasonable fallbacks, in a current JVM.)  Getting the full benefit of unboxing and arrays will require some new JVM magic. Although the JVM emphasizes portability, system dependent code will benefit from using machine-level types larger than 64 bits.  For example, the back end of a linear algebra package might benefit from value types like Float4 which map to stock vector types.  This is probably only worthwhile if the unboxing arrays can be packed with such values. More Daydreams A more finely-divided design for dynamic enforcement of value safety could feature separate marker interfaces for each invariant.  An empty marker interface Unsynchronizable could cause suitable exceptions for monitor instructions on objects in marked classes.  More radically, a Interchangeable marker interface could cause JVM primitives that are sensitive to object identity to raise exceptions; the strangest result would be that the acmp instruction would have to be specified as raising an exception. @ValueSafe public interface ValueType extends java.io.Serializable,         Unsynchronizable, Interchangeable { … public class Complex implements ValueType {     // inherits Serializable, Unsynchronizable, Interchangeable, @ValueSafe     … It seems possible that Integer and the other wrapper types could be retro-fitted as value-safe types.  This is a major change, since wrapper objects would be unsynchronizable and their references interchangeable.  It is likely that code which violates value-safety for wrapper types exists but is uncommon.  It is less plausible to retro-fit String, since the prominent operation String.intern is often used with value-unsafe code. We should also reconsider the distinction between boxed and unboxed values in code.  The design presented above obscures that distinction.  As another thought experiment, we could imagine making a first class distinction in the type system between boxed and unboxed representations.  Since only primitive types are named with a lower-case initial letter, we could define that the capitalized version of a value type name always refers to the boxed representation, while the initial lower-case variant always refers to boxed.  For example: complex pi = complex.valueOf(Math.PI, 0); Complex boxPi = pi;  // convert to boxed myList.add(boxPi); complex z = myList.get(0);  // unbox Such a convention could perhaps absorb the current difference between int and Integer, double and Double. It might also allow the programmer to express a helpful distinction among array types. As said above, array types are crucial to bulk data interfaces, but are limited in the JVM.  Extending arrays beyond the present limitations is worth thinking about; for example, the Maxine JVM implementation has a hybrid object/array type.  Something like this which can also accommodate value type components seems worthwhile.  On the other hand, does it make sense for value types to contain short arrays?  And why should random-access arrays be the end of our design process, when bulk data is often sequentially accessed, and it might make sense to have heterogeneous streams of data as the natural “jumbo” data structure.  These considerations must wait for another day and another note. More Work It seems to me that a good sequence for introducing such value types would be as follows: Add the value-safety restrictions to an experimental version of javac. Code some sample applications with value types, including Complex and DecimalValue. Create an experimental JVM which internally unboxes value types but does not require new bytecodes to do so.  Ensure the feasibility of the performance model for the sample applications. Add tuple-like bytecodes (with or without generic type reification) to a major revision of the JVM, and teach the Java compiler to switch in the new bytecodes without code changes. A staggered roll-out like this would decouple language changes from bytecode changes, which is always a convenient thing. A similar investigation should be applied (concurrently) to array types.  In this case, it seems to me that the starting point is in the JVM: Add an experimental unboxing array data structure to a production JVM, perhaps along the lines of Maxine hybrids.  No bytecode or language support is required at first; everything can be done with encapsulated unsafe operations and/or method handles. Create an experimental JVM which internally unboxes value types but does not require new bytecodes to do so.  Ensure the feasibility of the performance model for the sample applications. Add tuple-like bytecodes (with or without generic type reification) to a major revision of the JVM, and teach the Java compiler to switch in the new bytecodes without code changes. That’s enough musing me for now.  Back to work!

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  • Entity Framework Batch Update and Future Queries

    - by pwelter34
    Entity Framework Extended Library A library the extends the functionality of Entity Framework. Features Batch Update and Delete Future Queries Audit Log Project Package and Source NuGet Package PM> Install-Package EntityFramework.Extended NuGet: http://nuget.org/List/Packages/EntityFramework.Extended Source: http://github.com/loresoft/EntityFramework.Extended Batch Update and Delete A current limitations of the Entity Framework is that in order to update or delete an entity you have to first retrieve it into memory. Now in most scenarios this is just fine. There are however some senerios where performance would suffer. Also, for single deletes, the object must be retrieved before it can be deleted requiring two calls to the database. Batch update and delete eliminates the need to retrieve and load an entity before modifying it. Deleting //delete all users where FirstName matches context.Users.Delete(u => u.FirstName == "firstname"); Update //update all tasks with status of 1 to status of 2 context.Tasks.Update( t => t.StatusId == 1, t => new Task {StatusId = 2}); //example of using an IQueryable as the filter for the update var users = context.Users .Where(u => u.FirstName == "firstname"); context.Users.Update( users, u => new User {FirstName = "newfirstname"}); Future Queries Build up a list of queries for the data that you need and the first time any of the results are accessed, all the data will retrieved in one round trip to the database server. Reducing the number of trips to the database is a great. Using this feature is as simple as appending .Future() to the end of your queries. To use the Future Queries, make sure to import the EntityFramework.Extensions namespace. Future queries are created with the following extension methods... Future() FutureFirstOrDefault() FutureCount() Sample // build up queries var q1 = db.Users .Where(t => t.EmailAddress == "[email protected]") .Future(); var q2 = db.Tasks .Where(t => t.Summary == "Test") .Future(); // this triggers the loading of all the future queries var users = q1.ToList(); In the example above, there are 2 queries built up, as soon as one of the queries is enumerated, it triggers the batch load of both queries. // base query var q = db.Tasks.Where(t => t.Priority == 2); // get total count var q1 = q.FutureCount(); // get page var q2 = q.Skip(pageIndex).Take(pageSize).Future(); // triggers execute as a batch int total = q1.Value; var tasks = q2.ToList(); In this example, we have a common senerio where you want to page a list of tasks. In order for the GUI to setup the paging control, you need a total count. With Future, we can batch together the queries to get all the data in one database call. Future queries work by creating the appropriate IFutureQuery object that keeps the IQuerable. The IFutureQuery object is then stored in IFutureContext.FutureQueries list. Then, when one of the IFutureQuery objects is enumerated, it calls back to IFutureContext.ExecuteFutureQueries() via the LoadAction delegate. ExecuteFutureQueries builds a batch query from all the stored IFutureQuery objects. Finally, all the IFutureQuery objects are updated with the results from the query. Audit Log The Audit Log feature will capture the changes to entities anytime they are submitted to the database. The Audit Log captures only the entities that are changed and only the properties on those entities that were changed. The before and after values are recorded. AuditLogger.LastAudit is where this information is held and there is a ToXml() method that makes it easy to turn the AuditLog into xml for easy storage. The AuditLog can be customized via attributes on the entities or via a Fluent Configuration API. Fluent Configuration // config audit when your application is starting up... var auditConfiguration = AuditConfiguration.Default; auditConfiguration.IncludeRelationships = true; auditConfiguration.LoadRelationships = true; auditConfiguration.DefaultAuditable = true; // customize the audit for Task entity auditConfiguration.IsAuditable<Task>() .NotAudited(t => t.TaskExtended) .FormatWith(t => t.Status, v => FormatStatus(v)); // set the display member when status is a foreign key auditConfiguration.IsAuditable<Status>() .DisplayMember(t => t.Name); Create an Audit Log var db = new TrackerContext(); var audit = db.BeginAudit(); // make some updates ... db.SaveChanges(); var log = audit.LastLog;

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  • OSB and Coherence Integration

    - by mark.ms.smith
    Anyone who has tried to manage Coherence nodes or tried to cache results in OSB, will appreciate the new functionality now available. As of WebLogic Server 10.3.4, you can use the WebLogic Administration Server, via the Administration Console or WLST, and java-based Node Manager to manage and monitor the life cycle of stand-alone Coherence cache servers. This is a great step forward as the previous options mainly involved writing your own scripts to do this. You can find an excellent description of how this works at James Bayer’s blog. You can also find the WebLogic documentation here.As of Oracle Service Bus 11gR1 (11.1.1.3.0), OSB now supports service result caching for Business Bervices with Coherence. If you use Business Services that return somewhat static results that do not change often, you can configure those Business Services to cache results. For Business Services that use result caching, you can control the time to live for the cached result. After the cached result expires, the next Business Service call results in invoking the back-end service to get the result. This result is then stored in the cache for future requests to access. I’m thinking that this caching functionality would be perfect for some sort of cross reference data that was refreshed nightly by batch. You can find the OSB Business Service documentation here.Result Caching in a dedicated JVMThis example demonstrates these new features by configuring a OSB Business Service to cache results in a separate Coherence JVM managed by WebLogic. The reason why you may want to use a separate, dedicated JVM is that the result cache data could potentially be quite large and you may want to protect your OSB java heap.In this example, the client will call an OSB Proxy Service to get Employee data based on an Employee Id. Using a Business Service, OSB calls an external system. The results are automatically cached and when called again, the respective results are retrieved from the cache rather than the external system.Step 1 – Set up your Coherence Server Via the OSB Administration Server Console, create your Coherence Server to be used as the results cache.Here are the configured Coherence Server arguments from the Server Start tab. Note that I’m using the default Cache Config and Override files in the domain.-Xms256m -Xmx512m -XX:PermSize=128m -XX:MaxPermSize=256m -Dtangosol.coherence.override=/app/middleware/jdev_11.1.1.4/user_projects/domains/osb_domain2/config/osb/coherence/osb-coherence-override.xml -Dtangosol.coherence.cluster=OSB-cluster -Dtangosol.coherence.cacheconfig=/app/middleware/jdev_11.1.1.4/user_projects/domains/osb_domain2/config/osb/coherence/osb-coherence-cache-config.xml -Dtangosol.coherence.distributed.localstorage=true -Dtangosol.coherence.management=all -Dtangosol.coherence.management.remote=true -Dcom.sun.management.jmxremote Just incase you need it, here is my Coherence Server classpath:/app/middleware/jdev_11.1.1.4/oracle_common/modules/oracle.coherence_3.6/coherence.jar: /app/middleware/jdev_11.1.1.4/modules/features/weblogic.server.modules.coherence.server_10.3.4.0.jar: /app/middleware/jdev_11.1.1.4/oracle_osb/lib/osb-coherence-client.jarBy default, OSB will try and create a local result cache instance. You need to disable this by adding the following JVM parameters to each of the OSB Managed Servers:-Dtangosol.coherence.distributed.localstorage=false -DOSB.coherence.cluster=OSB-clusterIf you need more information on configuring a remote result cache, have a look at the configuration documentration under the heading Using an Out-of-Process Coherence Cache Server.Step 2 – Configure your Business Service Under the respective Business Service Message Handling Configuration (Advanced Properties), you need to enable “Result Caching”. Additionally, you need to determine what the cache data will be keyed on. In the example below, I’m keying it on the unique Employee Id.The Results As this test was on my laptop, the actual timings are just an indication that there is a benefit to caching results. Using my test harness, I sent 10,000 requests to OSB, all with the same Employee Id. In this case, I had result caching disabled.You can see that this caused the back end Business Service (BS_GetEmployeeData) to be called for each request. Then after enabling result caching, I sent the same number of identical requests.You can now see the Business Service was only invoked once on the first request. All subsequent requests used the Results Cache.

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  • JavaScript Intellisense Improvements with VS 2010

    - by ScottGu
    This is the twentieth in a series of blog posts I’m doing on the upcoming VS 2010 and .NET 4 release.  Today’s blog post covers some of the nice improvements coming with JavaScript intellisense with VS 2010 and the free Visual Web Developer 2010 Express.  You’ll find with VS 2010 that JavaScript Intellisense loads much faster for large script files and with large libraries, and that it now provides statement completion support for more advanced scenarios compared to previous versions of Visual Studio. [In addition to blogging, I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu] Improved JavaScript Intellisense Providing Intellisense for a dynamic language like JavaScript is more involved than doing so with a statically typed language like VB or C#.  Correctly inferring the shape and structure of variables, methods, etc is pretty much impossible without pseudo-executing the actual code itself – since JavaScript as a language is flexible enough to dynamically modify and morph these things at runtime.  VS 2010’s JavaScript code editor now has the smarts to perform this type of pseudo-code execution as you type – which is how its intellisense completion is kept accurate and complete.  Below is a simple walkthrough that shows off how rich and flexible it is with the final release. Scenario 1: Basic Type Inference When you declare a variable in JavaScript you do not have to declare its type.  Instead, the type of the variable is based on the value assigned to it.  Because VS 2010 pseudo-executes the code within the editor, it can dynamically infer the type of a variable, and provide the appropriate code intellisense based on the value assigned to a variable. For example, notice below how VS 2010 provides statement completion for a string (because we assigned a string to the “foo” variable): If we later assign a numeric value to “foo” the statement completion (after this assignment) automatically changes to provide intellisense for a number: Scenario 2: Intellisense When Manipulating Browser Objects It is pretty common with JavaScript to manipulate the DOM of a page, as well as work against browser objects available on the client.  Previous versions of Visual Studio would provide JavaScript statement completion against the standard browser objects – but didn’t provide much help with more advanced scenarios (like creating dynamic variables and methods).  VS 2010’s pseudo-execution of code within the editor now allows us to provide rich intellisense for a much broader set of scenarios. For example, below we are using the browser’s window object to create a global variable named “bar”.  Notice how we can now get intellisense (with correct type inference for a string) with VS 2010 when we later try and use it: When we assign the “bar” variable as a number (instead of as a string) the VS 2010 intellisense engine correctly infers its type and modifies statement completion appropriately to be that of a number instead: Scenario 3: Showing Off Because VS 2010 is psudo-executing code within the editor, it is able to handle a bunch of scenarios (both practical and wacky) that you throw at it – and is still able to provide accurate type inference and intellisense. For example, below we are using a for-loop and the browser’s window object to dynamically create and name multiple dynamic variables (bar1, bar2, bar3…bar9).  Notice how the editor’s intellisense engine identifies and provides statement completion for them: Because variables added via the browser’s window object are also global variables – they also now show up in the global variable intellisense drop-down as well: Better yet – type inference is still fully supported.  So if we assign a string to a dynamically named variable we will get type inference for a string.  If we assign a number we’ll get type inference for a number.  Just for fun (and to show off!) we could adjust our for-loop to assign a string for even numbered variables (bar2, bar4, bar6, etc) and assign a number for odd numbered variables (bar1, bar3, bar5, etc): Notice above how we get statement completion for a string for the “bar2” variable.  Notice below how for “bar1” we get statement completion for a number:   This isn’t just a cool pet trick While the above example is a bit contrived, the approach of dynamically creating variables, methods and event handlers on the fly is pretty common with many Javascript libraries.  Many of the more popular libraries use these techniques to keep the size of script library downloads as small as possible.  VS 2010’s support for parsing and pseudo-executing libraries that use these techniques ensures that you get better code Intellisense out of the box when programming against them. Summary Visual Studio 2010 (and the free Visual Web Developer 2010 Express) now provide much richer JavaScript intellisense support.  This support works with pretty much all popular JavaScript libraries.  It should help provide a much better development experience when coding client-side JavaScript and enabling AJAX scenarios within your ASP.NET applications. Hope this helps, Scott P.S. You can read my previous blog post on VS 2008’s JavaScript Intellisense to learn more about our previous JavaScript intellisense (and some of the scenarios it supported).  VS 2010 obviously supports all of the scenarios previously enabled with VS 2008.

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  • Getting Started with Prism (aka Composite Application Guidance for WPF and Silverlight)

    - by dotneteer
    Overview Prism is a framework from the Microsoft Patterns and Practice team that allow you to create WPF and Silverlight in a modular way. It is especially valuable for larger projects in which a large number of developers can develop in parallel. Prism achieves its goal by supplying several services: · Dependency Injection (DI) and Inversion of control (IoC): By using DI, Prism takes away the responsibility of instantiating and managing the life time of dependency objects from individual components to a container. Prism relies on containers to discover, manage and compose large number of objects. By varying the configuration, the container can also inject mock objects for unit testing. Out of the box, Prism supports Unity and MEF as container although it is possible to use other containers by subclassing the Bootstrapper class. · Modularity and Region: Prism supplies the framework to split application into modules from the application shell. Each module is a library project that contains both UI and code and is responsible to initialize itself when loaded by the shell. Each window can be further divided into regions. A region is a user control with associated model. · Model, view and view-model (MVVM) pattern: Prism promotes the user MVVM. The use of DI container makes it much easier to inject model into view. WPF already has excellent data binding and commanding mechanism. To be productive with Prism, it is important to understand WPF data binding and commanding well. · Event-aggregation: Prism promotes loosely coupled components. Prism discourages for components from different modules to communicate each other, thus leading to dependency. Instead, Prism supplies an event-aggregation mechanism that allows components to publish and subscribe events without knowing each other. Architecture In the following, I will go into a little more detail on the services provided by Prism. Bootstrapper In a typical WPF application, application start-up is controls by App.xaml and its code behind. The main window of the application is typically specified in the App.xaml file. In a Prism application, we start a bootstrapper in the App class and delegate the duty of main window to the bootstrapper. The bootstrapper will start a dependency-injection container so all future object instantiations are managed by the container. Out of box, Prism provides the UnityBootstrapper and MefUnityBootstrapper abstract classes. All application needs to either provide a concrete implementation of one of these bootstrappers, or alternatively, subclass the Bootstrapper class with another DI container. A concrete bootstrapper class must implement the CreateShell method. Its responsibility is to resolve and create the Shell object through the DI container to serve as the main window for the application. The other important method to override is ConfigureModuleCatalog. The bootstrapper can register modules for the application. In a more advance scenario, an application does not have to know all its modules at compile time. Modules can be discovered at run time. Readers to refer to one of the Open Modularity Quick Starts for more information. Modules Once modules are registered with or discovered by Prism, they are instantiated by the DI container and their Initialize method is called. The DI container can inject into a module a region registry that implements IRegionViewRegistry interface. The module, in its Initialize method, can then call RegisterViewWithRegion method of the registry to register its regions. Regions Regions, once registered, are managed by the RegionManager. The shell can then load regions either through the RegionManager.RegionName attached property or dynamically through code. When a view is created by the region manager, the DI container can inject view model and other services into the view. The view then has a reference to the view model through which it can interact with backend services. Service locator Although it is possible to inject services into dependent classes through a DI container, an alternative way is to use the ServiceLocator to retrieve a service on demard. Prism supplies a service locator implementation and it is possible to get an instance of the service by calling: ServiceLocator.Current.GetInstance<IServiceType>() Event aggregator Prism supplies an IEventAggregator interface and implementation that can be injected into any class that needs to communicate with each other in a loosely-coupled fashion. The event aggregator uses a publisher/subscriber model. A class can publishes an event by calling eventAggregator.GetEvent<EventType>().Publish(parameter) to raise an event. Other classes can subscribe the event by calling eventAggregator.GetEvent<EventType>().Subscribe(EventHandler, other options). Getting started The easiest way to get started with Prism is to go through the Prism Hands-On labs and look at the Hello World QuickStart. The Hello World QuickStart shows how bootstrapper, modules and region works. Next, I would recommend you to look at the Stock Trader Reference Implementation. It is a more in depth example that resemble we want to set up an application. Several other QuickStarts cover individual Prism services. Some scenarios, such as dynamic module discovery, are more advanced. Apart from the official prism document, you can get an overview by reading Glen Block’s MSDN Magazine article. I have found the best free training material is from the Boise Code Camp. To be effective with Prism, it is important to understands key concepts of WPF well first, such as the DependencyProperty system, data binding, resource, theme and ICommand. It is also important to know your DI container of choice well. I will try to explorer these subjects in depth in the future. Testimony Recently, I worked on a desktop WPF application using Prism. I had a wonderful experience with Prism. The Prism is flexible enough even in the presence of third party controls such as Telerik WPF controls. We have never encountered any significant obstacle.

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  • Oracle Big Data Software Downloads

    - by Mike.Hallett(at)Oracle-BI&EPM
    Companies have been making business decisions for decades based on transactional data stored in relational databases. Beyond that critical data, is a potential treasure trove of less structured data: weblogs, social media, email, sensors, and photographs that can be mined for useful information. Oracle offers a broad integrated portfolio of products to help you acquire and organize these diverse data sources and analyze them alongside your existing data to find new insights and capitalize on hidden relationships. Oracle Big Data Connectors Downloads here, includes: Oracle SQL Connector for Hadoop Distributed File System Release 2.1.0 Oracle Loader for Hadoop Release 2.1.0 Oracle Data Integrator Companion 11g Oracle R Connector for Hadoop v 2.1 Oracle Big Data Documentation The Oracle Big Data solution offers an integrated portfolio of products to help you organize and analyze your diverse data sources alongside your existing data to find new insights and capitalize on hidden relationships. Oracle Big Data, Release 2.2.0 - E41604_01 zip (27.4 MB) Integrated Software and Big Data Connectors User's Guide HTML PDF Oracle Data Integrator (ODI) Application Adapter for Hadoop Apache Hadoop is designed to handle and process data that is typically from data sources that are non-relational and data volumes that are beyond what is handled by relational databases. Typical processing in Hadoop includes data validation and transformations that are programmed as MapReduce jobs. Designing and implementing a MapReduce job usually requires expert programming knowledge. However, when you use Oracle Data Integrator with the Application Adapter for Hadoop, you do not need to write MapReduce jobs. Oracle Data Integrator uses Hive and the Hive Query Language (HiveQL), a SQL-like language for implementing MapReduce jobs. Employing familiar and easy-to-use tools and pre-configured knowledge modules (KMs), the application adapter provides the following capabilities: Loading data into Hadoop from the local file system and HDFS Performing validation and transformation of data within Hadoop Loading processed data from Hadoop to an Oracle database for further processing and generating reports Oracle Database Loader for Hadoop Oracle Loader for Hadoop is an efficient and high-performance loader for fast movement of data from a Hadoop cluster into a table in an Oracle database. It pre-partitions the data if necessary and transforms it into a database-ready format. Oracle Loader for Hadoop is a Java MapReduce application that balances the data across reducers to help maximize performance. Oracle R Connector for Hadoop Oracle R Connector for Hadoop is a collection of R packages that provide: Interfaces to work with Hive tables, the Apache Hadoop compute infrastructure, the local R environment, and Oracle database tables Predictive analytic techniques, written in R or Java as Hadoop MapReduce jobs, that can be applied to data in HDFS files You install and load this package as you would any other R package. Using simple R functions, you can perform tasks such as: Access and transform HDFS data using a Hive-enabled transparency layer Use the R language for writing mappers and reducers Copy data between R memory, the local file system, HDFS, Hive, and Oracle databases Schedule R programs to execute as Hadoop MapReduce jobs and return the results to any of those locations Oracle SQL Connector for Hadoop Distributed File System Using Oracle SQL Connector for HDFS, you can use an Oracle Database to access and analyze data residing in Hadoop in these formats: Data Pump files in HDFS Delimited text files in HDFS Hive tables For other file formats, such as JSON files, you can stage the input in Hive tables before using Oracle SQL Connector for HDFS. Oracle SQL Connector for HDFS uses external tables to provide Oracle Database with read access to Hive tables, and to delimited text files and Data Pump files in HDFS. Related Documentation Cloudera's Distribution Including Apache Hadoop Library HTML Oracle R Enterprise HTML Oracle NoSQL Database HTML Recent Blog Posts Big Data Appliance vs. DIY Price Comparison Big Data: Architecture Overview Big Data: Achieve the Impossible in Real-Time Big Data: Vertical Behavioral Analytics Big Data: In-Memory MapReduce Flume and Hive for Log Analytics Building Workflows in Oozie

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  • MySQL Cluster 7.3: On-Demand Webinar and Q&A Available

    - by Mat Keep
    The on-demand webinar for the MySQL Cluster 7.3 Development Release is now available. You can learn more about the design, implementation and getting started with all of the new MySQL Cluster 7.3 features from the comfort and convenience of your own device, including: - Foreign Key constraints in MySQL Cluster - Node.js NoSQL API  - Auto-installation of higher performance distributed, clusters We received some great questions over the course of the webinar, and I wanted to share those for the benefit of a broader audience. Q. What Foreign Key actions are supported: A. The core referential actions defined in the SQL:2003 standard are implemented: CASCADE RESTRICT NO ACTION SET NULL Q. Where are Foreign Keys implemented, ie data nodes or SQL nodes? A. They are implemented in the data nodes, therefore can be enforced for both the SQL and NoSQL APIs Q. Are they compatible with the InnoDB Foreign Key implementation? A. Yes, with the following exceptions: - InnoDB doesn’t support “No Action” constraints, MySQL Cluster does - You can choose to suspend FK constraint enforcement with InnoDB using the FOREIGN_KEY_CHECKS parameter; at the moment, MySQL Cluster ignores that parameter. - You cannot set up FKs between 2 tables where one is stored using MySQL Cluster and the other InnoDB. - You cannot change primary keys through the NDB API which means that the MySQL Server actually has to simulate such operations by deleting and re-adding the row. If the PK in the parent table has a FK constraint on it then this causes non-ideal behaviour. With Restrict or No Action constraints, the change will result in an error. With Cascaded constraints, you’d want the rows in the child table to be updated with the new FK value but, the implicit delete of the row from the parent table would remove the associated rows from the child table and the subsequent implicit insert into the parent wouldn’t reinstate the child rows. For this reason, an attempt to add an ON UPDATE CASCADE where the parent column is a primary key will be rejected. Q. Does adding or dropping Foreign Keys cause downtime due to a schema change? A. Nope, this is an online operation. MySQL Cluster supports a number of on-line schema changes, ie adding and dropping indexes, adding columns, etc. Q. Where can I see an example of node.js with MySQL Cluster? A. Check out the tutorial and download the code from GitHub Q. Can I use the auto-installer to support remote deployments? How about setting up MySQL Cluster 7.2? A. Yes to both! Q. Can I get a demo Check out the tutorial. You can download the code from http://labs.mysql.com/ Go to Select Build drop-down box Q. What is be minimum internet speen required for Geo distributed cluster with synchronous replication? A. if you're splitting you cluster between sites then we recommend a network latency of 20ms or less. Alternatively, use MySQL asynchronous replication where the latency of your WAN doesn't impact the latency of your reads/writes. Q. Where you can one learn more about the PayPal project with MySQL Cluster? A. Take a look at the following - you'll find press coverage, a video and slides from their keynote presentation  So, if you want to learn more, listen to the new MySQL Cluster 7.3 on-demand webinar  MySQL Cluster 7.3 is still in the development phase, so it would be great to get your feedback on these new features, and things you want to see!

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  • Orchestrating the Virtual Enterprise, Part II

    - by Kathryn Perry
    A guest post by Jon Chorley, Oracle's CSO & Vice President, SCM Product Strategy Almost everyone has ordered from Amazon.com at one time or another. Our orders are as likely to be fulfilled by third parties as they are by Amazon itself. To deliver the order promptly and efficiently, Amazon has to send it to the right fulfillment location and know the availability in that location. It needs to be able to track status of the fulfillment and deal with exceptions. As a virtual enterprise, Amazon's operations, using thousands of trading partners, requires a very different approach to fulfillment than the traditional 'take an order and ship it from your own warehouse' model. Amazon had no choice but to develop a complex, expensive and custom solution to tackle this problem as there used to be no product solution available. Now, other companies who want to follow similar models have a better off-the-shelf choice -- Oracle Distributed Order Orchestration (DOO).  Consider how another of our customers is using our distributed orchestration solution. This major airplane manufacturer has a highly complex business and interacts regularly with the U.S. Government and major airlines. It sits in the middle of an intricate supply chain and needed to improve visibility across its many different entities. Oracle Fusion DOO gives the company an orchestration mechanism so it could improve quality, speed, flexibility, and consistency without requiring an organ transplant of these highly complex legacy systems. Many retailers face the challenge of dealing with brick and mortar, Web, and reseller channels. They all need to be knitted together into a virtual enterprise experience that is consistent for their customers. When a large U.K. grocer with a strong brick and mortar retail operation added an online business, they turned to Oracle Fusion DOO to bring these entities together. Disturbing the Peace with Acquisitions Quite often a company's ERP system is disrupted when it acquires a new company. An acquisition can inject a new set of processes and systems -- or even introduce an entirely new business like Sun's hardware did at Oracle. This challenge has been a driver for some of our DOO customers. A large power management company is using Oracle Fusion DOO to provide the flexibility to rapidly integrate additional products and services into its central fulfillment operation. The Flip Side of Fulfillment Meanwhile, we haven't ignored similar challenges on the supply side of the equation. Specifically, how to manage complex supply in a flexible way when there are multiple trading parties involved? How to manage the supply to suppliers? How to manage critical components that need to merge in a tier two or tier three supply chain? By investing in supply orchestration solutions for the virtual enterprise, we plan to give users better visibility into their network of suppliers to help them drive down costs. We also think this technology and full orchestration process can be applied to the financial side of organizations. An example is transactions that flow through complex internal structures to minimize tax exposure. We can help companies manage those transactions effectively by thinking about the internal organization as a virtual enterprise and bringing the same solution set to this internal challenge.  The Clear Front Runner No other company is investing in solving the virtual enterprise supply chain issues like Oracle is. Oracle is in a unique position to become the gold standard in this market space. We have the infrastructure of Oracle technology. We already have an Oracle Fusion DOO application which embraces the best of what's required in this area. And we're absolutely committed to extending our Fusion solution to other use cases and delivering even more business value. Jon ChorleyChief Sustainability Officer & Vice President, SCM Product StrategyOracle Corporation

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  • Azure Mobile Services: available modules

    - by svdoever
    Azure Mobile Services has documented a set of objects available in your Azure Mobile Services server side scripts at their documentation page Mobile Services server script reference. Although the documented list is a nice list of objects for the common things you want to do, it will be sooner than later that you will look for more functionality to be included in your script, especially with the new provided feature that you can now create your custom API’s. If you use GIT it is now possible to add any NPM module (node package manager module, say the NuGet of the node world), but why include a module if it is already available out of the box. And you can only use GIT with Azure Mobile Services if you are an administrator on your Azure Mobile Service, not if you are a co-administrator (will be solved in the future). Until now I did some trial and error experimentation to test if a certain module was available. This is easiest to do as follows:   Create a custom API, for example named experiment. In this API use the following code: exports.get = function (request, response) { var module = "nonexistingmodule"; var m = require(module); response.send(200, "Module '%s' found.", module); }; You can now test your service with the following request in your browser: https://yourservice.azure-mobile.net/api/experiment If you get the result: {"code":500,"error":"Error: Internal Server Error"} you know that the module does not exist. In your logs you will find the following error: Error in script '/api/experiment.json'. Error: Cannot find module 'nonexistingmodule' [external code] atC:\DWASFiles\Sites\yourservice\VirtualDirectory0\site\wwwroot\App_Data\config\scripts\api\experiment.js:3:13[external code] If you require an existing (undocumented) module like the OAuth module in the following code, you will get success as a result: exports.get = function (request, response) { var module = "oauth"; var m = require(module); response.send(200, "Module '" + module + "' found."); }; If we look at the standard node.js documentation we see an extensive list of modules that can be used from your code. If we look at the list of files available in the Azure Mobile Services platform as documented in the blog post Azure Mobile Services: what files does it consist of? we see a folder node_modules with many more modules are used to build the Azure Mobile Services functionality on, but that can also be utilized from your server side node script code: apn - An interface to the Apple Push Notification service for Node.js. dpush - Send push notifications to Android devices using GCM. mpns - A Node.js interface to the Microsoft Push Notification Service (MPNS) for Windows Phone. wns - Send push notifications to Windows 8 devices using WNS. pusher - Node library for the Pusher server API (see also: http://pusher.com/) azure - Windows Azure Client Library for node. express - Sinatra inspired web development framework. oauth - Library for interacting with OAuth 1.0, 1.0A, 2 and Echo. Provides simplified client access and allows for construction of more complex apis and OAuth providers. request - Simplified HTTP request client. sax - An evented streaming XML parser in JavaScript sendgrid - A NodeJS implementation of the SendGrid Api. sqlserver – In node repository known as msnodesql - Microsoft Driver for Node.js for SQL Server. tripwire - Break out from scripts blocking node.js event loop. underscore - JavaScript's functional programming helper library. underscore.string - String manipulation extensions for Underscore.js javascript library. xml2js - Simple XML to JavaScript object converter. xmlbuilder - An XML builder for node.js. As stated before, many of these modules are used to provide the functionality of Azure Mobile Services platform, and in general should not be used directly. On the other hand, I needed OAuth badly to authenticate to the new v1.1 services of Twitter, and was very happy that a require('oauth') and a few lines of code did the job. Based on the above modules and a lot of code in the other javascript files in the Azure Mobile Services platform a set of global objects is provided that can be used from your server side node.js script code. In future blog posts I will go into more details with respect to how this code is built-up, all starting at the node.js express entry point app.js.

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  • Blueprints for Oracle NoSQL Database

    - by dan.mcclary
    I think that some of the most interesting analytic problems are graph problems.  I'm always interested in new ways to store and access graphs.  As such, I really like the work being done by Tinkerpop to create Open Source Software to make property graphs more accessible over a wide variety of datastores.  Since key-value stores like Oracle NoSQL Database are well-suited to storing property graphs, I decided to extend the Blueprints API to work with it.  Below I'll discuss some of the implementation details, but you can check out the finished product here: http://github.com/dwmclary/blueprints-oracle-nosqldb.  What's in a Property Graph?  In the most general sense, a graph is just a collection of vertices and edges.  Vertices and edges can have properties: weights, names, or any number of other traits.  In an undirected graph, edges connect vertices without direction.  A directed graph specifies that all edges have a head and a tail --- a direction.  A multi-graph allows multiple edges to connect two vertices.  A "property graph" encompasses all of these traits. Key-Value Stores for Property Graphs Key-Value stores like Oracle NoSQL Database tend to be ideal for implementing property graphs.  First, if any vertex or edge can have any number of traits, we can treat it as a hash map.  For example: Vertex["name"] = "Mary" Vertex["age"] = 28 Vertex["ID"] = 12345  and so on.  This is a natural key-value relationship: the key "name" maps to the value "Mary."  Moreover if we maintain two hash maps, one for vertex objects and one for edge objects, we've essentially captured the graph.  As such, any scalable key-value store is fertile ground for planting graphs. Oracle NoSQL Database as a Scalable Graph Database While Oracle NoSQL Database offers useful features like tunable consistency, what lends it to storing property graphs is the storage guarantees around its key structure.  Keys in Oracle NoSQL Database are divided into two parts: a major key and a minor key.  The storage guarantee is simple.  Major keys will be distributed across storage nodes, which could encompass a large number of servers.  However, all minor keys which are children of a given major key are guaranteed to be stored on the same storage node.  For example, the vertices: /Personnel/Vertex/1  and /Personnel/Vertex/2 May be stored on different servers, but /Personnel/Vertex/1-/name and  /Personnel/Vertex/1-/age will always be on the same server.  This means that we can structure our graph database such that retrieving all the properties for a vertex or edge requires I/O from only a single storage node.  Moreover, Oracle NoSQL Database provides a storeIterator which allows us to store a huge number of vertices and edges in a scalable fashion.  By storing the vertices and edges as major keys, we guarantee that they are distributed evenly across all storage nodes.  At the same time we can use a partial major key to iterate over all the vertices or edges (e.g. we search over /Personnel/Vertex to iterate over all vertices). Fork It! The Blueprints API and Oracle NoSQL Database present a great way to get started using a scalable key-value database to store and access graph data.  However, a graph store isn't useful without a good graph to work on.  I encourage you to fork or pull the repository, store some data, and try using Gremlin or any other language to explore.

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  • Sort Data in Windows Phone using Collection View Source

    - by psheriff
    When you write a Windows Phone application you will most likely consume data from a web service somewhere. If that service returns data to you in a sort order that you do not want, you have an easy alternative to sort the data without writing any C# or VB code. You use the built-in CollectionViewSource object in XAML to perform the sorting for you. This assumes that you can get the data into a collection that implements the IEnumerable or IList interfaces.For this example, I will be using a simple Product class with two properties, and a list of Product objects using the Generic List class. Try this out by creating a Product class as shown in the following code:public class Product {  public Product(int id, string name)   {    ProductId = id;    ProductName = name;  }  public int ProductId { get; set; }  public string ProductName { get; set; }}Create a collection class that initializes a property called DataCollection with some sample data as shown in the code below:public class Products : List<Product>{  public Products()  {    InitCollection();  }  public List<Product> DataCollection { get; set; }  List<Product> InitCollection()  {    DataCollection = new List<Product>();    DataCollection.Add(new Product(3,        "PDSA .NET Productivity Framework"));    DataCollection.Add(new Product(1,        "Haystack Code Generator for .NET"));    DataCollection.Add(new Product(2,        "Fundamentals of .NET eBook"));    return DataCollection;  }}Notice that the data added to the collection is not in any particular order. Create a Windows Phone page and add two XML namespaces to the Page.xmlns:scm="clr-namespace:System.ComponentModel;assembly=System.Windows"xmlns:local="clr-namespace:WPSortData"The 'local' namespace is an alias to the name of the project that you created (in this case WPSortData). The 'scm' namespace references the System.Windows.dll and is needed for the SortDescription class that you will use for sorting the data. Create a phone:PhoneApplicationPage.Resources section in your Windows Phone page that looks like the following:<phone:PhoneApplicationPage.Resources>  <local:Products x:Key="products" />  <CollectionViewSource x:Key="prodCollection"      Source="{Binding Source={StaticResource products},                       Path=DataCollection}">    <CollectionViewSource.SortDescriptions>      <scm:SortDescription PropertyName="ProductName"                           Direction="Ascending" />    </CollectionViewSource.SortDescriptions>  </CollectionViewSource></phone:PhoneApplicationPage.Resources>The first line of code in the resources section creates an instance of your Products class. The constructor of the Products class calls the InitCollection method which creates three Product objects and adds them to the DataCollection property of the Products class. Once the Products object is instantiated you now add a CollectionViewSource object in XAML using the Products object as the source of the data to this collection. A CollectionViewSource has a SortDescriptions collection that allows you to specify a set of SortDescription objects. Each object can set a PropertyName and a Direction property. As you see in the above code you set the PropertyName equal to the ProductName property of the Product object and tell it to sort in an Ascending direction.All you have to do now is to create a ListBox control and set its ItemsSource property to the CollectionViewSource object. The ListBox displays the data in sorted order by ProductName and you did not have to write any LINQ queries or write other code to sort the data!<ListBox    ItemsSource="{Binding Source={StaticResource prodCollection}}"   DisplayMemberPath="ProductName" />SummaryIn this blog post you learned that you can sort any data without having to change the source code of where the data comes from. Simply feed the data into a CollectionViewSource in XAML and set some sort descriptions in XAML and the rest is done for you! This comes in very handy when you are consuming data from a source where the data is given to you and you do not have control over the sorting.NOTE: You can download this article and many samples like the one shown in this blog entry at my website. http://www.pdsa.com/downloads. Select “Tips and Tricks”, then “Sort Data in Windows Phone using Collection View Source” from the drop down list.Good Luck with your Coding,Paul Sheriff** SPECIAL OFFER FOR MY BLOG READERS **We frequently offer a FREE gift for readers of my blog. Visit http://www.pdsa.com/Event/Blog for your FREE gift!

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  • SSIS: Building SQL databases on-the-fly using concatenated SQL scripts

    - by DrJohn
    Over the years I have developed many techniques which help automate the whole SQL Server build process. In my current process, where I need to build entire OLAP data marts on-the-fly, I make regular use of a simple but very effective mechanism to concatenate all the SQL Scripts together from my SSMS (SQL Server Management Studio) projects. This proves invaluable because in two clicks I can redeploy an entire SQL Server database with all tables, views, stored procedures etc. Indeed, I can also use the concatenated SQL scripts with SSIS to build SQL Server databases on-the-fly. You may be surprised to learn that I often redeploy the database several times per day, or even several times per hour, during the development process. This is because the deployment errors are logged and you can quickly see where SQL Scripts have object dependency errors. For example, after changing a table structure you may have forgotten to change any related views. The deployment log immediately points out all the objects which failed to build so you can fix and redeploy the database very quickly. The alternative approach (i.e. doing changes in the database directly using the SSMS UI) would require you to check all dependent objects before making changes. The chances are that you will miss something and wonder why your app returns the wrong data – a common problem caused by changing a table without re-creating dependent views. Using SQL Projects in SSMS A great many developers fail to make use of SQL Projects in SSMS (SQL Server Management Studio). To me they are invaluable way of organizing your SQL Scripts. The screenshot below shows a typical SSMS solution made up of several projects – one project for tables, another for views etc. The key point is that the projects naturally fall into the right order in file system because of the project name. The number in the folder or file name ensures that the projects the SQL scripts are concatenated together in the order that they need to be executed. Hence the script filenames start with 100, 110 etc. Concatenating SQL Scripts To concatenate the SQL Scripts together into one file, I use notepad.exe to create a simple batch file (see example screenshot) which uses the TYPE command to write the content of the SQL Script files into a combined file. As the SQL Scripts are in several folders, I simply use several TYPE command multiple times and append the output together. If you are unfamiliar with batch files, you may not know that the angled bracket (>) means write output of the program into a file. Two angled brackets (>>) means append output of this program into a file. So the command-line DIR > filelist.txt would write the content of the DIR command into a file called filelist.txt. In the example shown above, the concatenated file is called SB_DDS.sql If, like me you place the concatenated file under source code control, then the source code control system will change the file's attribute to "read-only" which in turn would cause the TYPE command to fail. The ATTRIB command can be used to remove the read-only flag. Using SQLCmd to execute the concatenated file Now that the SQL Scripts are all in one big file, we can execute the script against a database using SQLCmd using another batch file as shown below: SQLCmd has numerous options, but the script shown above simply executes the SS_DDS.sql file against the SB_DDS_DB database on the local machine and logs the errors to a file called SB_DDS.log. So after executing the batch file you can simply check the error log to see if your database built without a hitch. If you have errors, then simply fix the source files, re-create the concatenated file and re-run the SQLCmd to rebuild the database. This two click operation allows you to quickly identify and fix errors in your entire database definition.Using SSIS to execute the concatenated file To execute the concatenated SQL script using SSIS, you simply drop an Execute SQL task into your package and set the database connection as normal and then select File Connection as the SQLSourceType (as shown below). Create a file connection to your concatenated SQL script and you are ready to go.   Tips and TricksAdd a new-line at end of every fileThe most common problem encountered with this approach is that the GO statement on the last line of one file is placed on the same line as the comment at the top of the next file by the TYPE command. The easy fix to this is to ensure all your files have a new-line at the end.Remove all USE database statementsThe SQLCmd identifies which database the script should be run against.  So you should remove all USE database commands from your scripts - otherwise you may get unintentional side effects!!Do the Create Database separatelyIf you are using SSIS to create the database as well as create the objects and populate the database, then invoke the CREATE DATABASE command against the master database using a separate package before calling the package that executes the concatenated SQL script.    

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  • Auto-Configuring SSIS Packages

    - by Davide Mauri
    SSIS Package Configurations are very useful to make packages flexible so that you can change objects properties at run-time and thus make the package configurable without having to open and edit it. In a complex scenario where you have dozen of packages (even in in the smallest BI project I worked on I had 50 packages), each package may have its own configuration needs. This means that each time you have to run the package you have to pass the correct Package Configuration. I usually use XML configuration files and I also force everyone that works with me to make sure that an object that is used in several packages has the same name in all package where it is used, in order to simplify configurations usage. Connection Managers are a good example of one of those objects. For example, all the packages that needs to access to the Data Warehouse database must have a Connection Manager named DWH. Basically we define a set of “global” objects so that we can have a configuration file for them, so that it can be used by all packages. If a package as some specific configuration needs, we create a specific – or “local” – XML configuration file or we set the value that needs to be configured at runtime using DTLoggedExec’s Package Parameters: http://dtloggedexec.davidemauri.it/Package%20Parameters.ashx Now, how we can improve this even more? I’d like to have a package that, when it’s run, automatically goes “somewhere” and search for global or local configuration, loads it and applies it to itself. That’s the basic idea of Auto-Configuring Packages. The “somewhere” is a SQL Server table, defined in this way In this table you’ll put the values that you want to be used at runtime by your package: The ConfigurationFilter column specify to which package that configuration line has to be applied. A package will use that line only if the value specified in the ConfigurationFilter column is equal to its name. In the above sample. only the package named “simple-package” will use the line number two. There is an exception here: the $$Global value indicate a configuration row that has to be applied to any package. With this simple behavior it’s possible to replicate the “global” and the “local” configuration approach I’ve described before. The ConfigurationValue contains the value you want to be applied at runtime and the PackagePath contains the object to which that value will be applied. The ConfiguredValueType column defined the data type of the value and the Checksum column is contains a calculated value that is simply the hash value of ConfigurationFilter plus PackagePath so that it can be used as a Primary Key to guarantee uniqueness of configuration rows. As you may have noticed the table is very similar to the table originally used by SSIS in order to put DTS Configuration into SQL Server tables: SQL Server SSIS Configuration Type: http://msdn.microsoft.com/en-us/library/ms141682.aspx Now, how it works? It’s very easy: you just have to call DTLoggedExec with the /AC option: DTLoggedExec.exe /FILE:”mypackage.dtsx” /AC:"localhost;ssis_auto_configuration;ssiscfg.configuration" the AC option expects a string with the following format: <database_server>;<database_name>;<table_name>; only Windows Authentication is supported. When DTLoggedExec finds an Auto-Configuration request, it injects a new connection manager in the loaded package. The injected connection manager is named $$DTLoggedExec_AutoConfigure and is used by the two SQL Server DTS Configuration ($$DTLoggedExec_Global and $$DTLoggedExec_Local) also injected by DTLoggedExec, used to load “local” and “global” configuration. Now, you may start to wonder why this approach cannot be used without having all this stuff going around, but just passing to a package always two XML DTS Configuration files, (to have to “local” and the “global” configurations) doing something like this: DTLoggedExec.exe /FILE:”mypackage.dtsx” /CONF:”global.dtsConfig” /CONF:”mypackage.dtsConfig” The problem is that this approach doesn’t work if you have, in one of the two configuration file, a value that has to be applied to an object that doesn’t exists in the loaded package. This situation will raise an error that will halt package execution. To solve this problem, you may want to create a configuration file for each package. Unfortunately this will make deployment and management harder, since you’ll have to deal with a great number of configuration files. The Auto-Configuration approach solve all these problems at once! We’re using it in a project where we have hundreds of packages and I can tell you that deployment of packages and their configuration for the pre-production and production environment has never been so easy! To use the Auto-Configuration option you have to download the latest DTLoggedExec release: http://dtloggedexec.codeplex.com/releases/view/62218 Feedback, as usual, are very welcome!

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  • My Dog, Cross-Channel Shopping, and Fusion SCM

    - by Kathryn Perry
    A guest post by Mark Carson, Director, Oracle Fusion Supply Chain Management I was walking my dog Max in an open space behind my house. As we tromped through the tall weeds I remembered it is tick season and that I should get Max some protection. While he sniffed merrily in the tick infested brush, I started shopping in the middle of an open field on my phone. I thought it would be convenient to pick up the tick medicine from a pet store on the way home. Searching the pet store website I saw that they had the medicine, but there was no information on whether the store had any in stock and there were no options for shipping it to the store for pickup. I could return it, but not pick it up which seamed kind of odd. I really didn't feel like making calls to the local stores to find out if they had it. Since the product is popular, I tried one of the large 'everything' stores. Browsing its website I could see that it could be shipped to me, shipped to the store for free, and that the store nearest to me had it in stock. Needless to say, this store became a better option. This experience is a small example of why retailers, distributors, and manufactures have placed a high priority on enabling 'cross-channel commerce.' Shoppers like you and me expect to be able to search, compare, buy and return products on-line and over the phone using a variety of devices including PDAs, tablets and in-store kiosks. The pet store lost my business because its web channel had limited information about its stores. I have spoken with many customers and prospects about cross-channel commerce. They all realize the business implications and urgency behind cross-channel commerce but recognize there are challenges to enable it. New and existing applications must be integrated together globally through a consistent cross-channel business process. Integration is required between applications that provide the initial shopping experience and delivery applications associated with warehouses, stores, and partners. The enablement must be accomplished in a flexible way to react to fast-changing product portfolios and new acquisitions, while at the same time minimizing costs through reuse of existing systems. Meanwhile, the business must continue to grow and decision makers need to balance new capability with peak seasons. The challenges above are not unique to retail. Any customer in any industry who has multiple points for capturing orders and multiple points for fulfilling orders will face these challenges. With this in mind, we had a unique opportunity in Fusion SCM to re-think how to build a set of modular and flexible applications in the order management space that would make these challenges easier to conquer. The results are Fusion Distributed Order Orchestration and Global Order Promising. These applications can help companies, such as the pet store, enable true cross-channel commerce. The apps provide highly adaptable and flexible business processes to automate order orchestration across multiple cross-channel systems. They also show a global view of supply across warehouses, stores, and partners for real-time availability and more accurate order promising. Additional capability includes a standards-based integration framework for seamless execution and the ability to reuse existing systems for faster and lower cost implementations. OK, that was a mouthful of features and benefits. As Max waited to cross the street (he can do basic math too), I wondered if he could relate. He does not care about leash laws, pick-up courtesy, where he can/can't walk, what time of day it is, or even ticks. He does not care about how all these things could make walking complicated. He just wants to walk. Similarly, customers just want to shop and companies just want to make it easier to sell and deliver. You can learn more about Distributed Order Orchestration and Global Order Promising in cross-channel here.

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  • Scripting Part 1

    - by rbishop
    Dynamic Scripting is a large topic, so let me get a couple of things out of the way first. If you aren't familiar with JavaScript, I can suggest CodeAcademy's JavaScript series. There are also many other websites and books that cover JavaScript from every possible angle.The second thing we need to deal with is JavaScript as a programming language versus a JavaScript environment running in a web browser. Many books, tutorials, and websites completely blur these two together but they are in fact completely separate. What does this really mean in relation to DRM? Since DRM isn't a web browser, there are no document, window, history, screen, or location objects. There are no events like mousedown or click. Trying to call alert('hello!') in DRM will just cause an error. Those concepts are all related to an HTML document (web page) and are part of the Browser Object Model or Document Object Model. DRM has its own object model that exposes DRM-related objects. In practice, feel free to use those sorts of tutorials or practice within your browser; Many of the concepts are directly translatable to writing scripts in DRM. Just don't try to call document.getElementById in your property definition!I think learning by example tends to work the best, so let's try getting a list of all the unique property values for a given node and its children. var uniqueValues = {}; var childEnumerator = node.GetChildEnumerator(); while(childEnumerator.MoveNext()) { var propValue = childEnumerator.GetCurrent().PropValue("Custom.testpropstr1"); print(propValue); if(propValue != null && propValue != '' && !uniqueValues[propValue]) uniqueValues[propValue] = true; } var result = ''; for(var value in uniqueValues){ result += "Found value " + value + ","; } return result;  Now lets break this down piece by piece. var uniqueValues = {}; This declares a variable and initializes it as a new empty Object. You could also have written var uniqueValues = new Object(); Why use an object here? JavaScript objects can also function as a list of keys and we'll use that later to store each property value as a key on the object. var childEnumerator = node.GetChildEnumerator(); while(childEnumerator.MoveNext()) { This gets an enumerator for the node's children. The enumerator allows us to loop through the children one by one. If we wanted to get a filtered list of children, we would instead use ChildrenWith(). When we reach the end of the child list, the enumerator will return false for MoveNext() and that will stop the loop. var propValue = childEnumerator.GetCurrent().PropValue("Custom.testpropstr1"); print(propValue); if(propValue != null && propValue != '' && !uniqueValues[propValue]) uniqueValues[propValue] = true; } This gets the node the enumerator is currently pointing at, then calls PropValue() on it to get the value of a property. We then make sure the prop value isn't null or the empty string, then we make sure the value doesn't already exist as a key. Assuming it doesn't we add it as a key with a value (true in this case because it makes checking for an existing value faster when the value exists). A quick word on the print() function. When viewing the prop grid, running an export, or performing normal DRM operations it does nothing. If you have a lot of print() calls with complicated arguments it can slow your script down slightly, but otherwise has no effect. But when using the script editor, all the output of print() will be shown in the Warnings area. This gives you an extremely useful debugging tool to see what exactly a script is doing. var result = ''; for(var value in uniqueValues){ result += "Found value " + value + ","; } return result; Now we build a string by looping through all the keys in uniqueValues and adding that value to our string. The last step is to simply return the result. Hopefully this small example demonstrates some of the core Dynamic Scripting concepts. Next time, we can try checking for node references in other hierarchies to see if they are using duplicate property values.

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  • New R Interface to Oracle Data Mining Available for Download

    - by charlie.berger
      The R Interface to Oracle Data Mining ( R-ODM) allows R users to access the power of Oracle Data Mining's in-database functions using the familiar R syntax. R-ODM provides a powerful environment for prototyping data analysis and data mining methodologies. R-ODM is especially useful for: Quick prototyping of vertical or domain-based applications where the Oracle Database supports the application Scripting of "production" data mining methodologies Customizing graphics of ODM data mining results (examples: classification, regression, anomaly detection) The R-ODM interface allows R users to mine data using Oracle Data Mining from the R programming environment. It consists of a set of function wrappers written in source R language that pass data and parameters from the R environment to the Oracle RDBMS enterprise edition as standard user PL/SQL queries via an ODBC interface. The R-ODM interface code is a thin layer of logic and SQL that calls through an ODBC interface. R-ODM does not use or expose any Oracle product code as it is completely an external interface and not part of any Oracle product. R-ODM is similar to the example scripts (e.g., the PL/SQL demo code) that illustrates the use of Oracle Data Mining, for example, how to create Data Mining models, pass arguments, retrieve results etc. R-ODM is packaged as a standard R source package and is distributed freely as part of the R environment's Comprehensive R Archive Network (CRAN). For information about the R environment, R packages and CRAN, see www.r-project.org. R-ODM is particularly intended for data analysts and statisticians familiar with R but not necessarily familiar with the Oracle database environment or PL/SQL. It is a convenient environment to rapidly experiment and prototype Data Mining models and applications. Data Mining models prototyped in the R environment can easily be deployed in their final form in the database environment, just like any other standard Oracle Data Mining model. What is R? R is a system for statistical computation and graphics. It consists of a language plus a run-time environment with graphics, a debugger, access to certain system functions, and the ability to run programs stored in script files. The design of R has been heavily influenced by two existing languages: Becker, Chambers & Wilks' S and Sussman's Scheme. Whereas the resulting language is very similar in appearance to S, the underlying implementation and semantics are derived from Scheme. R was initially written by Ross Ihaka and Robert Gentleman at the Department of Statistics of the University of Auckland in Auckland, New Zealand. Since mid-1997 there has been a core group (the "R Core Team") who can modify the R source code archive. Besides this core group many R users have contributed application code as represented in the near 1,500 publicly-available packages in the CRAN archive (which has shown exponential growth since 2001; R News Volume 8/2, October 2008). Today the R community is a vibrant and growing group of dozens of thousands of users worldwide. It is free software distributed under a GNU-style copyleft, and an official part of the GNU project ("GNU S"). Resources: R website / CRAN R-ODM

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  • Myths about Coding Craftsmanship part 2

    - by tom
    Myth 3: The source of all bad code is inept developers and stupid people When you review code is this what you assume?  Shame on you.  You are probably making assumptions in your code if you are assuming so much already.  Bad code can be the result of any number of causes including but not limited to using dated techniques (like boxing when generics are available), not following standards (“look how he does the spacing between arguments!” or “did he really just name that variable ‘bln_Hello_Cats’?”), being redundant, using properties, methods, or objects in a novel way (like switching on button.Text between “Hello World” and “Hello World “ //clever use of space character… sigh), not following the SOLID principals, hacking around assumptions made in earlier iterations / hacking in features that should be worked into the overall design.  The first two issues, while annoying are pretty easy to spot and can be fixed so easily.  If your coding team is made up of experienced professionals who are passionate about staying current then these shouldn’t be happening.  If you work with a variety of skills, backgrounds, and experience then there will be some of this stuff going on.  If you have an opportunity to mentor such a developer who is receptive to constructive criticism don’t be a jerk; help them and the codebase will improve.  A little patience can improve the codebase, your work environment, and even your perspective. The novelty and redundancy I have encountered has often been the use of creativity when language knowledge was perceived as unavailable or too time consuming.  When developers learn on the job you get a lot of this.  Rather than going to MSDN developers will use what they know.  Depending on the constraints of their assignment hacking together what they know may seem quite practical.  This was not stupid though I often wonder how much time is actually “saved” by hacking.  These issues are often harder to untangle if we ever do.  They can also grow out of control as we write hack after hack to make it work and get back to some development that is satisfying. Hacking upon an existing hack is what I call “feeding the monster”.  Code monsters are anti-patterns and hacks gone wild.  The reason code monsters continue to get bigger is that they keep growing in scope, touching more and more of the application.  This is not the result of dumb developers. It is probably the result of avoiding design, not taking the time to understand the problems or anticipate or communicate the vision of the product.  If our developers don’t understand the purpose of a feature or product how do we expect potential customers to do so? Forethought and organization are often what is missing from bad code.  Developers who do not use the SOLID principals should be encouraged to learn these principals and be given guidance on how to apply them.  The time “saved” by giving hackers room to hack will be made up for and then some. Not as technical debt but as shoddy work that if not replaced will be struggled with again and again.  Bad code is not the result of dumb developers (usually) it is the result of trying to do too much without the proper resources and neglecting the right thing that needs doing with the first thoughtless thing that comes into our heads. Object oriented code is all about relationships between objects.  Coders who believe their coworkers are all fools tend to write objects that are difficult to work with, not eager to explain themselves, and perform erratically and irrationally.  If you constantly find you are surrounded by idiots you may want to ask yourself if you are being unreasonable, if you are being closed minded, of if you have chosen the right profession.  Opening your mind up to the idea that you probably work with rational, well-intentioned people will probably make you a better coder and it might even make you less grumpy.  If you are surrounded by jerks who do not engage in the exchange of ideas who do not care about their customers or the durability of the code you are building together then I suggest you find a new place to work.  Myth 4: Customers don’t care about “beautiful” code Craftsmanship is customer focused because it means that the job was done right, the product will withstand the abuse, modifications, and scrutiny of our customers.  Users can appreciate a predictable timeline for a release, a product delivered on time and on budget, a feature set that does not interfere with the task(s) it is supporting, quick turnarounds on exception messages, self healing issues, and less issues.  These are all hindered by skimping on craftsmanship.  When we write data access and when we write reusable code.   What do you think?  Does bad code come primarily from low IQ individuals?  Do customers care about beautiful code?

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  • concurrency::index<N> from amp.h

    - by Daniel Moth
    Overview C++ AMP introduces a new template class index<N>, where N can be any value greater than zero, that represents a unique point in N-dimensional space, e.g. if N=2 then an index<2> object represents a point in 2-dimensional space. This class is essentially a coordinate vector of N integers representing a position in space relative to the origin of that space. It is ordered from most-significant to least-significant (so, if the 2-dimensional space is rows and columns, the first component represents the rows). The underlying type is a signed 32-bit integer, and component values can be negative. The rank field returns N. Creating an index The default parameterless constructor returns an index with each dimension set to zero, e.g. index<3> idx; //represents point (0,0,0) An index can also be created from another index through the copy constructor or assignment, e.g. index<3> idx2(idx); //or index<3> idx2 = idx; To create an index representing something other than 0, you call its constructor as per the following 4-dimensional example: int temp[4] = {2,4,-2,0}; index<4> idx(temp); Note that there are convenience constructors (that don’t require an array argument) for creating index objects of rank 1, 2, and 3, since those are the most common dimensions used, e.g. index<1> idx(3); index<2> idx(3, 6); index<3> idx(3, 6, 12); Accessing the component values You can access each component using the familiar subscript operator, e.g. One-dimensional example: index<1> idx(4); int i = idx[0]; // i=4 Two-dimensional example: index<2> idx(4,5); int i = idx[0]; // i=4 int j = idx[1]; // j=5 Three-dimensional example: index<3> idx(4,5,6); int i = idx[0]; // i=4 int j = idx[1]; // j=5 int k = idx[2]; // k=6 Basic operations Once you have your multi-dimensional point represented in the index, you can now treat it as a single entity, including performing common operations between it and an integer (through operator overloading): -- (pre- and post- decrement), ++ (pre- and post- increment), %=, *=, /=, +=, -=,%, *, /, +, -. There are also operator overloads for operations between index objects, i.e. ==, !=, +=, -=, +, –. Here is an example (where no assertions are broken): index<2> idx_a; index<2> idx_b(0, 0); index<2> idx_c(6, 9); _ASSERT(idx_a.rank == 2); _ASSERT(idx_a == idx_b); _ASSERT(idx_a != idx_c); idx_a += 5; idx_a[1] += 3; idx_a++; _ASSERT(idx_a != idx_b); _ASSERT(idx_a == idx_c); idx_b = idx_b + 10; idx_b -= index<2>(4, 1); _ASSERT(idx_a == idx_b); Usage You'll most commonly use index<N> objects to index into data types that we'll cover in future posts (namely array and array_view). Also when we look at the new parallel_for_each function we'll see that an index<N> object is the single parameter to the lambda, representing the (multi-dimensional) thread index… In the next post we'll go beyond being able to represent an N-dimensional point in space, and we'll see how to define the N-dimensional space itself through the extent<N> class. Comments about this post by Daniel Moth welcome at the original blog.

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  • Developing Schema Compare for Oracle (Part 5): Query Snapshots

    - by Simon Cooper
    If you've emailed us about a bug you've encountered with the EAP or beta versions of Schema Compare for Oracle, we probably asked you to send us a query snapshot of your databases. Here, I explain what a query snapshot is, and how it helps us fix your bug. Problem 1: Debugging users' bug reports When we started the Schema Compare project, we knew we were going to get problems with users' databases - configurations we hadn't considered, features that weren't installed, unicode issues, wierd dependencies... With SQL Compare, users are generally happy to send us a database backup that we can restore using a single RESTORE DATABASE command on our test servers and immediately reproduce the problem. Oracle, on the other hand, would be a lot more tricky. As Oracle generally has a 1-to-1 mapping between instances and databases, any databases users sent would have to be restored to their own instance. Furthermore, the number of steps required to get a properly working database, and the size of most oracle databases, made it infeasible to ask every customer who came across a bug during our beta program to send us their databases. We also knew that there would be lots of issues with data security that would make it hard to get backups. So we needed an easier way to be able to debug customers issues and sort out what strange schema data Oracle was returning. Problem 2: Test execution time Another issue we knew we would have to solve was the execution time of the tests we would produce for the Schema Compare engine. Our initial prototype showed that querying the data dictionary for schema information was going to be slow (at least 15 seconds per database), and this is generally proportional to the size of the database. If you're running thousands of tests on the same databases, each one registering separate schemas, not only would the tests would take hours and hours to run, but the test servers would be hammered senseless. The solution To solve these, we needed to be able to populate the schema of a database without actually connecting to it. Well, the IDataReader interface is the primary way we read data from an Oracle server. The data dictionary queries we use return their data in terms of simple strings and numbers, which we then process and reconstruct into an object model, and the results of these queries are identical for identical schemas. So, we can record the raw results of the queries once, and then replay these results to construct the same object model as many times as required without needing to actually connect to the original database. This is what query snapshots do. They are binary files containing the raw unprocessed data we get back from the oracle server for all the queries we run on the data dictionary to get schema information. The core of the query snapshot generation takes the results of the IDataReader we get from running queries on Oracle, and passes the row data to a BinaryWriter that writes it straight to a file. The query snapshot can then be replayed to create the same object model; when the results of a specific query is needed by the population code, we can simply read the binary data stored in the file on disk and present it through an IDataReader wrapper. This is far faster than querying the server over the network, and allows us to run tests in a reasonable time. They also allow us to easily debug a customers problem; using a simple snapshot generation program, users can generate a query snapshot that could be sent along with a bug report that we can immediately replay on our machines to let us debug the issue, rather than having to obtain database backups and restore databases to test systems. There are also far fewer problems with data security; query snapshots only contain schema information, which is generally less sensitive than table data. Query snapshots implementation However, actually implementing such a feature did have a couple of 'gotchas' to it. My second blog post detailed the development of the dependencies algorithm we use to ensure we get all the dependencies in the database, and that algorithm uses data from both databases to find all the needed objects - what database you're comparing to affects what objects get populated from both databases. We get information on these additional objects using an appropriate WHERE clause on all the population queries. So, in order to accurately replay the results of querying the live database, the query snapshot needs to be a snapshot of a comparison of two databases, not just populating a single database. Furthermore, although the code population queries (eg querying all_tab_cols to get column information) can simply be passed straight from the IDataReader to the BinaryWriter, we need to hook into and run the live dependencies algorithm while we're creating the snapshot to ensure we get the same WHERE clauses, and the same query results, as if we were populating straight from a live system. We also need to store the results of the dependencies queries themselves, as the resulting dependency graph is stored within the OracleDatabase object that is produced, and is later used to help order actions in synchronization scripts. This is significantly helped by the dependencies algorithm being a deterministic algorithm - given the same input, it will always return the same output. Therefore, when we're replaying a query snapshot, and processing dependency information, we simply have to return the results of the queries in the order we got them from the live database, rather than trying to calculate the contents of all_dependencies on the fly. Query snapshots are a significant feature in Schema Compare that really helps us to debug problems with the tool, as well as making our testers happier. Although not really user-visible, they are very useful to the development team to help us fix bugs in the product much faster than we otherwise would be able to.

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  • Understanding the 'High Performance' meaning in Extreme Transaction Processing

    - by kyap
    Despite my previous blogs entries on SOA/BPM and Identity Management, the domain where I'm the most passionated is definitely the Extreme Transaction Processing, commonly called XTP.I came across XTP back to 2007 while I was still FMW Product Manager in EMEA. At that time Oracle acquired a company called Tangosol, which owned an unique product called Coherence that we renamed to Oracle Coherence. Beside this innovative renaming of the product, to be honest, I didn't know much about it, except being a "distributed in-memory cache for Extreme Transaction Processing"... not very helpful still.In general when people doesn't fully understand a technology or a concept, they tend to find some shortcuts, either correct or not, to justify their lack-of understanding... and of course I was part of this category of individuals. And the shortcut was "Oracle Coherence Cache helps to improve Performance". Excellent marketing slogan... but not very meaningful still. By chance I was able to get away quickly from that group in July 2007* at Thames Valley Park (UK), after I attended one of the most interesting workshops, in my 10 years career in Oracle, delivered by Brian Oliver. The biggest mistake I made was to assume that performance improvement with Coherence was related to the response time. Which can be considered as legitimus at that time, because after-all caches help to reduce latency on cached data access, hence reduce the response-time. But like all caches, you need to define caching and expiration policies, thinking about the cache-missed strategy, and most of the time you have to re-write partially your application in order to work with the cache. At a result, the expected benefit vanishes... so, not very useful then?The key mistake I made was my perception or obsession on how performance improvement should be driven, but I strongly believe this is still a common problem to most of the developers. In fact we all know the that the performance of a system is generally presented by the Capacity (or Throughput), with the 2 important dimensions Speed (response-time) and Volume (load) :Capacity (TPS) = Volume (T) / Speed (S)To increase the Capacity, we can either reduce the Speed(in terms of response-time), or to increase the Volume. However we tend to only focus on reducing the Speed dimension, perhaps it is more concrete and tangible to measure, and nicer to present to our management because there's a direct impact onto the end-users experience. On the other hand, we assume the Volume can be addressed by the underlying hardware or software stack, so if we need more capacity (scale out), we just add more hardware or software. Unfortunately, the reality proves that IT is never as ideal as we assume...The challenge with Speed improvement approach is that it is generally difficult and costly to make things already fast... faster. And by adding Coherence will not necessarily help either. Even though we manage to do so, the Capacity can not increase forever because... the Speed can be influenced by the Volume. For all system, we always have a performance illustration as follow: In all traditional system, the increase of Volume (Transaction) will also increase the Speed (Response-Time) as some point. The reason is simple: most of the time the Application logics were not designed to scale. As an example, if you have a while-loop in your application, it is natural to conceive that parsing 200 entries will require double execution-time compared to 100 entries. If you need to "Speed-up" the execution, you can only upgrade your hardware (scale-up) with faster CPU and/or network to reduce network latency. It is technically limited and economically inefficient. And this is exactly where XTP and Coherence kick in. The primary objective of XTP is about designing applications which can scale-out for increasing the Volume, by applying coding techniques to keep the execution-time as constant as possible, independently of the number of runtime data being manipulated. It is actually not just about having an application running as fast as possible, but about having a much more predictable system, with constant response-time and linearly scale, so we can easily increase throughput by adding more hardwares in parallel. It is in general combined with the Low Latency Programming model, where we tried to optimize the network usage as much as possible, either from the programmatic angle (less network-hoops to complete a task), and/or from a hardware angle (faster network equipments). In this picture, Oracle Coherence can be considered as software-level XTP enabler, via the Distributed-Cache because it can guarantee: - Constant Data Objects access time, independently from the number of Objects and the Coherence Cluster size - Data Objects Distribution by Affinity for in-memory data grouping - In-place Data Processing for parallel executionTo summarize, Oracle Coherence is indeed useful to improve your application performance, just not in the way we commonly think. It's not about the Speed itself, but about the overall Capacity with Extreme Load while keeping consistant Speed. In the future I will keep adding new blog entries around this topic, with some sample codes experiences sharing that I capture in the last few years. In the meanwhile if you want to know more how Oracle Coherence, I strongly suggest you to start with checking how our worldwide customers are using Oracle Coherence first, then you can start playing with the product through our tutorial.Have Fun !

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  • Application Logging needs work

    Application Logging Application logging is the act of logging events that occur within an application much like how a court report documents what happens in court case. Application logs can be useful for several reasons, but the most common use for logs is to recreate steps to find the root cause of applications errors. Other uses can include the detection of Fraud, verification of user activity, or provide audits on user/data interactions. “Logs can contain different kinds of data. The selection of the data used is normally affected by the motivation leading to the logging. “ (OWASP, 2009) OWASP also stats that logging include applicable debugging information like the event date time, responsible process, and a description of the event. “There are many reasons why a logging system is a necessary part of delivering a distributed application. One of the most important is the ability to track exactly how many users are using the application during different time periods.” (Hatton, 2000) Hatton also states that application logging helps system designers determine whether parts of an application aren't being used as designed. He implies that low usage can be used to identify if users like or do not like aspects of a system based on user usage of the application. This enables application designers to extract why users don't like aspects of an application so that changes can be made to increase its usefulness and effectiveness. “Logging memory usage can also assist you in tuning up the internals of your application. If you're experiencing a randomly occurring problem, being able to match activities performed with the memory status at the time may enable you to discover the cause of the problem. It also gives you a good indication of the health of the distributed server machine at the time any activity is performed. “ (Hatton, 2000) Commonly Logged Application Events (Defined by OWASP) Access of Data Creation of Data Modification of Data in any form Administrative Functions  Configuration Changes Debugging Information(Application Events)  Authorization Attempts  Data Deletion Network Communication  Authentication Events  Errors/Exceptions Application Error Logging The functionality associated with application error logging is actually the combination of proper error handling and applications logging.  If we look back at Figure 4 and Figure 5, these code examples allow developers to handle various types of errors that occur within the life cycle of an application’s execution. Application logging can be applied within the Catch section of the TryCatch statement allowing for the errors to be logged when they occur. By placing the logging within the Catch section specific error details can be accessed that help identify the source of the error, the path to the error, what caused the error and definition of the error that occurred. This can then be logged and reviewed at a later date in order recreate the error that was received based data found in the application log. By allowing applications to log errors developers IT staff can use them to recreate errors that are encountered by end-users or other dependent systems.

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