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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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  • 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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  • World Record Batch Rate on Oracle JD Edwards Consolidated Workload with SPARC T4-2

    - by Brian
    Oracle produced a World Record batch throughput for single system results on Oracle's JD Edwards EnterpriseOne Day-in-the-Life benchmark using Oracle's SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2. The workload includes both online and batch workload. The SPARC T4-2 server delivered a result of 8,000 online users while concurrently executing a mix of JD Edwards EnterpriseOne Long and Short batch processes at 95.5 UBEs/min (Universal Batch Engines per minute). In order to obtain this record benchmark result, the JD Edwards EnterpriseOne, Oracle WebLogic and Oracle Database 11g Release 2 servers were executed each in separate Oracle Solaris Containers which enabled optimal system resources distribution and performance together with scalable and manageable virtualization. One SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2 utilized only 55% of the available CPU power. The Oracle DB server in a Shared Server configuration allows for optimized CPU resource utilization and significant memory savings on the SPARC T4-2 server without sacrificing performance. This configuration with SPARC T4-2 server has achieved 33% more Users/core, 47% more UBEs/min and 78% more Users/rack unit than the IBM Power 770 server. The SPARC T4-2 server with 2 processors ran the JD Edwards "Day-in-the-Life" benchmark and supported 8,000 concurrent online users while concurrently executing mixed batch workloads at 95.5 UBEs per minute. The IBM Power 770 server with twice as many processors supported only 12,000 concurrent online users while concurrently executing mixed batch workloads at only 65 UBEs per minute. This benchmark demonstrates more than 2x cost savings by consolidating the complete solution in a single SPARC T4-2 server compared to earlier published results of 10,000 users and 67 UBEs per minute on two SPARC T4-2 and SPARC T4-1. The Oracle DB server used mirrored (RAID 1) volumes for the database providing high availability for the data without impacting performance. Performance Landscape JD Edwards EnterpriseOne Day in the Life (DIL) Benchmark Consolidated Online with Batch Workload System Rack Units BatchRate(UBEs/m) Online Users Users /Units Users /Core Version SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 3 95.5 8,000 2,667 500 9.0.2 IBM Power 770 (4 x POWER7, 3.3 GHz, 32 cores) 8 65 12,000 1,500 375 9.0.2 Batch Rate (UBEs/m) — Batch transaction rate in UBEs per minute Configuration Summary Hardware Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 4 x 300 GB 10K RPM SAS internal disk 2 x 300 GB internal SSD 2 x Sun Storage F5100 Flash Arrays Software Configuration: Oracle Solaris 10 Oracle Solaris Containers JD Edwards EnterpriseOne 9.0.2 JD Edwards EnterpriseOne Tools (8.98.4.2) Oracle WebLogic Server 11g (10.3.4) Oracle HTTP Server 11g Oracle Database 11g Release 2 (11.2.0.1) Benchmark Description JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations. Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company. The workload consists of online transactions and the UBE – Universal Business Engine workload of 61 short and 4 long UBEs. LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time. The UBE processes workload runs from the JD Enterprise Application server. Oracle's UBE processes come as three flavors: Short UBEs < 1 minute engage in Business Report and Summary Analysis, Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address, Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs. The UBE workload generates large numbers of PDF files reports and log files. The UBE Queues are categorized as the QBATCHD, a single threaded queue for large and medium UBEs, and the QPROCESS queue for short UBEs run concurrently. Oracle's UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute. Key Points and Best Practices Two JD Edwards EnterpriseOne Application Servers, two Oracle WebLogic Servers 11g Release 1 coupled with two Oracle Web Tier HTTP server instances and one Oracle Database 11g Release 2 database on a single SPARC T4-2 server were hosted in separate Oracle Solaris Containers bound to four processor sets to demonstrate consolidation of multiple applications, web servers and the database with best resource utilizations. Interrupt fencing was configured on all Oracle Solaris Containers to channel the interrupts to processors other than the processor sets used for the JD Edwards Application server, Oracle WebLogic servers and the database server. A Oracle WebLogic vertical cluster was configured on each WebServer Container with twelve managed instances each to load balance users' requests and to provide the infrastructure that enables scaling to high number of users with ease of deployment and high availability. The database log writer was run in the real time RT class and bound to a processor set. The database redo logs were configured on the raw disk partitions. The Oracle Solaris Container running the Enterprise Application server completed 61 Short UBEs, 4 Long UBEs concurrently as the mixed size batch workload. The mixed size UBEs ran concurrently from the Enterprise Application server with the 8,000 online users driven by the LoadRunner. See Also SPARC T4-2 Server oracle.com OTN JD Edwards EnterpriseOne oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Oracle Fusion Middleware oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 09/30/2012.

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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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  • How to restore your production database without needing additional storage

    - by David Atkinson
    Production databases can get very large. This in itself is to be expected, but when a copy of the database is needed the database must be restored, requiring additional and costly storage.  For example, if you want to give each developer a full copy of your production server, you'll need n times the storage cost for your n-developer team. The same is true for any test databases that are created during the course of your project lifecycle. If you've read my previous blog posts, you'll be aware that I've been focusing on the database continuous integration theme. In my CI setup I create a "production"-equivalent database directly from its source control representation, and use this to test my upgrade scripts. Despite this being a perfectly valid and practical thing to do as part of a CI setup, it's not the exact equivalent to running the upgrade script on a copy of the actual production database. So why shouldn't I instead simply restore the most recent production backup as part of my CI process? There are two reasons why this would be impractical. 1. My CI environment isn't an exact copy of my production environment. Indeed, this would be the case in a perfect world, and it is strongly recommended as a good practice if you follow Jez Humble and David Farley's "Continuous Delivery" teachings, but in practical terms this might not always be possible, especially where storage is concerned. It may just not be possible to restore a huge production database on the environment you've been allotted. 2. It's not just about the storage requirements, it's also the time it takes to do the restore. The whole point of continuous integration is that you are alerted as early as possible whether the build (yes, the database upgrade script counts!) is broken. If I have to run an hour-long restore each time I commit a change to source control I'm just not going to get the feedback quickly enough to react. So what's the solution? Red Gate has a technology, SQL Virtual Restore, that is able to restore a database without using up additional storage. Although this sounds too good to be true, the explanation is quite simple (although I'm sure the technical implementation details under the hood are quite complex!) Instead of restoring the backup in the conventional sense, SQL Virtual Restore will effectively mount the backup using its HyperBac technology. It creates a data and log file, .vmdf, and .vldf, that becomes the delta between the .bak file and the virtual database. This means that both read and write operations are permitted on a virtual database as from SQL Server's point of view it is no different from a conventional database. Instead of doubling the storage requirements upon a restore, there is no 'duplicate' storage requirements, other than the trivially small virtual log and data files (see illustration below). The benefit is magnified the more databases you mount to the same backup file. This technique could be used to provide a large development team a full development instance of a large production database. It is also incredibly easy to set up. Once SQL Virtual Restore is installed, you simply run a conventional RESTORE command to create the virtual database. This is what I have running as part of a nightly "release test" process triggered by my CI tool. RESTORE DATABASE WidgetProduction_virtual FROM DISK=N'C:\WidgetWF\ProdBackup\WidgetProduction.bak' WITH MOVE N'WidgetProduction' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_WidgetProduction_Virtual.vmdf', MOVE N'WidgetProduction_log' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_log_WidgetProduction_Virtual.vldf', NORECOVERY, STATS=1, REPLACE GO RESTORE DATABASE mydatabase WITH RECOVERY   Note the only change from what you would do normally is the naming of the .vmdf and .vldf files. SQL Virtual Restore intercepts this by monitoring the extension and applies its magic, ensuring the 'virtual' restore happens rather than the conventional storage-heavy restore. My automated release test then applies the upgrade scripts to the virtual production database and runs some validation tests, giving me confidence that were I to run this on production for real, all would go smoothly. For illustration, here is my 8Gb production database: And its corresponding backup file: Here are the .vldf and .vmdf files, which represent the only additional used storage for the new database following the virtual restore.   The beauty of this product is its simplicity. Once it is installed, the interaction with the backup and virtual database is exactly the same as before, as the clever stuff is being done at a lower level. SQL Virtual Restore can be downloaded as a fully functional 14-day trial. Technorati Tags: SQL Server

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  • How to restore your production database without needing additional storage

    - by David Atkinson
    Production databases can get very large. This in itself is to be expected, but when a copy of the database is needed the database must be restored, requiring additional and costly storage.  For example, if you want to give each developer a full copy of your production server, you’ll need n times the storage cost for your n-developer team. The same is true for any test databases that are created during the course of your project lifecycle. If you’ve read my previous blog posts, you’ll be aware that I’ve been focusing on the database continuous integration theme. In my CI setup I create a “production”-equivalent database directly from its source control representation, and use this to test my upgrade scripts. Despite this being a perfectly valid and practical thing to do as part of a CI setup, it’s not the exact equivalent to running the upgrade script on a copy of the actual production database. So why shouldn’t I instead simply restore the most recent production backup as part of my CI process? There are two reasons why this would be impractical. 1. My CI environment isn’t an exact copy of my production environment. Indeed, this would be the case in a perfect world, and it is strongly recommended as a good practice if you follow Jez Humble and David Farley’s “Continuous Delivery” teachings, but in practical terms this might not always be possible, especially where storage is concerned. It may just not be possible to restore a huge production database on the environment you’ve been allotted. 2. It’s not just about the storage requirements, it’s also the time it takes to do the restore. The whole point of continuous integration is that you are alerted as early as possible whether the build (yes, the database upgrade script counts!) is broken. If I have to run an hour-long restore each time I commit a change to source control I’m just not going to get the feedback quickly enough to react. So what’s the solution? Red Gate has a technology, SQL Virtual Restore, that is able to restore a database without using up additional storage. Although this sounds too good to be true, the explanation is quite simple (although I’m sure the technical implementation details under the hood are quite complex!) Instead of restoring the backup in the conventional sense, SQL Virtual Restore will effectively mount the backup using its HyperBac technology. It creates a data and log file, .vmdf, and .vldf, that becomes the delta between the .bak file and the virtual database. This means that both read and write operations are permitted on a virtual database as from SQL Server’s point of view it is no different from a conventional database. Instead of doubling the storage requirements upon a restore, there is no ‘duplicate’ storage requirements, other than the trivially small virtual log and data files (see illustration below). The benefit is magnified the more databases you mount to the same backup file. This technique could be used to provide a large development team a full development instance of a large production database. It is also incredibly easy to set up. Once SQL Virtual Restore is installed, you simply run a conventional RESTORE command to create the virtual database. This is what I have running as part of a nightly “release test” process triggered by my CI tool. RESTORE DATABASE WidgetProduction_Virtual FROM DISK=N'D:\VirtualDatabase\WidgetProduction.bak' WITH MOVE N'WidgetProduction' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_WidgetProduction_Virtual.vmdf', MOVE N'WidgetProduction_log' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_log_WidgetProduction_Virtual.vldf', NORECOVERY, STATS=1, REPLACE GO RESTORE DATABASE WidgetProduction_Virtual WITH RECOVERY   Note the only change from what you would do normally is the naming of the .vmdf and .vldf files. SQL Virtual Restore intercepts this by monitoring the extension and applies its magic, ensuring the ‘virtual’ restore happens rather than the conventional storage-heavy restore. My automated release test then applies the upgrade scripts to the virtual production database and runs some validation tests, giving me confidence that were I to run this on production for real, all would go smoothly. For illustration, here is my 8Gb production database: And its corresponding backup file: Here are the .vldf and .vmdf files, which represent the only additional used storage for the new database following the virtual restore.   The beauty of this product is its simplicity. Once it is installed, the interaction with the backup and virtual database is exactly the same as before, as the clever stuff is being done at a lower level. SQL Virtual Restore can be downloaded as a fully functional 14-day trial. Technorati Tags: SQL Server

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  • Is Linear Tape File System (LTFS) Best For Transportable Storage?

    - by rickramsey
    Those of us in tape storage engineering take a lot of pride in what we do, but understand that tape is the right answer to a storage problem only some of the time. And, unfortunately for a storage medium with such a long history, it has built up a few preconceived notions that are no longer valid. When I hear customers debate whether to implement tape vs. disk, one of the common strikes against tape is its perceived lack of usability. If you could go back a few generations of corporate acquisitions, you would discover that StorageTek engineers recognized this problem and started developing a solution where a tape drive could look just like a memory stick to a user. The goal was to not have to care about where files were on the cartridge, but to simply see the list of files that were on the tape, and click on them to open them up. Eventually, our friends in tape over at IBM built upon our work at StorageTek and Sun Microsystems and released the Linear Tape File System (LTFS) feature for the current LTO5 generation of tape drives as an open specification. LTFS is really a wonderful feature and we’re proud to have taken part in its beginnings and, as you’ll soon read, its future. Today we offer LTFS-Open Edition, which is free for you to use in your in Oracle Enterprise Linux 5.5 environment - not only on your LTO5 drives, but also on your Oracle StorageTek T10000C drives. You can download it free from Oracle and try it out. LTFS does exactly what its forefathers imagined. Now you can see immediately which files are on a cartridge. LTFS does this by splitting a cartridge into two partitions. The first holds all of the necessary metadata to create a directory structure for you to easily view the contents of the cartridge. The second partition holds all of the files themselves. When tape media is loaded onto a drive, a complete file system image is presented to the user. Adding files to a cartridge can be as simple as a drag-and-drop just as you do today on your laptop when transferring files from your hard drive to a thumb drive or with standard POSIX file operations. You may be thinking all of this sounds nice, but asking, “when will I actually use it?” As I mentioned at the beginning, tape is not the right solution all of the time. However, if you ever need to physically move data between locations, tape storage with LTFS should be your most cost-effective and reliable answer. I will give you a few use cases examples of when LTFS can be utilized. Media and Entertainment (M&E), Oil and Gas (O&G), and other industries have a strong need for their storage to be transportable. For example, an O&G company hunting for new oil deposits in remote locations takes very large underground seismic images which need to be shipped back to a central data center. M&E operations conduct similar activities when shooting video for productions. M&E companies also often transfers files to third-parties for editing and other activities. These companies have three highly flawed options for transporting data: electronic transfer, disk storage transport, or tape storage transport. The first option, electronic transfer, is impractical because of the expense of the bandwidth required to transfer multi-terabyte files reliably and efficiently. If there’s one place that has bandwidth, it’s your local post office so many companies revert to physically shipping storage media. Typically, M&E companies rely on transporting disk storage between sites even though it, too, is expensive. Tape storage should be the preferred format because as IDC points out, “Tape is more suitable for physical transportation of large amounts of data as it is less vulnerable to mechanical damage during transportation compared with disk" (See note 1, below). However, tape storage has not been used in the past because of the restrictions created by proprietary formats. A tape may only be readable if both the sender and receiver have the same proprietary application used to write the file. In addition, the workflows may be slowed by the need to read the entire tape cartridge during recall. LTFS solves both of these problems, clearing the way for tape to become the standard platform for transferring large files. LTFS is open and, as long as you’ve downloaded the free reader from our website or that of anyone in the LTO consortium, you can read the data. So if a movie studio ships a scene to a third-party partner to add, for example, sounds effects or a music score, it doesn’t have to care what technology the third-party has. If it’s written back to an LTFS-formatted tape cartridge, it can be read. Some tape vendors like to claim LTFS is a “standard,” but beauty is in the eye of the beholder. It’s a specification at this point, not a standard. That said, we’re already seeing application vendors create functionality to write in an LTFS format based on the specification. And it’s my belief that both customers and the tape storage industry will see the most benefit if we all follow the same path. As such, we have volunteered to lead the way in making LTFS a standard first with the Storage Network Industry Association (SNIA), and eventually through to standard bodies such as American National Standards Institute (ANSI). Expect to hear good news soon about our efforts. So, if storage transportability is one of your requirements, I recommend giving LTFS a look. It makes tape much more user-friendly and it’s free, which allows tape to maintain all of its cost advantages over disk! Note 1 - IDC Report. April, 2011. “IDC’s Archival Storage Solutions Taxonomy, 2011” - Brian Zents Website Newsletter Facebook Twitter

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  • How to restore your production database without needing additional storage

    - by David Atkinson
    Production databases can get very large. This in itself is to be expected, but when a copy of the database is needed the database must be restored, requiring additional and costly storage.  For example, if you want to give each developer a full copy of your production server, you'll need n times the storage cost for your n-developer team. The same is true for any test databases that are created during the course of your project lifecycle. If you've read my previous blog posts, you'll be aware that I've been focusing on the database continuous integration theme. In my CI setup I create a "production"-equivalent database directly from its source control representation, and use this to test my upgrade scripts. Despite this being a perfectly valid and practical thing to do as part of a CI setup, it's not the exact equivalent to running the upgrade script on a copy of the actual production database. So why shouldn't I instead simply restore the most recent production backup as part of my CI process? There are two reasons why this would be impractical. 1. My CI environment isn't an exact copy of my production environment. Indeed, this would be the case in a perfect world, and it is strongly recommended as a good practice if you follow Jez Humble and David Farley's "Continuous Delivery" teachings, but in practical terms this might not always be possible, especially where storage is concerned. It may just not be possible to restore a huge production database on the environment you've been allotted. 2. It's not just about the storage requirements, it's also the time it takes to do the restore. The whole point of continuous integration is that you are alerted as early as possible whether the build (yes, the database upgrade script counts!) is broken. If I have to run an hour-long restore each time I commit a change to source control I'm just not going to get the feedback quickly enough to react. So what's the solution? Red Gate has a technology, SQL Virtual Restore, that is able to restore a database without using up additional storage. Although this sounds too good to be true, the explanation is quite simple (although I'm sure the technical implementation details under the hood are quite complex!) Instead of restoring the backup in the conventional sense, SQL Virtual Restore will effectively mount the backup using its HyperBac technology. It creates a data and log file, .vmdf, and .vldf, that becomes the delta between the .bak file and the virtual database. This means that both read and write operations are permitted on a virtual database as from SQL Server's point of view it is no different from a conventional database. Instead of doubling the storage requirements upon a restore, there is no 'duplicate' storage requirements, other than the trivially small virtual log and data files (see illustration below). The benefit is magnified the more databases you mount to the same backup file. This technique could be used to provide a large development team a full development instance of a large production database. It is also incredibly easy to set up. Once SQL Virtual Restore is installed, you simply run a conventional RESTORE command to create the virtual database. This is what I have running as part of a nightly "release test" process triggered by my CI tool. RESTORE DATABASE WidgetProduction_virtual FROM DISK=N'C:\WidgetWF\ProdBackup\WidgetProduction.bak' WITH MOVE N'WidgetProduction' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_WidgetProduction_Virtual.vmdf', MOVE N'WidgetProduction_log' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_log_WidgetProduction_Virtual.vldf', NORECOVERY, STATS=1, REPLACE GO RESTORE DATABASE mydatabase WITH RECOVERY   Note the only change from what you would do normally is the naming of the .vmdf and .vldf files. SQL Virtual Restore intercepts this by monitoring the extension and applies its magic, ensuring the 'virtual' restore happens rather than the conventional storage-heavy restore. My automated release test then applies the upgrade scripts to the virtual production database and runs some validation tests, giving me confidence that were I to run this on production for real, all would go smoothly. For illustration, here is my 8Gb production database: And its corresponding backup file: Here are the .vldf and .vmdf files, which represent the only additional used storage for the new database following the virtual restore.   The beauty of this product is its simplicity. Once it is installed, the interaction with the backup and virtual database is exactly the same as before, as the clever stuff is being done at a lower level. SQL Virtual Restore can be downloaded as a fully functional 14-day trial. Technorati Tags: SQL Server

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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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  • 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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  • 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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  • Educause Top-Ten IT Issues - the most change in a decade or more

    - by user739873
    The Education IT Issue Panel has released the 2012 top-ten issues facing higher education IT leadership, and instead of the customary reshuffling of the same deck, the issues reflect much of the tumult and dynamism facing higher education generally.  I find it interesting (and encouraging) that at the top of this year's list is "Updating IT Professionals' Skills and Roles to Accommodate Emerging Technologies and Changing IT Management and Service Delivery Models."  This reflects, in my view, the realization that higher education IT must change in order to fully realize the potential for transforming the institution, and therefore it's people must learn new skills, understand and accept new ways of solving problems, and not be tied down by past practices or institutional inertia. What follows in the remaining 9 top issues all speak, in some form or fashion, to the need for dramatic change, but not just in the areas of "funding IT" (code for cost containment or reduction), but rather the need to increase effectiveness and efficiency of the institution through the use of technology—leveraging the wave of BYOD (Bring Your Own Device) to the institution's advantage, rather than viewing it as a threat and a problem to be contained. Although it's #10 of 10, IT Governance (and establishment and implementation of the governance model throughout the institution) is key to effectively acting upon many of the preceding issues in this year's list.  In the majority of cases, technology exists to meet the needs and requirements to effectively address many of the challenges outlined in top-ten issues list. Which brings me to my next point. Although I try not to sound too much like an Oracle commercial in these (all too infrequent) blog posts, I can't help but point out how much confluence there is between several of the top issues this year and what my colleagues and I have been evangelizing for some time. Starting from the bottom of the list up: 1) I'm gratified that research and the IT challenges it presents has made the cut.  Big Data (or Large Data as it's phased in the report) is rapidly going to overwhelm much of what exists today even at our most prepared and well-equipped research universities.  Combine large data with the significantly more stringent requirements around data preservation, archiving, sharing, curation, etc. coming from granting agencies like NSF, and you have the brewing storm that could result in a lot of "one-off" solutions to a problem that could very well be addressed collectively and "at scale."   2) Transformative effects of IT – while I see more and more examples of this, there is still much more that can be achieved. My experience tells me that culture (as the report indicates or at least poses the question) gets in the way more than technology not being up to task.  We spend too much time on "context" and not "core," and get lost in the weeds on the journey to truly transforming the institution with technology. 3) Analytics as a key element in improving various institutional outcomes.  In our work around Student Success, we see predictive "academic" analytics as essential to getting in front of the Student Success issue, regardless of how an institution or collections of institutions defines success.  Analytics must be part of the fabric of the key academic enterprise applications, not a bolt-on.  We will spend a significant amount of time on this topic during our semi-annual Education Industry Strategy Council meeting in Washington, D.C. later this month. 4) Cloud strategy for the broad range of applications in the academic enterprise.  Some of the recent work by Casey Green at the Campus Computing Survey would seem to indicate that there is movement in this area but mostly in what has been termed "below the campus" application areas such as collaboration tools, recruiting, and alumni relations.  It's time to get serious about sourcing elements of mature applications like student information systems, HR, Finance, etc. leveraging a model other than traditional on-campus custom. I've only selected a few areas of the list to highlight, but the unifying theme here (and this is where I run the risk of sounding like an Oracle commercial) is that these lofty goals cry out for partners that can bring economies of scale to bear on the problems married with a deep understanding of the nuances unique to higher education.  In a recent piece in Educause Review on Student Information Systems, the author points out that "best of breed is back". Unfortunately I am compelled to point out that best of breed is a large part of the reason we have made as little progress as we have as an industry in advancing some of the causes outlined above.  Don't confuse "integrated" and "full stack" for vendor lock-in.  The best-of-breed market forces that Ron points to ensure that solutions have to be "integratable" or they don't survive in the marketplace. However, by leveraging the efficiencies afforded by adopting solutions that are pre-integrated (and possibly metered out as a service) allows us to shed unnecessary costs – as difficult as these decisions are to make and to drive throughout the organization. Cole

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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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  • Hiring New IT Employees versus Promoting Internally for IT Positions

    Recently I was asked my opinion regarding the hiring of IT professionals in regards to the option of hiring new IT employees versus promoting internally for IT positions. After thinking a little more about this question regarding staffing, specifically pertaining to promoting internally verses new employees; I think my answer to this question is that it truly depends on the situation. However, in most cases I would side with promoting internally. The key factors in this decision should be based on a company/department’s current values, culture, attitude, and existing priorities.  For example if a company values retaining all of its hard earned business knowledge then they would tend to promote existing employees internal over hiring a new employee. Moreover, the company will have to pay to train an existing employee to learn a new technology and the learning curve for some technologies can be very steep. Conversely, if a company values new technologies and technical proficiency over business knowledge then a company would tend to hire new employees because they may already have experience with a technology that the company is planning on using. In this scenario, the company would have to take on the additional overhead of allowing a new employee to learn how the business operates prior to them being fully effective. To illustrate my points above let us look at contractor that builds in ground pools for example.  He has the option to hire employees that are very strong but use small shovels to dig, or employees weak in physical strength but use large shovels to dig. Which employee should the contractor use to dig a hole for a new in ground pool? If we compare the possible candidates for this job we will find that they are very similar to hiring someone internally verses a new hire. The first example represents the existing workers that are very strong regarding the understanding how the business operates and the reasons why in a specific manner. However this employee could be potentially weaker than an outsider pertaining to specific technologies and would need some time to build their technical prowess for a new position much like the strong worker upgrading their shovels in order to remove more dirt at once when digging. The other employee is very similar to hiring a new person that may already have the large shovel but will need to increase their strength in order to use the shovel properly and efficiently so that they can move a maximum amount of dirt in a minimal amount of time. This can be compared to new employ learning how a business operates before they can be fully functional and integrated in the company/department. Another key factor in this dilemma pertains to existing employee and their passion for their work, their ability to accept new responsibility when given, and the willingness to take on responsibilities when they see a need in the business. As much as possible should be considered in this decision down to the mood of the team, the quality of existing staff, learning cure for both technology and business, and the potential side effects of the existing staff.  In addition, there are many more consideration based on the current team/department/companies culture and mood. There are several factors that need to be considered when promoting an individual or hiring new blood for a team. They both can provide great benefits as well as create controversy to a group. Personally, staffing especially in the IT world is like building a large scale system in that all of the components and modules must fit together and preform as one cohesive system in the same way a team must come together using their individually acquired skills so that they can work as one team.  If a module is out of place or is nonexistent then the rest of the team will suffer until the all of its issues are addressed and resolved. Benefits of Promoting Internally Internal promotions give employees a reason to constantly upgrade their technology, business, and communication skills if they want to further their career Employees can control their own destiny based on personal desires Employee already knows how the business operates Companies can save money by promoting internally because the initial overhead of allowing new hires to learn how a company operates is very expensive Newly promoted employees can assist in training their replacements while transitioning to their new role within a company. Existing employees already have a proven track record in regards fitting in with the business culture; this is always an unknown with all new hires Benefits of a New Hire New employees can energize and excite existing employees New employees can bring new ideas and advancements in technology New employees can offer a different perspective on existing issues based on their past experience. As you can see the decision to promote an existing employee from within a company verses hiring a new person should be based on several factors that should ultimately place the business in the best possible situation for the immediate and long term future. How would you handle this situation? Would you hire a new employee or promote from within?

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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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  • Is it feasible and useful to auto-generate some code of unit tests?

    - by skiwi
    Earlier today I have come up with an idea, based upon a particular real use case, which I would want to have checked for feasability and usefulness. This question will feature a fair chunk of Java code, but can be applied to all languages running inside a VM, and maybe even outside. While there is real code, it uses nothing language-specific, so please read it mostly as pseudo code. The idea Make unit testing less cumbersome by adding in some ways to autogenerate code based on human interaction with the codebase. I understand this goes against the principle of TDD, but I don't think anyone ever proved that doing TDD is better over first creating code and then immediatly therafter the tests. This may even be adapted to be fit into TDD, but that is not my current goal. To show how it is intended to be used, I'll copy one of my classes here, for which I need to make unit tests. public class PutMonsterOnFieldAction implements PlayerAction { private final int handCardIndex; private final int fieldMonsterIndex; public PutMonsterOnFieldAction(final int handCardIndex, final int fieldMonsterIndex) { this.handCardIndex = Arguments.requirePositiveOrZero(handCardIndex, "handCardIndex"); this.fieldMonsterIndex = Arguments.requirePositiveOrZero(fieldMonsterIndex, "fieldCardIndex"); } @Override public boolean isActionAllowed(final Player player) { Objects.requireNonNull(player, "player"); Hand hand = player.getHand(); Field field = player.getField(); if (handCardIndex >= hand.getCapacity()) { return false; } if (fieldMonsterIndex >= field.getMonsterCapacity()) { return false; } if (field.hasMonster(fieldMonsterIndex)) { return false; } if (!(hand.get(handCardIndex) instanceof MonsterCard)) { return false; } return true; } @Override public void performAction(final Player player) { Objects.requireNonNull(player); if (!isActionAllowed(player)) { throw new PlayerActionNotAllowedException(); } Hand hand = player.getHand(); Field field = player.getField(); field.setMonster(fieldMonsterIndex, (MonsterCard)hand.play(handCardIndex)); } } We can observe the need for the following tests: Constructor test with valid input Constructor test with invalid inputs isActionAllowed test with valid input isActionAllowed test with invalid inputs performAction test with valid input performAction test with invalid inputs My idea mainly focuses on the isActionAllowed test with invalid inputs. Writing these tests is not fun, you need to ensure a number of conditions and you check whether it really returns false, this can be extended to performAction, where an exception needs to be thrown in that case. The goal of my idea is to generate those tests, by indicating (through GUI of IDE hopefully) that you want to generate tests based on a specific branch. The implementation by example User clicks on "Generate code for branch if (handCardIndex >= hand.getCapacity())". Now the tool needs to find a case where that holds. (I haven't added the relevant code as that may clutter the post ultimately) To invalidate the branch, the tool needs to find a handCardIndex and hand.getCapacity() such that the condition >= holds. It needs to construct a Player with a Hand that has a capacity of at least 1. It notices that the capacity private int of Hand needs to be at least 1. It searches for ways to set it to 1. Fortunately it finds a constructor that takes the capacity as an argument. It uses 1 for this. Some more work needs to be done to succesfully construct a Player instance, involving the creation of objects that have constraints that can be seen by inspecting the source code. It has found the hand with the least capacity possible and is able to construct it. Now to invalidate the test it will need to set handCardIndex = 1. It constructs the test and asserts it to be false (the returned value of the branch) What does the tool need to work? In order to function properly, it will need the ability to scan through all source code (including JDK code) to figure out all constraints. Optionally this could be done through the javadoc, but that is not always used to indicate all constraints. It could also do some trial and error, but it pretty much stops if you cannot attach source code to compiled classes. Then it needs some basic knowledge of what the primitive types are, including arrays. And it needs to be able to construct some form of "modification trees". The tool knows that it needs to change a certain variable to a different value in order to get the correct testcase. Hence it will need to list all possible ways to change it, without using reflection obviously. What this tool will not replace is the need to create tailored unit tests that tests all kinds of conditions when a certain method actually works. It is purely to be used to test methods when they invalidate constraints. My questions: Is creating such a tool feasible? Would it ever work, or are there some obvious problems? Would such a tool be useful? Is it even useful to automatically generate these testcases at all? Could it be extended to do even more useful things? Does, by chance, such a project already exist and would I be reinventing the wheel? If not proven useful, but still possible to make such thing, I will still consider it for fun. If it's considered useful, then I might make an open source project for it depending on the time. For people searching more background information about the used Player and Hand classes in my example, please refer to this repository. At the time of writing the PutMonsterOnFieldAction has not been uploaded to the repo yet, but this will be done once I'm done with the unit tests.

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  • Clouds, Clouds, Clouds Everywhere, Not a Drop of Rain!

    - by sxkumar
    At the recently concluded Oracle OpenWorld 2012, the center of discussion was clearly Cloud. Over the five action packed days, I got to meet a large number of customers and most of them had serious interest in all things cloud.  Public Cloud - particularly the Oracle Cloud - clearly got a lot of attention and interest. I think the use cases and the value proposition for public cloud is pretty straight forward. However, when it comes to private cloud, there were some interesting revelations.  Well, I shouldn’t really call them revelations since they are pretty consistent with what I have heard from customers at other conferences as well as during 1:1 interactions. While the interest in enterprise private cloud remains to be very high, only a handful of enterprises have truly embarked on a journey to create what the purists would call true private cloud - with capabilities such as self-service and chargeback/show back. For a large majority, today's reality is simply consolidation and virtualization - and they are quite far off from creating an agile, self-service and transparent IT infrastructure which is what the enterprise cloud is all about.  Even a handful of those who have actually implemented a close-to-real enterprise private cloud have taken an infrastructure centric approach and are seeing only limited business upside. Quite a few were frank enough to admit that chargeback and self-service isn’t something that they see an immediate need for.  This is in quite contrast to the picture being painted by all those surveys out there that show a large number of enterprises having already implemented an enterprise private cloud.  On the face of it, this seems quite contrary to the observations outlined above. So what exactly is the reality? Well, the reality is that there is undoubtedly a huge amount of interest among enterprises about transforming their legacy IT environment - which is often seen as too rigid, too fragmented, and ultimately too expensive - to something more agile, transparent and business-focused. At the same time however, there is a great deal of confusion among CIOs and architects about how to get there. This isn't very surprising given all the buzz and hype surrounding cloud computing. Every IT vendor claims to have the most unique solution and there isn't a single IT product out there that does not have a cloud angle to it. Add to this the chatter on the blogosphere, it will get even a sane mind spinning.  Consequently, most  enterprises are still struggling to fully understand the concept and value of enterprise private cloud.  Even among those who have chosen to move forward relatively early, quite a few have made their decisions more based on vendor influence/preferences rather than what their businesses actually need.  Clearly, there is a disconnect between the promise of the enterprise private cloud and the current adoption trends.  So what is the way forward?  I certainly do not claim to have all the answers. But here is a perspective that many cloud practitioners have found useful and thus worth sharing. To take a step back, the fundamental premise of the enterprise private cloud is IT transformation. It is the quest to create a more agile, transparent and efficient IT infrastructure that is driven more by business needs rather than constrained by operational and procedural inefficiencies. It is the new way of delivering and consuming IT services - where the IT organizations operate more like enablers of  strategic services rather than just being the gatekeepers of IT resources. In an enterprise private cloud environment, IT organizations are expected to empower the end users via self-service access/control and provide the business stakeholders a transparent view of how the resources are being used, what’s the cost of delivering a given service, how well are the customers being served, etc.  But the most important thing to note here is the enterprise private cloud is not just an IT project, rather it is a business initiative to create an IT setup that is more aligned with the needs of today's dynamic and highly competitive business environment. Surprised? You shouldn’t be. Just remember how the business users have been at the forefront of public cloud adoption within enterprises and private cloud is no exception.   Such a broad-based transformation makes cloud more than a technology initiative. It requires people (organizational) and process changes as well, and these changes are as critical as is the choice of right tools and technology. In my next blog,  I will share how essential it is for enterprise cloud technology to go hand-in hand with process re-engineering and organization changes to unlock true value of  enterprise cloud. I am sharing a short video from my session "Managing your private Cloud" at Oracle OpenWorld 2012. More videos from this session will be posted at the recently introduced Zero to Cloud resource page. Many other experts of Oracle enterprise private cloud solution will join me on this blog "Zero to Cloud"  and share best practices , deployment tips and information on how to plan, build, deploy, monitor, manage , meter and optimize the enterprise private cloud. We look forward to your feedback, suggestions and having an engaging conversion with you on this blog.

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  • Using XA Transactions in Coherence-based Applications

    - by jpurdy
    While the costs of XA transactions are well known (e.g. increased data contention, higher latency, significant disk I/O for logging, availability challenges, etc.), in many cases they are the most attractive option for coordinating logical transactions across multiple resources. There are a few common approaches when integrating Coherence into applications via the use of an application server's transaction manager: Use of Coherence as a read-only cache, applying transactions to the underlying database (or any system of record) instead of the cache. Use of TransactionMap interface via the included resource adapter. Use of the new ACID transaction framework, introduced in Coherence 3.6.   Each of these may have significant drawbacks for certain workloads. Using Coherence as a read-only cache is the simplest option. In this approach, the application is responsible for managing both the database and the cache (either within the business logic or via application server hooks). This approach also tends to provide limited benefit for many workloads, particularly those workloads that either have queries (given the complexity of maintaining a fully cached data set in Coherence) or are not read-heavy (where the cost of managing the cache may outweigh the benefits of reading from it). All updates are made synchronously to the database, leaving it as both a source of latency as well as a potential bottleneck. This approach also prevents addressing "hot data" problems (when certain objects are updated by many concurrent transactions) since most database servers offer no facilities for explicitly controlling concurrent updates. Finally, this option tends to be a better fit for key-based access (rather than filter-based access such as queries) since this makes it easier to aggressively invalidate cache entries without worrying about when they will be reloaded. The advantage of this approach is that it allows strong data consistency as long as optimistic concurrency control is used to ensure that database updates are applied correctly regardless of whether the cache contains stale (or even dirty) data. Another benefit of this approach is that it avoids the limitations of Coherence's write-through caching implementation. TransactionMap is generally used when Coherence acts as system of record. TransactionMap is not generally compatible with write-through caching, so it will usually be either used to manage a standalone cache or when the cache is backed by a database via write-behind caching. TransactionMap has some restrictions that may limit its utility, the most significant being: The lock-based concurrency model is relatively inefficient and may introduce significant latency and contention. As an example, in a typical configuration, a transaction that updates 20 cache entries will require roughly 40ms just for lock management (assuming all locks are granted immediately, and excluding validation and writing which will require a similar amount of time). This may be partially mitigated by denormalizing (e.g. combining a parent object and its set of child objects into a single cache entry), at the cost of increasing false contention (e.g. transactions will conflict even when updating different child objects). If the client (application server JVM) fails during the commit phase, locks will be released immediately, and the transaction may be partially committed. In practice, this is usually not as bad as it may sound since the commit phase is usually very short (all locks having been previously acquired). Note that this vulnerability does not exist when a single NamedCache is used and all updates are confined to a single partition (generally implying the use of partition affinity). The unconventional TransactionMap API is cumbersome but manageable. Only a few methods are transactional, primarily get(), put() and remove(). The ACID transactions framework (accessed via the Connection class) provides atomicity guarantees by implementing the NamedCache interface, maintaining its own cache data and transaction logs inside a set of private partitioned caches. This feature may be used as either a local transactional resource or as logging XA resource. However, a lack of database integration precludes the use of this functionality for most applications. A side effect of this is that this feature has not seen significant adoption, meaning that any use of this is subject to the usual headaches associated with being an early adopter (greater chance of bugs and greater risk of hitting an unoptimized code path). As a result, for the moment, we generally recommend against using this feature. In summary, it is possible to use Coherence in XA-oriented applications, and several customers are doing this successfully, but it is not a core usage model for the product, so care should be taken before committing to this path. For most applications, the most robust solution is normally to use Coherence as a read-only cache of the underlying data resources, even if this prevents taking advantage of certain product features.

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  • Using an alternate JSON Serializer in ASP.NET Web API

    - by Rick Strahl
    The new ASP.NET Web API that Microsoft released alongside MVC 4.0 Beta last week is a great framework for building REST and AJAX APIs. I've been working with it for quite a while now and I really like the way it works and the complete set of features it provides 'in the box'. It's about time that Microsoft gets a decent API for building generic HTTP endpoints into the framework. DataContractJsonSerializer sucks As nice as Web API's overall design is one thing still sucks: The built-in JSON Serialization uses the DataContractJsonSerializer which is just too limiting for many scenarios. The biggest issues I have with it are: No support for untyped values (object, dynamic, Anonymous Types) MS AJAX style Date Formatting Ugly serialization formats for types like Dictionaries To me the most serious issue is dealing with serialization of untyped objects. I have number of applications with AJAX front ends that dynamically reformat data from business objects to fit a specific message format that certain UI components require. The most common scenario I have there are IEnumerable query results from a database with fields from the result set rearranged to fit the sometimes unconventional formats required for the UI components (like jqGrid for example). Creating custom types to fit these messages seems like overkill and projections using Linq makes this much easier to code up. Alas DataContractJsonSerializer doesn't support it. Neither does DataContractSerializer for XML output for that matter. What this means is that you can't do stuff like this in Web API out of the box:public object GetAnonymousType() { return new { name = "Rick", company = "West Wind", entered= DateTime.Now }; } Basically anything that doesn't have an explicit type DataContractJsonSerializer will not let you return. FWIW, the same is true for XmlSerializer which also doesn't work with non-typed values for serialization. The example above is obviously contrived with a hardcoded object graph, but it's not uncommon to get dynamic values returned from queries that have anonymous types for their result projections. Apparently there's a good possibility that Microsoft will ship Json.NET as part of Web API RTM release.  Scott Hanselman confirmed this as a footnote in his JSON Dates post a few days ago. I've heard several other people from Microsoft confirm that Json.NET will be included and be the default JSON serializer, but no details yet in what capacity it will show up. Let's hope it ends up as the default in the box. Meanwhile this post will show you how you can use it today with the beta and get JSON that matches what you should see in the RTM version. What about JsonValue? To be fair Web API DOES include a new JsonValue/JsonObject/JsonArray type that allow you to address some of these scenarios. JsonValue is a new type in the System.Json assembly that can be used to build up an object graph based on a dictionary. It's actually a really cool implementation of a dynamic type that allows you to create an object graph and spit it out to JSON without having to create .NET type first. JsonValue can also receive a JSON string and parse it without having to actually load it into a .NET type (which is something that's been missing in the core framework). This is really useful if you get a JSON result from an arbitrary service and you don't want to explicitly create a mapping type for the data returned. For serialization you can create an object structure on the fly and pass it back as part of an Web API action method like this:public JsonValue GetJsonValue() { dynamic json = new JsonObject(); json.name = "Rick"; json.company = "West Wind"; json.entered = DateTime.Now; dynamic address = new JsonObject(); address.street = "32 Kaiea"; address.zip = "96779"; json.address = address; dynamic phones = new JsonArray(); json.phoneNumbers = phones; dynamic phone = new JsonObject(); phone.type = "Home"; phone.number = "808 123-1233"; phones.Add(phone); phone = new JsonObject(); phone.type = "Home"; phone.number = "808 123-1233"; phones.Add(phone); //var jsonString = json.ToString(); return json; } which produces the following output (formatted here for easier reading):{ name: "rick", company: "West Wind", entered: "2012-03-08T15:33:19.673-10:00", address: { street: "32 Kaiea", zip: "96779" }, phoneNumbers: [ { type: "Home", number: "808 123-1233" }, { type: "Mobile", number: "808 123-1234" }] } If you need to build a simple JSON type on the fly these types work great. But if you have an existing type - or worse a query result/list that's already formatted JsonValue et al. become a pain to work with. As far as I can see there's no way to just throw an object instance at JsonValue and have it convert into JsonValue dictionary. It's a manual process. Using alternate Serializers in Web API So, currently the default serializer in WebAPI is DataContractJsonSeriaizer and I don't like it. You may not either, but luckily you can swap the serializer fairly easily. If you'd rather use the JavaScriptSerializer built into System.Web.Extensions or Json.NET today, it's not too difficult to create a custom MediaTypeFormatter that uses these serializers and can replace or partially replace the native serializer. Here's a MediaTypeFormatter implementation using the ASP.NET JavaScriptSerializer:using System; using System.Net.Http.Formatting; using System.Threading.Tasks; using System.Web.Script.Serialization; using System.Json; using System.IO; namespace Westwind.Web.WebApi { public class JavaScriptSerializerFormatter : MediaTypeFormatter { public JavaScriptSerializerFormatter() { SupportedMediaTypes.Add(new System.Net.Http.Headers.MediaTypeHeaderValue("application/json")); } protected override bool CanWriteType(Type type) { // don't serialize JsonValue structure use default for that if (type == typeof(JsonValue) || type == typeof(JsonObject) || type== typeof(JsonArray) ) return false; return true; } protected override bool CanReadType(Type type) { if (type == typeof(IKeyValueModel)) return false; return true; } protected override System.Threading.Tasks.Taskobject OnReadFromStreamAsync(Type type, System.IO.Stream stream, System.Net.Http.Headers.HttpContentHeaders contentHeaders, FormatterContext formatterContext) { var task = Taskobject.Factory.StartNew(() = { var ser = new JavaScriptSerializer(); string json; using (var sr = new StreamReader(stream)) { json = sr.ReadToEnd(); sr.Close(); } object val = ser.Deserialize(json,type); return val; }); return task; } protected override System.Threading.Tasks.Task OnWriteToStreamAsync(Type type, object value, System.IO.Stream stream, System.Net.Http.Headers.HttpContentHeaders contentHeaders, FormatterContext formatterContext, System.Net.TransportContext transportContext) { var task = Task.Factory.StartNew( () = { var ser = new JavaScriptSerializer(); var json = ser.Serialize(value); byte[] buf = System.Text.Encoding.Default.GetBytes(json); stream.Write(buf,0,buf.Length); stream.Flush(); }); return task; } } } Formatter implementation is pretty simple: You override 4 methods to tell which types you can handle and then handle the input or output streams to create/parse the JSON data. Note that when creating output you want to take care to still allow JsonValue/JsonObject/JsonArray types to be handled by the default serializer so those objects serialize properly - if you let either JavaScriptSerializer or JSON.NET handle them they'd try to render the dictionaries which is very undesirable. If you'd rather use Json.NET here's the JSON.NET version of the formatter:// this code requires a reference to JSON.NET in your project #if true using System; using System.Net.Http.Formatting; using System.Threading.Tasks; using System.Web.Script.Serialization; using System.Json; using Newtonsoft.Json; using System.IO; using Newtonsoft.Json.Converters; namespace Westwind.Web.WebApi { public class JsonNetFormatter : MediaTypeFormatter { public JsonNetFormatter() { SupportedMediaTypes.Add(new System.Net.Http.Headers.MediaTypeHeaderValue("application/json")); } protected override bool CanWriteType(Type type) { // don't serialize JsonValue structure use default for that if (type == typeof(JsonValue) || type == typeof(JsonObject) || type == typeof(JsonArray)) return false; return true; } protected override bool CanReadType(Type type) { if (type == typeof(IKeyValueModel)) return false; return true; } protected override System.Threading.Tasks.Taskobject OnReadFromStreamAsync(Type type, System.IO.Stream stream, System.Net.Http.Headers.HttpContentHeaders contentHeaders, FormatterContext formatterContext) { var task = Taskobject.Factory.StartNew(() = { var settings = new JsonSerializerSettings() { NullValueHandling = NullValueHandling.Ignore, }; var sr = new StreamReader(stream); var jreader = new JsonTextReader(sr); var ser = new JsonSerializer(); ser.Converters.Add(new IsoDateTimeConverter()); object val = ser.Deserialize(jreader, type); return val; }); return task; } protected override System.Threading.Tasks.Task OnWriteToStreamAsync(Type type, object value, System.IO.Stream stream, System.Net.Http.Headers.HttpContentHeaders contentHeaders, FormatterContext formatterContext, System.Net.TransportContext transportContext) { var task = Task.Factory.StartNew( () = { var settings = new JsonSerializerSettings() { NullValueHandling = NullValueHandling.Ignore, }; string json = JsonConvert.SerializeObject(value, Formatting.Indented, new JsonConverter[1] { new IsoDateTimeConverter() } ); byte[] buf = System.Text.Encoding.Default.GetBytes(json); stream.Write(buf,0,buf.Length); stream.Flush(); }); return task; } } } #endif   One advantage of the Json.NET serializer is that you can specify a few options on how things are formatted and handled. You get null value handling and you can plug in the IsoDateTimeConverter which is nice to product proper ISO dates that I would expect any Json serializer to output these days. Hooking up the Formatters Once you've created the custom formatters you need to enable them for your Web API application. To do this use the GlobalConfiguration.Configuration object and add the formatter to the Formatters collection. Here's what this looks like hooked up from Application_Start in a Web project:protected void Application_Start(object sender, EventArgs e) { // Action based routing (used for RPC calls) RouteTable.Routes.MapHttpRoute( name: "StockApi", routeTemplate: "stocks/{action}/{symbol}", defaults: new { symbol = RouteParameter.Optional, controller = "StockApi" } ); // WebApi Configuration to hook up formatters and message handlers // optional RegisterApis(GlobalConfiguration.Configuration); } public static void RegisterApis(HttpConfiguration config) { // Add JavaScriptSerializer formatter instead - add at top to make default //config.Formatters.Insert(0, new JavaScriptSerializerFormatter()); // Add Json.net formatter - add at the top so it fires first! // This leaves the old one in place so JsonValue/JsonObject/JsonArray still are handled config.Formatters.Insert(0, new JsonNetFormatter()); } One thing to remember here is the GlobalConfiguration object which is Web API's static configuration instance. I think this thing is seriously misnamed given that GlobalConfiguration could stand for anything and so is hard to discover if you don't know what you're looking for. How about WebApiConfiguration or something more descriptive? Anyway, once you know what it is you can use the Formatters collection to insert your custom formatter. Note that I insert my formatter at the top of the list so it takes precedence over the default formatter. I also am not removing the old formatter because I still want JsonValue/JsonObject/JsonArray to be handled by the default serialization mechanism. Since they process in sequence and I exclude processing for these types JsonValue et al. still get properly serialized/deserialized. Summary Currently DataContractJsonSerializer in Web API is a pain, but at least we have the ability with relatively limited effort to replace the MediaTypeFormatter and plug in our own JSON serializer. This is useful for many scenarios - if you have existing client applications that used MVC JsonResult or ASP.NET AJAX results from ASMX AJAX services you can plug in the JavaScript serializer and get exactly the same serializer you used in the past so your results will be the same and don't potentially break clients. JSON serializers do vary a bit in how they serialize some of the more complex types (like Dictionaries and dates for example) and so if you're migrating it might be helpful to ensure your client code doesn't break when you switch to ASP.NET Web API. Going forward it looks like Microsoft is planning on plugging in Json.Net into Web API and make that the default. I think that's an awesome choice since Json.net has been around forever, is fast and easy to use and provides a ton of functionality as part of this great library. I just wish Microsoft would have figured this out sooner instead of now at the last minute integrating with it especially given that Json.Net has a similar set of lower level JSON objects JsonValue/JsonObject etc. which now will end up being duplicated by the native System.Json stuff. It's not like we don't already have enough confusion regarding which JSON serializer to use (JavaScriptSerializer, DataContractJsonSerializer, JsonValue/JsonObject/JsonArray and now Json.net). For years I've been using my own JSON serializer because the built in choices are both limited. However, with an official encorsement of Json.Net I'm happily moving on to use that in my applications. Let's see and hope Microsoft gets this right before ASP.NET Web API goes gold.© Rick Strahl, West Wind Technologies, 2005-2012Posted in Web Api  AJAX  ASP.NET   Tweet !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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