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  • Differences between Dynamic Dispatch and Dynamic Binding

    - by Prog
    I've been looking on Google for a clear diffrentiation with examples but couldn't find any. I'm trying to understand the differences between Dynamic Dispatch and Dynamic Binding in Object Oriented languages. As far as I understand, Dynamic Dispatch is what happens when the concrete method invoked is decided at runtime, based on the concrete type. For example: public void doStuff(SuperType object){ object.act(); } SuperType has several subclasses. The concrete class of the object will only be known at runtime, and so the concrete act() implementation invoked will be decided at runtime. However, I'm not sure what Dynamic Binding means, and how it differs from Dynamic Dispatch. Please explain Dynamic Binding and how it's different from Dynamic Dispatch. Java examples would be welcome.

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  • Dynamic Types and DynamicObject References in C#

    - by Rick Strahl
    I've been working a bit with C# custom dynamic types for several customers recently and I've seen some confusion in understanding how dynamic types are referenced. This discussion specifically centers around types that implement IDynamicMetaObjectProvider or subclass from DynamicObject as opposed to arbitrary type casts of standard .NET types. IDynamicMetaObjectProvider types  are treated special when they are cast to the dynamic type. Assume for a second that I've created my own implementation of a custom dynamic type called DynamicFoo which is about as simple of a dynamic class that I can think of:public class DynamicFoo : DynamicObject { Dictionary<string, object> properties = new Dictionary<string, object>(); public string Bar { get; set; } public DateTime Entered { get; set; } public override bool TryGetMember(GetMemberBinder binder, out object result) { result = null; if (!properties.ContainsKey(binder.Name)) return false; result = properties[binder.Name]; return true; } public override bool TrySetMember(SetMemberBinder binder, object value) { properties[binder.Name] = value; return true; } } This class has an internal dictionary member and I'm exposing this dictionary member through a dynamic by implementing DynamicObject. This implementation exposes the properties dictionary so the dictionary keys can be referenced like properties (foo.NewProperty = "Cool!"). I override TryGetMember() and TrySetMember() which are fired at runtime every time you access a 'property' on a dynamic instance of this DynamicFoo type. Strong Typing and Dynamic Casting I now can instantiate and use DynamicFoo in a couple of different ways: Strong TypingDynamicFoo fooExplicit = new DynamicFoo(); var fooVar = new DynamicFoo(); These two commands are essentially identical and use strong typing. The compiler generates identical code for both of them. The var statement is merely a compiler directive to infer the type of fooVar at compile time and so the type of fooExplicit is DynamicFoo, just like fooExplicit. This is very static - nothing dynamic about it - and it completely ignores the IDynamicMetaObjectProvider implementation of my class above as it's never used. Using either of these I can access the native properties:DynamicFoo fooExplicit = new DynamicFoo();// static typing assignmentsfooVar.Bar = "Barred!"; fooExplicit.Entered = DateTime.Now; // echo back static values Console.WriteLine(fooVar.Bar); Console.WriteLine(fooExplicit.Entered); but I have no access whatsoever to the properties dictionary. Basically this creates a strongly typed instance of the type with access only to the strongly typed interface. You get no dynamic behavior at all. The IDynamicMetaObjectProvider features don't kick in until you cast the type to dynamic. If I try to access a non-existing property on fooExplicit I get a compilation error that tells me that the property doesn't exist. Again, it's clearly and utterly non-dynamic. Dynamicdynamic fooDynamic = new DynamicFoo(); fooDynamic on the other hand is created as a dynamic type and it's a completely different beast. I can also create a dynamic by simply casting any type to dynamic like this:DynamicFoo fooExplicit = new DynamicFoo(); dynamic fooDynamic = fooExplicit; Note that dynamic typically doesn't require an explicit cast as the compiler automatically performs the cast so there's no need to use as dynamic. Dynamic functionality works at runtime and allows for the dynamic wrapper to look up and call members dynamically. A dynamic type will look for members to access or call in two places: Using the strongly typed members of the object Using theIDynamicMetaObjectProvider Interface methods to access members So rather than statically linking and calling a method or retrieving a property, the dynamic type looks up - at runtime  - where the value actually comes from. It's essentially late-binding which allows runtime determination what action to take when a member is accessed at runtime *if* the member you are accessing does not exist on the object. Class members are checked first before IDynamicMetaObjectProvider interface methods are kick in. All of the following works with the dynamic type:dynamic fooDynamic = new DynamicFoo(); // dynamic typing assignments fooDynamic.NewProperty = "Something new!"; fooDynamic.LastAccess = DateTime.Now; // dynamic assigning static properties fooDynamic.Bar = "dynamic barred"; fooDynamic.Entered = DateTime.Now; // echo back dynamic values Console.WriteLine(fooDynamic.NewProperty); Console.WriteLine(fooDynamic.LastAccess); Console.WriteLine(fooDynamic.Bar); Console.WriteLine(fooDynamic.Entered); The dynamic type can access the native class properties (Bar and Entered) and create and read new ones (NewProperty,LastAccess) all using a single type instance which is pretty cool. As you can see it's pretty easy to create an extensible type this way that can dynamically add members at runtime dynamically. The Alter Ego of IDynamicObject The key point here is that all three statements - explicit, var and dynamic - declare a new DynamicFoo(), but the dynamic declaration results in completely different behavior than the first two simply because the type has been cast to dynamic. Dynamic binding means that the type loses its typical strong typing, compile time features. You can see this easily in the Visual Studio code editor. As soon as you assign a value to a dynamic you lose Intellisense and you see which means there's no Intellisense and no compiler type checking on any members you apply to this instance. If you're new to the dynamic type it might seem really confusing that a single type can behave differently depending on how it is cast, but that's exactly what happens when you use a type that implements IDynamicMetaObjectProvider. Declare the type as its strong type name and you only get to access the native instance members of the type. Declare or cast it to dynamic and you get dynamic behavior which accesses native members plus it uses IDynamicMetaObjectProvider implementation to handle any missing member definitions by running custom code. You can easily cast objects back and forth between dynamic and the original type:dynamic fooDynamic = new DynamicFoo(); fooDynamic.NewProperty = "New Property Value"; DynamicFoo foo = fooDynamic; foo.Bar = "Barred"; Here the code starts out with a dynamic cast and a dynamic assignment. The code then casts back the value to the DynamicFoo. Notice that when casting from dynamic to DynamicFoo and back we typically do not have to specify the cast explicitly - the compiler can induce the type so I don't need to specify as dynamic or as DynamicFoo. Moral of the Story This easy interchange between dynamic and the underlying type is actually super useful, because it allows you to create extensible objects that can expose non-member data stores and expose them as an object interface. You can create an object that hosts a number of strongly typed properties and then cast the object to dynamic and add additional dynamic properties to the same type at runtime. You can easily switch back and forth between the strongly typed instance to access the well-known strongly typed properties and to dynamic for the dynamic properties added at runtime. Keep in mind that dynamic object access has quite a bit of overhead and is definitely slower than strongly typed binding, so if you're accessing the strongly typed parts of your objects you definitely want to use a strongly typed reference. Reserve dynamic for the dynamic members to optimize your code. The real beauty of dynamic is that with very little effort you can build expandable objects or objects that expose different data stores to an object interface. I'll have more on this in my next post when I create a customized and extensible Expando object based on DynamicObject.© Rick Strahl, West Wind Technologies, 2005-2012Posted in CSharp  .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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  • 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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  • Creating a dynamic, extensible C# Expando Object

    - by Rick Strahl
    I love dynamic functionality in a strongly typed language because it offers us the best of both worlds. In C# (or any of the main .NET languages) we now have the dynamic type that provides a host of dynamic features for the static C# language. One place where I've found dynamic to be incredibly useful is in building extensible types or types that expose traditionally non-object data (like dictionaries) in easier to use and more readable syntax. I wrote about a couple of these for accessing old school ADO.NET DataRows and DataReaders more easily for example. These classes are dynamic wrappers that provide easier syntax and auto-type conversions which greatly simplifies code clutter and increases clarity in existing code. ExpandoObject in .NET 4.0 Another great use case for dynamic objects is the ability to create extensible objects - objects that start out with a set of static members and then can add additional properties and even methods dynamically. The .NET 4.0 framework actually includes an ExpandoObject class which provides a very dynamic object that allows you to add properties and methods on the fly and then access them again. For example with ExpandoObject you can do stuff like this:dynamic expand = new ExpandoObject(); expand.Name = "Rick"; expand.HelloWorld = (Func<string, string>) ((string name) => { return "Hello " + name; }); Console.WriteLine(expand.Name); Console.WriteLine(expand.HelloWorld("Dufus")); Internally ExpandoObject uses a Dictionary like structure and interface to store properties and methods and then allows you to add and access properties and methods easily. As cool as ExpandoObject is it has a few shortcomings too: It's a sealed type so you can't use it as a base class It only works off 'properties' in the internal Dictionary - you can't expose existing type data It doesn't serialize to XML or with DataContractSerializer/DataContractJsonSerializer Expando - A truly extensible Object ExpandoObject is nice if you just need a dynamic container for a dictionary like structure. However, if you want to build an extensible object that starts out with a set of strongly typed properties and then allows you to extend it, ExpandoObject does not work because it's a sealed class that can't be inherited. I started thinking about this very scenario for one of my applications I'm building for a customer. In this system we are connecting to various different user stores. Each user store has the same basic requirements for username, password, name etc. But then each store also has a number of extended properties that is available to each application. In the real world scenario the data is loaded from the database in a data reader and the known properties are assigned from the known fields in the database. All unknown fields are then 'added' to the expando object dynamically. In the past I've done this very thing with a separate property - Properties - just like I do for this class. But the property and dictionary syntax is not ideal and tedious to work with. I started thinking about how to represent these extra property structures. One way certainly would be to add a Dictionary, or an ExpandoObject to hold all those extra properties. But wouldn't it be nice if the application could actually extend an existing object that looks something like this as you can with the Expando object:public class User : Westwind.Utilities.Dynamic.Expando { public string Email { get; set; } public string Password { get; set; } public string Name { get; set; } public bool Active { get; set; } public DateTime? ExpiresOn { get; set; } } and then simply start extending the properties of this object dynamically? Using the Expando object I describe later you can now do the following:[TestMethod] public void UserExampleTest() { var user = new User(); // Set strongly typed properties user.Email = "[email protected]"; user.Password = "nonya123"; user.Name = "Rickochet"; user.Active = true; // Now add dynamic properties dynamic duser = user; duser.Entered = DateTime.Now; duser.Accesses = 1; // you can also add dynamic props via indexer user["NickName"] = "AntiSocialX"; duser["WebSite"] = "http://www.west-wind.com/weblog"; // Access strong type through dynamic ref Assert.AreEqual(user.Name,duser.Name); // Access strong type through indexer Assert.AreEqual(user.Password,user["Password"]); // access dyanmically added value through indexer Assert.AreEqual(duser.Entered,user["Entered"]); // access index added value through dynamic Assert.AreEqual(user["NickName"],duser.NickName); // loop through all properties dynamic AND strong type properties (true) foreach (var prop in user.GetProperties(true)) { object val = prop.Value; if (val == null) val = "null"; Console.WriteLine(prop.Key + ": " + val.ToString()); } } As you can see this code somewhat blurs the line between a static and dynamic type. You start with a strongly typed object that has a fixed set of properties. You can then cast the object to dynamic (as I discussed in my last post) and add additional properties to the object. You can also use an indexer to add dynamic properties to the object. To access the strongly typed properties you can use either the strongly typed instance, the indexer or the dynamic cast of the object. Personally I think it's kinda cool to have an easy way to access strongly typed properties by string which can make some data scenarios much easier. To access the 'dynamically added' properties you can use either the indexer on the strongly typed object, or property syntax on the dynamic cast. Using the dynamic type allows all three modes to work on both strongly typed and dynamic properties. Finally you can iterate over all properties, both dynamic and strongly typed if you chose. Lots of flexibility. Note also that by default the Expando object works against the (this) instance meaning it extends the current object. You can also pass in a separate instance to the constructor in which case that object will be used to iterate over to find properties rather than this. Using this approach provides some really interesting functionality when use the dynamic type. To use this we have to add an explicit constructor to the Expando subclass:public class User : Westwind.Utilities.Dynamic.Expando { public string Email { get; set; } public string Password { get; set; } public string Name { get; set; } public bool Active { get; set; } public DateTime? ExpiresOn { get; set; } public User() : base() { } // only required if you want to mix in seperate instance public User(object instance) : base(instance) { } } to allow the instance to be passed. When you do you can now do:[TestMethod] public void ExpandoMixinTest() { // have Expando work on Addresses var user = new User( new Address() ); // cast to dynamicAccessToPropertyTest dynamic duser = user; // Set strongly typed properties duser.Email = "[email protected]"; user.Password = "nonya123"; // Set properties on address object duser.Address = "32 Kaiea"; //duser.Phone = "808-123-2131"; // set dynamic properties duser.NonExistantProperty = "This works too"; // shows default value Address.Phone value Console.WriteLine(duser.Phone); } Using the dynamic cast in this case allows you to access *three* different 'objects': The strong type properties, the dynamically added properties in the dictionary and the properties of the instance passed in! Effectively this gives you a way to simulate multiple inheritance (which is scary - so be very careful with this, but you can do it). How Expando works Behind the scenes Expando is a DynamicObject subclass as I discussed in my last post. By implementing a few of DynamicObject's methods you can basically create a type that can trap 'property missing' and 'method missing' operations. When you access a non-existant property a known method is fired that our code can intercept and provide a value for. Internally Expando uses a custom dictionary implementation to hold the dynamic properties you might add to your expandable object. Let's look at code first. The code for the Expando type is straight forward and given what it provides relatively short. Here it is.using System; using System.Collections.Generic; using System.Linq; using System.Dynamic; using System.Reflection; namespace Westwind.Utilities.Dynamic { /// <summary> /// Class that provides extensible properties and methods. This /// dynamic object stores 'extra' properties in a dictionary or /// checks the actual properties of the instance. /// /// This means you can subclass this expando and retrieve either /// native properties or properties from values in the dictionary. /// /// This type allows you three ways to access its properties: /// /// Directly: any explicitly declared properties are accessible /// Dynamic: dynamic cast allows access to dictionary and native properties/methods /// Dictionary: Any of the extended properties are accessible via IDictionary interface /// </summary> [Serializable] public class Expando : DynamicObject, IDynamicMetaObjectProvider { /// <summary> /// Instance of object passed in /// </summary> object Instance; /// <summary> /// Cached type of the instance /// </summary> Type InstanceType; PropertyInfo[] InstancePropertyInfo { get { if (_InstancePropertyInfo == null && Instance != null) _InstancePropertyInfo = Instance.GetType().GetProperties(BindingFlags.Instance | BindingFlags.Public | BindingFlags.DeclaredOnly); return _InstancePropertyInfo; } } PropertyInfo[] _InstancePropertyInfo; /// <summary> /// String Dictionary that contains the extra dynamic values /// stored on this object/instance /// </summary> /// <remarks>Using PropertyBag to support XML Serialization of the dictionary</remarks> public PropertyBag Properties = new PropertyBag(); //public Dictionary<string,object> Properties = new Dictionary<string, object>(); /// <summary> /// This constructor just works off the internal dictionary and any /// public properties of this object. /// /// Note you can subclass Expando. /// </summary> public Expando() { Initialize(this); } /// <summary> /// Allows passing in an existing instance variable to 'extend'. /// </summary> /// <remarks> /// You can pass in null here if you don't want to /// check native properties and only check the Dictionary! /// </remarks> /// <param name="instance"></param> public Expando(object instance) { Initialize(instance); } protected virtual void Initialize(object instance) { Instance = instance; if (instance != null) InstanceType = instance.GetType(); } /// <summary> /// Try to retrieve a member by name first from instance properties /// followed by the collection entries. /// </summary> /// <param name="binder"></param> /// <param name="result"></param> /// <returns></returns> public override bool TryGetMember(GetMemberBinder binder, out object result) { result = null; // first check the Properties collection for member if (Properties.Keys.Contains(binder.Name)) { result = Properties[binder.Name]; return true; } // Next check for Public properties via Reflection if (Instance != null) { try { return GetProperty(Instance, binder.Name, out result); } catch { } } // failed to retrieve a property result = null; return false; } /// <summary> /// Property setter implementation tries to retrieve value from instance /// first then into this object /// </summary> /// <param name="binder"></param> /// <param name="value"></param> /// <returns></returns> public override bool TrySetMember(SetMemberBinder binder, object value) { // first check to see if there's a native property to set if (Instance != null) { try { bool result = SetProperty(Instance, binder.Name, value); if (result) return true; } catch { } } // no match - set or add to dictionary Properties[binder.Name] = value; return true; } /// <summary> /// Dynamic invocation method. Currently allows only for Reflection based /// operation (no ability to add methods dynamically). /// </summary> /// <param name="binder"></param> /// <param name="args"></param> /// <param name="result"></param> /// <returns></returns> public override bool TryInvokeMember(InvokeMemberBinder binder, object[] args, out object result) { if (Instance != null) { try { // check instance passed in for methods to invoke if (InvokeMethod(Instance, binder.Name, args, out result)) return true; } catch { } } result = null; return false; } /// <summary> /// Reflection Helper method to retrieve a property /// </summary> /// <param name="instance"></param> /// <param name="name"></param> /// <param name="result"></param> /// <returns></returns> protected bool GetProperty(object instance, string name, out object result) { if (instance == null) instance = this; var miArray = InstanceType.GetMember(name, BindingFlags.Public | BindingFlags.GetProperty | BindingFlags.Instance); if (miArray != null && miArray.Length > 0) { var mi = miArray[0]; if (mi.MemberType == MemberTypes.Property) { result = ((PropertyInfo)mi).GetValue(instance,null); return true; } } result = null; return false; } /// <summary> /// Reflection helper method to set a property value /// </summary> /// <param name="instance"></param> /// <param name="name"></param> /// <param name="value"></param> /// <returns></returns> protected bool SetProperty(object instance, string name, object value) { if (instance == null) instance = this; var miArray = InstanceType.GetMember(name, BindingFlags.Public | BindingFlags.SetProperty | BindingFlags.Instance); if (miArray != null && miArray.Length > 0) { var mi = miArray[0]; if (mi.MemberType == MemberTypes.Property) { ((PropertyInfo)mi).SetValue(Instance, value, null); return true; } } return false; } /// <summary> /// Reflection helper method to invoke a method /// </summary> /// <param name="instance"></param> /// <param name="name"></param> /// <param name="args"></param> /// <param name="result"></param> /// <returns></returns> protected bool InvokeMethod(object instance, string name, object[] args, out object result) { if (instance == null) instance = this; // Look at the instanceType var miArray = InstanceType.GetMember(name, BindingFlags.InvokeMethod | BindingFlags.Public | BindingFlags.Instance); if (miArray != null && miArray.Length > 0) { var mi = miArray[0] as MethodInfo; result = mi.Invoke(Instance, args); return true; } result = null; return false; } /// <summary> /// Convenience method that provides a string Indexer /// to the Properties collection AND the strongly typed /// properties of the object by name. /// /// // dynamic /// exp["Address"] = "112 nowhere lane"; /// // strong /// var name = exp["StronglyTypedProperty"] as string; /// </summary> /// <remarks> /// The getter checks the Properties dictionary first /// then looks in PropertyInfo for properties. /// The setter checks the instance properties before /// checking the Properties dictionary. /// </remarks> /// <param name="key"></param> /// /// <returns></returns> public object this[string key] { get { try { // try to get from properties collection first return Properties[key]; } catch (KeyNotFoundException ex) { // try reflection on instanceType object result = null; if (GetProperty(Instance, key, out result)) return result; // nope doesn't exist throw; } } set { if (Properties.ContainsKey(key)) { Properties[key] = value; return; } // check instance for existance of type first var miArray = InstanceType.GetMember(key, BindingFlags.Public | BindingFlags.GetProperty); if (miArray != null && miArray.Length > 0) SetProperty(Instance, key, value); else Properties[key] = value; } } /// <summary> /// Returns and the properties of /// </summary> /// <param name="includeProperties"></param> /// <returns></returns> public IEnumerable<KeyValuePair<string,object>> GetProperties(bool includeInstanceProperties = false) { if (includeInstanceProperties && Instance != null) { foreach (var prop in this.InstancePropertyInfo) yield return new KeyValuePair<string, object>(prop.Name, prop.GetValue(Instance, null)); } foreach (var key in this.Properties.Keys) yield return new KeyValuePair<string, object>(key, this.Properties[key]); } /// <summary> /// Checks whether a property exists in the Property collection /// or as a property on the instance /// </summary> /// <param name="item"></param> /// <returns></returns> public bool Contains(KeyValuePair<string, object> item, bool includeInstanceProperties = false) { bool res = Properties.ContainsKey(item.Key); if (res) return true; if (includeInstanceProperties && Instance != null) { foreach (var prop in this.InstancePropertyInfo) { if (prop.Name == item.Key) return true; } } return false; } } } Although the Expando class supports an indexer, it doesn't actually implement IDictionary or even IEnumerable. It only provides the indexer and Contains() and GetProperties() methods, that work against the Properties dictionary AND the internal instance. The reason for not implementing IDictionary is that a) it doesn't add much value since you can access the Properties dictionary directly and that b) I wanted to keep the interface to class very lean so that it can serve as an entity type if desired. Implementing these IDictionary (or even IEnumerable) causes LINQ extension methods to pop up on the type which obscures the property interface and would only confuse the purpose of the type. IDictionary and IEnumerable are also problematic for XML and JSON Serialization - the XML Serializer doesn't serialize IDictionary<string,object>, nor does the DataContractSerializer. The JavaScriptSerializer does serialize, but it treats the entire object like a dictionary and doesn't serialize the strongly typed properties of the type, only the dictionary values which is also not desirable. Hence the decision to stick with only implementing the indexer to support the user["CustomProperty"] functionality and leaving iteration functions to the publicly exposed Properties dictionary. Note that the Dictionary used here is a custom PropertyBag class I created to allow for serialization to work. One important aspect for my apps is that whatever custom properties get added they have to be accessible to AJAX clients since the particular app I'm working on is a SIngle Page Web app where most of the Web access is through JSON AJAX calls. PropertyBag can serialize to XML and one way serialize to JSON using the JavaScript serializer (not the DCS serializers though). The key components that make Expando work in this code are the Properties Dictionary and the TryGetMember() and TrySetMember() methods. The Properties collection is public so if you choose you can explicitly access the collection to get better performance or to manipulate the members in internal code (like loading up dynamic values form a database). Notice that TryGetMember() and TrySetMember() both work against the dictionary AND the internal instance to retrieve and set properties. This means that user["Name"] works against native properties of the object as does user["Name"] = "RogaDugDog". What's your Use Case? This is still an early prototype but I've plugged it into one of my customer's applications and so far it's working very well. The key features for me were the ability to easily extend the type with values coming from a database and exposing those values in a nice and easy to use manner. I'm also finding that using this type of object for ViewModels works very well to add custom properties to view models. I suspect there will be lots of uses for this - I've been using the extra dictionary approach to extensibility for years - using a dynamic type to make the syntax cleaner is just a bonus here. What can you think of to use this for? Resources Source Code and Tests (GitHub) Also integrated in Westwind.Utilities of the West Wind Web Toolkit West Wind Utilities NuGet© Rick Strahl, West Wind Technologies, 2005-2012Posted in CSharp  .NET  Dynamic Types   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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  • SQL Server and Hyper-V Dynamic Memory - Part 1

    - by SQLOS Team
    SQL and Dynamic Memory Blog Post Series   Hyper-V Dynamic Memory is a new feature in Windows Server 2008 R2 SP1 that allows the memory assigned to guest virtual machines to vary according to demand. Using this feature with SQL Server is supported, but how well does it work in an environment where available memory can vary dynamically, especially since SQL Server likes memory, and is not very eager to let go of it? The next three posts will look at this question in detail. In Part 1 Serdar Sutay, a program manager in the Windows Hyper-V team, introduces Dynamic Memory with an overview of the basic architecture, configuration and monitoring concepts. In subsequent parts we will look at SQL Server memory handling, and develop some guidelines on using SQL Server with Dynamic Memory.   Part 1: Dynamic Memory Introduction   In virtualized environments memory is often the bottleneck for reaching higher VM densities. In Windows Server 2008 R2 SP1 Hyper-V introduced a new feature “Dynamic Memory” to improve VM densities on Hyper-V hosts. Dynamic Memory increases the memory utilization in virtualized environments by enabling VM memory to be changed dynamically when the VM is running.   This brings up the question of how to utilize this feature with SQL Server VMs as SQL Server performance is very sensitive to the memory being used. In the next three posts we’ll discuss the internals of Dynamic Memory, SQL Server Memory Management and how to use Dynamic Memory with SQL Server VMs.   Memory Utilization Efficiency in Virtualized Environments   The primary reason memory is usually the bottleneck for higher VM densities is that users tend to be generous when assigning memory to their VMs. Here are some memory sizing practices we’ve heard from customers:   ·         I assign 4 GB of memory to my VMs. I don’t know if all of it is being used by the applications but no one complains. ·         I take the minimum system requirements and add 50% more. ·         I go with the recommendations provided by my software vendor.   In reality correctly sizing a virtual machine requires significant effort to monitor the memory usage of the applications. Since this is not done in most environments, VMs are usually over-provisioned in terms of memory. In other words, a SQL Server VM that is assigned 4 GB of memory may not need to use 4 GB.   How does Dynamic Memory help?   Dynamic Memory improves the memory utilization by removing the requirement to determine the memory need for an application. Hyper-V determines the memory needed by applications in the VM by evaluating the memory usage information in the guest with Dynamic Memory. VMs can start with a small amount of memory and they can be assigned more memory dynamically based on the workload of applications running inside.   Overview of Dynamic Memory Concepts   ·         Startup Memory: Startup Memory is the starting amount of memory when Dynamic Memory is enabled for a VM. Dynamic Memory will make sure that this amount of memory is always assigned to the VMs by default.   ·         Maximum Memory: Maximum Memory specifies the maximum amount of memory that a VM can grow to with Dynamic Memory. ·         Memory Demand: Memory Demand is the amount determined by Dynamic Memory as the memory needed by the applications in the VM. In Windows Server 2008 R2 SP1, this is equal to the total amount of committed memory of the VM. ·         Memory Buffer: Memory Buffer is the amount of memory assigned to the VMs in addition to their memory demand to satisfy immediate memory requirements and file cache needs.   Once Dynamic Memory is enabled for a VM, it will start with the “Startup Memory”. After the boot process Dynamic Memory will determine the “Memory Demand” of the VM. Based on this memory demand it will determine the amount of “Memory Buffer” that needs to be assigned to the VM. Dynamic Memory will assign the total of “Memory Demand” and “Memory Buffer” to the VM as long as this value is less than “Maximum Memory” and as long as physical memory is available on the host.   What happens when there is not enough physical memory available on the host?   Once there is not enough physical memory on the host to satisfy VM needs, Dynamic Memory will assign less than needed amount of memory to the VMs based on their importance. A concept known as “Memory Weight” is used to determine how much VMs should be penalized based on their needed amount of memory. “Memory Weight” is a configuration setting on the VM. It can be configured to be higher for the VMs with high performance requirements. Under high memory pressure on the host, the “Memory Weight” of the VMs are evaluated in a relative manner and the VMs with lower relative “Memory Weight” will be penalized more than the ones with higher “Memory Weight”.   Dynamic Memory Configuration   Based on these concepts “Startup Memory”, “Maximum Memory”, “Memory Buffer” and “Memory Weight” can be configured as shown below in Windows Server 2008 R2 SP1 Hyper-V Manager. Memory Demand is automatically calculated by Dynamic Memory once VMs start running.     Dynamic Memory Monitoring    In Windows Server 2008 R2 SP1, Hyper-V Manager displays the memory status of VMs in the following three columns:         ·         Assigned Memory represents the current physical memory assigned to the VM. In regular conditions this will be equal to the sum of “Memory Demand” and “Memory Buffer” assigned to the VM. When there is not enough memory on the host, this value can go below the Memory Demand determined for the VM. ·         Memory Demand displays the current “Memory Demand” determined for the VM. ·         Memory Status displays the current memory status of the VM. This column can represent three values for a VM: o   OK: In this condition the VM is assigned the total of Memory Demand and Memory Buffer it needs. o   Low: In this condition the VM is assigned all the Memory Demand and a certain percentage of the Memory Buffer it needs. o   Warning: In this condition the VM is assigned a lower memory than its Memory Demand. When VMs are running in this condition, it’s likely that they will exhibit performance problems due to internal paging happening in the VM.    So far so good! But how does it work with SQL Server?   SQL Server is aggressive in terms of memory usage for good reasons. This raises the question: How do SQL Server and Dynamic Memory work together? To understand the full story, we’ll first need to understand how SQL Server Memory Management works. This will be covered in our second post in “SQL and Dynamic Memory” series. Meanwhile if you want to dive deeper into Dynamic Memory you can check the below posts from the Windows Virtualization Team Blog:   http://blogs.technet.com/virtualization/archive/2010/03/18/dynamic-memory-coming-to-hyper-v.aspx   http://blogs.technet.com/virtualization/archive/2010/03/25/dynamic-memory-coming-to-hyper-v-part-2.aspx   http://blogs.technet.com/virtualization/archive/2010/04/07/dynamic-memory-coming-to-hyper-v-part-3.aspx   http://blogs.technet.com/b/virtualization/archive/2010/04/21/dynamic-memory-coming-to-hyper-v-part-4.aspx   http://blogs.technet.com/b/virtualization/archive/2010/05/20/dynamic-memory-coming-to-hyper-v-part-5.aspx   http://blogs.technet.com/b/virtualization/archive/2010/07/12/dynamic-memory-coming-to-hyper-v-part-6.aspx   - Serdar Sutay   Originally posted at http://blogs.msdn.com/b/sqlosteam/

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  • SQL Server and Hyper-V Dynamic Memory - Part 1

    - by SQLOS Team
    SQL and Dynamic Memory Blog Post Series   Hyper-V Dynamic Memory is a new feature in Windows Server 2008 R2 SP1 that allows the memory assigned to guest virtual machines to vary according to demand. Using this feature with SQL Server is supported, but how well does it work in an environment where available memory can vary dynamically, especially since SQL Server likes memory, and is not very eager to let go of it? The next three posts will look at this question in detail. In Part 1 Serdar Sutay, a program manager in the Windows Hyper-V team, introduces Dynamic Memory with an overview of the basic architecture, configuration and monitoring concepts. In subsequent parts we will look at SQL Server memory handling, and develop some guidelines on using SQL Server with Dynamic Memory.   Part 1: Dynamic Memory Introduction   In virtualized environments memory is often the bottleneck for reaching higher VM densities. In Windows Server 2008 R2 SP1 Hyper-V introduced a new feature “Dynamic Memory” to improve VM densities on Hyper-V hosts. Dynamic Memory increases the memory utilization in virtualized environments by enabling VM memory to be changed dynamically when the VM is running.   This brings up the question of how to utilize this feature with SQL Server VMs as SQL Server performance is very sensitive to the memory being used. In the next three posts we’ll discuss the internals of Dynamic Memory, SQL Server Memory Management and how to use Dynamic Memory with SQL Server VMs.   Memory Utilization Efficiency in Virtualized Environments   The primary reason memory is usually the bottleneck for higher VM densities is that users tend to be generous when assigning memory to their VMs. Here are some memory sizing practices we’ve heard from customers:   ·         I assign 4 GB of memory to my VMs. I don’t know if all of it is being used by the applications but no one complains. ·         I take the minimum system requirements and add 50% more. ·         I go with the recommendations provided by my software vendor.   In reality correctly sizing a virtual machine requires significant effort to monitor the memory usage of the applications. Since this is not done in most environments, VMs are usually over-provisioned in terms of memory. In other words, a SQL Server VM that is assigned 4 GB of memory may not need to use 4 GB.   How does Dynamic Memory help?   Dynamic Memory improves the memory utilization by removing the requirement to determine the memory need for an application. Hyper-V determines the memory needed by applications in the VM by evaluating the memory usage information in the guest with Dynamic Memory. VMs can start with a small amount of memory and they can be assigned more memory dynamically based on the workload of applications running inside.   Overview of Dynamic Memory Concepts   ·         Startup Memory: Startup Memory is the starting amount of memory when Dynamic Memory is enabled for a VM. Dynamic Memory will make sure that this amount of memory is always assigned to the VMs by default.   ·         Maximum Memory: Maximum Memory specifies the maximum amount of memory that a VM can grow to with Dynamic Memory. ·         Memory Demand: Memory Demand is the amount determined by Dynamic Memory as the memory needed by the applications in the VM. In Windows Server 2008 R2 SP1, this is equal to the total amount of committed memory of the VM. ·         Memory Buffer: Memory Buffer is the amount of memory assigned to the VMs in addition to their memory demand to satisfy immediate memory requirements and file cache needs.   Once Dynamic Memory is enabled for a VM, it will start with the “Startup Memory”. After the boot process Dynamic Memory will determine the “Memory Demand” of the VM. Based on this memory demand it will determine the amount of “Memory Buffer” that needs to be assigned to the VM. Dynamic Memory will assign the total of “Memory Demand” and “Memory Buffer” to the VM as long as this value is less than “Maximum Memory” and as long as physical memory is available on the host.   What happens when there is not enough physical memory available on the host?   Once there is not enough physical memory on the host to satisfy VM needs, Dynamic Memory will assign less than needed amount of memory to the VMs based on their importance. A concept known as “Memory Weight” is used to determine how much VMs should be penalized based on their needed amount of memory. “Memory Weight” is a configuration setting on the VM. It can be configured to be higher for the VMs with high performance requirements. Under high memory pressure on the host, the “Memory Weight” of the VMs are evaluated in a relative manner and the VMs with lower relative “Memory Weight” will be penalized more than the ones with higher “Memory Weight”.   Dynamic Memory Configuration   Based on these concepts “Startup Memory”, “Maximum Memory”, “Memory Buffer” and “Memory Weight” can be configured as shown below in Windows Server 2008 R2 SP1 Hyper-V Manager. Memory Demand is automatically calculated by Dynamic Memory once VMs start running.     Dynamic Memory Monitoring    In Windows Server 2008 R2 SP1, Hyper-V Manager displays the memory status of VMs in the following three columns:         ·         Assigned Memory represents the current physical memory assigned to the VM. In regular conditions this will be equal to the sum of “Memory Demand” and “Memory Buffer” assigned to the VM. When there is not enough memory on the host, this value can go below the Memory Demand determined for the VM. ·         Memory Demand displays the current “Memory Demand” determined for the VM. ·         Memory Status displays the current memory status of the VM. This column can represent three values for a VM: o   OK: In this condition the VM is assigned the total of Memory Demand and Memory Buffer it needs. o   Low: In this condition the VM is assigned all the Memory Demand and a certain percentage of the Memory Buffer it needs. o   Warning: In this condition the VM is assigned a lower memory than its Memory Demand. When VMs are running in this condition, it’s likely that they will exhibit performance problems due to internal paging happening in the VM.    So far so good! But how does it work with SQL Server?   SQL Server is aggressive in terms of memory usage for good reasons. This raises the question: How do SQL Server and Dynamic Memory work together? To understand the full story, we’ll first need to understand how SQL Server Memory Management works. This will be covered in our second post in “SQL and Dynamic Memory” series. Meanwhile if you want to dive deeper into Dynamic Memory you can check the below posts from the Windows Virtualization Team Blog:   http://blogs.technet.com/virtualization/archive/2010/03/18/dynamic-memory-coming-to-hyper-v.aspx   http://blogs.technet.com/virtualization/archive/2010/03/25/dynamic-memory-coming-to-hyper-v-part-2.aspx   http://blogs.technet.com/virtualization/archive/2010/04/07/dynamic-memory-coming-to-hyper-v-part-3.aspx   http://blogs.technet.com/b/virtualization/archive/2010/04/21/dynamic-memory-coming-to-hyper-v-part-4.aspx   http://blogs.technet.com/b/virtualization/archive/2010/05/20/dynamic-memory-coming-to-hyper-v-part-5.aspx   http://blogs.technet.com/b/virtualization/archive/2010/07/12/dynamic-memory-coming-to-hyper-v-part-6.aspx   - Serdar Sutay   Originally posted at http://blogs.msdn.com/b/sqlosteam/

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  • How can I set up multiple dynamic users to update a single network's dynamic IP

    - by d3vid
    On my home network we are allocated a dynamic IP. I want to configure ddclient (or an equivalent) to send IP updates to DNS-O-Matic/OpenDNS only when I am on my home network. I do not want to send IP updates when I'm on my office network. Can this be done? I am prepared to use different FLOSS software or a different free DNS service. Additionally, there are multiple users who may be on the home network or away on other networks. How can we configure ddclient on each machine so that whoever is on the home network updates the IP (i.e. so we don't have to rely on a particular machine being on the network to update the IP). OpenDNS support have said we can't simply install updater software on each machine.

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  • SQL Server and Hyper-V Dynamic Memory Part 3

    - by SQLOS Team
    In parts 1 and 2 of this series we looked at the basics of Hyper-V Dynamic Memory and SQL Server memory management. In this part Serdar looks at configuration guidelines for SQL Server memory management. Part 3: Configuration Guidelines for Hyper-V Dynamic Memory and SQL Server Now that we understand SQL Server Memory Management and Hyper-V Dynamic Memory basics, let’s take a look at general configuration guidelines in order to utilize benefits of Hyper-V Dynamic Memory in your SQL Server VMs. Requirements Host Operating System Requirements Hyper-V Dynamic Memory feature is introduced with Windows Server 2008 R2 SP1. Therefore in order to use Dynamic Memory for your virtual machines, you need to have Windows Server 2008 R2 SP1 or Microsoft Hyper-V Server 2008 R2 SP1 in your Hyper-V host. Guest Operating System Requirements In addition to this Dynamic Memory is only supported in Standard, Web, Enterprise and Datacenter editions of windows running inside VMs. Make sure that your VM is running one of these editions. For additional requirements on each operating system see “Dynamic Memory Configuration Guidelines” here. SQL Server Requirements All versions of SQL Server support Hyper-V Dynamic Memory. However, only certain editions of SQL Server are aware of dynamically changing system memory. To have a truly dynamic environment for your SQL Server VMs make sure that you are running one of the SQL Server editions listed below: ·         SQL Server 2005 Enterprise ·         SQL Server 2008 Enterprise / Datacenter Editions ·         SQL Server 2008 R2 Enterprise / Datacenter Editions Configuration guidelines for other versions of SQL Server are covered below in the FAQ section. Guidelines for configuring Dynamic Memory Parameters Here is how to configure Dynamic Memory for your SQL VMs in a nutshell: Hyper-V Dynamic Memory Parameter Recommendation Startup RAM 1 GB + SQL Min Server Memory Maximum RAM > SQL Max Server Memory Memory Buffer % 5 Memory Weight Based on performance needs   Startup RAM In order to ensure that your SQL Server VMs can start correctly, ensure that Startup RAM is higher than configured SQL Min Server Memory for your VMs. Otherwise SQL Server service will need to do paging in order to start since it will not be able to see enough memory during startup. Also note that Startup Memory will always be reserved for your VMs. This will guarantee a certain level of performance for your SQL Servers, however setting this too high will limit the consolidation benefits you’ll get out of your virtualization environment. Maximum RAM This one is obvious. If you’ve configured SQL Max Server Memory for your SQL Server, make sure that Dynamic Memory Maximum RAM configuration is higher than this value. Otherwise your SQL Server will not grow to memory values higher than the value configured for Dynamic Memory. Memory Buffer % Memory buffer configuration is used to provision file cache to virtual machines in order to improve performance. Due to the fact that SQL Server is managing its own buffer pool, Memory Buffer setting should be configured to the lowest value possible, 5%. Configuring a higher memory buffer will prevent low resource notifications from Windows Memory Manager and it will prevent reclaiming memory from SQL Server VMs. Memory Weight Memory weight configuration defines the importance of memory to a VM. Configure higher values for the VMs that have higher performance requirements. VMs with higher memory weight will have more memory under high memory pressure conditions on your host. Questions and Answers Q1 – Which SQL Server memory model is best for Dynamic Memory? The best SQL Server model for Dynamic Memory is “Locked Page Memory Model”. This memory model ensures that SQL Server memory is never paged out and it’s also adaptive to dynamically changing memory in the system. This will be extremely useful when Dynamic Memory is attempting to remove memory from SQL Server VMs ensuring no SQL Server memory is paged out. You can find instructions on configuring “Locked Page Memory Model” for your SQL Servers here. Q2 – What about other SQL Server Editions, how should I configure Dynamic Memory for them? Other editions of SQL Server do not adapt to dynamically changing environments. They will determine how much memory they should allocate during startup and don’t change this value afterwards. Therefore make sure that you configure a higher startup memory for your VM because that will be all the memory that SQL Server utilize Tune Maximum Memory and Memory Buffer based on the other workloads running on the system. If there are no other workloads consider using Static Memory for these editions. Q3 – What if I have multiple SQL Server instances in a VM? Having multiple SQL Server instances in a VM is not a general recommendation for predictable performance, manageability and isolation. In order to achieve a predictable behavior make sure that you configure SQL Min Server Memory and SQL Max Server Memory for each instance in the VM. And make sure that: ·         Dynamic Memory Startup Memory is greater than the sum of SQL Min Server Memory values for the instances in the VM ·         Dynamic Memory Maximum Memory is greater than the sum of SQL Max Server Memory values for the instances in the VM Q4 – I’m using Large Page Memory Model for my SQL Server. Can I still use Dynamic Memory? The short answer is no. SQL Server does not dynamically change its memory size when configured with Large Page Memory Model. In virtualized environments Hyper-V provides large page support by default. Most of the time, Large Page Memory Model doesn’t bring any benefits to a SQL Server if it’s running in virtualized environments. Q5 – How do I monitor SQL performance when I’m trying Dynamic Memory on my VMs? Use the performance counters below to monitor memory performance for SQL Server: Process - Working Set: This counter is available in the VM via process performance counters. It represents the actual amount of physical memory being used by SQL Server process in the VM. SQL Server – Buffer Cache Hit Ratio: This counter is available in the VM via SQL Server counters. This represents the paging being done by SQL Server. A rate of 90% or higher is desirable. Conclusion These blog posts are a quick start to a story that will be developing more in the near future. We’re still continuing our testing and investigations to provide more detailed configuration guidelines with example performance numbers with a white paper in the upcoming months. Now it’s time to give SQL Server and Hyper-V Dynamic Memory a try. Use this guidelines to kick-start your environment. See what you think about it and let us know of your experiences. - Serdar Sutay Originally posted at http://blogs.msdn.com/b/sqlosteam/

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  • C# 4.0: Dynamic Programming

    - by Paulo Morgado
    The major feature of C# 4.0 is dynamic programming. Not just dynamic typing, but dynamic in broader sense, which means talking to anything that is not statically typed to be a .NET object. Dynamic Language Runtime The Dynamic Language Runtime (DLR) is piece of technology that unifies dynamic programming on the .NET platform, the same way the Common Language Runtime (CLR) has been a common platform for statically typed languages. The CLR always had dynamic capabilities. You could always use reflection, but its main goal was never to be a dynamic programming environment and there were some features missing. The DLR is built on top of the CLR and adds those missing features to the .NET platform. The Dynamic Language Runtime is the core infrastructure that consists of: Expression Trees The same expression trees used in LINQ, now improved to support statements. Dynamic Dispatch Dispatches invocations to the appropriate binder. Call Site Caching For improved efficiency. Dynamic languages and languages with dynamic capabilities are built on top of the DLR. IronPython and IronRuby were already built on top of the DLR, and now, the support for using the DLR is being added to C# and Visual Basic. Other languages built on top of the CLR are expected to also use the DLR in the future. Underneath the DLR there are binders that talk to a variety of different technologies: .NET Binder Allows to talk to .NET objects. JavaScript Binder Allows to talk to JavaScript in SilverLight. IronPython Binder Allows to talk to IronPython. IronRuby Binder Allows to talk to IronRuby. COM Binder Allows to talk to COM. Whit all these binders it is possible to have a single programming experience to talk to all these environments that are not statically typed .NET objects. The dynamic Static Type Let’s take this traditional statically typed code: Calculator calculator = GetCalculator(); int sum = calculator.Sum(10, 20); Because the variable that receives the return value of the GetCalulator method is statically typed to be of type Calculator and, because the Calculator type has an Add method that receives two integers and returns an integer, it is possible to call that Sum method and assign its return value to a variable statically typed as integer. Now lets suppose the calculator was not a statically typed .NET class, but, instead, a COM object or some .NET code we don’t know he type of. All of the sudden it gets very painful to call the Add method: object calculator = GetCalculator(); Type calculatorType = calculator.GetType(); object res = calculatorType.InvokeMember("Add", BindingFlags.InvokeMethod, null, calculator, new object[] { 10, 20 }); int sum = Convert.ToInt32(res); And what if the calculator was a JavaScript object? ScriptObject calculator = GetCalculator(); object res = calculator.Invoke("Add", 10, 20); int sum = Convert.ToInt32(res); For each dynamic domain we have a different programming experience and that makes it very hard to unify the code. With C# 4.0 it becomes possible to write code this way: dynamic calculator = GetCalculator(); int sum = calculator.Add(10, 20); You simply declare a variable who’s static type is dynamic. dynamic is a pseudo-keyword (like var) that indicates to the compiler that operations on the calculator object will be done dynamically. The way you should look at dynamic is that it’s just like object (System.Object) with dynamic semantics associated. Anything can be assigned to a dynamic. dynamic x = 1; dynamic y = "Hello"; dynamic z = new List<int> { 1, 2, 3 }; At run-time, all object will have a type. In the above example x is of type System.Int32. When one or more operands in an operation are typed dynamic, member selection is deferred to run-time instead of compile-time. Then the run-time type is substituted in all variables and normal overload resolution is done, just like it would happen at compile-time. The result of any dynamic operation is always dynamic and, when a dynamic object is assigned to something else, a dynamic conversion will occur. Code Resolution Method double x = 1.75; double y = Math.Abs(x); compile-time double Abs(double x) dynamic x = 1.75; dynamic y = Math.Abs(x); run-time double Abs(double x) dynamic x = 2; dynamic y = Math.Abs(x); run-time int Abs(int x) The above code will always be strongly typed. The difference is that, in the first case the method resolution is done at compile-time, and the others it’s done ate run-time. IDynamicMetaObjectObject The DLR is pre-wired to know .NET objects, COM objects and so forth but any dynamic language can implement their own objects or you can implement your own objects in C# through the implementation of the IDynamicMetaObjectProvider interface. When an object implements IDynamicMetaObjectProvider, it can participate in the resolution of how method calls and property access is done. The .NET Framework already provides two implementations of IDynamicMetaObjectProvider: DynamicObject : IDynamicMetaObjectProvider The DynamicObject class enables you to define which operations can be performed on dynamic objects and how to perform those operations. For example, you can define what happens when you try to get or set an object property, call a method, or perform standard mathematical operations such as addition and multiplication. ExpandoObject : IDynamicMetaObjectProvider The ExpandoObject class enables you to add and delete members of its instances at run time and also to set and get values of these members. This class supports dynamic binding, which enables you to use standard syntax like sampleObject.sampleMember, instead of more complex syntax like sampleObject.GetAttribute("sampleMember").

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  • SQL Server and Hyper-V Dynamic Memory Part 2

    - by SQLOS Team
    Part 1 of this series was an introduction and overview of Hyper-V Dynamic Memory. This part looks at SQL Server memory management and how the SQL engine responds to changing OS memory conditions.   Part 2: SQL Server Memory Management As with any Windows process, sqlserver.exe has a virtual address space (VAS) of 4GB on 32-bit and 8TB in 64-bit editions. Pages in its VAS are mapped to pages in physical memory when the memory is committed and referenced for the first time. The collection of VAS pages that have been recently referenced is known as the Working Set. How and when SQL Server allocates virtual memory and grows its working set depends on the memory model it uses. SQL Server supports three basic memory models:   1. Conventional Memory Model   The Conventional model is the default SQL Server memory model and has the following properties: - Dynamic - can grow or shrink its working set in response to load and external (operating system) memory conditions. - OS uses 4K pages – (not to be confused with SQL Server “pages” which are 8K regions of committed memory).- Pageable - Can be paged out to disk by the operating system.   2. Locked Page Model The locked page memory model is set when SQL Server is started with "Lock Pages in Memory" privilege*. It has the following characteristics: - Dynamic - can grow or shrink its working set in the same way as the Conventional model.- OS uses 4K pages - Non-Pageable – When memory is committed it is locked in memory, meaning that it will remain backed by physical memory and will not be paged out by the operating system. A common misconception is to interpret "locked" as non-dynamic. A SQL Server instance using the locked page memory model will grow and shrink (allocate memory and release memory) in response to changing workload and OS memory conditions in the same way as it does with the conventional model.   This is an important consideration when we look at Hyper-V Dynamic Memory – “locked” memory works perfectly well with “dynamic” memory.   * Note in “Denali” (Standard Edition and above), and in SQL 2008 R2 64-bit (Enterprise and above editions) the Lock Pages in Memory privilege is all that is required to set this model. In 2008 R2 64-Bit standard edition it also requires trace flag 845 to be set, in 2008 R2 32-bit editions it requires sp_configure 'awe enabled' 1.   3. Large Page Model The Large page model is set using trace flag 834 and potentially offers a small performance boost for systems that are configured with large pages. It is characterized by: - Static - memory is allocated at startup and does not change. - OS uses large (>2MB) pages - Non-Pageable The large page model is supported with Hyper-V Dynamic Memory (and Hyper-V also supports large pages), but you get no benefit from using Dynamic Memory with this model since SQL Server memory does not grow or shrink. The rest of this article will focus on the locked and conventional SQL Server memory models.   When does SQL Server grow? For “dynamic” configurations (Conventional and Locked memory models), the sqlservr.exe process grows – allocates and commits memory from the OS – in response to a workload. As much memory is allocated as is required to optimally run the query and buffer data for future queries, subject to limitations imposed by:   - SQL Server max server memory setting. If this configuration option is set, the buffer pool is not allowed to grow to more than this value. In SQL Server 2008 this value represents single page allocations, and in “Denali” it represents any size page allocations and also managed CLR procedure allocations.   - Memory signals from OS. The operating system sets a signal on memory resource notification objects to indicate whether it has memory available or whether it is low on available memory. If there is only 32MB free for every 4GB of memory a low memory signal is set, which continues until 64MB/4GB is free. If there is 96MB/4GB free the operating system sets a high memory signal. SQL Server only allocates memory when the high memory signal is set.   To summarize, for SQL Server to grow you need three conditions: a workload, max server memory setting higher than the current allocation, high memory signals from the OS.    When does SQL Server shrink caches? SQL Server as a rule does not like to return memory to the OS, but it will shrink its caches in response to memory pressure. Memory pressure can be divided into “internal” and “external”.   - External memory pressure occurs when the operating system is running low on memory and low memory signals are set. The SQL Server Resource Monitor checks for low memory signals approximately every 5 seconds and it will attempt to free memory until the signals stop.   To free memory SQL Server does the following: ·         Frees unused memory. ·         Notifies Memory Manager Clients to release memory o   Caches – Free unreferenced cache objects. o   Buffer pool - Based on oldest access times.   The freed memory is released back to the operating system. This process continues until the low memory resource notifications stop.    - Internal memory pressure occurs when the size of different caches and allocations increase but the SQL Server process needs to keep its total memory within a target value. For example if max server memory is set and certain caches are growing large, it will cause SQL to free memory for re-use internally, but not to release memory back to the OS. If you lower the value of max server memory you will generate internal memory pressure that will cause SQL to release memory back to the OS.    Memory pressure handling has not changed much since SQL 2005 and it was described in detail in a blog post by Slava Oks.   Note that SQL Server Express is an exception to the above behavior. Unlike other editions it does not assume it is the most important process running on the system but tries to be more “desktop” friendly. It will empty its working set after a period of inactivity.   How does SQL Server respond to changing OS memory?    In SQL Server 2005 support for Hot-Add memory was introduced. This feature, available in Enterprise and above editions, allows the server to make use of any extra physical memory that was added after SQL Server started. Being able to add physical memory when the system is running is limited to specialized hardware, but with the Hyper-V Dynamic Memory feature, when new memory is allocated to a guest virtual machine, it looks like hot-add physical memory to the guest. What this means is that thanks to the hot-add memory feature, SQL Server 2005 and higher can dynamically grow if more “physical” memory is granted to a guest VM by Hyper-V dynamic memory.   SQL Server checks OS memory every second and dynamically adjusts its “target” (based on available OS memory and max server memory) accordingly.   In “Denali” Standard Edition will also have sqlserver.exe support for hot-add memory when running virtualized (i.e. detecting and acting on Hyper-V Dynamic Memory allocations).   How does a SQL Server workload in a guest VM impact Hyper-V dynamic memory scheduling?   When a SQL workload causes the sqlserver.exe process to grow its working set, the Hyper-V memory scheduler will detect memory pressure in the guest VM and add memory to it. SQL Server will then detect the extra memory and grow according to workload demand. In our tests we have seen this feedback process cause a guest VM to grow quickly in response to SQL workload - we are still working on characterizing this ramp-up.    How does SQL Server respond when Hyper-V removes memory from a guest VM through ballooning?   If pressure from other VM's cause Hyper-V Dynamic Memory to take memory away from a VM through ballooning (allocating memory with a virtual device driver and returning it to the host OS), Windows Memory Manager will page out unlocked portions of memory and signal low resource notification events. When SQL Server detects these events it will shrink memory until the low memory notifications stop (see cache shrinking description above).    This raises another question. Can we make SQL Server release memory more readily and hence behave more "dynamically" without compromising performance? In certain circumstances where the application workload is predictable it may be possible to have a job which varies "max server memory" according to need, lowering it when the engine is inactive and raising it before a period of activity. This would have limited applicaability but it is something we're looking into.   What Memory Management changes are there in SQL Server “Denali”?   In SQL Server “Denali” (aka SQL11) the Memory Manager has been re-written to be more efficient. The main changes are summarized in this post. An important change with respect to Hyper-V Dynamic Memory support is that now the max server memory setting includes any size page allocations and managed CLR procedure allocations it now represents a closer approximation to total sqlserver.exe memory usage. This makes it easier to calculate a value for max server memory, which becomes important when configuring virtual machines to work well with Hyper-V Dynamic Memory Startup and Maximum RAM settings.   Another important change is no more AWE or hot-add support for 32-bit edition. This means if you're running a 32-bit edition of Denali you're limited to a 4GB address space and will not be able to take advantage of dynamically added OS memory that wasn't present when SQL Server started (though Hyper-V Dynamic Memory is still a supported configuration).   In part 3 we’ll develop some best practices for configuring and using SQL Server with Dynamic Memory. Originally posted at http://blogs.msdn.com/b/sqlosteam/

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  • Free Dynamic DNS Nameservers

    - by Maxim Zaslavsky
    I recently set up a home server that I want to use as my primary hosting platform. So far, I've mapped some domains to it by setting up A records for them that point to my home IP. As my home IP can change randomly and without notice, however, I'm afraid of such downtime. Thus, I'm looking for a dynamic DNS solution. So far, I've set up DynDNS, but I haven't found a way to use dynamic DNS with an existing domain. Are there any free dynamic DNS nameserver services available?

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  • Using JSON.NET for dynamic JSON parsing

    - by Rick Strahl
    With the release of ASP.NET Web API as part of .NET 4.5 and MVC 4.0, JSON.NET has effectively pushed out the .NET native serializers to become the default serializer for Web API. JSON.NET is vastly more flexible than the built in DataContractJsonSerializer or the older JavaScript serializer. The DataContractSerializer in particular has been very problematic in the past because it can't deal with untyped objects for serialization - like values of type object, or anonymous types which are quite common these days. The JavaScript Serializer that came before it actually does support non-typed objects for serialization but it can't do anything with untyped data coming in from JavaScript and it's overall model of extensibility was pretty limited (JavaScript Serializer is what MVC uses for JSON responses). JSON.NET provides a robust JSON serializer that has both high level and low level components, supports binary JSON, JSON contracts, Xml to JSON conversion, LINQ to JSON and many, many more features than either of the built in serializers. ASP.NET Web API now uses JSON.NET as its default serializer and is now pulled in as a NuGet dependency into Web API projects, which is great. Dynamic JSON Parsing One of the features that I think is getting ever more important is the ability to serialize and deserialize arbitrary JSON content dynamically - that is without mapping the JSON captured directly into a .NET type as DataContractSerializer or the JavaScript Serializers do. Sometimes it isn't possible to map types due to the differences in languages (think collections, dictionaries etc), and other times you simply don't have the structures in place or don't want to create them to actually import the data. If this topic sounds familiar - you're right! I wrote about dynamic JSON parsing a few months back before JSON.NET was added to Web API and when Web API and the System.Net HttpClient libraries included the System.Json classes like JsonObject and JsonArray. With the inclusion of JSON.NET in Web API these classes are now obsolete and didn't ship with Web API or the client libraries. I re-linked my original post to this one. In this post I'll discus JToken, JObject and JArray which are the dynamic JSON objects that make it very easy to create and retrieve JSON content on the fly without underlying types. Why Dynamic JSON? So, why Dynamic JSON parsing rather than strongly typed parsing? Since applications are interacting more and more with third party services it becomes ever more important to have easy access to those services with easy JSON parsing. Sometimes it just makes lot of sense to pull just a small amount of data out of large JSON document received from a service, because the third party service isn't directly related to your application's logic most of the time - and it makes little sense to map the entire service structure in your application. For example, recently I worked with the Google Maps Places API to return information about businesses close to me (or rather the app's) location. The Google API returns a ton of information that my application had no interest in - all I needed was few values out of the data. Dynamic JSON parsing makes it possible to map this data, without having to map the entire API to a C# data structure. Instead I could pull out the three or four values I needed from the API and directly store it on my business entities that needed to receive the data - no need to map the entire Maps API structure. Getting JSON.NET The easiest way to use JSON.NET is to grab it via NuGet and add it as a reference to your project. You can add it to your project with: PM> Install-Package Newtonsoft.Json From the Package Manager Console or by using Manage NuGet Packages in your project References. As mentioned if you're using ASP.NET Web API or MVC 4 JSON.NET will be automatically added to your project. Alternately you can also go to the CodePlex site and download the latest version including source code: http://json.codeplex.com/ Creating JSON on the fly with JObject and JArray Let's start with creating some JSON on the fly. It's super easy to create a dynamic object structure with any of the JToken derived JSON.NET objects. The most common JToken derived classes you are likely to use are JObject and JArray. JToken implements IDynamicMetaProvider and so uses the dynamic  keyword extensively to make it intuitive to create object structures and turn them into JSON via dynamic object syntax. Here's an example of creating a music album structure with child songs using JObject for the base object and songs and JArray for the actual collection of songs:[TestMethod] public void JObjectOutputTest() { // strong typed instance var jsonObject = new JObject(); // you can explicitly add values here using class interface jsonObject.Add("Entered", DateTime.Now); // or cast to dynamic to dynamically add/read properties dynamic album = jsonObject; album.AlbumName = "Dirty Deeds Done Dirt Cheap"; album.Artist = "AC/DC"; album.YearReleased = 1976; album.Songs = new JArray() as dynamic; dynamic song = new JObject(); song.SongName = "Dirty Deeds Done Dirt Cheap"; song.SongLength = "4:11"; album.Songs.Add(song); song = new JObject(); song.SongName = "Love at First Feel"; song.SongLength = "3:10"; album.Songs.Add(song); Console.WriteLine(album.ToString()); } This produces a complete JSON structure: { "Entered": "2012-08-18T13:26:37.7137482-10:00", "AlbumName": "Dirty Deeds Done Dirt Cheap", "Artist": "AC/DC", "YearReleased": 1976, "Songs": [ { "SongName": "Dirty Deeds Done Dirt Cheap", "SongLength": "4:11" }, { "SongName": "Love at First Feel", "SongLength": "3:10" } ] } Notice that JSON.NET does a nice job formatting the JSON, so it's easy to read and paste into blog posts :-). JSON.NET includes a bunch of configuration options that control how JSON is generated. Typically the defaults are just fine, but you can override with the JsonSettings object for most operations. The important thing about this code is that there's no explicit type used for holding the values to serialize to JSON. Rather the JSON.NET objects are the containers that receive the data as I build up my JSON structure dynamically, simply by adding properties. This means this code can be entirely driven at runtime without compile time restraints of structure for the JSON output. Here I use JObject to create a album 'object' and immediately cast it to dynamic. JObject() is kind of similar in behavior to ExpandoObject in that it allows you to add properties by simply assigning to them. Internally, JObject values are stored in pseudo collections of key value pairs that are exposed as properties through the IDynamicMetaObject interface exposed in JSON.NET's JToken base class. For objects the syntax is very clean - you add simple typed values as properties. For objects and arrays you have to explicitly create new JObject or JArray, cast them to dynamic and then add properties and items to them. Always remember though these values are dynamic - which means no Intellisense and no compiler type checking. It's up to you to ensure that the names and values you create are accessed consistently and without typos in your code. Note that you can also access the JObject instance directly (not as dynamic) and get access to the underlying JObject type. This means you can assign properties by string, which can be useful for fully data driven JSON generation from other structures. Below you can see both styles of access next to each other:// strong type instance var jsonObject = new JObject(); // you can explicitly add values here jsonObject.Add("Entered", DateTime.Now); // expando style instance you can just 'use' properties dynamic album = jsonObject; album.AlbumName = "Dirty Deeds Done Dirt Cheap"; JContainer (the base class for JObject and JArray) is a collection so you can also iterate over the properties at runtime easily:foreach (var item in jsonObject) { Console.WriteLine(item.Key + " " + item.Value.ToString()); } The functionality of the JSON objects are very similar to .NET's ExpandObject and if you used it before, you're already familiar with how the dynamic interfaces to the JSON objects works. Importing JSON with JObject.Parse() and JArray.Parse() The JValue structure supports importing JSON via the Parse() and Load() methods which can read JSON data from a string or various streams respectively. Essentially JValue includes the core JSON parsing to turn a JSON string into a collection of JsonValue objects that can be then referenced using familiar dynamic object syntax. Here's a simple example:public void JValueParsingTest() { var jsonString = @"{""Name"":""Rick"",""Company"":""West Wind"", ""Entered"":""2012-03-16T00:03:33.245-10:00""}"; dynamic json = JValue.Parse(jsonString); // values require casting string name = json.Name; string company = json.Company; DateTime entered = json.Entered; Assert.AreEqual(name, "Rick"); Assert.AreEqual(company, "West Wind"); } The JSON string represents an object with three properties which is parsed into a JObject class and cast to dynamic. Once cast to dynamic I can then go ahead and access the object using familiar object syntax. Note that the actual values - json.Name, json.Company, json.Entered - are actually of type JToken and I have to cast them to their appropriate types first before I can do type comparisons as in the Asserts at the end of the test method. This is required because of the way that dynamic types work which can't determine the type based on the method signature of the Assert.AreEqual(object,object) method. I have to either assign the dynamic value to a variable as I did above, or explicitly cast ( (string) json.Name) in the actual method call. The JSON structure can be much more complex than this simple example. Here's another example of an array of albums serialized to JSON and then parsed through with JsonValue():[TestMethod] public void JsonArrayParsingTest() { var jsonString = @"[ { ""Id"": ""b3ec4e5c"", ""AlbumName"": ""Dirty Deeds Done Dirt Cheap"", ""Artist"": ""AC/DC"", ""YearReleased"": 1976, ""Entered"": ""2012-03-16T00:13:12.2810521-10:00"", ""AlbumImageUrl"": ""http://ecx.images-amazon.com/images/I/61kTaH-uZBL._AA115_.jpg"", ""AmazonUrl"": ""http://www.amazon.com/gp/product/…ASIN=B00008BXJ4"", ""Songs"": [ { ""AlbumId"": ""b3ec4e5c"", ""SongName"": ""Dirty Deeds Done Dirt Cheap"", ""SongLength"": ""4:11"" }, { ""AlbumId"": ""b3ec4e5c"", ""SongName"": ""Love at First Feel"", ""SongLength"": ""3:10"" }, { ""AlbumId"": ""b3ec4e5c"", ""SongName"": ""Big Balls"", ""SongLength"": ""2:38"" } ] }, { ""Id"": ""7b919432"", ""AlbumName"": ""End of the Silence"", ""Artist"": ""Henry Rollins Band"", ""YearReleased"": 1992, ""Entered"": ""2012-03-16T00:13:12.2800521-10:00"", ""AlbumImageUrl"": ""http://ecx.images-amazon.com/images/I/51FO3rb1tuL._SL160_AA160_.jpg"", ""AmazonUrl"": ""http://www.amazon.com/End-Silence-Rollins-Band/dp/B0000040OX/ref=sr_1_5?ie=UTF8&qid=1302232195&sr=8-5"", ""Songs"": [ { ""AlbumId"": ""7b919432"", ""SongName"": ""Low Self Opinion"", ""SongLength"": ""5:24"" }, { ""AlbumId"": ""7b919432"", ""SongName"": ""Grip"", ""SongLength"": ""4:51"" } ] } ]"; JArray jsonVal = JArray.Parse(jsonString) as JArray; dynamic albums = jsonVal; foreach (dynamic album in albums) { Console.WriteLine(album.AlbumName + " (" + album.YearReleased.ToString() + ")"); foreach (dynamic song in album.Songs) { Console.WriteLine("\t" + song.SongName); } } Console.WriteLine(albums[0].AlbumName); Console.WriteLine(albums[0].Songs[1].SongName); } JObject and JArray in ASP.NET Web API Of course these types also work in ASP.NET Web API controller methods. If you want you can accept parameters using these object or return them back to the server. The following contrived example receives dynamic JSON input, and then creates a new dynamic JSON object and returns it based on data from the first:[HttpPost] public JObject PostAlbumJObject(JObject jAlbum) { // dynamic input from inbound JSON dynamic album = jAlbum; // create a new JSON object to write out dynamic newAlbum = new JObject(); // Create properties on the new instance // with values from the first newAlbum.AlbumName = album.AlbumName + " New"; newAlbum.NewProperty = "something new"; newAlbum.Songs = new JArray(); foreach (dynamic song in album.Songs) { song.SongName = song.SongName + " New"; newAlbum.Songs.Add(song); } return newAlbum; } The raw POST request to the server looks something like this: POST http://localhost/aspnetwebapi/samples/PostAlbumJObject HTTP/1.1User-Agent: FiddlerContent-type: application/jsonHost: localhostContent-Length: 88 {AlbumName: "Dirty Deeds",Songs:[ { SongName: "Problem Child"},{ SongName: "Squealer"}]} and the output that comes back looks like this: {  "AlbumName": "Dirty Deeds New",  "NewProperty": "something new",  "Songs": [    {      "SongName": "Problem Child New"    },    {      "SongName": "Squealer New"    }  ]} The original values are echoed back with something extra appended to demonstrate that we're working with a new object. When you receive or return a JObject, JValue, JToken or JArray instance in a Web API method, Web API ignores normal content negotiation and assumes your content is going to be received and returned as JSON, so effectively the parameter and result type explicitly determines the input and output format which is nice. Dynamic to Strong Type Mapping You can also map JObject and JArray instances to a strongly typed object, so you can mix dynamic and static typing in the same piece of code. Using the 2 Album jsonString shown earlier, the code below takes an array of albums and picks out only a single album and casts that album to a static Album instance.[TestMethod] public void JsonParseToStrongTypeTest() { JArray albums = JArray.Parse(jsonString) as JArray; // pick out one album JObject jalbum = albums[0] as JObject; // Copy to a static Album instance Album album = jalbum.ToObject<Album>(); Assert.IsNotNull(album); Assert.AreEqual(album.AlbumName,jalbum.Value<string>("AlbumName")); Assert.IsTrue(album.Songs.Count > 0); } This is pretty damn useful for the scenario I mentioned earlier - you can read a large chunk of JSON and dynamically walk the property hierarchy down to the item you want to access, and then either access the specific item dynamically (as shown earlier) or map a part of the JSON to a strongly typed object. That's very powerful if you think about it - it leaves you in total control to decide what's dynamic and what's static. Strongly typed JSON Parsing With all this talk of dynamic let's not forget that JSON.NET of course also does strongly typed serialization which is drop dead easy. Here's a simple example on how to serialize and deserialize an object with JSON.NET:[TestMethod] public void StronglyTypedSerializationTest() { // Demonstrate deserialization from a raw string var album = new Album() { AlbumName = "Dirty Deeds Done Dirt Cheap", Artist = "AC/DC", Entered = DateTime.Now, YearReleased = 1976, Songs = new List<Song>() { new Song() { SongName = "Dirty Deeds Done Dirt Cheap", SongLength = "4:11" }, new Song() { SongName = "Love at First Feel", SongLength = "3:10" } } }; // serialize to string string json2 = JsonConvert.SerializeObject(album,Formatting.Indented); Console.WriteLine(json2); // make sure we can serialize back var album2 = JsonConvert.DeserializeObject<Album>(json2); Assert.IsNotNull(album2); Assert.IsTrue(album2.AlbumName == "Dirty Deeds Done Dirt Cheap"); Assert.IsTrue(album2.Songs.Count == 2); } JsonConvert is a high level static class that wraps lower level functionality, but you can also use the JsonSerializer class, which allows you to serialize/parse to and from streams. It's a little more work, but gives you a bit more control. The functionality available is easy to discover with Intellisense, and that's good because there's not a lot in the way of documentation that's actually useful. Summary JSON.NET is a pretty complete JSON implementation with lots of different choices for JSON parsing from dynamic parsing to static serialization, to complex querying of JSON objects using LINQ. It's good to see this open source library getting integrated into .NET, and pushing out the old and tired stock .NET parsers so that we finally have a bit more flexibility - and extensibility - in our JSON parsing. Good to go! Resources Sample Test Project http://json.codeplex.com/© Rick Strahl, West Wind Technologies, 2005-2012Posted in .NET  Web Api  AJAX   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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  • SQL SERVER – Wait Stats – Wait Types – Wait Queues – Day 0 of 28

    - by pinaldave
    This blog post will have running account of the all the blog post I will be doing in this month related to SQL Server Wait Types and Wait Queues. SQL SERVER – Introduction to Wait Stats and Wait Types – Wait Type – Day 1 of 28 SQL SERVER – Signal Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28 SQL SERVER – DMV – sys.dm_os_wait_stats Explanation – Wait Type – Day 3 of 28 SQL SERVER – DMV – sys.dm_os_waiting_tasks and sys.dm_exec_requests – Wait Type – Day 4 of 28 SQL SERVER – Capturing Wait Types and Wait Stats Information at Interval – Wait Type – Day 5 of 28 SQL SERVER – CXPACKET – Parallelism – Usual Solution – Wait Type – Day 6 of 28 SQL SERVER – CXPACKET – Parallelism – Advanced Solution – Wait Type – Day 7 of 28 SQL SERVER – SOS_SCHEDULER_YIELD – Wait Type – Day 8 of 28 SQL SERVER – PAGEIOLATCH_DT, PAGEIOLATCH_EX, PAGEIOLATCH_KP, PAGEIOLATCH_SH, PAGEIOLATCH_UP – Wait Type – Day 9 of 28 SQL SERVER – IO_COMPLETION – Wait Type – Day 10 of 28 SQL SERVER – ASYNC_IO_COMPLETION – Wait Type – Day 11 of 28 SQL SERVER – PAGELATCH_DT, PAGELATCH_EX, PAGELATCH_KP, PAGELATCH_SH, PAGELATCH_UP – Wait Type – Day 12 of 28 SQL SERVER – FT_IFTS_SCHEDULER_IDLE_WAIT – Full Text – Wait Type – Day 13 of 28 SQL SERVER – BACKUPIO, BACKUPBUFFER – Wait Type – Day 14 of 28 SQL SERVER – LCK_M_XXX – Wait Type – Day 15 of 28 Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – Wait Stats – Wait Types – Wait Queues – Day 0 of 28

    - by pinaldave
    This blog post will have running account of the all the blog post I will be doing in this month related to SQL Server Wait Types and Wait Queues. SQL SERVER – Introduction to Wait Stats and Wait Types – Wait Type – Day 1 of 28 SQL SERVER – Single Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28 Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – Guest Post – Jacob Sebastian – Filestream – Wait Types – Wait Queues – Day 22 of 28

    - by pinaldave
    Jacob Sebastian is a SQL Server MVP, Author, Speaker and Trainer. Jacob is one of the top rated expert community. Jacob wrote the book The Art of XSD – SQL Server XML Schema Collections and wrote the XML Chapter in SQL Server 2008 Bible. See his Blog | Profile. He is currently researching on the subject of Filestream and have submitted this interesting article on the very subject. What is FILESTREAM? FILESTREAM is a new feature introduced in SQL Server 2008 which provides an efficient storage and management option for BLOB data. Many applications that deal with BLOB data today stores them in the file system and stores the path to the file in the relational tables. Storing BLOB data in the file system is more efficient that storing them in the database. However, this brings up a few disadvantages as well. When the BLOB data is stored in the file system, it is hard to ensure transactional consistency between the file system data and relational data. Some applications store the BLOB data within the database to overcome the limitations mentioned earlier. This approach ensures transactional consistency between the relational data and BLOB data, but is very bad in terms of performance. FILESTREAM combines the benefits of both approaches mentioned above without the disadvantages we examined. FILESTREAM stores the BLOB data in the file system (thus takes advantage of the IO Streaming capabilities of NTFS) and ensures transactional consistency between the BLOB data in the file system and the relational data in the database. For more information on the FILESTREAM feature, visit: http://beyondrelational.com/filestream/default.aspx FILESTREAM Wait Types Since this series is on the different SQL Server wait types, let us take a look at the various wait types that are related to the FILESTREAM feature. FS_FC_RWLOCK This wait type is generated by FILESTREAM Garbage Collector. This occurs when Garbage collection is disabled prior to a backup/restore operation or when a garbage collection cycle is being executed. FS_GARBAGE_COLLECTOR_SHUTDOWN This wait type occurs when during the cleanup process of a garbage collection cycle. It indicates that that garbage collector is waiting for the cleanup tasks to be completed. FS_HEADER_RWLOCK This wait type indicates that the process is waiting for obtaining access to the FILESTREAM header file for read or write operation. The FILESTREAM header is a disk file located in the FILESTREAM data container and is named “filestream.hdr”. FS_LOGTRUNC_RWLOCK This wait type indicates that the process is trying to perform a FILESTREAM log truncation related operation. It can be either a log truncate operation or to disable log truncation prior to a backup or restore operation. FSA_FORCE_OWN_XACT This wait type occurs when a FILESTREAM file I/O operation needs to bind to the associated transaction, but the transaction is currently owned by another session. FSAGENT This wait type occurs when a FILESTREAM file I/O operation is waiting for a FILESTREAM agent resource that is being used by another file I/O operation. FSTR_CONFIG_MUTEX This wait type occurs when there is a wait for another FILESTREAM feature reconfiguration to be completed. FSTR_CONFIG_RWLOCK This wait type occurs when there is a wait to serialize access to the FILESTREAM configuration parameters. Waits and Performance System waits has got a direct relationship with the overall performance. In most cases, when waits increase the performance degrades. SQL Server documentation does not say much about how we can reduce these waits. However, following the FILESTREAM best practices will help you to improve the overall performance and reduce the wait types to a good extend. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology Tagged: Filestream

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  • SQLAuthority News – Online Webcast How to Identify Resource Bottlenecks – Wait Types and Queues

    - by pinaldave
    As all of you know I have been working a recently on the subject SQL Server Wait Statistics, the reason is since I have published book on this subject SQL Wait Stats Joes 2 Pros: SQL Performance Tuning Techniques Using Wait Statistics, Types & Queues [Amazon] | [Flipkart] | [Kindle], lots of question and answers I am encountering. When I was writing the book, I kept version 1 of the book in front of me. I wanted to write something which one can use right away. I wanted to create an primer for everybody who have not explored wait stats method of performance tuning. Well, the books have been very well received and in fact we ran out of huge stock 2 times in India so far and once in USA during SQLPASS. I have received so many questions on this subject that I feel I can write one more book of the same size. I have been asked if I can create videos which can go along with this book. Personally I am working with SQL Server 2012 CTP3 and there are so many new wait types, I feel the subject of wait stats is going to be very very crucial in next version of SQL Server. If you have not started learning about this subject, I suggest you at least start exploring this right now. Learn how to begin on this subject atleast as when the next version comes in, you know how to read DMVs. I will be presenting on the same subject of performance tuning by wait stats in webcast embarcadero SQL Server Community Webinar. Here are few topics which we will be covering during the webinar. Beginning with SQL Wait Stats Understanding various aspect of SQL Wait Stats Understanding Query Life Cycle Identifying three TOP wait Stats Resolution of the common 3 wait types and queues Details of the webcast: How to Identify Resource Bottlenecks – Wait Types and Queues Date and Time: Wednesday, November 2, 11:00 AM PDT Registration Link I thank embarcadero for organizing opportunity for me to share my experience on subject of wait stats and connecting me with community to further take this subject to next level. One more interesting thing, I will ask one question at the end of the webinar and I will be giving away 5 copy of my SQL Wait Stats print book to first five correct answers. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: About Me, Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Web server behind MikroTik and dynamic dns

    - by danielrvt
    I recently purchased a MikroTik router, it works great! However, I haven't been able to make my web server work from outside my lan I'll explain better: I have two domains in my disposal, before I switched to Mikrotik, the were working perfectly and all my websites were online. Since I changed the router, every time I try to access my websites from outside my lan, my websites can't be found. I have my websites domains associated with a dynamic dns provider, I managed to create a port forwarding rule to redirect all my incoming traffic from port 80 to my web server, and it works, but only when I'm connected to my MikroTik router. Is there something else I have to do? PD: I also created a static dns rule in my router with my domains to associate it to my webserver (which is behind my router) PD2: All I want is to redirect requests from outside to my webserver...

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  • How do I serve dynamic WebDAV directory listings using Apache

    - by Jack Douglas
    I can use mod_rewrite to redirect /dynamic.php/xyz.php to /dynamic.php and then server different content for xyz.php using $_SERVER - where xyz.php is any arbitrary filename requested by a client. No problem so far. When a client connects to my WebDAV server they can list the contents of a directory, eg / or /dynamic.php/ - how do I intercept this request so I can dynamically generate a list of available files for the client (which requests this list using PROPFIND)?

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  • What functionality does dynamic typing allow?

    - by Justin984
    I've been using python for a few days now and I think I understand the difference between dynamic and static typing. What I don't understand is under what circumstances it would be preferred. It is flexible and readable, but at the expense of more runtime checks and additional required unit testing. Aside from non-functional criteria like flexibility and readability, what reasons are there to choose dynamic typing? What can I do with dynamic typing that isn't possible otherwise? What specific code example can you think of that illustrates a concrete advantage of dynamic typing?

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  • SQL SERVER – Introduction to Wait Stats and Wait Types – Wait Type – Day 1 of 28

    - by pinaldave
    I have been working a lot on Wait Stats and Wait Types recently. Last Year, I requested blog readers to send me their respective server’s wait stats. I appreciate their kind response as I have received  Wait stats from my readers. I took each of the results and carefully analyzed them. I provided necessary feedback to the person who sent me his wait stats and wait types. Based on the feedbacks I got, many of the readers have tuned their server. After a while I got further feedbacks on my recommendations and again, I collected wait stats. I recorded the wait stats and my recommendations and did further research. At some point at time, there were more than 10 different round trips of the recommendations and suggestions. Finally, after six month of working my hands on performance tuning, I have collected some real world wisdom because of this. Now I plan to share my findings with all of you over here. Before anything else, please note that all of these are based on my personal observations and opinions. They may or may not match the theory available at other places. Some of the suggestions may not match your situation. Remember, every server is different and consequently, there is more than one solution to a particular problem. However, this series is written with kept wait stats in mind. While I was working on various performance tuning consultations, I did many more things than just tuning wait stats. Today we will discuss how to capture the wait stats. I use the script diagnostic script created by my friend and SQL Server Expert Glenn Berry to collect wait stats. Here is the script to collect the wait stats: -- Isolate top waits for server instance since last restart or statistics clear WITH Waits AS (SELECT wait_type, wait_time_ms / 1000. AS wait_time_s, 100. * wait_time_ms / SUM(wait_time_ms) OVER() AS pct, ROW_NUMBER() OVER(ORDER BY wait_time_ms DESC) AS rn FROM sys.dm_os_wait_stats WHERE wait_type NOT IN ('CLR_SEMAPHORE','LAZYWRITER_SLEEP','RESOURCE_QUEUE','SLEEP_TASK' ,'SLEEP_SYSTEMTASK','SQLTRACE_BUFFER_FLUSH','WAITFOR', 'LOGMGR_QUEUE','CHECKPOINT_QUEUE' ,'REQUEST_FOR_DEADLOCK_SEARCH','XE_TIMER_EVENT','BROKER_TO_FLUSH','BROKER_TASK_STOP','CLR_MANUAL_EVENT' ,'CLR_AUTO_EVENT','DISPATCHER_QUEUE_SEMAPHORE', 'FT_IFTS_SCHEDULER_IDLE_WAIT' ,'XE_DISPATCHER_WAIT', 'XE_DISPATCHER_JOIN', 'SQLTRACE_INCREMENTAL_FLUSH_SLEEP')) SELECT W1.wait_type, CAST(W1.wait_time_s AS DECIMAL(12, 2)) AS wait_time_s, CAST(W1.pct AS DECIMAL(12, 2)) AS pct, CAST(SUM(W2.pct) AS DECIMAL(12, 2)) AS running_pct FROM Waits AS W1 INNER JOIN Waits AS W2 ON W2.rn <= W1.rn GROUP BY W1.rn, W1.wait_type, W1.wait_time_s, W1.pct HAVING SUM(W2.pct) - W1.pct < 99 OPTION (RECOMPILE); -- percentage threshold GO This script uses Dynamic Management View sys.dm_os_wait_stats to collect the wait stats. It omits the system-related wait stats which are not useful to diagnose performance-related bottleneck. Additionally, not OPTION (RECOMPILE) at the end of the DMV will ensure that every time the query runs, it retrieves new data and not the cached data. This dynamic management view collects all the information since the time when the SQL Server services have been restarted. You can also manually clear the wait stats using the following command: DBCC SQLPERF('sys.dm_os_wait_stats', CLEAR); Once the wait stats are collected, we can start analysis them and try to see what is causing any particular wait stats to achieve higher percentages than the others. Many waits stats are related to one another. When the CPU pressure is high, all the CPU-related wait stats show up on top. But when that is fixed, all the wait stats related to the CPU start showing reasonable percentages. It is difficult to have a sure solution, but there are good indications and good suggestions on how to solve this. I will keep this blog post updated as I will post more details about wait stats and how I reduce them. The reference to Book On Line is over here. Of course, I have selected February to run this Wait Stats series. I am already cheating by having the smallest month to run this series. :) Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: DMV, Pinal Dave, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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