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  • Making a grid on iPhone using Opengl

    - by TheGambler
    I'm trying to make a grid similar to what you would see in these geo games(geoDefense/geometry wars). I'm wanting to apply separate transformation matrixes to each to create different effects. So, it makes since to me that I need to draw each square separately to that I can apply a different transformation to each one. The problem I'm having is mapping these grids out or connecting the squares. The coordinate systems is still confusing to me. I know it would be easy just to create a huge triangle strip but I'm not able to figure out a way to apply separate transformations to each square( quad ) if I use triangle strips. So first question: Can you apply different transformations to quads if you use a triangle strip to draw a huge grid? If so, any tips suggestions on how to do so? If not, how does one usually connect textures without using triangle strips? Here is my coord setup: const GLfloat zNear = 0.01, zFar = 1000.0, fieldOfView = 45.0; GLfloat size; glEnable(GL_DEPTH_TEST); glMatrixMode(GL_PROJECTION); size = zNear * tanf(DEGREES_TO_RADIANS(fieldOfView) / 2.0); CGRect rect = view.bounds; glFrustumf(-size, size, -size / (rect.size.width / rect.size.height), size / (rect.size.width / rect.size.height), zNear, zFar); glViewport(0, 0, rect.size.width, rect.size.height); Here is my draw: - (void)drawView:(GLView*)view; { int loop; //glColor4f(1.0, 1.0, 1.0, 0.5); glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT); //Grid Loop for( loop = 0; loop < kNumberSectionsInGrid; loop++ ) { //glLoadIdentity(); static Matrix3D shearMatrix; Matrix3DSetShear(shearMatrix, 0.2, 0.2); static Matrix3D finalMatrix; //Matrix3DMultiply(temp2Matrix, shearMatrix, finalMatrix); glLoadMatrixf(shearMatrix); glTranslatef(-1.0f,(float)loop,-3.0f); glScalef(0.1, 0.1, 0.0); Vertex3D vertices[] = { {-1.0, 1.0, 0.5}, { 1.0, 1.0, 0.5}, { -1.0, -1.0, 0.5}, { 1.0, -1.0, 0.5} }; static const Vector3D normals[] = { {0.0, 0.0, 1.0}, {0.0, 0.0, 1.0}, {0.0, 0.0, 1.0}, {0.0, 0.0, 1.0}, }; GLfloat texCoords[] = { 0.0, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0 }; glEnableClientState(GL_VERTEX_ARRAY); glEnableClientState(GL_NORMAL_ARRAY); glEnableClientState(GL_TEXTURE_COORD_ARRAY); glBindTexture(GL_TEXTURE_2D, texture[0]); glVertexPointer(3, GL_FLOAT, 0, vertices); glNormalPointer(GL_FLOAT, 0, normals); glTexCoordPointer(2, GL_FLOAT, 0, texCoords); glDrawArrays(GL_TRIANGLE_STRIP, 0, 4); glDisableClientState(GL_VERTEX_ARRAY); glDisableClientState(GL_NORMAL_ARRAY); glDisableClientState(GL_TEXTURE_COORD_ARRAY); } } glMatrixMode(GL_MODELVIEW);

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  • What is the best way to debug OpenGL?

    - by dreamlax
    I find that a lot of the time, OpenGL will show you it failed by not drawing anything. I'm trying to find ways to debug OpenGL programs, by inspecting the transformation matrix stack and so on. What is the best way to debug OpenGL? If the code looks and feels like the vertices are in the right place, how can you be sure they are?

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  • CSS Print Style Sheets - Examples

    - by bsreekanth
    Trying to learn about how to effectively use print.css, so that graphical and navigational elements are not shown in print preview/print. Read some articles, and part of print css of html5 boilerplate. Two sites, which was quite impressive the way they change the look during print are http://css-tricks.com/ http://bottlerocketcreative.com/ But I cannot see the css related to print. Can you please point to the css they use to learn how to do similar transformation. thanks.

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  • Generating text file from database

    - by Goldmember
    I have a requirement to hand-code an text file from data residing in a SQL table. Just wondering if there are any best practices here. Should I write it as an XMLDocument first and transform using XSL or just use Streamwriter and skip transformation altogether? The generated text file will be in EDIFACT format, so layout is very specific.

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  • How can I make XSLT work in chrome?

    - by Eric
    I have an XML document here that is served with a corresponding XSL file. The transformation is left to be executed client-side, without JavaScript. This works fine in IE (shock horror), but in Google Chrome, just displays the document's text nodes. I know that it is possible to do client-side XSL in Chrome, as I have seen examples of it, but I am yet to be able to replicate this success myself What am I doing wrong?

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  • How to merge 2 XML streams in Java by XSLT

    - by user327933
    I'd like to merge 2 XML streams (strings) in Java, necessarily by XSLT (that I could change the transformation), but the problem is that the XMLs come as a string. There are many examples, but through the files. Can this be done without saving them in files? Thanks.

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  • problem with XSLT

    - by sindhu
    Hi all, I am trying to create a html based template with xslt transformation.The string result returned by the transformer is perfectly fine.but when i try to send it to display, the browser is not interpreting it. The output looks like<html><body>...</body></html>. when i do view source it is displaying &lt;html&gt;... How can i resolve it?Please help. Thanks in advance

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  • How to apply a function to a collection of elements

    - by Cue
    Consider I have an array of elements out of which I want to create a new 'iterable' which on every next applies a custom 'transformation'. What's the proper way of doing it under python 2.x? For people familiar with Java, the equivalent is Iterables#transform from google's collections framework.

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  • catch output from linux telnet to a python script

    - by sandra
    Hello. My problem is that i want to do something like this in linux console telnet 192.168.255.28 process.py i.e i would like to do some transformation with console telnet output using python script. I'm see Popen in python for this case, but i can't understand how can i get input from telnet if it do not stop all time.. Pleas any ideas.

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  • Apply Xslt on in-memory Xml and returning in-memory Xml

    - by Jan Willem B
    I am looking for a static function in the .NET framework which takes an XML snippet and an Xslt file, applies the transformation in memory, and returns the transformed XML. I would like to do this: string rawXml = invoiceTemplateDoc.MainDocumentPart.Document.InnerXml; rawXml = DoXsltTransformation(rawXml, @"c:\prepare-invoice.xslt")); // ... do more manipulations on the rawXml Alternatively, instead of taking and returning strings, it could be taking and returning XmlNodes. Is there such a function?

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  • Naming a file downloaded from url in iPhone

    - by hgpc
    I would like to save a file downloaded from the internet in iPhone. Can I use the url as the file name? If not, what transformation should I apply to the url to obtain a valid file name? I need to find the local copy of the file later using its url.

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  • standard c library for escaping a string.

    - by rampion
    Is there a standard C library function to escape C-strings? For example, if I had the C string: char example[] = "first line\nsecond line: \"inner quotes\""; And I wanted to print "first line\nsecond line: \"inner quotes\"" Is there a library function that will do that transformation for me? Rolling my own just seems a little silly. Bonus points if I can give it a length to escape (so it stops before or beyond the \0).

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  • Writing an ostream filter?

    - by shoosh
    I'd like to write a simple ostream which wraps an argument ostream and changes the stream in some way before passing it on to the argument stream. The transformation is something simple like changing a letter or erasing a word What would a simple class inheriting from ostream look like? What methods should I override?

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  • Accessing Extension Objects

    - by LB
    I've added an object to the XsltArgumentList. I was wondering how I could access and display it in my transformation? xslarg.AddExtensionObject("someKey", "someValue"); However, when I transform, I wan't to be able to display "someValue". Any idea how? Thanks.

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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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  • Oracle Data Mining a Star Schema: Telco Churn Case Study

    - by charlie.berger
    There is a complete and detailed Telco Churn case study "How to" Blog Series just posted by Ari Mozes, ODM Dev. Manager.  In it, Ari provides detailed guidance in how to leverage various strengths of Oracle Data Mining including the ability to: mine Star Schemas and join tables and views together to obtain a complete 360 degree view of a customer combine transactional data e.g. call record detail (CDR) data, etc. define complex data transformation, model build and model deploy analytical methodologies inside the Database  His blog is posted in a multi-part series.  Below are some opening excerpts for the first 3 blog entries.  This is an excellent resource for any novice to skilled data miner who wants to gain competitive advantage by mining their data inside the Oracle Database.  Many thanks Ari! Mining a Star Schema: Telco Churn Case Study (1 of 3) One of the strengths of Oracle Data Mining is the ability to mine star schemas with minimal effort.  Star schemas are commonly used in relational databases, and they often contain rich data with interesting patterns.  While dimension tables may contain interesting demographics, fact tables will often contain user behavior, such as phone usage or purchase patterns.  Both of these aspects - demographics and usage patterns - can provide insight into behavior.Churn is a critical problem in the telecommunications industry, and companies go to great lengths to reduce the churn of their customer base.  One case study1 describes a telecommunications scenario involving understanding, and identification of, churn, where the underlying data is present in a star schema.  That case study is a good example for demonstrating just how natural it is for Oracle Data Mining to analyze a star schema, so it will be used as the basis for this series of posts...... Mining a Star Schema: Telco Churn Case Study (2 of 3) This post will follow the transformation steps as described in the case study, but will use Oracle SQL as the means for preparing data.  Please see the previous post for background material, including links to the case study and to scripts that can be used to replicate the stages in these posts.1) Handling missing values for call data recordsThe CDR_T table records the number of phone minutes used by a customer per month and per call type (tariff).  For example, the table may contain one record corresponding to the number of peak (call type) minutes in January for a specific customer, and another record associated with international calls in March for the same customer.  This table is likely to be fairly dense (most type-month combinations for a given customer will be present) due to the coarse level of aggregation, but there may be some missing values.  Missing entries may occur for a number of reasons: the customer made no calls of a particular type in a particular month, the customer switched providers during the timeframe, or perhaps there is a data entry problem.  In the first situation, the correct interpretation of a missing entry would be to assume that the number of minutes for the type-month combination is zero.  In the other situations, it is not appropriate to assume zero, but rather derive some representative value to replace the missing entries.  The referenced case study takes the latter approach.  The data is segmented by customer and call type, and within a given customer-call type combination, an average number of minutes is computed and used as a replacement value.In SQL, we need to generate additional rows for the missing entries and populate those rows with appropriate values.  To generate the missing rows, Oracle's partition outer join feature is a perfect fit.  select cust_id, cdre.tariff, cdre.month, minsfrom cdr_t cdr partition by (cust_id) right outer join     (select distinct tariff, month from cdr_t) cdre     on (cdr.month = cdre.month and cdr.tariff = cdre.tariff);   ....... Mining a Star Schema: Telco Churn Case Study (3 of 3) Now that the "difficult" work is complete - preparing the data - we can move to building a predictive model to help identify and understand churn.The case study suggests that separate models be built for different customer segments (high, medium, low, and very low value customer groups).  To reduce the data to a single segment, a filter can be applied: create or replace view churn_data_high asselect * from churn_prep where value_band = 'HIGH'; It is simple to take a quick look at the predictive aspects of the data on a univariate basis.  While this does not capture the more complex multi-variate effects as would occur with the full-blown data mining algorithms, it can give a quick feel as to the predictive aspects of the data as well as validate the data preparation steps.  Oracle Data Mining includes a predictive analytics package which enables quick analysis. begin  dbms_predictive_analytics.explain(   'churn_data_high','churn_m6','expl_churn_tab'); end; /select * from expl_churn_tab where rank <= 5 order by rank; ATTRIBUTE_NAME       ATTRIBUTE_SUBNAME EXPLANATORY_VALUE RANK-------------------- ----------------- ----------------- ----------LOS_BAND                                      .069167052          1MINS_PER_TARIFF_MON  PEAK-5                   .034881648          2REV_PER_MON          REV-5                    .034527798          3DROPPED_CALLS                                 .028110322          4MINS_PER_TARIFF_MON  PEAK-4                   .024698149          5From the above results, it is clear that some predictors do contain information to help identify churn (explanatory value > 0).  The strongest uni-variate predictor of churn appears to be the customer's (binned) length of service.  The second strongest churn indicator appears to be the number of peak minutes used in the most recent month.  The subname column contains the interior piece of the DM_NESTED_NUMERICALS column described in the previous post.  By using the object relational approach, many related predictors are included within a single top-level column. .....   NOTE:  These are just EXCERPTS.  Click here to start reading the Oracle Data Mining a Star Schema: Telco Churn Case Study from the beginning.    

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  • Complex type support in process flow &ndash; XMLTYPE

    - by shawn
        Before OWB 11.2 release, there are only 5 simple data types supported in process flow: DATE, BOOLEAN, INTEGER, FLOAT and STRING. A new complex data type – XMLTYPE is added in 11.2, in order to support complex data being passed between the process flow activities. In this article we will give a simple example to illustrate the usage of the new type and some related editors.     Suppose there is a bookstore that uses XML format orders as shown below (we use the simplest form for the illustration purpose), then we can create a process flow to handle the order, take the order as the input, then extract necessary information, and generate a confirmation email to the customer automatically. <order id=’0001’>     <customer>         <name>Tom</name>         <email>[email protected]</email>     </customer>     <book id=’Java_001’>         <quantity>3</quantity>     </book> </order>     Considering a simple user case here: we use an input parameter/variable with XMLTYPE to hold the XML content of the order; then we can use an Assign activity to retrieve the email info from the order; after that, we can create an email activity to send the email (Other activities might be added in practical case, but will not be described here). 1) Set XML content value     For testing purpose, we will create a variable to hold the sample order, and then this will be used among the process flow activities. When the variable is of XMLTYPE and the “Literal” value is set the true, the advance editor will be enabled.     Click the “Advance Editor” shown as above, a simple xml editor will popup. The editor has basic features like syntax highlight and check as shown below:     We can also do the basic validation or validation against schema with the editor by selecting the normalized schema. With this, it will be easier to provide the value for XMLTYPE variables. 2) Extract information from XML content     After setting the value, we need to extract the email information with the Assign activity. In process flow, an enhanced expression builder is used to help users construct the XPath for extracting values from XML content. When the variable’s literal value is set the false, the advance editor is enabled.     Click the button, the advance editor will popup, as shown below:     The editor is based on the expression builder (which is often used in mapping etc), an XPath lib panel is appended which provides some help information on how to write the XPath. The expression used here is: “XMLTYPE.EXTRACT(XML_ORDER,'/order/customer/email/text()').getStringVal()”, which uses ‘/order/customer/email/text()’ as the XPath to extract the email info from the XML document.     A variable called “EMAIL_ADDR” is created with String data type to hold the value extracted.     Then we bind the “VARIABLE” parameter of Assign activity to “EMAIL_ADDR” variable, which means the value of the “EMAIL_ADDR” activity will be set to the result of the “VALUE” parameter of Assign activity. 3) Use the extracted information in Email activity     We bind the “TO_ADDRESS” parameter of the email activity to the “EMAIL_ADDR” variable created in above step.     We can also extract other information from the xml order directly through the expression, for example, we can set the “MESSAGE_BODY” with value “'Dear '||XMLTYPE.EXTRACT(XML_ORDER,'/order/customer/name/text()').getStringVal()||chr(13)||chr(10)||'   You have ordered '||XMLTYPE.EXTRACT(XML_ORDER,'/order/book/quantity/text()').getStringVal()||' '||XMLTYPE.EXTRACT(XML_ORDER,'/order/book/@id').getStringVal()”. This expression will extract the customer name, the quantity and the book id from the order to compose the message body.     To make the email activity work, we need provide some other necessary information, Such as “SMTP_SERVER” (which is the SMTP server used to send the emails, like “mail.bookstore.com”. The default PORT number is set to 25. You need to change the value accordingly), “FROM_ADDRESS” and “SUBJECT”. Then the process flow is ready to go.     After deploying the process flow package, we can simply run the process flow to check if the result is as expected (An email will be sent to the specified email address with proper subject and message body).     Note: In oracle 11g, there is an enhanced security feature - ACL (Access Control List), which restrict the network access within db, so we need to edit the list to allow UTL_SMTP work if you are using oracle 11g. Refer to chapter “Access Control Lists for UTL_TCP/HTTP/SMTP” and “Managing Fine-Grained Access to External Network Services” for more details.       In previous releases, XMLTYPE already exists in other OWB objects, like mapping/transformation etc. When the mapping/transformation is dragged into a process flow, the parameters with XMLTYPE are mapped to STRING. Now with the XMLTYPE support in process flow, the XMLTYPE will map to XMLTYPE in a more natural way, and we can leverage the new data type for the design.

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  • Why Fusion Middleware matters to Oracle Applications and Fusion Applications customers?

    - by Harish Gaur
    Did you miss this general session on Monday morning presented by Amit Zavery, VP of Oracle Fusion Middleware Product Management? There will be a recording made available shortly and in the meanwhile, here is a recap. Amit presented 5 strategies customers can leverage today to extend their applications. Figure 1: 5 Oracle Fusion Middleware strategies to extend Oracle Applications & Oracle Fusion Apps 1. Engage Everyone – Provide intuitive and social experience for application users using Oracle WebCenter 2. Extend Enterprise – Extend Oracle Applications to mobile devices using Oracle ADF Mobile 3. Orchestrate Processes – Automate key organization processes across on-premise & cloud applications using Oracle BPM Suite & Oracle SOA Suite 4. Secure the core – Provide single sign-on and self-service provisioning across multiple apps using Oracle Identity Management 5. Optimize Performance – Leverage Exalogic stack to consolidate multiple instance and improve performance of Oracle Applications Session included 3 demonstrations to illustrate these strategies. 1. First demo highlighted significance of mobile applications for unlocking existing investment in Applications such as EBS. Using a native iPhone application interacting with e-Business Suite, demo showed how expense approval can be mobile enabled with enhanced visibility using BI dashboards. 2. Second demo showed how you can extend a banking process in Siebel and Oracle Policy Automation with Oracle BPM Suite.Process starts in Siebel with a customer requesting a loan, and then jumps to OPA for loan recommendations and decision making and loan processing with approvals in handled in BPM Suite. Once approvals are completed Siebel is updated to complete the process. 3. Final demo showcased FMW components inside Fusion Applications, specifically WebCenter. Boeing, Underwriter Laboratories and Electronic Arts joined this quest and discussed 3 different approaches of leveraging Fusion Middleware stack to maximize their investment in Oracle Applications and/or Fusion Applications technology. Let’s briefly review what these customers shared during the session: 1. Extend Fusion Applications We know that Oracle Fusion Middleware is the underlying technology infrastructure for Oracle Fusion Applications. Architecturally, Oracle Fusion Apps leverages several components of Oracle Fusion Middleware from Oracle WebCenter for rich collaborative interface, Oracle SOA Suite & Oracle BPM Suite for orchestrating key underlying processes to Oracle BIEE for dash boarding and analytics. Boeing talked about how they are using Oracle BPM Suite 11g, a key component of Oracle Fusion Middleware with Oracle Fusion Apps to transform their supply chain. Tim Murnin, Director of Supply Chain talked about Boeing’s 5 year supply chain transformation journey. Boeing’s Integrated and Information Management division began with automation of critical RFQ process using Oracle BPM Suite. This 1st phase resulted in 38% reduction in labor costs for RFP. As a next step in this effort, Boeing is now creating a platform to enable electronic Order Management. Fusion Apps are playing a significant role in this phase. Boeing has gone live with Oracle Fusion Product Hub and efforts are underway with Oracle Fusion Distributed Order Orchestration (DOO). So, where does Oracle BPM Suite 11g fit in this equation? Let me explain. Business processes within Fusion Apps are designed using 2 standards: Business Process Execution Language (BPEL) and Business Process Modeling Notation (BPMN). These processes can be easily configured using declarative set of tools. Boeing leverages Oracle BPM Suite 11g (which supports BPMN 2.0) and Oracle SOA Suite (which supports BPEL) to “extend” these applications. Traditionally, customizations are done within an app using native technologies. But, instead of making process changes within Fusion Apps, Boeing has taken an approach of building “extensions” layer on top of the application. Fig 2: Boeing’s use of Oracle BPM Suite to orchestrate key supply chain processes across Fusion Apps 2. Maximize Oracle Applications investment Fusion Middleware appeals not only to Fusion Apps customers, but is also leveraged by Oracle E-Business Suite, PeopleSoft, Siebel and JD Edwards customers significantly. Using Oracle BPM Suite and Oracle SOA Suite is the recommended extension strategy for Oracle Fusion Apps and Oracle Applications Unlimited customers. Electronic Arts, E-Business Suite customer, spoke about their strategy to transform their order-to-cash process using Oracle SOA Suite, Oracle Foundation Packs and Oracle BAM. Udesh Naicker, Sr Director of IT at Elecronic Arts (EA), discussed how growth of social and digital gaming had started to put tremendous pressure on EA’s existing IT infrastructure. He discussed the challenge with millions of micro-transactions coming from several sources – Microsoft Xbox, Paypal, several service providers. EA found Order-2-Cash processes stretched to their limits. They lacked visibility into these transactions across the entire value chain. EA began by consolidating their E-Business Suite R11 instances into single E-Business Suite R12. EA needed to cater to a variety of service requirements, connectivity methods, file formats, and information latency. Their integration strategy was tactical, i.e., using file uploads, TIBCO, SQL scripts. After consolidating E-Business suite, EA standardized their integration approach with Oracle SOA Suite and Oracle AIA Foundation Pack. Oracle SOA Suite is the platform used to extend E-Business Suite R12 and standardize 60+ interfaces across several heterogeneous systems including PeopleSoft, Demantra, SF.com, Workday, and Managed EDI services spanning on-premise, hosted and cloud applications. EA believes that Oracle SOA Suite 11g based extension strategy has helped significantly in the followings ways: - It helped them keep customizations out of E-Business Suite, thereby keeping EBS R12 vanilla and upgrade safe - Developers are now proficient in technology which is also leveraged by Fusion Apps. This has helped them prepare for adoption of Fusion Apps in the future Fig 3: Using Oracle SOA Suite & Oracle e-Business Suite, Electronic Arts built new platform for order processing 3. Consolidate apps and improve scalability Exalogic is an optimal platform for customers to consolidate their application deployments and enhance performance. Underwriter Laboratories talked about their strategy to run their mission critical applications including e-Business Suite on Exalogic. Christian Anschuetz, CIO of Underwriter Laboratories (UL) shared how UL is on a growth path - $1B to $2.5B in 5 years- and planning a significant business transformation from a not-for-profit to a for-profit business. To support this growth, UL is planning to simplify its IT environment and the deployment complexity associated with ERP applications and technology it runs on. Their current applications were deployed on variety of hardware platforms and lacked comprehensive disaster recovery architecture. UL embarked on a mission to deploy E-Business Suite on Exalogic. UL’s solution is unique because it is one of the first to deploy a large number of Oracle applications and related Fusion Middleware technologies (SOA, BI, Analytical Applications AIA Foundation Pack and AIA EBS to Siebel UCM prebuilt integration) on the combined Exalogic and Exadata environment. UL is planning to move to a virtualized architecture toward the end of 2012 to securely host external facing applications like iStore Fig 4: Underwrites Labs deployed e-Business Suite on Exalogic to achieve performance gains Key takeaways are: - Fusion Middleware platform is certified with major Oracle Applications Unlimited offerings. Fusion Middleware is the underlying technological infrastructure for Fusion Apps - Customers choose Oracle Fusion Middleware to extend their applications (Apps Unlimited or Fusion Apps) to keep applications upgrade safe and prepare for Fusion Apps - Exalogic is an optimum platform to consolidate applications deployments and enhance performance

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  • Why Fusion Middleware matters to Oracle Applications and Fusion Applications customers?

    - by Harish Gaur
    Did you miss this general session on Monday morning presented by Amit Zavery, VP of Oracle Fusion Middleware Product Management? There will be a recording made available shortly and in the meanwhile, here is a recap. Amit presented 5 strategies customers can leverage today to extend their applications. Figure 1: 5 Oracle Fusion Middleware strategies to extend Oracle Applications & Oracle Fusion Apps 1. Engage Everyone – Provide intuitive and social experience for application users using Oracle WebCenter 2. Extend Enterprise – Extend Oracle Applications to mobile devices using Oracle ADF Mobile 3. Orchestrate Processes – Automate key organization processes across on-premise & cloud applications using Oracle BPM Suite & Oracle SOA Suite 4. Secure the core – Provide single sign-on and self-service provisioning across multiple apps using Oracle Identity Management 5. Optimize Performance – Leverage Exalogic stack to consolidate multiple instance and improve performance of Oracle Applications Session included 3 demonstrations to illustrate these strategies. 1. First demo highlighted significance of mobile applications for unlocking existing investment in Applications such as EBS. Using a native iPhone application interacting with e-Business Suite, demo showed how expense approval can be mobile enabled with enhanced visibility using BI dashboards. 2. Second demo showed how you can extend a banking process in Siebel and Oracle Policy Automation with Oracle BPM Suite.Process starts in Siebel with a customer requesting a loan, and then jumps to OPA for loan recommendations and decision making and loan processing with approvals in handled in BPM Suite. Once approvals are completed Siebel is updated to complete the process. 3. Final demo showcased FMW components inside Fusion Applications, specifically WebCenter. Boeing, Underwriter Laboratories and Electronic Arts joined this quest and discussed 3 different approaches of leveraging Fusion Middleware stack to maximize their investment in Oracle Applications and/or Fusion Applications technology. Let’s briefly review what these customers shared during the session: 1. Extend Fusion Applications We know that Oracle Fusion Middleware is the underlying technology infrastructure for Oracle Fusion Applications. Architecturally, Oracle Fusion Apps leverages several components of Oracle Fusion Middleware from Oracle WebCenter for rich collaborative interface, Oracle SOA Suite & Oracle BPM Suite for orchestrating key underlying processes to Oracle BIEE for dash boarding and analytics. Boeing talked about how they are using Oracle BPM Suite 11g, a key component of Oracle Fusion Middleware with Oracle Fusion Apps to transform their supply chain. Tim Murnin, Director of Supply Chain talked about Boeing’s 5 year supply chain transformation journey. Boeing’s Integrated and Information Management division began with automation of critical RFQ process using Oracle BPM Suite. This 1st phase resulted in 38% reduction in labor costs for RFP. As a next step in this effort, Boeing is now creating a platform to enable electronic Order Management. Fusion Apps are playing a significant role in this phase. Boeing has gone live with Oracle Fusion Product Hub and efforts are underway with Oracle Fusion Distributed Order Orchestration (DOO). So, where does Oracle BPM Suite 11g fit in this equation? Let me explain. Business processes within Fusion Apps are designed using 2 standards: Business Process Execution Language (BPEL) and Business Process Modeling Notation (BPMN). These processes can be easily configured using declarative set of tools. Boeing leverages Oracle BPM Suite 11g (which supports BPMN 2.0) and Oracle SOA Suite (which supports BPEL) to “extend” these applications. Traditionally, customizations are done within an app using native technologies. But, instead of making process changes within Fusion Apps, Boeing has taken an approach of building “extensions” layer on top of the application. Fig 2: Boeing’s use of Oracle BPM Suite to orchestrate key supply chain processes across Fusion Apps 2. Maximize Oracle Applications investment Fusion Middleware appeals not only to Fusion Apps customers, but is also leveraged by Oracle E-Business Suite, PeopleSoft, Siebel and JD Edwards customers significantly. Using Oracle BPM Suite and Oracle SOA Suite is the recommended extension strategy for Oracle Fusion Apps and Oracle Applications Unlimited customers. Electronic Arts, E-Business Suite customer, spoke about their strategy to transform their order-to-cash process using Oracle SOA Suite, Oracle Foundation Packs and Oracle BAM. Udesh Naicker, Sr Director of IT at Elecronic Arts (EA), discussed how growth of social and digital gaming had started to put tremendous pressure on EA’s existing IT infrastructure. He discussed the challenge with millions of micro-transactions coming from several sources – Microsoft Xbox, Paypal, several service providers. EA found Order-2-Cash processes stretched to their limits. They lacked visibility into these transactions across the entire value chain. EA began by consolidating their E-Business Suite R11 instances into single E-Business Suite R12. EA needed to cater to a variety of service requirements, connectivity methods, file formats, and information latency. Their integration strategy was tactical, i.e., using file uploads, TIBCO, SQL scripts. After consolidating E-Business suite, EA standardized their integration approach with Oracle SOA Suite and Oracle AIA Foundation Pack. Oracle SOA Suite is the platform used to extend E-Business Suite R12 and standardize 60+ interfaces across several heterogeneous systems including PeopleSoft, Demantra, SF.com, Workday, and Managed EDI services spanning on-premise, hosted and cloud applications. EA believes that Oracle SOA Suite 11g based extension strategy has helped significantly in the followings ways: - It helped them keep customizations out of E-Business Suite, thereby keeping EBS R12 vanilla and upgrade safe - Developers are now proficient in technology which is also leveraged by Fusion Apps. This has helped them prepare for adoption of Fusion Apps in the future Fig 3: Using Oracle SOA Suite & Oracle e-Business Suite, Electronic Arts built new platform for order processing 3. Consolidate apps and improve scalability Exalogic is an optimal platform for customers to consolidate their application deployments and enhance performance. Underwriter Laboratories talked about their strategy to run their mission critical applications including e-Business Suite on Exalogic. Christian Anschuetz, CIO of Underwriter Laboratories (UL) shared how UL is on a growth path - $1B to $2.5B in 5 years- and planning a significant business transformation from a not-for-profit to a for-profit business. To support this growth, UL is planning to simplify its IT environment and the deployment complexity associated with ERP applications and technology it runs on. Their current applications were deployed on variety of hardware platforms and lacked comprehensive disaster recovery architecture. UL embarked on a mission to deploy E-Business Suite on Exalogic. UL’s solution is unique because it is one of the first to deploy a large number of Oracle applications and related Fusion Middleware technologies (SOA, BI, Analytical Applications AIA Foundation Pack and AIA EBS to Siebel UCM prebuilt integration) on the combined Exalogic and Exadata environment. UL is planning to move to a virtualized architecture toward the end of 2012 to securely host external facing applications like iStore Fig 4: Underwrites Labs deployed e-Business Suite on Exalogic to achieve performance gains Key takeaways are: - Fusion Middleware platform is certified with major Oracle Applications Unlimited offerings. Fusion Middleware is the underlying technological infrastructure for Fusion Apps - Customers choose Oracle Fusion Middleware to extend their applications (Apps Unlimited or Fusion Apps) to keep applications upgrade safe and prepare for Fusion Apps - Exalogic is an optimum platform to consolidate applications deployments and enhance performance TAGS: Fusion Apps, Exalogic, BPM Suite, SOA Suite, e-Business Suite Integration

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  • Big Data Matters with ODI12c

    - by Madhu Nair
    contributed by Mike Eisterer On October 17th, 2013, Oracle announced the release of Oracle Data Integrator 12c (ODI12c).  This release signifies improvements to Oracle’s Data Integration portfolio of solutions, particularly Big Data integration. Why Big Data = Big Business Organizations are gaining greater insights and actionability through increased storage, processing and analytical benefits offered by Big Data solutions.  New technologies and frameworks like HDFS, NoSQL, Hive and MapReduce support these benefits now. As further data is collected, analytical requirements increase and the complexity of managing transformations and aggregations of data compounds and organizations are in need for scalable Data Integration solutions. ODI12c provides enterprise solutions for the movement, translation and transformation of information and data heterogeneously and in Big Data Environments through: The ability for existing ODI and SQL developers to leverage new Big Data technologies. A metadata focused approach for cataloging, defining and reusing Big Data technologies, mappings and process executions. Integration between many heterogeneous environments and technologies such as HDFS and Hive. Generation of Hive Query Language. Working with Big Data using Knowledge Modules  ODI12c provides developers with the ability to define sources and targets and visually develop mappings to effect the movement and transformation of data.  As the mappings are created, ODI12c leverages a rich library of prebuilt integrations, known as Knowledge Modules (KMs).  These KMs are contextual to the technologies and platforms to be integrated.  Steps and actions needed to manage the data integration are pre-built and configured within the KMs.  The Oracle Data Integrator Application Adapter for Hadoop provides a series of KMs, specifically designed to integrate with Big Data Technologies.  The Big Data KMs include: Check Knowledge Module Reverse Engineer Knowledge Module Hive Transform Knowledge Module Hive Control Append Knowledge Module File to Hive (LOAD DATA) Knowledge Module File-Hive to Oracle (OLH-OSCH) Knowledge Module  Nothing to beat an Example: To demonstrate the use of the KMs which are part of the ODI Application Adapter for Hadoop, a mapping may be defined to move data between files and Hive targets.  The mapping is defined by dragging the source and target into the mapping, performing the attribute (column) mapping (see Figure 1) and then selecting the KM which will govern the process.  In this mapping example, movie data is being moved from an HDFS source into a Hive table.  Some of the attributes, such as “CUSTID to custid”, have been mapped over. Figure 1  Defining the Mapping Before the proper KM can be assigned to define the technology for the mapping, it needs to be added to the ODI project.  The Big Data KMs have been made available to the project through the KM import process.   Generally, this is done prior to defining the mapping. Figure 2  Importing the Big Data Knowledge Modules Following the import, the KMs are available in the Designer Navigator. v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false EN-US ZH-TW X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Figure 3  The Project View in Designer, Showing Installed IKMs Once the KM is imported, it may be assigned to the mapping target.  This is done by selecting the Physical View of the mapping and examining the Properties of the Target.  In this case MOVIAPP_LOG_STAGE is the target of our mapping. Figure 4  Physical View of the Mapping and Assigning the Big Data Knowledge Module to the Target Alternative KMs may have been selected as well, providing flexibility and abstracting the logical mapping from the physical implementation.  Our mapping may be applied to other technologies as well. The mapping is now complete and is ready to run.  We will see more in a future blog about running a mapping to load Hive. To complete the quick ODI for Big Data Overview, let us take a closer look at what the IKM File to Hive is doing for us.  ODI provides differentiated capabilities by defining the process and steps which normally would have to be manually developed, tested and implemented into the KM.  As shown in figure 5, the KM is preparing the Hive session, managing the Hive tables, performing the initial load from HDFS and then performing the insert into Hive.  HDFS and Hive options are selected graphically, as shown in the properties in Figure 4. Figure 5  Process and Steps Managed by the KM What’s Next Big Data being the shape shifting business challenge it is is fast evolving into the deciding factor between market leaders and others. Now that an introduction to ODI and Big Data has been provided, look for additional blogs coming soon using the Knowledge Modules which make up the Oracle Data Integrator Application Adapter for Hadoop: Importing Big Data Metadata into ODI, Testing Data Stores and Loading Hive Targets Generating Transformations using Hive Query language Loading Oracle from Hadoop Sources For more information now, please visit the Oracle Data Integrator Application Adapter for Hadoop web site, http://www.oracle.com/us/products/middleware/data-integration/hadoop/overview/index.html Do not forget to tune in to the ODI12c Executive Launch webcast on the 12th to hear more about ODI12c and GG12c. Normal 0 false false false EN-US ZH-TW X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";}

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  • The Top 5 MDM Sessions You Can’t Miss at OpenWorld

    - by Mala Narasimharajan
    Sessions, Demo pods, Hands On Labs, and much more – but where should you focus?  MDM has some excellent sessions planned for OOW –  here is a top 5 list to identify the sessions you just can’t afford to miss. October 3, 2012  1:15 PM - 2:15 PM    Moscone West - 3002/3004     What's There to Know About Oracle’s Master Data Management Portfolio and Roadmap? Hear about product strategy our vision for the future and how Oracle MDM is positioned to excel in helping organizations make the most of their customer,      partner, supplier or product data. October 3, 2012  5:00 PM - 6:00 PM   Westin San Francisco – Metropolitan I Oracle Customer MDM Applications: Implementation Best Practices, Data Governance, and ROI       Customers successes provide solid examples of technology at work and how organizations derive value from it. Attend this session and hear from our customers on how they built a business case, established governance and are realizing the benefits of Oracle Customer Hub. October 2, 2012  10:15 AM - 11:15 AM   Moscone West – 3001 Mastering Product Data: Strategies for Effective Product Information Management                                                                      Product data is vital for any enterprise in being able to provide a consolidated representation of products to their partners, customers and suppliers.  Hear how our customers leverage product information to be a leader in their respective area and how Oracle is critical to achieving this. October 2, 2012  11:45 AM - 12:45 PM   Moscone West – 2022 Enabling Trusted Enterprise Product Data with Oracle Fusion Product Hub                                                                                       Learn how Oracle Fusion Product Hub is paving the way for providing organizations with trusted product data as well as helping organizations make the most of the information and infrastructure they already possess. October 1, 2012  4:45 PM – 5:45 PM   InterContinental - Ballroom A Oracle Hyperion Data Relationship Management: Enabling Enterprise Transformation                                                                         Hear how Data Relationship Management drives enterprise transformation and why any organization embarking on an master data management initiative needs it, plus hear from our customers best practices as well as lessons learned.  Check out the Master Data Management Focus On document for all our sessions at OpenWorld 2012. 

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