Search Results

Search found 8367 results on 335 pages for 'temporal difference'.

Page 264/335 | < Previous Page | 260 261 262 263 264 265 266 267 268 269 270 271  | Next Page >

  • 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!

    Read the article

  • Using R to Analyze G1GC Log Files

    - by user12620111
    Using R to Analyze G1GC Log Files body, td { font-family: sans-serif; background-color: white; font-size: 12px; margin: 8px; } tt, code, pre { font-family: 'DejaVu Sans Mono', 'Droid Sans Mono', 'Lucida Console', Consolas, Monaco, monospace; } h1 { font-size:2.2em; } h2 { font-size:1.8em; } h3 { font-size:1.4em; } h4 { font-size:1.0em; } h5 { font-size:0.9em; } h6 { font-size:0.8em; } a:visited { color: rgb(50%, 0%, 50%); } pre { margin-top: 0; max-width: 95%; border: 1px solid #ccc; white-space: pre-wrap; } pre code { display: block; padding: 0.5em; } code.r, code.cpp { background-color: #F8F8F8; } table, td, th { border: none; } blockquote { color:#666666; margin:0; padding-left: 1em; border-left: 0.5em #EEE solid; } hr { height: 0px; border-bottom: none; border-top-width: thin; border-top-style: dotted; border-top-color: #999999; } @media print { * { background: transparent !important; color: black !important; filter:none !important; -ms-filter: none !important; } body { font-size:12pt; max-width:100%; } a, a:visited { text-decoration: underline; } hr { visibility: hidden; page-break-before: always; } pre, blockquote { padding-right: 1em; page-break-inside: avoid; } tr, img { page-break-inside: avoid; } img { max-width: 100% !important; } @page :left { margin: 15mm 20mm 15mm 10mm; } @page :right { margin: 15mm 10mm 15mm 20mm; } p, h2, h3 { orphans: 3; widows: 3; } h2, h3 { page-break-after: avoid; } } pre .operator, pre .paren { color: rgb(104, 118, 135) } pre .literal { color: rgb(88, 72, 246) } pre .number { color: rgb(0, 0, 205); } pre .comment { color: rgb(76, 136, 107); } pre .keyword { color: rgb(0, 0, 255); } pre .identifier { color: rgb(0, 0, 0); } pre .string { color: rgb(3, 106, 7); } var hljs=new function(){function m(p){return p.replace(/&/gm,"&").replace(/"}while(y.length||w.length){var v=u().splice(0,1)[0];z+=m(x.substr(q,v.offset-q));q=v.offset;if(v.event=="start"){z+=t(v.node);s.push(v.node)}else{if(v.event=="stop"){var p,r=s.length;do{r--;p=s[r];z+=("")}while(p!=v.node);s.splice(r,1);while(r'+M[0]+""}else{r+=M[0]}O=P.lR.lastIndex;M=P.lR.exec(L)}return r+L.substr(O,L.length-O)}function J(L,M){if(M.sL&&e[M.sL]){var r=d(M.sL,L);x+=r.keyword_count;return r.value}else{return F(L,M)}}function I(M,r){var L=M.cN?'':"";if(M.rB){y+=L;M.buffer=""}else{if(M.eB){y+=m(r)+L;M.buffer=""}else{y+=L;M.buffer=r}}D.push(M);A+=M.r}function G(N,M,Q){var R=D[D.length-1];if(Q){y+=J(R.buffer+N,R);return false}var P=q(M,R);if(P){y+=J(R.buffer+N,R);I(P,M);return P.rB}var L=v(D.length-1,M);if(L){var O=R.cN?"":"";if(R.rE){y+=J(R.buffer+N,R)+O}else{if(R.eE){y+=J(R.buffer+N,R)+O+m(M)}else{y+=J(R.buffer+N+M,R)+O}}while(L1){O=D[D.length-2].cN?"":"";y+=O;L--;D.length--}var r=D[D.length-1];D.length--;D[D.length-1].buffer="";if(r.starts){I(r.starts,"")}return R.rE}if(w(M,R)){throw"Illegal"}}var E=e[B];var D=[E.dM];var A=0;var x=0;var y="";try{var s,u=0;E.dM.buffer="";do{s=p(C,u);var t=G(s[0],s[1],s[2]);u+=s[0].length;if(!t){u+=s[1].length}}while(!s[2]);if(D.length1){throw"Illegal"}return{r:A,keyword_count:x,value:y}}catch(H){if(H=="Illegal"){return{r:0,keyword_count:0,value:m(C)}}else{throw H}}}function g(t){var p={keyword_count:0,r:0,value:m(t)};var r=p;for(var q in e){if(!e.hasOwnProperty(q)){continue}var s=d(q,t);s.language=q;if(s.keyword_count+s.rr.keyword_count+r.r){r=s}if(s.keyword_count+s.rp.keyword_count+p.r){r=p;p=s}}if(r.language){p.second_best=r}return p}function i(r,q,p){if(q){r=r.replace(/^((]+|\t)+)/gm,function(t,w,v,u){return w.replace(/\t/g,q)})}if(p){r=r.replace(/\n/g,"")}return r}function n(t,w,r){var x=h(t,r);var v=a(t);var y,s;if(v){y=d(v,x)}else{return}var q=c(t);if(q.length){s=document.createElement("pre");s.innerHTML=y.value;y.value=k(q,c(s),x)}y.value=i(y.value,w,r);var u=t.className;if(!u.match("(\\s|^)(language-)?"+v+"(\\s|$)")){u=u?(u+" "+v):v}if(/MSIE [678]/.test(navigator.userAgent)&&t.tagName=="CODE"&&t.parentNode.tagName=="PRE"){s=t.parentNode;var p=document.createElement("div");p.innerHTML=""+y.value+"";t=p.firstChild.firstChild;p.firstChild.cN=s.cN;s.parentNode.replaceChild(p.firstChild,s)}else{t.innerHTML=y.value}t.className=u;t.result={language:v,kw:y.keyword_count,re:y.r};if(y.second_best){t.second_best={language:y.second_best.language,kw:y.second_best.keyword_count,re:y.second_best.r}}}function o(){if(o.called){return}o.called=true;var r=document.getElementsByTagName("pre");for(var p=0;p|=||=||=|\\?|\\[|\\{|\\(|\\^|\\^=|\\||\\|=|\\|\\||~";this.ER="(?![\\s\\S])";this.BE={b:"\\\\.",r:0};this.ASM={cN:"string",b:"'",e:"'",i:"\\n",c:[this.BE],r:0};this.QSM={cN:"string",b:'"',e:'"',i:"\\n",c:[this.BE],r:0};this.CLCM={cN:"comment",b:"//",e:"$"};this.CBLCLM={cN:"comment",b:"/\\*",e:"\\*/"};this.HCM={cN:"comment",b:"#",e:"$"};this.NM={cN:"number",b:this.NR,r:0};this.CNM={cN:"number",b:this.CNR,r:0};this.BNM={cN:"number",b:this.BNR,r:0};this.inherit=function(r,s){var p={};for(var q in r){p[q]=r[q]}if(s){for(var q in s){p[q]=s[q]}}return p}}();hljs.LANGUAGES.cpp=function(){var a={keyword:{"false":1,"int":1,"float":1,"while":1,"private":1,"char":1,"catch":1,"export":1,virtual:1,operator:2,sizeof:2,dynamic_cast:2,typedef:2,const_cast:2,"const":1,struct:1,"for":1,static_cast:2,union:1,namespace:1,unsigned:1,"long":1,"throw":1,"volatile":2,"static":1,"protected":1,bool:1,template:1,mutable:1,"if":1,"public":1,friend:2,"do":1,"return":1,"goto":1,auto:1,"void":2,"enum":1,"else":1,"break":1,"new":1,extern:1,using:1,"true":1,"class":1,asm:1,"case":1,typeid:1,"short":1,reinterpret_cast:2,"default":1,"double":1,register:1,explicit:1,signed:1,typename:1,"try":1,"this":1,"switch":1,"continue":1,wchar_t:1,inline:1,"delete":1,alignof:1,char16_t:1,char32_t:1,constexpr:1,decltype:1,noexcept:1,nullptr:1,static_assert:1,thread_local:1,restrict:1,_Bool:1,complex:1},built_in:{std:1,string:1,cin:1,cout:1,cerr:1,clog:1,stringstream:1,istringstream:1,ostringstream:1,auto_ptr:1,deque:1,list:1,queue:1,stack:1,vector:1,map:1,set:1,bitset:1,multiset:1,multimap:1,unordered_set:1,unordered_map:1,unordered_multiset:1,unordered_multimap:1,array:1,shared_ptr:1}};return{dM:{k:a,i:"",k:a,r:10,c:["self"]}]}}}();hljs.LANGUAGES.r={dM:{c:[hljs.HCM,{cN:"number",b:"\\b0[xX][0-9a-fA-F]+[Li]?\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\b\\d+(?:[eE][+\\-]?\\d*)?L\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\b\\d+\\.(?!\\d)(?:i\\b)?",e:hljs.IMMEDIATE_RE,r:1},{cN:"number",b:"\\b\\d+(?:\\.\\d*)?(?:[eE][+\\-]?\\d*)?i?\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\.\\d+(?:[eE][+\\-]?\\d*)?i?\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"keyword",b:"(?:tryCatch|library|setGeneric|setGroupGeneric)\\b",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\.\\.\\.",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\.\\.\\d+(?![\\w.])",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\b(?:function)",e:hljs.IMMEDIATE_RE,r:2},{cN:"keyword",b:"(?:if|in|break|next|repeat|else|for|return|switch|while|try|stop|warning|require|attach|detach|source|setMethod|setClass)\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"literal",b:"(?:NA|NA_integer_|NA_real_|NA_character_|NA_complex_)\\b",e:hljs.IMMEDIATE_RE,r:10},{cN:"literal",b:"(?:NULL|TRUE|FALSE|T|F|Inf|NaN)\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"identifier",b:"[a-zA-Z.][a-zA-Z0-9._]*\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"operator",b:"|=||   Using R to Analyze G1GC Log Files   Using R to Analyze G1GC Log Files Introduction Working in Oracle Platform Integration gives an engineer opportunities to work on a wide array of technologies. My team’s goal is to make Oracle applications run best on the Solaris/SPARC platform. When looking for bottlenecks in a modern applications, one needs to be aware of not only how the CPUs and operating system are executing, but also network, storage, and in some cases, the Java Virtual Machine. I was recently presented with about 1.5 GB of Java Garbage First Garbage Collector log file data. If you’re not familiar with the subject, you might want to review Garbage First Garbage Collector Tuning by Monica Beckwith. The customer had been running Java HotSpot 1.6.0_31 to host a web application server. I was told that the Solaris/SPARC server was running a Java process launched using a commmand line that included the following flags: -d64 -Xms9g -Xmx9g -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -XX:InitiatingHeapOccupancyPercent=80 -XX:PermSize=256m -XX:MaxPermSize=256m -XX:+PrintGC -XX:+PrintGCTimeStamps -XX:+PrintHeapAtGC -XX:+PrintGCDateStamps -XX:+PrintFlagsFinal -XX:+DisableExplicitGC -XX:+UnlockExperimentalVMOptions -XX:ParallelGCThreads=8 Several sources on the internet indicate that if I were to print out the 1.5 GB of log files, it would require enough paper to fill the bed of a pick up truck. Of course, it would be fruitless to try to scan the log files by hand. Tools will be required to summarize the contents of the log files. Others have encountered large Java garbage collection log files. There are existing tools to analyze the log files: IBM’s GC toolkit The chewiebug GCViewer gchisto HPjmeter Instead of using one of the other tools listed, I decide to parse the log files with standard Unix tools, and analyze the data with R. Data Cleansing The log files arrived in two different formats. I guess that the difference is that one set of log files was generated using a more verbose option, maybe -XX:+PrintHeapAtGC, and the other set of log files was generated without that option. Format 1 In some of the log files, the log files with the less verbose format, a single trace, i.e. the report of a singe garbage collection event, looks like this: {Heap before GC invocations=12280 (full 61): garbage-first heap total 9437184K, used 7499918K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 1 young (4096K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. 2014-05-14T07:24:00.988-0700: 60586.353: [GC pause (young) 7324M->7320M(9216M), 0.1567265 secs] Heap after GC invocations=12281 (full 61): garbage-first heap total 9437184K, used 7496533K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 0 young (0K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. } A simple grep can be used to extract a summary: $ grep "\[ GC pause (young" g1gc.log 2014-05-13T13:24:35.091-0700: 3.109: [GC pause (young) 20M->5029K(9216M), 0.0146328 secs] 2014-05-13T13:24:35.440-0700: 3.459: [GC pause (young) 9125K->6077K(9216M), 0.0086723 secs] 2014-05-13T13:24:37.581-0700: 5.599: [GC pause (young) 25M->8470K(9216M), 0.0203820 secs] 2014-05-13T13:24:42.686-0700: 10.704: [GC pause (young) 44M->15M(9216M), 0.0288848 secs] 2014-05-13T13:24:48.941-0700: 16.958: [GC pause (young) 51M->20M(9216M), 0.0491244 secs] 2014-05-13T13:24:56.049-0700: 24.066: [GC pause (young) 92M->26M(9216M), 0.0525368 secs] 2014-05-13T13:25:34.368-0700: 62.383: [GC pause (young) 602M->68M(9216M), 0.1721173 secs] But that format wasn't easily read into R, so I needed to be a bit more tricky. I used the following Unix command to create a summary file that was easy for R to read. $ echo "SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime" $ grep "\[GC pause (young" g1gc.log | grep -v mark | sed -e 's/[A-SU-z\(\),]/ /g' -e 's/->/ /' -e 's/: / /g' | more SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime 2014-05-13T13:24:35.091-0700 3.109 20 5029 9216 0.0146328 2014-05-13T13:24:35.440-0700 3.459 9125 6077 9216 0.0086723 2014-05-13T13:24:37.581-0700 5.599 25 8470 9216 0.0203820 2014-05-13T13:24:42.686-0700 10.704 44 15 9216 0.0288848 2014-05-13T13:24:48.941-0700 16.958 51 20 9216 0.0491244 2014-05-13T13:24:56.049-0700 24.066 92 26 9216 0.0525368 2014-05-13T13:25:34.368-0700 62.383 602 68 9216 0.1721173 Format 2 In some of the log files, the log files with the more verbose format, a single trace, i.e. the report of a singe garbage collection event, was more complicated than Format 1. Here is a text file with an example of a single G1GC trace in the second format. As you can see, it is quite complicated. It is nice that there is so much information available, but the level of detail can be overwhelming. I wrote this awk script (download) to summarize each trace on a single line. #!/usr/bin/env awk -f BEGIN { printf("SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize\n") } ###################### # Save count data from lines that are at the start of each G1GC trace. # Each trace starts out like this: # {Heap before GC invocations=14 (full 0): # garbage-first heap total 9437184K, used 325496K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) ###################### /{Heap.*full/{ gsub ( "\\)" , "" ); nf=split($0,a,"="); split(a[2],b," "); getline; if ( match($0, "first") ) { G1GC=1; IncrementalCount=b[1]; FullCount=substr( b[3], 1, length(b[3])-1 ); } else { G1GC=0; } } ###################### # Pull out time stamps that are in lines with this format: # 2014-05-12T14:02:06.025-0700: 94.312: [GC pause (young), 0.08870154 secs] ###################### /GC pause/ { DateTime=$1; SecondsSinceLaunch=substr($2, 1, length($2)-1); } ###################### # Heap sizes are in lines that look like this: # [ 4842M->4838M(9216M)] ###################### /\[ .*]$/ { gsub ( "\\[" , "" ); gsub ( "\ \]" , "" ); gsub ( "->" , " " ); gsub ( "\\( " , " " ); gsub ( "\ \)" , " " ); split($0,a," "); if ( split(a[1],b,"M") > 1 ) {BeforeSize=b[1]*1024;} if ( split(a[1],b,"K") > 1 ) {BeforeSize=b[1];} if ( split(a[2],b,"M") > 1 ) {AfterSize=b[1]*1024;} if ( split(a[2],b,"K") > 1 ) {AfterSize=b[1];} if ( split(a[3],b,"M") > 1 ) {TotalSize=b[1]*1024;} if ( split(a[3],b,"K") > 1 ) {TotalSize=b[1];} } ###################### # Emit an output line when you find input that looks like this: # [Times: user=1.41 sys=0.08, real=0.24 secs] ###################### /\[Times/ { if (G1GC==1) { gsub ( "," , "" ); split($2,a,"="); UserTime=a[2]; split($3,a,"="); SysTime=a[2]; split($4,a,"="); RealTime=a[2]; print DateTime,SecondsSinceLaunch,IncrementalCount,FullCount,UserTime,SysTime,RealTime,BeforeSize,AfterSize,TotalSize; G1GC=0; } } The resulting summary is about 25X smaller that the original file, but still difficult for a human to digest. SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ... 2014-05-12T18:36:34.669-0700: 3985.744 561 0 0.57 0.06 0.16 1724416 1720320 9437184 2014-05-12T18:36:34.839-0700: 3985.914 562 0 0.51 0.06 0.19 1724416 1720320 9437184 2014-05-12T18:36:35.069-0700: 3986.144 563 0 0.60 0.04 0.27 1724416 1721344 9437184 2014-05-12T18:36:35.354-0700: 3986.429 564 0 0.33 0.04 0.09 1725440 1722368 9437184 2014-05-12T18:36:35.545-0700: 3986.620 565 0 0.58 0.04 0.17 1726464 1722368 9437184 2014-05-12T18:36:35.726-0700: 3986.801 566 0 0.43 0.05 0.12 1726464 1722368 9437184 2014-05-12T18:36:35.856-0700: 3986.930 567 0 0.30 0.04 0.07 1726464 1723392 9437184 2014-05-12T18:36:35.947-0700: 3987.023 568 0 0.61 0.04 0.26 1727488 1723392 9437184 2014-05-12T18:36:36.228-0700: 3987.302 569 0 0.46 0.04 0.16 1731584 1724416 9437184 Reading the Data into R Once the GC log data had been cleansed, either by processing the first format with the shell script, or by processing the second format with the awk script, it was easy to read the data into R. g1gc.df = read.csv("summary.txt", row.names = NULL, stringsAsFactors=FALSE,sep="") str(g1gc.df) ## 'data.frame': 8307 obs. of 10 variables: ## $ row.names : chr "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ... ## $ SecondsSinceLaunch: num 1.16 1.47 1.97 3.83 6.1 ... ## $ IncrementalCount : int 0 1 2 3 4 5 6 7 8 9 ... ## $ FullCount : int 0 0 0 0 0 0 0 0 0 0 ... ## $ UserTime : num 0.11 0.05 0.04 0.21 0.08 0.26 0.31 0.33 0.34 0.56 ... ## $ SysTime : num 0.04 0.01 0.01 0.05 0.01 0.06 0.07 0.06 0.07 0.09 ... ## $ RealTime : num 0.02 0.02 0.01 0.04 0.02 0.04 0.05 0.04 0.04 0.06 ... ## $ BeforeSize : int 8192 5496 5768 22528 24576 43008 34816 53248 55296 93184 ... ## $ AfterSize : int 1400 1672 2557 4907 7072 14336 16384 18432 19456 21504 ... ## $ TotalSize : int 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 ... head(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount ## 1 2014-05-12T14:00:32.868-0700: 1.161 0 ## 2 2014-05-12T14:00:33.179-0700: 1.472 1 ## 3 2014-05-12T14:00:33.677-0700: 1.969 2 ## 4 2014-05-12T14:00:35.538-0700: 3.830 3 ## 5 2014-05-12T14:00:37.811-0700: 6.103 4 ## 6 2014-05-12T14:00:41.428-0700: 9.720 5 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 1 0 0.11 0.04 0.02 8192 1400 9437184 ## 2 0 0.05 0.01 0.02 5496 1672 9437184 ## 3 0 0.04 0.01 0.01 5768 2557 9437184 ## 4 0 0.21 0.05 0.04 22528 4907 9437184 ## 5 0 0.08 0.01 0.02 24576 7072 9437184 ## 6 0 0.26 0.06 0.04 43008 14336 9437184 Basic Statistics Once the data has been read into R, simple statistics are very easy to generate. All of the numbers from high school statistics are available via simple commands. For example, generate a summary of every column: summary(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount FullCount ## Length:8307 Min. : 1 Min. : 0 Min. : 0.0 ## Class :character 1st Qu.: 9977 1st Qu.:2048 1st Qu.: 0.0 ## Mode :character Median :12855 Median :4136 Median : 12.0 ## Mean :12527 Mean :4156 Mean : 31.6 ## 3rd Qu.:15758 3rd Qu.:6262 3rd Qu.: 61.0 ## Max. :55484 Max. :8391 Max. :113.0 ## UserTime SysTime RealTime BeforeSize ## Min. :0.040 Min. :0.0000 Min. : 0.0 Min. : 5476 ## 1st Qu.:0.470 1st Qu.:0.0300 1st Qu.: 0.1 1st Qu.:5137920 ## Median :0.620 Median :0.0300 Median : 0.1 Median :6574080 ## Mean :0.751 Mean :0.0355 Mean : 0.3 Mean :5841855 ## 3rd Qu.:0.920 3rd Qu.:0.0400 3rd Qu.: 0.2 3rd Qu.:7084032 ## Max. :3.370 Max. :1.5600 Max. :488.1 Max. :8696832 ## AfterSize TotalSize ## Min. : 1380 Min. :9437184 ## 1st Qu.:5002752 1st Qu.:9437184 ## Median :6559744 Median :9437184 ## Mean :5785454 Mean :9437184 ## 3rd Qu.:7054336 3rd Qu.:9437184 ## Max. :8482816 Max. :9437184 Q: What is the total amount of User CPU time spent in garbage collection? sum(g1gc.df$UserTime) ## [1] 6236 As you can see, less than two hours of CPU time was spent in garbage collection. Is that too much? To find the percentage of time spent in garbage collection, divide the number above by total_elapsed_time*CPU_count. In this case, there are a lot of CPU’s and it turns out the the overall amount of CPU time spent in garbage collection isn’t a problem when viewed in isolation. When calculating rates, i.e. events per unit time, you need to ask yourself if the rate is homogenous across the time period in the log file. Does the log file include spikes of high activity that should be separately analyzed? Averaging in data from nights and weekends with data from business hours may alias problems. If you have a reason to suspect that the garbage collection rates include peaks and valleys that need independent analysis, see the “Time Series” section, below. Q: How much garbage is collected on each pass? The amount of heap space that is recovered per GC pass is surprisingly low: At least one collection didn’t recover any data. (“Min.=0”) 25% of the passes recovered 3MB or less. (“1st Qu.=3072”) Half of the GC passes recovered 4MB or less. (“Median=4096”) The average amount recovered was 56MB. (“Mean=56390”) 75% of the passes recovered 36MB or less. (“3rd Qu.=36860”) At least one pass recovered 2GB. (“Max.=2121000”) g1gc.df$Delta = g1gc.df$BeforeSize - g1gc.df$AfterSize summary(g1gc.df$Delta) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0 3070 4100 56400 36900 2120000 Q: What is the maximum User CPU time for a single collection? The worst garbage collection (“Max.”) is many standard deviations away from the mean. The data appears to be right skewed. summary(g1gc.df$UserTime) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0.040 0.470 0.620 0.751 0.920 3.370 sd(g1gc.df$UserTime) ## [1] 0.3966 Basic Graphics Once the data is in R, it is trivial to plot the data with formats including dot plots, line charts, bar charts (simple, stacked, grouped), pie charts, boxplots, scatter plots histograms, and kernel density plots. Histogram of User CPU Time per Collection I don't think that this graph requires any explanation. hist(g1gc.df$UserTime, main="User CPU Time per Collection", xlab="Seconds", ylab="Frequency") Box plot to identify outliers When the initial data is viewed with a box plot, you can see the one crazy outlier in the real time per GC. Save this data point for future analysis and drop the outlier so that it’s not throwing off our statistics. Now the box plot shows many outliers, which will be examined later, using times series analysis. Notice that the scale of the x-axis changes drastically once the crazy outlier is removed. par(mfrow=c(2,1)) boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(dominated by a crazy outlier)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") crazy.outlier.df=g1gc.df[g1gc.df$RealTime > 400,] g1gc.df=g1gc.df[g1gc.df$RealTime < 400,] boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(crazy outlier excluded)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") box(which = "outer", lty = "solid") Here is the crazy outlier for future analysis: crazy.outlier.df ## row.names SecondsSinceLaunch IncrementalCount ## 8233 2014-05-12T23:15:43.903-0700: 20741 8316 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 8233 112 0.55 0.42 488.1 8381440 8235008 9437184 ## Delta ## 8233 146432 R Time Series Data To analyze the garbage collection as a time series, I’ll use Z’s Ordered Observations (zoo). “zoo is the creator for an S3 class of indexed totally ordered observations which includes irregular time series.” require(zoo) ## Loading required package: zoo ## ## Attaching package: 'zoo' ## ## The following objects are masked from 'package:base': ## ## as.Date, as.Date.numeric head(g1gc.df[,1]) ## [1] "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" ## [3] "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ## [5] "2014-05-12T14:00:37.811-0700:" "2014-05-12T14:00:41.428-0700:" options("digits.secs"=3) times=as.POSIXct( g1gc.df[,1], format="%Y-%m-%dT%H:%M:%OS%z:") g1gc.z = zoo(g1gc.df[,-c(1)], order.by=times) head(g1gc.z) ## SecondsSinceLaunch IncrementalCount FullCount ## 2014-05-12 17:00:32.868 1.161 0 0 ## 2014-05-12 17:00:33.178 1.472 1 0 ## 2014-05-12 17:00:33.677 1.969 2 0 ## 2014-05-12 17:00:35.538 3.830 3 0 ## 2014-05-12 17:00:37.811 6.103 4 0 ## 2014-05-12 17:00:41.427 9.720 5 0 ## UserTime SysTime RealTime BeforeSize AfterSize ## 2014-05-12 17:00:32.868 0.11 0.04 0.02 8192 1400 ## 2014-05-12 17:00:33.178 0.05 0.01 0.02 5496 1672 ## 2014-05-12 17:00:33.677 0.04 0.01 0.01 5768 2557 ## 2014-05-12 17:00:35.538 0.21 0.05 0.04 22528 4907 ## 2014-05-12 17:00:37.811 0.08 0.01 0.02 24576 7072 ## 2014-05-12 17:00:41.427 0.26 0.06 0.04 43008 14336 ## TotalSize Delta ## 2014-05-12 17:00:32.868 9437184 6792 ## 2014-05-12 17:00:33.178 9437184 3824 ## 2014-05-12 17:00:33.677 9437184 3211 ## 2014-05-12 17:00:35.538 9437184 17621 ## 2014-05-12 17:00:37.811 9437184 17504 ## 2014-05-12 17:00:41.427 9437184 28672 Example of Two Benchmark Runs in One Log File The data in the following graph is from a different log file, not the one of primary interest to this article. I’m including this image because it is an example of idle periods followed by busy periods. It would be uninteresting to average the rate of garbage collection over the entire log file period. More interesting would be the rate of garbage collect in the two busy periods. Are they the same or different? Your production data may be similar, for example, bursts when employees return from lunch and idle times on weekend evenings, etc. Once the data is in an R Time Series, you can analyze isolated time windows. Clipping the Time Series data Flashing back to our test case… Viewing the data as a time series is interesting. You can see that the work intensive time period is between 9:00 PM and 3:00 AM. Lets clip the data to the interesting period:     par(mfrow=c(2,1)) plot(g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Complete Log File", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") clipped.g1gc.z=window(g1gc.z, start=as.POSIXct("2014-05-12 21:00:00"), end=as.POSIXct("2014-05-13 03:00:00")) plot(clipped.g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Limited to Benchmark Execution", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") box(which = "outer", lty = "solid") Cumulative Incremental and Full GC count Here is the cumulative incremental and full GC count. When the line is very steep, it indicates that the GCs are repeating very quickly. Notice that the scale on the Y axis is different for full vs. incremental. plot(clipped.g1gc.z[,c(2:3)], main="Cumulative Incremental and Full GC count", xlab="Time of Day", col="#1b9e77") GC Analysis of Benchmark Execution using Time Series data In the following series of 3 graphs: The “After Size” show the amount of heap space in use after each garbage collection. Many Java objects are still referenced, i.e. alive, during each garbage collection. This may indicate that the application has a memory leak, or may indicate that the application has a very large memory footprint. Typically, an application's memory footprint plateau's in the early stage of execution. One would expect this graph to have a flat top. The steep decline in the heap space may indicate that the application crashed after 2:00. The second graph shows that the outliers in real execution time, discussed above, occur near 2:00. when the Java heap seems to be quite full. The third graph shows that Full GCs are infrequent during the first few hours of execution. The rate of Full GC's, (the slope of the cummulative Full GC line), changes near midnight.   plot(clipped.g1gc.z[,c("AfterSize","RealTime","FullCount")], xlab="Time of Day", col=c("#1b9e77","red","#1b9e77")) GC Analysis of heap recovered Each GC trace includes the amount of heap space in use before and after the individual GC event. During garbage coolection, unreferenced objects are identified, the space holding the unreferenced objects is freed, and thus, the difference in before and after usage indicates how much space has been freed. The following box plot and bar chart both demonstrate the same point - the amount of heap space freed per garbage colloection is surprisingly low. par(mfrow=c(2,1)) boxplot(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", horizontal = TRUE, col="red") hist(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", breaks=100, col="red") box(which = "outer", lty = "solid") This graph is the most interesting. The dark blue area shows how much heap is occupied by referenced Java objects. This represents memory that holds live data. The red fringe at the top shows how much data was recovered after each garbage collection. barplot(clipped.g1gc.z[,c("AfterSize","Delta")], col=c("#7570b3","#e7298a"), xlab="Time of Day", border=NA) legend("topleft", c("Live Objects","Heap Recovered on GC"), fill=c("#7570b3","#e7298a")) box(which = "outer", lty = "solid") When I discuss the data in the log files with the customer, I will ask for an explaination for the large amount of referenced data resident in the Java heap. There are two are posibilities: There is a memory leak and the amount of space required to hold referenced objects will continue to grow, limited only by the maximum heap size. After the maximum heap size is reached, the JVM will throw an “Out of Memory” exception every time that the application tries to allocate a new object. If this is the case, the aplication needs to be debugged to identify why old objects are referenced when they are no longer needed. The application has a legitimate requirement to keep a large amount of data in memory. The customer may want to further increase the maximum heap size. Another possible solution would be to partition the application across multiple cluster nodes, where each node has responsibility for managing a unique subset of the data. Conclusion In conclusion, R is a very powerful tool for the analysis of Java garbage collection log files. The primary difficulty is data cleansing so that information can be read into an R data frame. Once the data has been read into R, a rich set of tools may be used for thorough evaluation.

    Read the article

  • How to enable gzip HTTP compression on Windows Azure dynamic content

    - by Steven
    Hi all, I've been trying unsuccessfully to enable gzip HTTP compression on my Windows Azure hosted WCF Restful service which returns JSON only from GET and POST requests. I have tried so many things that I would have a hard time listing all of them, and I now realise I have been working with conflicting information (regarding old version of azure etc) so think it best to start with a clean slate! I am working with Visual Studio 2008, using the February 2010 tools for Visual Studio. So, according to the following link, HTTP compression has now been enabled .. http://msdn.microsoft.com/en-us/library/ff436045.aspx ... and I've used the advice at the following page (the URL compression advice only), but I get no compression. http://blog.smarx.com/posts/iis-compression-in-windows-azure <urlCompression doStaticCompression="true" doDynamicCompression="false" dynamicCompressionBeforeCache="true" /> It doesn't help that I don't know what the difference is between urlCompression and httpCompression. I've tried to find out but to no avail! Could the fact that the tools for Visual Studio were released before the version of Azure which supports compression be a problem? I read somewhere that with the latest tools, you can choose which version of Azure OS you want to use when you publish ... but I don't know if that's true, and if it is, I can't find where to choose. Could I be using a pre-http enabled version? I've also tried blowery http compression module, but no results. Does any one have any up-to-date advice on how to achieve this? i.e. advice that relates to the current version of the Azure OS. Cheers! Steven

    Read the article

  • C# WebBrowser.ShowPrintDialog() not showing

    - by jeah_wicer
    I have this peculiar problem while wanting to print a html-report. The file itself is a normal local html file, located on my hard drive. To do this, I have tried the following: public static void PrintReport(string path) { WebBrowser wb = new WebBrowser(); wb.Navigate(path); wb.ShowPrintDialog() } And I have this form with a button with the click event: private void button1_Click(object sender, EventArgs e) { string path = @"D:\MyReport.html"; PrintReport(path); } This does absolutely nothing. Which is kind of strange... but things get stranger... When editing the print function to do the following: public static void PrintReport(string path) { WebBrowser wb = new WebBrowser(); wb.Navigate(path); MessageBox.Show("TEST"); wb.ShowPrintDialog() } It works. Yes, only adding a MessageBox. The MessageBox is showing and after it comes the print dialog. I have also tried with Thread.Sleep(1000) instead, which doesn't work. Can anyone explain to me what's going on here? Why would a messagebox make any difference? Can it be some kind of permission problem? I've reproduced this on both Windows 7 and 8, same thing. I made this small application with only the above code to isolate the problem. I am quite sure it works on windows XP though, since an older version of the application I'm working on runs on it. When trying to do this directly with the mshtml-dll instead I also get problems. Any input or clarification is greatly appreciated!

    Read the article

  • Exception "The operation is not valid for the state of the transaction" using TransactionScope

    - by Lanfear
    We have a web service on server #1 and a database on server #2. Web service uses transaction scope to produce distributed transaction. Everything is correct. And we have another database on server #3. We had some problems with this server and we reinstalled operation system and software. We configured MSDTC and tried to use web service from server #1 to communicate with database on this server. And now after first select statement within transaction scope we get: "The operation is not valid for the state of the transaction". This exception falls in every web service request if it is using transaction scope. Server #2 and Server #3 is almost similar. The difference can be only in settings. .NET framework 3.5 SP1 installed and SQL Server SP3 on all servers. Full stacktrace: System.Transactions.TransactionState.EnlistPromotableSinglePhase(InternalTransaction tx, IPromotableSinglePhaseNotification promotableSinglePhaseNotification, Transaction atomicTransaction) ? System.Transactions.Transaction.EnlistPromotableSinglePhase(IPromotableSinglePhaseNotification promotableSinglePhaseNotification) ? System.Data.SqlClient.SqlInternalConnection.EnlistNonNull(Transaction t ? System.Data.SqlClient.SqlInternalConnection.Enlist(Transaction t ? System.Data.SqlClient.SqlInternalConnectionTds.Activate(Transaction transaction) ? System.Data.ProviderBase.DbConnectionInternal.ActivateConnection(Transaction transaction) ? System.Data.ProviderBase.DbConnectionPool.GetConnection(DbConnection owningObject) ? System.Data.ProviderBase.DbConnectionFactory.GetConnection(DbConnection owningConnection) ? System.Data.ProviderBase.DbConnectionClosed.OpenConnection(DbConnection outerConnection, DbConnectionFactory connectionFactory) ? System.Data.SqlClient.SqlConnection.Open() ? NHibernate.Connection.DriverConnectionProvider.GetConnection() ? NHibernate.Impl.SessionFactoryImpl.OpenConnection() I searched this message but didn't found any appropriate solution. So what settings should I check and what exactly should I do to fix it?

    Read the article

  • Core Data migration problem: "Persistent store migration failed, missing source managed object model

    - by John Gallagher
    The Background A Cocoa Non Document Core Data project with two Managed Object Models. Model 1 stays the same. Model 2 has changed, so I want to migrate the store. I've created a new version by Design Data Model Add Model Version in Xcode. The difference between versions is a single relationship that's been changed from to a one to many. I've made my changes to the model, then saved. I've made a new Mapping Model that has the old model as a source and new model as a destination. I've ensured all Mapping Models and Data Models and are being compiled and all are copied to the Resource folder of my app bundle. I've switched on migrations by passing in a dictionary with the NSMigratePersistentStoresAutomaticallyOption key as [NSNumber numberWithBool:YES] when adding the Persistent Store. Rather than merging all models in the bundle, I've specified the two models I want to use (model 1 and the new version of model 2) and merged them using modelByMergingModels: The Problem No matter what I do to migrate, I get the error message: "Persistent store migration failed, missing source managed object model." What I've Tried I clean after every single build. I've tried various combinations of having only the model I'm migrating to in Resources, being compiled, or both. Since the error message implies it can't find the source model for my migration, I've tried having every version of the model in both the Resources folder and being compiled. I've made sure I'm not making a really basic error by switching back to the original version of my data model. The app runs fine. I've deleted the Mapping Model and the new version of the model, cleaned, then recreated both. I've tried making a different change in the new model - deleting an entity instead. I'm at my wits end. I can't help but think I've made a huge mistake somewhere that I'm not seeing. Any ideas?

    Read the article

  • Ninject.Web, OnePerRequestModule, and IIS7 Integrated Pipeline

    - by Ted
    Using Ninject.Web with ASP.NET WebForms project. Works without issues using classic pipeline, but when it's under integrated pipeline, a null reference exception occurs on every request (which I've narrowed down to the use of the OnePerRequestModule): [NullReferenceException: Object reference not set to an instance of an object.] System.Web.PipelineStepManager.ResumeSteps(Exception error) +1216 System.Web.HttpApplication.BeginProcessRequestNotification(HttpContext context, AsyncCallback cb) +113 System.Web.HttpRuntime.ProcessRequestNotificationPrivate(IIS7WorkerRequest wr, HttpContext context) +616 The above always occurs unless I remove the OnePerRequestModule initializization. occurs consistently on a very basic test app I put together. On a standard app where I actually want to implement it, I can solve the issue by initializing the OnePerRequestModule like so: protected override IKernel CreateKernel() { // This will always blow up. //var module = new OnePerRequestModule(); //module.Init(this); IKernel kernel = new StandardKernel(new MyModule()); // This works on larger app, but on basic app, it makes no difference under integrated pipeline as the above exception is always thrown. var module = new OnePerRequestModule(); module.Init(this); return kernel; } Before I start spelunking further, is anybody out there using Ninject.Web extension successfully under the integrated pipeline in IIS7 AND using the OnePerRequestModule? There are certain restrictions for modules under the integrated pipeline that weren't there in previous IIS versions/classic pipeline. Quickly thrown together sample project at http://www.filedropper.com/test_59 And in case it's not obvious with Ninject.Web: it's an ASP.NET WebForms project.

    Read the article

  • jqGrid dynamic select option

    - by Jo
    I'm creating a jqgrid with drop down columns and I'm using cell editing. I need the options of the drop down columns to change dynamically and I've tried implementing this by setting the column to be: { name: "AccountLookup", index: "AccountLookup", width: 90, editable: true, resizable: true, edittype: "select", formatter: "select" }, and then in the beforeCellEdit event I have: beforeEditCell: function(id, name, val, iRow, iCol) { if(name=='AccountLookup') { var listdata = GetLookupValues(id, name); if (listdata == null) listdata = "1:1"; jQuery("#grid").setColProp(name, { editoptions: { value: listdata.toString()} }) } }, GetLookupValues just returns a string in the format "1:One;2:Two" etc. That works fine however the options are populated one click behind - ie i click on AccountID in row 1, and the dropdown is empty, however when I then click on AccountID in row 3 the options I set in the row 1 click are shown in the row 3 click. And so on. So always one click behind. Is there another way of achieving what I need? Bacially the dropdown options displayed are always changing and I need to load them as user enters the cell for editing. Perhaps I can somehow get at the select control in the beforeEditCell event and manually enter its values instead of using the setColProp call? If so could I get an example of doing that please? Another thing - if the dropdown is empty and a user doesn't cancel the cell edit, the grid script throws an error. I'm using clientarray editing if that makes a difference. Greatly appreciate any help. Regards, Jo

    Read the article

  • Why is ValidateInput(False) not working?

    - by xenosyde
    I am converting an application I created using webforms to the asp.net mvc framework using vb.net. I have a problem with one of my views. I get the yellow screen of death saying "A potentially dangerous Request.Form value was detected from the client" when I submit my form. I am using tinymce as my RTE. I have set on the view itself ValidateRequest="false" I know that in MVC it doesn't respect it on the view from what I've read so far. So I put it on the controller action as well. I have tried different setups: <ValidateInput(False), AcceptVerbs(HttpVerbs.Post)> _ ...and... <AcceptVerbs(HttpVerbs.Post), ValidateInput(False)> _ ...and like this as well... <ValidateInput(False)> _ <AcceptVerbs(HttpVerbs.Post)> _ Just to see if it made a difference, yet I still get the yellow screen of death. I only want to set it for this view and the specific action in my controller that my post pertains to. Am I missing something?

    Read the article

  • High Profile ASP.NET websites

    - by nandos
    About twice a month I get asked to justify the reason "Why are we using ASP.NET and not PHP or Java, or buzz-word-of-the-month-here, etc". 100% of the time the questions come from people that do not understand anything about technology. People that would not know the difference between FTP and HTTP. The best approach I found (so far) to justify it to people without getting into technical details is to just say "XXX website uses it". Which I get back "Oh...I did not know that, so ASP.NET must be good". I know, I know, it hurts. But it works. So, without getting into the merit of why I'm using ASP.NET (which could trigger an endless argument for other platforms), I'm trying to compile a list of high profile websites that are implemented in ASP.NET. (No, they would have no idea what StackOverflow is). Can you name a high-profile website implemented in ASP.NET? EDIT: Current list (thanks for all the responses): (trying to avoid tech sites and prioritizing retail sites) Costco - http://www.costco.com/ Crate & Barrel - http://www.crateandbarrel.com/ Home Shopping Network - http://www.hsn.com/ Buy.com - http://www.buy.com/ Dell - http://www.dell.com Nasdaq - http://www.nasdaq.com/ Virgin - http://www.virgin.com/ 7-Eleven - http://www.7-eleven.com/ Carnival Cruise Lines - http://www.carnival.com/ L'Oreal - http://www.loreal.com/ The White House - http://www.whitehouse.gov/ Remax - http://www.remax.com/ Monster Jobs - http://www.monster.com/ USA Today - http://www.usatoday.com/ ComputerJobs.com - http://computerjobs.com/ Match.com - http://www.match.com National Health Services (UK) - http://www.nhs.uk/ CarrerBuilder.com - http://www.careerbuilder.com/

    Read the article

  • DataView.RowFilter Vs DataTable.Select() vs DataTable.Rows.Find()

    - by Aseem Gautam
    Considering the code below: Dataview someView = new DataView(sometable) someView.RowFilter = someFilter; if(someView.count > 0) { …. } Quite a number of articles which say Datatable.Select() is better than using DataViews, but these are prior to VS2008. Solved: The Mystery of DataView's Poor Performance with Large Recordsets Array of DataRecord vs. DataView: A Dramatic Difference in Performance Googling on this topic I found some articles/forum topics which mention Datatable.Select() itself is quite buggy(not sure on this) and underperforms in various scenarios. On this(Best Practices ADO.NET) topic on msdn it is suggested that if there is primary key defined on a datatable the findrows() or find() methods should be used insted of Datatable.Select(). This article here (.NET 1.1) benchmarks all the three approaches plus a couple more. But this is for version 1.1 so not sure if these are valid still now. Accroding to this DataRowCollection.Find() outperforms all approaches and Datatable.Select() outperforms DataView.RowFilter. So I am quite confused on what might be the best approach on finding rows in a datatable. Or there is no single good way to do this, multiple solutions exist depending upon the scenario?

    Read the article

  • adding UIImageView to UIScrollView throws exception cocoa touch for iPad

    - by Brodie4598
    I am a noob at OBJ-C :) I am trying to add a UIImageView to a UIScrollView to display a large image in my iPad app. I have followed the tutorial here exactly: http://howtomakeiphoneapps.com/2009/12/how-to-use-uiscrollview-in-your-iphone-app/ The only difference is that in my App the View is in a seperate tab and I am using a different image. here is my code: - (void)viewDidLoad { [super viewDidLoad]; UIImageView *tempImageView = [[UIImageView alloc] initWithImage:[UIImage imageNamed:@"Cheyenne81"]]; self.imageView = tempImageView; [tempImageView release]; scrollView.contentSize = CGSizeMake(imageView.frame.size.width, imageView.frame.size.height); scrollView.maximumZoomScale = 4.0; scrollView.minimumZoomScale = 0.75; scrollView.clipsToBounds = YES; scrollView.delegate = self; [scrollView addSubview:imageView]; } - (UIView *)viewForZoomingInScrollView:(UIScrollView *)scrollView{ return imageView; } and: @interface UseScrollViewViewController : UIViewController<UIScrollViewDelegate>{ IBOutlet UIScrollView *scrollView; UIImageView *imageView; } @property (nonatomic, retain) UIScrollView *scrollView; @property (nonatomic, retain) UIImageView *imageView; @end I then create a UIScrollView in Interface Builder and link it to the scrollView outlet. Thats when I get the problem. When I run the program it crashes instantly. If I run it without linking the scrollView to the outlet, it will run (allbeit with a blnk screen). The following is the error I get in the console: 2010-03-27 20:18:13.467 UseScrollViewViewController[7421:207] * Terminating app due to uncaught exception 'NSUnknownKeyException', reason: '[ setValue:forUndefinedKey:]: this class is not key value coding-compliant for the key scrollView.'

    Read the article

  • -[UIImage drawInRect:] / CGContextDrawImage() not releasing memory?

    - by sohocoke
    I wanted to easily blend a UIImage on top of another background image, so wrote a category method for UIImage, adapted from http://stackoverflow.com/questions/1309757/blend-two-uiimages : - (UIImage *) blendedImageOn:(UIImage *) backgroundImage { NSAutoreleasePool* pool = [[NSAutoreleasePool alloc] init]; UIGraphicsBeginImageContext(backgroundImage.size); CGRect rect = CGRectMake(0, 0, backgroundImage.size.width, backgroundImage.size.height); [backgroundImage drawInRect:rect]; [self drawInRect:rect]; UIImage* blendedImage = UIGraphicsGetImageFromCurrentImageContext(); UIGraphicsEndImageContext(); [pool release]; return blendedImage; } Unfortunately my app that uses the above method to load around 20 images and blend them with background and gloss images (so probably around 40 calls), is being jettisoned on the device. An Instruments session revealed that calls to malloc stemming from the calls to drawInRect: are responsible for the bulk of the memory usage. I tried replacing the drawInRect: messages with equivalent function calls to the function CGContextDrawImage but it didn't help. The AutoReleasePool was added after I found the memory usage problem; it also didn't make a difference. I'm thinking this is probably because I'm not using graphics contexts appropriately. Would calling the above method in a loop be a bad idea because of the number of contexts I create? Or did I simply miss something?

    Read the article

  • Do SEO-friendly URLs really affect a page's ranking?

    - by Lee Harold
    SEO-friendly URLs are all the rage these days. But do they actually have a meaningful impact on a page's ranking in Google and other search engines? If so, why? If not, why not? (Note that I would absolutely agree that SEO-friendly URLs are nicer to use for human beings. My question is whether they actually make a difference to the ranking algorithms.) Update: As it turns out, the Google post that endorphine points to here has caused tremendous confusion in the SEO community. For a sampling of the discussion, see here, here, and here. Part of the problem is that the Google post is addressing the worst case where URL rewriting is done poorly and so you'd be better off sticking with a dynamic URL rather than a mangled static "SEO-friendly" URL. There's no question dynamic URLs can be crawled by Google and can achieve high rankings. Maybe it would be easier to reframe the question more concretely: given 2 otherwise equivalent pages, which will rank higher for the search "do seo friendly urls really affect page ranking"? A) http://stackoverflow.com/questions/505793/do-seo-friendly-urls-really-affect-a-pages-ranking or B) http://stackoverflow.com?question=505793 (a fake URL for comparison only)

    Read the article

  • Can plugins loaded with MEF resolve their own internal dependencies with the same MEF container for

    - by Dave
    From my experimentation, I think the answer is "kind of", but I could have made a mistake. I have an application that loads appliance plugins with MEF. That part is working fine. Now let's say that my BlenderAppliance wants to resolve several of its dependencies with MEF, which each implement IApplianceFeature. I've just used the ImportMany attribute to my plugin. I made sure to create the plugin using MEF so that the Imports work properly. I said "kind of" because some of the plugin's internals (i.e. the model) are loading with MEF just fine, but the IApplianceFeatures aren't. The difference here is that the IApplianceFeatures are themselves, assemblies. And at the moment, they are in one folder above that of the plugin itself, i.e. + application folder | IApplianceFeature1.dll | IApplianceFeature2.dll +---+ plugin folder | BlenderAppliance.dll Now if my application uses an AggregateCatalog to load the "." and ".\plugins" folders, why doesn't it ever load the IApplianceFeature assemblies for me? Is it possible / advisable to have the plugin create its own MEF container to resolve its dependencies, or does really nasty stuff happen? If you have any stories about this scenario, please share. :)

    Read the article

  • Linq to SQL EntitySet Binding the MVVM way

    - by Savvas Sopiadis
    Hi everybody! In a WPF application i'm using LINQ to SQL classes (created by SQL Metal, thus implementing POCOs). Let's assume i have a table User and a Table Pictures. These pictures are actually created from one picture, the difference between them may be the size, coloring,... So every user may has more than one Pictures, so the association is 1:N (User:Pictures). My problems: a) how do i bind, in a MVVM manner, a picture control to one picture (i will take one specific picture) in the EntitySet, to show it up? b) everytime a user changes her picture the whole EntitySet should be thrown away and the newly created Picture(s) should be a added. Is this the correct way? e.g. //create the 1st piture object UserPicture1 = new UserPicture(); UserPicture1.Description = "... some description.. "; USerPicture1.Image = imgBytes; //array of bytes //create the 2nd piture object UserPicture2 = new UserPicture(); UserPicture2.Description = "... another description.. "; UserPicture2.Image = DoSomethingWithPreviousImg(imgBytes); //array of bytes //Assuming that the entityset is called Pictures //add these pictures to the corresponding user User.Pictures.Add(UserPicture1); User.Pictures.Add(UserPicture2); //save changes datacontext.Save() Thanks in advance

    Read the article

  • Why were namespaces removed from ECMAScript consideration?

    - by Bob
    Namespaces were once a consideration for ECMAScript (the old ECMAScript 4) but were taken out. As Brendan Eich says in this message: One of the use-cases for namespaces in ES4 was early binding (use namespace intrinsic), both for performance and for programmer comprehension -- no chance of runtime name binding disagreeing with any earlier binding. But early binding in any dynamic code loading scenario like the web requires a prioritization or reservation mechanism to avoid early versus late binding conflicts. Plus, as some JS implementors have noted with concern, multiple open namespaces impose runtime cost unless an implementation works significantly harder. For these reasons, namespaces and early binding (like packages before them, this past April) must go. But I'm not sure I understand all of that. What exactly is a prioritization or reservation mechanism and why would either of those be needed? Also, must early binding and namespaces go hand-in-hand? For some reason I can't wrap my head around the issues involved. Can anyone attempt a more fleshed out explanation? Also, why would namespaces impose runtime costs? In my mind I can't help but see little difference in concept between a namespace and a function using closures. For instance, Yahoo and Google both have YAHOO and google objects that "act like" namespaces in that they contain all of their public and private variables, functions, and objects within a single access point. So why, then, would a namespace be so significantly different in implementation? Maybe I just have a misconception as to what a namespace is exactly.

    Read the article

  • Invalid byte 1 of 1-byte UTF-8 sequence

    - by user275886
    I have a MyFaces Facelets application, where the page coding is a bit rugged. Anyway, it's developed with Eclipse and built with Ant, and kindof runs ok in Tomcat 2.0.26. So far so good. Now, I'd rather build with Maven, so I made a couple of pom-files, opened them in Netbeans and built, and now I have a war file that deploys ok. However, on any facelet page it barfs out with com.sun.org.apache.xerces.internal.impl.io.MalformedByteSequenceException: Invalid byte 1 of 1-byte UTF-8 sequence. at com.sun.org.apache.xerces.internal.impl.io.UTF8Reader.invalidByte(UTF8Reader.java:684) at com.sun.org.apache.xerces.internal.impl.io.UTF8Reader.read(UTF8Reader.java:554) at com.sun.org.apache.xerces.internal.impl.XMLEntityScanner.load(XMLEntityScanner.java:1742) So, I've tried a lot of different things, and the application actually run simple pages without facelet stuff. But, everything runs if I just build with Ant instead ... So my question is: What's the most likely difference between an ant build and a maven build that may cause this? It also seems that even though I've configured for UTF-8 in Netbeans and pom-files, Netbeans eventually ends up reporting the facelet files as ISO-8859-1 after some editing. I've made sure that most central libs are of same version (especially xerces 2.3.0), I've added an encoding servlet filter that had no effect. And, I'd rather fix the maven build and keep the buggy pages, than the other way around ... it's my intention to introduce Naven, not fix buggy pages.

    Read the article

  • Visual Studio 2010 Crashes when Creating or Editing a Report (.rdlc) with the Report Designer

    - by ondesertverge
    This is an issue I had with VS 2010 RC and was hoping would be solved with the first official release. Sadly it wasn't. What I have is a number of reports originally created with VS 2008. When opening any of these for editing in VS 2010's Report Designer VS hangs for about two minutes and then shuts down. Same happens when creating a new report using the wizard. Only difference is that a dialog opens up showing a "Loading ..." message then hangs for about the same amount of time and crashes. Running devenv /log gives nothing of value. The Windows Application Event Viewer shows only this: Faulting application name: devenv.exe, version: 10.0.30319.1, time stamp: 0x4ba1fab3 Faulting module name: clr.dll, version: 4.0.30319.1, time stamp: 0x4ba1d9ef Exception code: 0xc00000fd Fault offset: 0x00001919 Faulting process id: 0xc38 Faulting And this: .NET Runtime version 2.0.50727.4927 - Fatal Execution Engine Error (6F551CF2) (0) Has anyone else experienced this and found a solution? OR -- Is there a better tool for rapidly creating decent reports within a WinForms app? Help would be greatly appreciated!

    Read the article

  • Drawing custom graphics on the iPhone: CALayer vs. CGContext

    - by Henry Cooke
    Hi all, I have an application in which I'm doing some custom drawing, a bunch of lines on a gradient background, like so (ignore the text, they're just UILabels): At the moment, that's all done by starting a new CGContext, drawing stuff into it with CGContextDrawLinearGradient and CGContextStrokePath, then finally saving the resulting image with UIGraphicsGetImageFromCurrentImageContext. The positioning info is calculated while I'm laying out those labels, so it'd be a PITA (and duplication of effort) to calculate it all over again when the containing UIView is drawn with drawRect, so I'm drawing it ahead of time into a UIImage. All works fine, so far so good. However, I have a sneaking suspicion that it may be more efficient to use CALayers to do this drawing. My (cursory) understanding of the difference between the two approaches is that a CALayer is more like a bunch of instructions to draw stuff, and so takes up less memory until it's actually drawn onscreen, whereas drawing everything into a UIImage ahead of time means that you've got a sodding great bitmap kicking around in memory all the time, whether it's drawn or not. Is that a correct understanding? What is generally considered to be the best way of drawing custom images on the iPhone?

    Read the article

  • Diffence between FQL query and Graph API object access

    - by jwynveen
    What's the difference between accessing user data with the Facebook Graph API (http://graph.facebook.com/btaylor) and using the Graph API to make a FQL query of the same user (https://api.facebook.com/method/fql.query?query=QUERY). Also, does anyone know which of them the Facebook Developer Toolkit (for ASP.NET) uses? The reason I ask is because I'm trying to access the logged in user's birthday after they begin a Facebook Connect session on my site, but when I use the toolkit it doesn't return it. However, if I make a manual call to the Graph API for that user object, it does return it. It's possible I might have something wrong with my call from the toolkit. I think I may need to include the session key, but I'm not sure how to get it. Here's the code I'm using: _connectSession = new ConnectSession(APPLICATION_KEY, SECRET_KEY); try { if (!_connectSession.IsConnected()) { // Not authenticated, proceed as usual. statusResponse = "Please sign-in with Facebook."; } else { // Authenticated, create API instance _facebookAPI = new Api(_connectSession); // Load user user user = _facebookAPI.Users.GetInfo(); statusResponse = user.ToString(); ViewData["fb_user"] = user; } } catch (Exception ex) { //An error happened, so disconnect session _connectSession.Logout(); statusResponse = "Please sign-in with Facebook."; }

    Read the article

  • Vimdiff with git mergetool error: "More than two buffers in diff mode"

    - by Elizabeth Buckwalter
    I've read Vimdiff and Viewing differences with Vimdiff plus doing various google searches using things like "vimdiff multiple", "vimdiff git", "vimdiff commands" etc. When using do or diffg I get the error "More than two buffers in diff mode, don't know which one to use". When using diffg v:fname_in I get "No matching buffer for v:fname_in". From the vimdiff documentation: :[range]diffg[et] [bufspec] Modify the current buffer to undo difference with another buffer. If [bufspec] is given, that buffer is used. If [bufspec] refers to the current buffer then nothing happens. Otherwise this only works if there is one other buffer in diff mode. and more: When 'diffexpr' is not empty, Vim evaluates to obtain a diff file in the format mentioned. These variables are set to the file names used: v:fname_in original file v:fname_new new version of the same file v:fname_out resulting diff file So, I need to get the name of bufspec, but the default variables (fname_in, fname_new, and fname_out) aren't set. I ran the command git mergetool on a linux box through a terminal.

    Read the article

  • how to use nokogiri methods .xpath & .at_xpath

    - by Radek
    I'm learning how to use nokogiri and few questions came to me based on the code below require 'rubygems' require 'mechanize' post_agent = WWW::Mechanize.new post_page = post_agent.get('http://www.vbulletin.org/forum/showthread.php?t=230708') puts "\nabsolute path with tbody gives nil" puts post_page.parser.xpath('/html/body/div/div/div/div/div/table/tbody/tr/td/div[2]').xpath('text()').to_s.strip.inspect puts "\n.at_xpath gives an empty string" puts post_page.parser.at_xpath("//div[@id='posts']/div/table/tr/td/div[2]").at_xpath('text()').to_s.strip.inspect puts "\ntwo lines solution with .at_xpath gives an empty string" rows = post_page.parser.xpath("//div[@id='posts']/div/table/tr/td/div[2]") puts rows[0].at_xpath('text()').to_s.strip.inspect puts puts "two lines working code" rows = post_page.parser.xpath("//div[@id='posts']/div/table/tr/td/div[2]") puts rows[0].xpath('text()').to_s.strip puts "\none line working code" puts post_page.parser.xpath("//div[@id='posts']/div/table/tr/td/div[2]")[0].xpath('text()').to_s.strip puts "\nanother one line code" puts post_page.parser.at_xpath("//div[@id='posts']/div/table/tr/td/div[2]").xpath('text()').to_s.strip puts "\none line code with full path" puts post_page.parser.xpath("/html/body/div/div/div/div/div/table/tr/td/div[2]")[0].xpath('text()').to_s.strip is it better to use // or / in xpath? @AnthonyWJones says that 'the use of an unprefixed //' is not so good idea I had to remove tbody from any working xpath otherwise I got 'nil' result. How is possible to remove an element from the xpath to get things work? do I have to use .xpath twice to extract data if not using full xpath? why I cannot make .at_xpath working to extract data? it works nicely here what is the difference?

    Read the article

  • SSRS 2008 and SSAS 2008 transport error

    - by dan english
    I am testing an upgrade to SSAS 2008 and verifying existing reports working properly. I am able to get some SSRS reports that are using SSAS as a datasource to run without any issues. They are simple and only have a single dataset. The reports that I am unable to get to work correctly against SSAS 2008 have multiple datasets and have a fitler setup with a data range setup as a parameter. As soon as I setup that filter as a parameter and deploy them the report returns a "The connection either timed out or was lost. Unable to read data from the transport connection: An existing connection was forcibly closed by the remote host. An existing connection was forcibly closed by the remote host" message. The funny thing is that the report works fine when I run it locally in BIDS and it works fine once deployed if I point it to a SSAS 2005 server. Once I point it to the SSAS 2008 server it fails. I can get other reports to work fine, but not the ones with this type of a filter setup. I can see that the start and end date parameter MDX statements get run in the trace, but that is it. After those run then we receive the transport connection message. Another funny thing is that in the production environment the reports are working fine, but that has SSRS 2005 and SSAS 2008. Does this make sense? What could be causing this? I have tried setting the single transaction level on the datasource too, but that does not seem to make a difference.

    Read the article

  • dijit tree and focus node

    - by user220836
    Hello, I cannot get focusNode() or expandNode() get working. I also tried switching back to dojo 1.32 and even 1.3, no difference to 1.4. And I debugged with firebug, the node is a valid tree node and no errors occur but the node wont get focused. Help is VERY appreciated! <head> <script type="text/javascript"> dojo.declare("itcTree",[dijit.Tree], { focusNodeX : function(/* string */ id) { var node=this._itemNodesMap[id]; this.focusNode(node); } }); </script> </head> <body class="tundra"> <div dojoType="dojo.data.ItemFileReadStore" jsId="continentStore" url="countries.json"> </div> <div dojoType="dijit.tree.ForestStoreModel" jsId="continentModel" store="continentStore" query="{type:'continent'}" rootId="continentRoot" rootLabel="Continents" childrenAttrs="children"> </div> <div dojoType="itcTree" id="mytree" model="continentModel" openOnClick="true"> <script type="dojo/method" event="onClick" args="item"> dijit.byId('mytree').focusNodeX('AF'); </script> </div> <p> <button onclick="dijit.byId('mytree').focusNode('DE');">klick</button> </p> </body>

    Read the article

< Previous Page | 260 261 262 263 264 265 266 267 268 269 270 271  | Next Page >