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  • New Wine in New Bottles

    - by Tony Davis
    How many people, when their car shows signs of wear and tear, would consider upgrading the engine and keeping the shell? Even if you're cash-strapped, you'll soon work out the subtlety of the economics, the cost of sudden breakdowns, the precious time lost coping with the hassle, and the low 'book value'. You'll generally buy a new car. The same philosophy should apply to database systems. Mainstream support for SQL Server 2005 ends on April 12; many DBAS, if they haven't done so already, will be considering the migration to SQL Server 2008 R2. Hopefully, that upgrade plan will include a fresh install of the operating system on brand new hardware. SQL Server 2008 R2 and Windows Server 2008 R2 are designed to work together. The improved architecture, processing power, and hyper-threading capabilities of modern processors will dramatically improve the performance of many SQL Server workloads, and allow consolidation opportunities. Of course, there will be many DBAs smiling ruefully at the suggestion of such indulgence. This is nothing like the real world, this halcyon place where hardware and software budgets are limitless, development and testing resources are plentiful, and third party vendors immediately certify their applications for the latest-and-greatest platform! As with cars, or any other technology, the justification for a complete upgrade is complex. With Servers, the extra cost at time of upgrade will generally pay you back in terms of the increased performance of your business applications, reduced maintenance costs, training costs and downtime. Also, if you plan and design carefully, it's possible to offset hardware costs with reduced SQL Server licence costs. In his forthcoming SQL Server Hardware book, Glenn Berry describes a recent case where he was able to replace 4 single-socket database servers with one two-socket server, saving about $90K in hardware costs and $350K in SQL Server license costs. Of course, there are exceptions. If you do have a stable, reliable, secure SQL Server 6.5 system that still admirably meets the needs of a specific business requirement, and has no security vulnerabilities, then by all means leave it alone. Why upgrade just for the sake of it? However, as soon as a system shows sign of being unfit for purpose, or is moving out of mainstream support, the ruthless DBA will make the strongest possible case for a belts-and-braces upgrade. We'd love to hear what you think. What does your typical upgrade path look like? What are the major obstacles? Cheers, Tony.

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  • Advanced 2D and 3D Design Tools in ZWCAD 2010

    Last time I introduced you my initial experiences with a powerful CAD software - ZWCAD 2010 (http://www.zwcad.org/products_download_list.php?id=107). As I continued with my testing, I found more surp... [Author: Damian Chloe - Computers and Internet - March 29, 2010]

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  • World Record Oracle E-Business Consolidated Workload on SPARC T4-2

    - by Brian
    Oracle set a World Record for the Oracle E-Business Suite Standard Medium multiple-online module benchmark using Oracle's SPARC T4-2 and SPARC T4-4 servers which ran the application and database. Oracle's SPARC T4 servers demonstrate performance leadership and world-record results on Oracle E-Business Suite Applications R12 OLTP benchmark by publishing the first result using multiple concurrent online application modules with Oracle Database 11g Release 2 running Solaris.   This results shows that a multi-tier configuration of SPARC T4 servers running the Oracle E-Business Suite R12.1.2 application and Oracle Database 11g Release 2 is capable of supporting 4,100 online users with outstanding response-times, executing a mix of complex transactions consolidating 4 Oracle E-Business modules (iProcurement, Order Management, Customer Service and HR Self-Service).   The SPARC T4-2 server in the application tier utilized about 65% and the SPARC T4-4 server in the database tier utilized about 30%, providing significant headroom for additional Oracle E-Business Suite R12.1.2 processing modules, more online users, and future growth.   Oracle E-Business Suite Applications were run in Oracle Solaris Containers on SPARC T4 servers and provides a consolidation platform for multiple E-Business instances.   Performance Landscape Multiple Online Modules (Self-Service, Order-Management, iProcurement, Customer-Service) Medium Configuration System Users AverageResponse Time 90th PercentileResponse Time SPARC T4-2 4,100 2.08 sec 2.52 sec Configuration Summary Application Tier Configuration: 1 x SPARC T4-2 server 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 3 x 300 GB internal disks Oracle Solaris 10 Oracle E-Business Suite 12.1.2 Database Tier Configuration: 1 x SPARC T4-4 server 4 x SPARC T4 processors, 3.0 GHz 256 GB memory 2 x 300 GB internal disks Oracle Solaris 10 Oracle Solaris Containers Oracle Database 11g Release 2 Storage Configuration: 1 x Sun Storage F5100 Flash Array (80 x 24 GB flash modules) Benchmark Description The Oracle R12 E-Business Suite Standard Benchmark combines online transaction execution by simulated users with multiple online concurrent modules to model a typical scenario for a global enterprise. The online component exercises the common UI flows which are most frequently used by a majority of our customers. This benchmark utilized four concurrent flows of OLTP transactions, for Order to Cash, iProcurement, Customer Service and HR Self-Service and measured the response times. The selected flows model simultaneous business activities inclusive of managing customers, services, products and employees. See Also Oracle R12 E-Business Suite Standard Benchmark Results Oracle R12 E-Business Suite Standard Benchmark Overview Oracle R12 E-Business Benchmark Description E-Business Suite Applications R2 (R12.1.2) Online Benchmark - Using Oracle Database 11g on Oracle's SPARC T4-2 and Oracle's SPARC T4-4 Servers oracle.com SPARC T4-2 Server oracle.com OTN SPARC T4-4 Server oracle.com OTN Oracle E-Business Suite oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Oracle E-Business Suite R12 medium multiple-online module benchmark, SPARC T4-2, SPARC T4, 2.85 GHz, 2 chips, 16 cores, 128 threads, 256 GB memory, SPARC T4-4, SPARC T4, 3.0 GHz, 4 chips, 32 cores, 256 threads, 256 GB memory, average response time 2.08 sec, 90th percentile response time 2.52 sec, Oracle Solaris 10, Oracle Solaris Containers, Oracle E-Business Suite 12.1.2, Oracle Database 11g Release 2, Results as of 9/30/2012.

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  • Is Unix/Linux adoption a measure of developer skill? [closed]

    - by adeptsage
    Is Linux/Unix based OS adoption for development (or recreation) a rough measure of the awareness, adaptability and/or skill of a developer, after considering factors like learning curve for effective code testing via the CLI, basic scripting, tweaking, etc. I have no intention of starting flame wars between Windows and Linux as better dev environments, and personal choice of OSes for dev, but what i do wish to know is that - will the level of adaptability of a person who uses a Unix based system be defined by the fact that he programs on a Unix based OS?

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  • Please help me give this principle a name

    - by Brent Arias
    As a designer, I like providing interfaces that cater to a power/simplicity balance. For example, I think the LINQ designers followed that principle because they offered both dot-notation and query-notation. The first is more powerful, but the second is easier to read and follow. If you disagree with my assessment of LINQ, please try to see my point anyway; LINQ was just an example, my post is not about LINQ. I call this principle "dial-able power". But I'd like to know what other people call it. Certainly some will say "KISS" is the common term. But I see KISS as a superset, or a "consumerism" practice. Using LINQ as my example again, in my view, a team of programmers who always try to use query notation over dot-notation are practicing KISS. Thus the LINQ designers practiced "dial-able power", whereas the LINQ consumers practice KISS. The two make beautiful music together. I'll give another example. Imagine a C# logging tool that has two signatures allowing two uses: void Write(string message); void Write(Func<string> messageCallback); The purpose of the two signatures is to fulfill these needs: //Every-day "simple" usage, nothing special. myLogger.Write("Something Happened" + error.ToString() ); //This is performance critical, do not call ToString() if logging is //disabled. myLogger.Write( () => { "Something Happened" + error.ToString() }); Having these overloads represents "dial-able power," because the consumer has the choice of a simple interface or a powerful interface. A KISS-loving consumer will use the simpler signature most of the time, and will allow the "busy" looking signature when the power is needed. This also helps self-documentation, because usage of the powerful signature tells the reader that the code is performance critical. If the logger had only the powerful signature, then there would be no "dial-able power." So this comes full-circle. I'm happy to keep my own "dial-able power" coinage if none yet exists, but I can't help think I'm missing an obvious designation for this practice. p.s. Another example that is related, but is not the same as "dial-able power", is Scott Meyer's principle "make interfaces easy to use correctly, and hard to use incorrectly."

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  • Why Solid-State Drives Slow Down As You Fill Them Up

    - by Chris Hoffman
    The benchmarks are clear: Solid-state drives slow down as you fill them up. Fill your solid-state drive to near-capacity and its write performance will decrease dramatically. The reason why lies in the way SSDs and NAND Flash storage work. Filling the drive to capacity is one of the things you should never do with a solid-state drive. A nearly full solid-state drive will have much slower write operations, slowing down your computer.    

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  • Save the date! Manageability Partner Community Forum at Oracle Openworld - Oct. 1st

    - by Javier Puerta
    The Exadata & Manageability Partner Communities will be celebrating a Community Forum in San Francisco during Oracle Openworld. The session will take place on Monday, October 1st, from 4:00 - 6:00 pm local time.If you would like to present an experience around a customer project or sales best practice in the Manageability or Quality & Testing areas, please contact [email protected] with a short description of your proposal.

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  • TestRail 1.0 Test Management Software released

    Gurock Software just released its new test management solution TestRail. TestRail is a web-based test case management software that helps software development teams and QA departments to efficiently manage, track and organize software testing efforts.

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  • C#/.NET Little Wonders: The Generic Func Delegates

    - by James Michael Hare
    Once again, in this series of posts I look at the parts of the .NET Framework that may seem trivial, but can help improve your code by making it easier to write and maintain. The index of all my past little wonders posts can be found here. Back in one of my three original “Little Wonders” Trilogy of posts, I had listed generic delegates as one of the Little Wonders of .NET.  Later, someone posted a comment saying said that they would love more detail on the generic delegates and their uses, since my original entry just scratched the surface of them. Last week, I began our look at some of the handy generic delegates built into .NET with a description of delegates in general, and the Action family of delegates.  For this week, I’ll launch into a look at the Func family of generic delegates and how they can be used to support generic, reusable algorithms and classes. Quick Delegate Recap Delegates are similar to function pointers in C++ in that they allow you to store a reference to a method.  They can store references to either static or instance methods, and can actually be used to chain several methods together in one delegate. Delegates are very type-safe and can be satisfied with any standard method, anonymous method, or a lambda expression.  They can also be null as well (refers to no method), so care should be taken to make sure that the delegate is not null before you invoke it. Delegates are defined using the keyword delegate, where the delegate’s type name is placed where you would typically place the method name: 1: // This delegate matches any method that takes string, returns nothing 2: public delegate void Log(string message); This delegate defines a delegate type named Log that can be used to store references to any method(s) that satisfies its signature (whether instance, static, lambda expression, etc.). Delegate instances then can be assigned zero (null) or more methods using the operator = which replaces the existing delegate chain, or by using the operator += which adds a method to the end of a delegate chain: 1: // creates a delegate instance named currentLogger defaulted to Console.WriteLine (static method) 2: Log currentLogger = Console.Out.WriteLine; 3:  4: // invokes the delegate, which writes to the console out 5: currentLogger("Hi Standard Out!"); 6:  7: // append a delegate to Console.Error.WriteLine to go to std error 8: currentLogger += Console.Error.WriteLine; 9:  10: // invokes the delegate chain and writes message to std out and std err 11: currentLogger("Hi Standard Out and Error!"); While delegates give us a lot of power, it can be cumbersome to re-create fairly standard delegate definitions repeatedly, for this purpose the generic delegates were introduced in various stages in .NET.  These support various method types with particular signatures. Note: a caveat with generic delegates is that while they can support multiple parameters, they do not match methods that contains ref or out parameters. If you want to a delegate to represent methods that takes ref or out parameters, you will need to create a custom delegate. We’ve got the Func… delegates Just like it’s cousin, the Action delegate family, the Func delegate family gives us a lot of power to use generic delegates to make classes and algorithms more generic.  Using them keeps us from having to define a new delegate type when need to make a class or algorithm generic. Remember that the point of the Action delegate family was to be able to perform an “action” on an item, with no return results.  Thus Action delegates can be used to represent most methods that take 0 to 16 arguments but return void.  You can assign a method The Func delegate family was introduced in .NET 3.5 with the advent of LINQ, and gives us the power to define a function that can be called on 0 to 16 arguments and returns a result.  Thus, the main difference between Action and Func, from a delegate perspective, is that Actions return nothing, but Funcs return a result. The Func family of delegates have signatures as follows: Func<TResult> – matches a method that takes no arguments, and returns value of type TResult. Func<T, TResult> – matches a method that takes an argument of type T, and returns value of type TResult. Func<T1, T2, TResult> – matches a method that takes arguments of type T1 and T2, and returns value of type TResult. Func<T1, T2, …, TResult> – and so on up to 16 arguments, and returns value of type TResult. These are handy because they quickly allow you to be able to specify that a method or class you design will perform a function to produce a result as long as the method you specify meets the signature. For example, let’s say you were designing a generic aggregator, and you wanted to allow the user to define how the values will be aggregated into the result (i.e. Sum, Min, Max, etc…).  To do this, we would ask the user of our class to pass in a method that would take the current total, the next value, and produce a new total.  A class like this could look like: 1: public sealed class Aggregator<TValue, TResult> 2: { 3: // holds method that takes previous result, combines with next value, creates new result 4: private Func<TResult, TValue, TResult> _aggregationMethod; 5:  6: // gets or sets the current result of aggregation 7: public TResult Result { get; private set; } 8:  9: // construct the aggregator given the method to use to aggregate values 10: public Aggregator(Func<TResult, TValue, TResult> aggregationMethod = null) 11: { 12: if (aggregationMethod == null) throw new ArgumentNullException("aggregationMethod"); 13:  14: _aggregationMethod = aggregationMethod; 15: } 16:  17: // method to add next value 18: public void Aggregate(TValue nextValue) 19: { 20: // performs the aggregation method function on the current result and next and sets to current result 21: Result = _aggregationMethod(Result, nextValue); 22: } 23: } Of course, LINQ already has an Aggregate extension method, but that works on a sequence of IEnumerable<T>, whereas this is designed to work more with aggregating single results over time (such as keeping track of a max response time for a service). We could then use this generic aggregator to find the sum of a series of values over time, or the max of a series of values over time (among other things): 1: // creates an aggregator that adds the next to the total to sum the values 2: var sumAggregator = new Aggregator<int, int>((total, next) => total + next); 3:  4: // creates an aggregator (using static method) that returns the max of previous result and next 5: var maxAggregator = new Aggregator<int, int>(Math.Max); So, if we were timing the response time of a web method every time it was called, we could pass that response time to both of these aggregators to get an idea of the total time spent in that web method, and the max time spent in any one call to the web method: 1: // total will be 13 and max 13 2: int responseTime = 13; 3: sumAggregator.Aggregate(responseTime); 4: maxAggregator.Aggregate(responseTime); 5:  6: // total will be 20 and max still 13 7: responseTime = 7; 8: sumAggregator.Aggregate(responseTime); 9: maxAggregator.Aggregate(responseTime); 10:  11: // total will be 40 and max now 20 12: responseTime = 20; 13: sumAggregator.Aggregate(responseTime); 14: maxAggregator.Aggregate(responseTime); The Func delegate family is useful for making generic algorithms and classes, and in particular allows the caller of the method or user of the class to specify a function to be performed in order to generate a result. What is the result of a Func delegate chain? If you remember, we said earlier that you can assign multiple methods to a delegate by using the += operator to chain them.  So how does this affect delegates such as Func that return a value, when applied to something like the code below? 1: Func<int, int, int> combo = null; 2:  3: // What if we wanted to aggregate the sum and max together? 4: combo += (total, next) => total + next; 5: combo += Math.Max; 6:  7: // what is the result? 8: var comboAggregator = new Aggregator<int, int>(combo); Well, in .NET if you chain multiple methods in a delegate, they will all get invoked, but the result of the delegate is the result of the last method invoked in the chain.  Thus, this aggregator would always result in the Math.Max() result.  The other chained method (the sum) gets executed first, but it’s result is thrown away: 1: // result is 13 2: int responseTime = 13; 3: comboAggregator.Aggregate(responseTime); 4:  5: // result is still 13 6: responseTime = 7; 7: comboAggregator.Aggregate(responseTime); 8:  9: // result is now 20 10: responseTime = 20; 11: comboAggregator.Aggregate(responseTime); So remember, you can chain multiple Func (or other delegates that return values) together, but if you do so you will only get the last executed result. Func delegates and co-variance/contra-variance in .NET 4.0 Just like the Action delegate, as of .NET 4.0, the Func delegate family is contra-variant on its arguments.  In addition, it is co-variant on its return type.  To support this, in .NET 4.0 the signatures of the Func delegates changed to: Func<out TResult> – matches a method that takes no arguments, and returns value of type TResult (or a more derived type). Func<in T, out TResult> – matches a method that takes an argument of type T (or a less derived type), and returns value of type TResult(or a more derived type). Func<in T1, in T2, out TResult> – matches a method that takes arguments of type T1 and T2 (or less derived types), and returns value of type TResult (or a more derived type). Func<in T1, in T2, …, out TResult> – and so on up to 16 arguments, and returns value of type TResult (or a more derived type). Notice the addition of the in and out keywords before each of the generic type placeholders.  As we saw last week, the in keyword is used to specify that a generic type can be contra-variant -- it can match the given type or a type that is less derived.  However, the out keyword, is used to specify that a generic type can be co-variant -- it can match the given type or a type that is more derived. On contra-variance, if you are saying you need an function that will accept a string, you can just as easily give it an function that accepts an object.  In other words, if you say “give me an function that will process dogs”, I could pass you a method that will process any animal, because all dogs are animals.  On the co-variance side, if you are saying you need a function that returns an object, you can just as easily pass it a function that returns a string because any string returned from the given method can be accepted by a delegate expecting an object result, since string is more derived.  Once again, in other words, if you say “give me a method that creates an animal”, I can pass you a method that will create a dog, because all dogs are animals. It really all makes sense, you can pass a more specific thing to a less specific parameter, and you can return a more specific thing as a less specific result.  In other words, pay attention to the direction the item travels (parameters go in, results come out).  Keeping that in mind, you can always pass more specific things in and return more specific things out. For example, in the code below, we have a method that takes a Func<object> to generate an object, but we can pass it a Func<string> because the return type of object can obviously accept a return value of string as well: 1: // since Func<object> is co-variant, this will access Func<string>, etc... 2: public static string Sequence(int count, Func<object> generator) 3: { 4: var builder = new StringBuilder(); 5:  6: for (int i=0; i<count; i++) 7: { 8: object value = generator(); 9: builder.Append(value); 10: } 11:  12: return builder.ToString(); 13: } Even though the method above takes a Func<object>, we can pass a Func<string> because the TResult type placeholder is co-variant and accepts types that are more derived as well: 1: // delegate that's typed to return string. 2: Func<string> stringGenerator = () => DateTime.Now.ToString(); 3:  4: // This will work in .NET 4.0, but not in previous versions 5: Sequence(100, stringGenerator); Previous versions of .NET implemented some forms of co-variance and contra-variance before, but .NET 4.0 goes one step further and allows you to pass or assign an Func<A, BResult> to a Func<Y, ZResult> as long as A is less derived (or same) as Y, and BResult is more derived (or same) as ZResult. Sidebar: The Func and the Predicate A method that takes one argument and returns a bool is generally thought of as a predicate.  Predicates are used to examine an item and determine whether that item satisfies a particular condition.  Predicates are typically unary, but you may also have binary and other predicates as well. Predicates are often used to filter results, such as in the LINQ Where() extension method: 1: var numbers = new[] { 1, 2, 4, 13, 8, 10, 27 }; 2:  3: // call Where() using a predicate which determines if the number is even 4: var evens = numbers.Where(num => num % 2 == 0); As of .NET 3.5, predicates are typically represented as Func<T, bool> where T is the type of the item to examine.  Previous to .NET 3.5, there was a Predicate<T> type that tended to be used (which we’ll discuss next week) and is still supported, but most developers recommend using Func<T, bool> now, as it prevents confusion with overloads that accept unary predicates and binary predicates, etc.: 1: // this seems more confusing as an overload set, because of Predicate vs Func 2: public static SomeMethod(Predicate<int> unaryPredicate) { } 3: public static SomeMethod(Func<int, int, bool> binaryPredicate) { } 4:  5: // this seems more consistent as an overload set, since just uses Func 6: public static SomeMethod(Func<int, bool> unaryPredicate) { } 7: public static SomeMethod(Func<int, int, bool> binaryPredicate) { } Also, even though Predicate<T> and Func<T, bool> match the same signatures, they are separate types!  Thus you cannot assign a Predicate<T> instance to a Func<T, bool> instance and vice versa: 1: // the same method, lambda expression, etc can be assigned to both 2: Predicate<int> isEven = i => (i % 2) == 0; 3: Func<int, bool> alsoIsEven = i => (i % 2) == 0; 4:  5: // but the delegate instances cannot be directly assigned, strongly typed! 6: // ERROR: cannot convert type... 7: isEven = alsoIsEven; 8:  9: // however, you can assign by wrapping in a new instance: 10: isEven = new Predicate<int>(alsoIsEven); 11: alsoIsEven = new Func<int, bool>(isEven); So, the general advice that seems to come from most developers is that Predicate<T> is still supported, but we should use Func<T, bool> for consistency in .NET 3.5 and above. Sidebar: Func as a Generator for Unit Testing One area of difficulty in unit testing can be unit testing code that is based on time of day.  We’d still want to unit test our code to make sure the logic is accurate, but we don’t want the results of our unit tests to be dependent on the time they are run. One way (of many) around this is to create an internal generator that will produce the “current” time of day.  This would default to returning result from DateTime.Now (or some other method), but we could inject specific times for our unit testing.  Generators are typically methods that return (generate) a value for use in a class/method. For example, say we are creating a CacheItem<T> class that represents an item in the cache, and we want to make sure the item shows as expired if the age is more than 30 seconds.  Such a class could look like: 1: // responsible for maintaining an item of type T in the cache 2: public sealed class CacheItem<T> 3: { 4: // helper method that returns the current time 5: private static Func<DateTime> _timeGenerator = () => DateTime.Now; 6:  7: // allows internal access to the time generator 8: internal static Func<DateTime> TimeGenerator 9: { 10: get { return _timeGenerator; } 11: set { _timeGenerator = value; } 12: } 13:  14: // time the item was cached 15: public DateTime CachedTime { get; private set; } 16:  17: // the item cached 18: public T Value { get; private set; } 19:  20: // item is expired if older than 30 seconds 21: public bool IsExpired 22: { 23: get { return _timeGenerator() - CachedTime > TimeSpan.FromSeconds(30.0); } 24: } 25:  26: // creates the new cached item, setting cached time to "current" time 27: public CacheItem(T value) 28: { 29: Value = value; 30: CachedTime = _timeGenerator(); 31: } 32: } Then, we can use this construct to unit test our CacheItem<T> without any time dependencies: 1: var baseTime = DateTime.Now; 2:  3: // start with current time stored above (so doesn't drift) 4: CacheItem<int>.TimeGenerator = () => baseTime; 5:  6: var target = new CacheItem<int>(13); 7:  8: // now add 15 seconds, should still be non-expired 9: CacheItem<int>.TimeGenerator = () => baseTime.AddSeconds(15); 10:  11: Assert.IsFalse(target.IsExpired); 12:  13: // now add 31 seconds, should now be expired 14: CacheItem<int>.TimeGenerator = () => baseTime.AddSeconds(31); 15:  16: Assert.IsTrue(target.IsExpired); Now we can unit test for 1 second before, 1 second after, 1 millisecond before, 1 day after, etc.  Func delegates can be a handy tool for this type of value generation to support more testable code.  Summary Generic delegates give us a lot of power to make truly generic algorithms and classes.  The Func family of delegates is a great way to be able to specify functions to calculate a result based on 0-16 arguments.  Stay tuned in the weeks that follow for other generic delegates in the .NET Framework!   Tweet Technorati Tags: .NET, C#, CSharp, Little Wonders, Generics, Func, Delegates

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  • Internal Mutation of Persistent Data Structures

    - by Greg Ros
    To clarify, when I mean use the terms persistent and immutable on a data structure, I mean that: The state of the data structure remains unchanged for its lifetime. It always holds the same data, and the same operations always produce the same results. The data structure allows Add, Remove, and similar methods that return new objects of its kind, modified as instructed, that may or may not share some of the data of the original object. However, while a data structure may seem to the user as persistent, it may do other things under the hood. To be sure, all data structures are, internally, at least somewhere, based on mutable storage. If I were to base a persistent vector on an array, and copy it whenever Add is invoked, it would still be persistent, as long as I modify only locally created arrays. However, sometimes, you can greatly increase performance by mutating a data structure under the hood. In more, say, insidious, dangerous, and destructive ways. Ways that might leave the abstraction untouched, not letting the user know anything has changed about the data structure, but being critical in the implementation level. For example, let's say that we have a class called ArrayVector implemented using an array. Whenever you invoke Add, you get a ArrayVector build on top of a newly allocated array that has an additional item. A sequence of such updates will involve n array copies and allocations. Here is an illustration: However, let's say we implement a lazy mechanism that stores all sorts of updates -- such as Add, Set, and others in a queue. In this case, each update requires constant time (adding an item to a queue), and no array allocation is involved. When a user tries to get an item in the array, all the queued modifications are applied under the hood, requiring a single array allocation and copy (since we know exactly what data the final array will hold, and how big it will be). Future get operations will be performed on an empty cache, so they will take a single operation. But in order to implement this, we need to 'switch' or mutate the internal array to the new one, and empty the cache -- a very dangerous action. However, considering that in many circumstances (most updates are going to occur in sequence, after all), this can save a lot of time and memory, it might be worth it -- you will need to ensure exclusive access to the internal state, of course. This isn't a question about the efficacy of such a data structure. It's a more general question. Is it ever acceptable to mutate the internal state of a supposedly persistent or immutable object in destructive and dangerous ways? Does performance justify it? Would you still be able to call it immutable? Oh, and could you implement this sort of laziness without mutating the data structure in the specified fashion?

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  • Example sites which use UCC certificates

    - by Brian
    Can anyone point me to a few sites that make use of a UCC (SAN) certificates? I tried to search for this but found a lot of information about UCC certficates without any examples. As a sanity check before buying/configuring a UCC certificate, I wish to do some basic testing to determine exactly how the certificate will look in different browsers. Yes, I realize I could just use makecert instead. I would rather just look at them in the wild.

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  • Website speed issues

    - by Jose David Garcia Llanos
    I am developing a website however i have noticed speed issues, i am not sure whether is due to the location of the server. I am not a guru when it comes to performance or speed issues, but according to a website speed test it seems that it takes quite a long time to connect to the website. Speed Test Results Can someone suggest something or give me some tips, the website address is http://www.n1bar.com

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  • Differences between TypeScript and Dart

    - by margabit
    Microsoft recently unveiled Typescript, a new JavaScript-like programming language. Some time ago, I heard about Dart, a new programming language created by Google to solve problems related to Javascript like performance, scalability, etc.. The purpose of both new languages seem the same to me.. What do you think? Are the purposes of the languages the same? What are the real differences about them?

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  • Téléchargez gratuitement l'ebook sur le développement d'applications 'Threaded' qui utilisent le har

    Téléchargez gratuitement l'ebook sur le développement d'applications ?Threaded' Les logiciels de développement Intel® Parallel Studio accélèrent le développement d'applications ?Threaded' qui utilisent le hardware des utilisateurs finaux, depuis le ?'supercomputer'' jusqu'à l'ordinateur portable ou les mobiles. Optimisez la performance de votre application sur architecture Intel® et obtenez plus des derniers processeurs multi-coeurs d'Intel®. Depuis la manière dont les produits fonctionnent ensemble jusqu'à leurs jeux de fonctionnalités uniques, le Threading est maintenant plus facile et plus viable que jamais. Les outils sont optimisés donc les novices peuvent facilement se former et les développeurs expérimentés peuvent aisément ...

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  • Join the Authors of SSIS Design Patterns at the PASS Summit 2012!

    - by andyleonard
    My fellow authors and I will be presenting a day-long pre-conference session titled SSIS Design Patterns at the PASS Summit 2012 in Seattle Monday 5 Nov 2012! Register to learn patterns for: Package execution Package logging Loading flat file sources Loading XML sources Loading the cloud Dynamic package generation SSIS Frameworks Data warehouse ETL Data flow performance   Presenting this session: Matt Masson Tim Mitchell Jessica Moss Michelle Ufford Andy Leonard I hope to see you in Seattle!...(read more)

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  • Expectations + Rewards = Innovation

    - by D'Arcy Lussier
    “Innovation” is a heavy word. We regard those that embrace it as “Innovators”. We describe organizations as being “Innovative”. We hold those associated with the word in high regard, even though its dictionary definition is very simple: Introducing something new. What our culture has done is wrapped Innovation in white robes and a gold crown. Innovation is rarely just introducing something new. Innovations and innovators are typically associated with other terms: groundbreaking, genius, industry-changing, creative, leading. Being a true innovator and creating innovations are a big deal, and something companies try to strive for…or at least say they strive for. There’s huge value in being recognized as an innovator in an industry, since the idea is that innovation equates to increased profitability. IBM ran an ad a few years back that showed what their view of innovation is: “The point of innovation is to make actual money.” If the money aspect makes you feel uneasy, consider it another way: the point of innovation is to <insert payoff here>. Companies that innovate will be more successful. Non-profits that innovate can better serve their target clients. Governments that innovate can better provide services to their citizens. True innovation is not easy to come by though. As with anything in business, how well an organization will innovate is reliant on the employees it retains, the expectations placed on those employees, and the rewards available to them. In a previous blog post I talked about one formula: Right Employees + Happy Employees = Productive Employees I want to introduce a new one, that builds upon the previous one: Expectations + Rewards = Innovation  The level of innovation your organization will realize is directly associated with the expectations you place on your staff and the rewards you make available to them. Expectations We may feel uncomfortable with the idea of placing expectations on our staff, mainly because expectation has somewhat of a negative or cold connotation to it: “I expect you to act this way or else!” The problem is in the or-else part…we focus on the negative aspects of failing to meet expectations instead of looking at the positive side. “I expect you to act this way because it will produce <insert benefit here>”. Expectations should not be set to punish but instead be set to ensure quality. At a recent conference I spoke with some Microsoft employees who told me that you have five years from starting with the company to reach a “Senior” level. If you don’t, then you’re let go. The expectation Microsoft placed on their staff is that they should be working towards improving themselves, taking more responsibility, and thus ensure that there is a constant level of quality in the workforce. Rewards Let me be clear: a paycheck is not a reward. A paycheck is simply the employer’s responsibility in the employee/employer relationship. A paycheck will never be the key motivator to drive innovation. Offering employees something over and above their required compensation can spur them to greater performance and achievement. Working in the food service industry, this tactic was used again and again: whoever has the highest sales over lunch will receive a free lunch/gift certificate/entry into a draw/etc. There was something to strive for, to try beyond the baseline of what our serving jobs were. It was through this that innovative sales techniques would be tried and honed, with key servers being top sellers time and time again. At a code camp I spoke at, I was amazed to see that all the employees from one company receive $100 Visa gift cards as a thank you for taking time to speak. Again, offering something over and above that can give that extra push for employees. Rewards work. But what about the fairness angle? In the restaurant example I gave, there were servers that would never win the competition. They just weren’t good enough at selling and never seemed to get better. So should those that did work at performing better and produce more sales for the restaurant not get rewarded because those who weren’t working at performing better might get upset? Of course not! Organizations succeed because of their top performers and those that strive to join their ranks. The Expectation/Reward Graph While the Expectations + Rewards = Innovation formula may seem like a simple mathematics formula, there’s much more going under the hood. In fact there are three different outcomes that could occur based on what you put in as values for Expectations and Rewards. Consider the graph below and the descriptions that follow: Disgruntled – High Expectation, Low Reward I worked at a company where the mantra was “Company First, Because We Pay You”. Even today I still hear stories of how this sentiment continues to be perpetuated: They provide you a paycheck and a means to live, therefore you should always put them as your top priority. Of course, this is a huge imbalance in the expectation/reward equation. Why would anyone willingly meet high expectations of availability, workload, deadlines, etc. when there is no reward other than a paycheck to show for it? Remember: paychecks are not rewards! Instead, you see employees be disgruntled which not only affects the level of production but also the level of quality within an organization. It also means that you see higher turnover. Complacent – Low Expectation, Low Reward Complacency is a systemic problem that typically exists throughout all levels of an organization. With no real expectations or rewards, nobody needs to excel. In fact, those that do try to innovate, improve, or introduce new things into the organization might be shunned or pushed out by the rest of the staff who are just doing things the same way they’ve always done it. The bigger issue for the organization with low/low values is that at best they’ll never grow beyond their current size (and may shrink actually), and at worst will cease to exist. Entitled – Low Expectation, High Reward It’s one thing to say you have the best people and reward them as such, but its another thing to actually have the best people and reward them as such. Organizations with Entitled employees are the former: their organization provides them with all types of comforts, benefits, and perks. But there’s no requirement before the rewards are dolled out, and there’s no short-list of who receives the rewards. Everyone in the company is treated the same and is given equal share of the spoils. Entitlement is actually almost identical with Complacency with one notable difference: just try to introduce higher expectations into an entitled organization! Entitled employees have been spoiled for so long that they can’t fathom having rewards taken from them, or having to achieve specific levels of performance before attaining them. Those running the organization also buy in to the Entitled sentiment, feeling that they must persist the same level of comforts to appease their staff…even though the quality of the employee pool may be suspect. Innovative – High Expectation, High Reward Finally we have the Innovative organization which places high expectations but also provides high rewards. This organization gets it: if you truly want the best employees you need to apply equal doses of pressure and praise. Realize that I’m not suggesting crazy overtime or un-realistic working conditions. I do not agree with the “Glengary-Glenross” method of encouragement. But as anyone who follows sports can tell you, the teams that win are the ones where the coaches push their players to be their best; to achieve new levels of performance that they didn’t know they could receive. And the result for the players is more money, fame, and opportunity. It’s in this environment that organizations can focus on innovation – true innovation that builds the business and allows everyone involved to truly benefit. In Closing Organizations love to use the word “Innovation” and its derivatives, but very few actually do innovate. For many, the term has just become another marketing buzzword to lump in with all the other business terms that get overused. But for those organizations that truly get the value of innovation, they will be the ones surging forward while other companies simply fade into the background. And they will be the organizations that expect more from their employees, and give them their just rewards.

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  • Get Started with .Net and Apache Cassandra

    - by Sazzad Hossain
    Just came across a easy and nice to read article explaining how to get started with noSQL database system. These no relational databases are getting increasingly popular to tackle the distribution and large data set problems.Cassandra's ColumnFamily data model offers the convenience of column indexes with the performance of log-structured updates, strong support for materialized views, and powerful built-in caching.The article is nicely written by Kellabyte  and shows step by step process how to get going with the programming in a .net platform.Read more here.

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  • Pentaho: Open Source BI Sales Soar

    <b>The VAR Guy:</b> "Pentaho, the open source business intelligence company, generated record results in 1Q 2010, according to VP of Marketing Joe McGonnell. Pentaho attributes much of its performance to a growing channel partner program."

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  • QAliber

    - by csharp-source.net
    QAliber includes 2 projects: a Visual Studio plug-in and Test Builder + Runner as execute framework. Visual Studio plug-in help writing automatic tests over GUI with control browser and record/play capabilities (but not only, since this project incorporate into development solution API testing is easy to do) The Test Builder is a framework for creating a scenario by simply drag and drop of created building blocks. It already provide big repository of test blocks performing most tasks without coding.

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  • Stairway to Server-side Tracing - Level 10: Profiler versus Server-Side tracing

    Compares and contrasts tracing using Profiler with server-side tracing, illustrating important performance differences so that one can choose the right tool for the task at hand. Make working with SQL a breezeSQL Prompt 5.3 is the effortless way to write, edit, and explore SQL. It's packed with features such as code completion, script summaries, and SQL reformatting, that make working with SQL a breeze. Try it now.

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  • Showplan Operator of the Week - Compute Scalar

    The third part of Fabiano's mission to describe the major Showplan Operators used by SQL Server's Query Optimiser continues with the 'Compute Scalar' operator. Fabiano shows how a tweak to SQL to avoid a 'Compute Scalar' step can improve its performance.

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  • SQLAuthority News Public Training Classes In Hyderabad 12-14 May SQL and 10-11 May SharePoint

    There were lots of request about providing more details for the blog post through email address specified in the article SQLAuthority News Public Training Classes In Hyderabad 12-14 May Microsoft SQL Server 2005/2008 Query Optimization & Performance Tuning. Here is the complete brochure of the course. There are two different courses are offered [...]...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Tuxedo Load Balancing

    - by Todd Little
    A question I often receive is how does Tuxedo perform load balancing.  This is often asked by customers that see an imbalance in the number of requests handled by servers offering a specific service. First of all let me say that Tuxedo really does load or request optimization instead of load balancing.  What I mean by that is that Tuxedo doesn't attempt to ensure that all servers offering a specific service get the same number of requests, but instead attempts to ensure that requests are processed in the least amount of time.   Simple round robin "load balancing" can be employed to ensure that all servers for a particular service are given the same number of requests.  But the question I ask is, "to what benefit"?  Instead Tuxedo scans the queues (which may or may not correspond to servers based upon SSSQ - Single Server Single Queue or MSSQ - Multiple Server Single Queue) to determine on which queue a request should be placed.  The scan is always performed in the same order and during the scan if a queue is empty the request is immediately placed on that queue and request routing is done.  However, should all the queues be busy, meaning that requests are currently being processed, Tuxedo chooses the queue with the least amount of "work" queued to it where work is the sum of all the requests queued weighted by their "load" value as defined in the UBBCONFIG file.  What this means is that under light loads, only the first few queues (servers) process all the requests as an empty queue is often found before reaching the end of the scan.  Thus the first few servers in the queue handle most of the requests.  While this sounds non-optimal, in fact it capitalizes on the underlying operating systems and hardware behavior to produce the best possible performance.  Round Robin scheduling would spread the requests across all the available servers and thus require all of them to be in memory, and likely not share much in the way of hardware or memory caches.  Tuxedo's system maximizes the various caches and thus optimizes overall performance.  Hopefully this makes sense and now explains why you may see a few servers handling most of the requests.  Under heavy load, meaning enough load to keep all servers that can handle a request busy, you should see a relatively equal number of requests processed.  Next post I'll try and cover how this applies to servers in a clustered (MP) environment because the load balancing there is a little more complicated. Regards,Todd LittleOracle Tuxedo Chief Architect

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