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  • C#: Optional Parameters - Pros and Pitfalls

    - by James Michael Hare
    When Microsoft rolled out Visual Studio 2010 with C# 4, I was very excited to learn how I could apply all the new features and enhancements to help make me and my team more productive developers. Default parameters have been around forever in C++, and were intentionally omitted in Java in favor of using overloading to satisfy that need as it was though that having too many default parameters could introduce code safety issues.  To some extent I can understand that move, as I’ve been bitten by default parameter pitfalls before, but at the same time I feel like Java threw out the baby with the bathwater in that move and I’m glad to see C# now has them. This post briefly discusses the pros and pitfalls of using default parameters.  I’m avoiding saying cons, because I really don’t believe using default parameters is a negative thing, I just think there are things you must watch for and guard against to avoid abuses that can cause code safety issues. Pro: Default Parameters Can Simplify Code Let’s start out with positives.  Consider how much cleaner it is to reduce all the overloads in methods or constructors that simply exist to give the semblance of optional parameters.  For example, we could have a Message class defined which allows for all possible initializations of a Message: 1: public class Message 2: { 3: // can either cascade these like this or duplicate the defaults (which can introduce risk) 4: public Message() 5: : this(string.Empty) 6: { 7: } 8:  9: public Message(string text) 10: : this(text, null) 11: { 12: } 13:  14: public Message(string text, IDictionary<string, string> properties) 15: : this(text, properties, -1) 16: { 17: } 18:  19: public Message(string text, IDictionary<string, string> properties, long timeToLive) 20: { 21: // ... 22: } 23: }   Now consider the same code with default parameters: 1: public class Message 2: { 3: // can either cascade these like this or duplicate the defaults (which can introduce risk) 4: public Message(string text = "", IDictionary<string, string> properties = null, long timeToLive = -1) 5: { 6: // ... 7: } 8: }   Much more clean and concise and no repetitive coding!  In addition, in the past if you wanted to be able to cleanly supply timeToLive and accept the default on text and properties above, you would need to either create another overload, or pass in the defaults explicitly.  With named parameters, though, we can do this easily: 1: var msg = new Message(timeToLive: 100);   Pro: Named Parameters can Improve Readability I must say one of my favorite things with the default parameters addition in C# is the named parameters.  It lets code be a lot easier to understand visually with no comments.  Think how many times you’ve run across a TimeSpan declaration with 4 arguments and wondered if they were passing in days/hours/minutes/seconds or hours/minutes/seconds/milliseconds.  A novice running through your code may wonder what it is.  Named arguments can help resolve the visual ambiguity: 1: // is this days/hours/minutes/seconds (no) or hours/minutes/seconds/milliseconds (yes) 2: var ts = new TimeSpan(1, 2, 3, 4); 3:  4: // this however is visually very explicit 5: var ts = new TimeSpan(days: 1, hours: 2, minutes: 3, seconds: 4);   Or think of the times you’ve run across something passing a Boolean literal and wondered what it was: 1: // what is false here? 2: var sub = CreateSubscriber(hostname, port, false); 3:  4: // aha! Much more visibly clear 5: var sub = CreateSubscriber(hostname, port, isBuffered: false);   Pitfall: Don't Insert new Default Parameters In Between Existing Defaults Now let’s consider a two potential pitfalls.  The first is really an abuse.  It’s not really a fault of the default parameters themselves, but a fault in the use of them.  Let’s consider that Message constructor again with defaults.  Let’s say you want to add a messagePriority to the message and you think this is more important than a timeToLive value, so you decide to put messagePriority before it in the default, this gives you: 1: public class Message 2: { 3: public Message(string text = "", IDictionary<string, string> properties = null, int priority = 5, long timeToLive = -1) 4: { 5: // ... 6: } 7: }   Oh boy have we set ourselves up for failure!  Why?  Think of all the code out there that could already be using the library that already specified the timeToLive, such as this possible call: 1: var msg = new Message(“An error occurred”, myProperties, 1000);   Before this specified a message with a TTL of 1000, now it specifies a message with a priority of 1000 and a time to live of -1 (infinite).  All of this with NO compiler errors or warnings. So the rule to take away is if you are adding new default parameters to a method that’s currently in use, make sure you add them to the end of the list or create a brand new method or overload. Pitfall: Beware of Default Parameters in Inheritance and Interface Implementation Now, the second potential pitfalls has to do with inheritance and interface implementation.  I’ll illustrate with a puzzle: 1: public interface ITag 2: { 3: void WriteTag(string tagName = "ITag"); 4: } 5:  6: public class BaseTag : ITag 7: { 8: public virtual void WriteTag(string tagName = "BaseTag") { Console.WriteLine(tagName); } 9: } 10:  11: public class SubTag : BaseTag 12: { 13: public override void WriteTag(string tagName = "SubTag") { Console.WriteLine(tagName); } 14: } 15:  16: public static class Program 17: { 18: public static void Main() 19: { 20: SubTag subTag = new SubTag(); 21: BaseTag subByBaseTag = subTag; 22: ITag subByInterfaceTag = subTag; 23:  24: // what happens here? 25: subTag.WriteTag(); 26: subByBaseTag.WriteTag(); 27: subByInterfaceTag.WriteTag(); 28: } 29: }   What happens?  Well, even though the object in each case is SubTag whose tag is “SubTag”, you will get: 1: SubTag 2: BaseTag 3: ITag   Why?  Because default parameter are resolved at compile time, not runtime!  This means that the default does not belong to the object being called, but by the reference type it’s being called through.  Since the SubTag instance is being called through an ITag reference, it will use the default specified in ITag. So the moral of the story here is to be very careful how you specify defaults in interfaces or inheritance hierarchies.  I would suggest avoiding repeating them, and instead concentrating on the layer of classes or interfaces you must likely expect your caller to be calling from. For example, if you have a messaging factory that returns an IMessage which can be either an MsmqMessage or JmsMessage, it only makes since to put the defaults at the IMessage level since chances are your user will be using the interface only. So let’s sum up.  In general, I really love default and named parameters in C# 4.0.  I think they’re a great tool to help make your code easier to read and maintain when used correctly. On the plus side, default parameters: Reduce redundant overloading for the sake of providing optional calling structures. Improve readability by being able to name an ambiguous argument. But remember to make sure you: Do not insert new default parameters in the middle of an existing set of default parameters, this may cause unpredictable behavior that may not necessarily throw a syntax error – add to end of list or create new method. Be extremely careful how you use default parameters in inheritance hierarchies and interfaces – choose the most appropriate level to add the defaults based on expected usage. Technorati Tags: C#,.NET,Software,Default Parameters

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  • Get the onended event for an AudioBuffer in HTML5/Chrome

    - by Matthew James Davis
    So I am playing audio file in Chrome and I want to detect when playing has ended so I can delete references to it. Here is my code var source = context.createBufferSource(); source.buffer = sound.buffer; source.loop = sound.loop; source.onended = function() { delete playingSounds[soundName]; } source.connect(mainNode); source.start(0, sound.start, sound.length); however, the event handler doesn't fire. Is this not yet supported as described by the W3 specification? Or am I doing something wrong?

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  • MDX using EXISTING, AGGREGATE, CROSSJOIN and WHERE

    - by James Rogers
    It is a well-published approach to using the EXISTING function to decode AGGREGATE members and nested sub-query filters.  Mosha wrote a good blog on it here and a more recent one here.  The use of EXISTING in these scenarios is very useful and sometimes the only option when dealing with multi-select filters.  However, there are some limitations I have run across when using the EXISTING function against an AGGREGATE member:   The AGGREGATE member must be assigned to the Dimension.Hierarchy being detected by the EXISTING function in the calculated measure. The AGGREGATE member cannot contain a crossjoin from any other dimension or hierarchy or EXISTING will not be able to detect the members in the AGGREGATE member.   Take the following query (from Adventure Works DW 2008):   With   member [Week Count] as 'count(existing([Date].[Fiscal Weeks].[Fiscal Week].members))'    member [Date].[Fiscal Weeks].[CM] as 'AGGREGATE({[Date].[Fiscal Weeks].[Fiscal Week].&[47]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[48]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[49]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[50]&[2004]})'   select   {[Week Count]} on columns from   [Adventure Works]     where   [Date].[Fiscal Weeks].[CM]   Here we are attempting to count the existing fiscal weeks in slicer.  This is useful to get a per-week average for another member. Many applications generate queries in this manner (such as Oracle OBIEE).  This query returns the correct result of (4) weeks. Now let's put a twist in it.  What if the querying application submits the query in the following manner:   With   member [Week Count] as 'count(existing([Date].[Fiscal Weeks].[Fiscal Week].members))'    member [Customer].[Customer Geography].[CM] as 'AGGREGATE({[Date].[Fiscal Weeks].[Fiscal Week].&[47]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[48]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[49]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[50]&[2004]})'   select   {[Week Count]} on columns from   [Adventure Works]     where   [Customer].[Customer Geography].[CM]   Here we are attempting to count the existing fiscal weeks in slicer.  However, the AGGREGATE member is built on a different dimension (in name) than the one EXISTING is trying to detect.  In this case the query returns (174) which is the total number of [Date].[Fiscal Weeks].[Fiscal Week].members defined in the dimension.   Now another twist, the AGGREGATE member will be named appropriately and contain the hierarchy we are trying to detect with EXISTING but it will be cross-joined with another hierarchy:   With   member [Week Count] as 'count(existing([Date].[Fiscal Weeks].[Fiscal Week].members))'    member [Date].[Fiscal Weeks].[CM] as 'AGGREGATE({[Date].[Fiscal Weeks].[Fiscal Week].&[47]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[48]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[49]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[50]&[2004]}*    {[Customer].[Customer Geography].[Country].&[Australia],[Customer].[Customer Geography].[Country].&[United States]})'  select   {[Week Count]} on columns from   [Adventure Works]    where   [Date].[Fiscal Weeks].[CM]   Once again, we are attempting to count the existing fiscal weeks in slicer.  Again, in this case the query returns (174) which is the total number of [Date].[Fiscal Weeks].[Fiscal Week].members defined in the dimension. However, in 2008 R2 this query returns the correct result of 4 and additionally , the following will return the count of existing countries as well (2):   With   member [Week Count] as 'count(existing([Date].[Fiscal Weeks].[Fiscal Week].members))'   member [Country Count] as 'count(existing([Customer].[Customer Geography].[Country].members))'  member [Date].[Fiscal Weeks].[CM] as 'AGGREGATE({[Date].[Fiscal Weeks].[Fiscal Week].&[47]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[48]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[49]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[50]&[2004]}*    {[Customer].[Customer Geography].[Country].&[Australia],[Customer].[Customer Geography].[Country].&[United States]})'  select   {[Week Count]} on columns from   [Adventure Works]    where   [Date].[Fiscal Weeks].[CM]   2008 R2 seems to work as long as the AGGREGATE member is on at least one of the hierarchies attempting to be detected (i.e. [Date].[Fiscal Weeks] or [Customer].[Customer Geography]). If not, it seems that the engine cannot find a "point of entry" into the aggregate member and ignores it for calculated members.   One way around this would be to put the sets from the AGGREGATE member explicitly in the WHERE clause (slicer).  I realize this is only supported in SSAS 2005 and 2008.  However, after talking with Chris Webb (his blog is here and I highly recommend following his efforts and musings) it is a far more efficient way to filter/slice a query:   With   member [Week Count] as 'count(existing([Date].[Fiscal Weeks].[Fiscal Week].members))'    select   {[Week Count]} on columns from   [Adventure Works]    where   ({[Date].[Fiscal Weeks].[Fiscal Week].&[47]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[48]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[49]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[50]&[2004]}   ,{[Customer].[Customer Geography].[Country].&[Australia],[Customer].[Customer Geography].[Country].&[United States]})   This query returns the correct result of (4) weeks.  Additionally, we can count the cross-join members of the two hierarchies in the slicer:   With   member [Week Count] as 'count(existing([Date].[Fiscal Weeks].[Fiscal Week].members)*existing([Customer].[Customer Geography].[Country].members))'    select   {[Week Count]} on columns from   [Adventure Works]    where   ({[Date].[Fiscal Weeks].[Fiscal Week].&[47]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[48]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[49]&[2004],[Date].[Fiscal Weeks].[Fiscal Week].&[50]&[2004]}   ,{[Customer].[Customer Geography].[Country].&[Australia],[Customer].[Customer Geography].[Country].&[United States]})   We get the correct number of (8) here.

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  • C#/.NET Little Wonders: ConcurrentBag and BlockingCollection

    - by James Michael Hare
    In the first week of concurrent collections, began with a general introduction and discussed the ConcurrentStack<T> and ConcurrentQueue<T>.  The last post discussed the ConcurrentDictionary<T> .  Finally this week, we shall close with a discussion of the ConcurrentBag<T> and BlockingCollection<T>. For more of the "Little Wonders" posts, see C#/.NET Little Wonders: A Redux. Recap As you'll recall from the previous posts, the original collections were object-based containers that accomplished synchronization through a Synchronized member.  With the advent of .NET 2.0, the original collections were succeeded by the generic collections which are fully type-safe, but eschew automatic synchronization.  With .NET 4.0, a new breed of collections was born in the System.Collections.Concurrent namespace.  Of these, the final concurrent collection we will examine is the ConcurrentBag and a very useful wrapper class called the BlockingCollection. For some excellent information on the performance of the concurrent collections and how they perform compared to a traditional brute-force locking strategy, see this informative whitepaper by the Microsoft Parallel Computing Platform team here. ConcurrentBag<T> – Thread-safe unordered collection. Unlike the other concurrent collections, the ConcurrentBag<T> has no non-concurrent counterpart in the .NET collections libraries.  Items can be added and removed from a bag just like any other collection, but unlike the other collections, the items are not maintained in any order.  This makes the bag handy for those cases when all you care about is that the data be consumed eventually, without regard for order of consumption or even fairness – that is, it’s possible new items could be consumed before older items given the right circumstances for a period of time. So why would you ever want a container that can be unfair?  Well, to look at it another way, you can use a ConcurrentQueue and get the fairness, but it comes at a cost in that the ordering rules and synchronization required to maintain that ordering can affect scalability a bit.  Thus sometimes the bag is great when you want the fastest way to get the next item to process, and don’t care what item it is or how long its been waiting. The way that the ConcurrentBag works is to take advantage of the new ThreadLocal<T> type (new in System.Threading for .NET 4.0) so that each thread using the bag has a list local to just that thread.  This means that adding or removing to a thread-local list requires very low synchronization.  The problem comes in where a thread goes to consume an item but it’s local list is empty.  In this case the bag performs “work-stealing” where it will rob an item from another thread that has items in its list.  This requires a higher level of synchronization which adds a bit of overhead to the take operation. So, as you can imagine, this makes the ConcurrentBag good for situations where each thread both produces and consumes items from the bag, but it would be less-than-idea in situations where some threads are dedicated producers and the other threads are dedicated consumers because the work-stealing synchronization would outweigh the thread-local optimization for a thread taking its own items. Like the other concurrent collections, there are some curiosities to keep in mind: IsEmpty(), Count, ToArray(), and GetEnumerator() lock collection Each of these needs to take a snapshot of whole bag to determine if empty, thus they tend to be more expensive and cause Add() and Take() operations to block. ToArray() and GetEnumerator() are static snapshots Because it is based on a snapshot, will not show subsequent updates after snapshot. Add() is lightweight Since adding to the thread-local list, there is very little overhead on Add. TryTake() is lightweight if items in thread-local list As long as items are in the thread-local list, TryTake() is very lightweight, much more so than ConcurrentStack() and ConcurrentQueue(), however if the local thread list is empty, it must steal work from another thread, which is more expensive. Remember, a bag is not ideal for all situations, it is mainly ideal for situations where a process consumes an item and either decomposes it into more items to be processed, or handles the item partially and places it back to be processed again until some point when it will complete.  The main point is that the bag works best when each thread both takes and adds items. For example, we could create a totally contrived example where perhaps we want to see the largest power of a number before it crosses a certain threshold.  Yes, obviously we could easily do this with a log function, but bare with me while I use this contrived example for simplicity. So let’s say we have a work function that will take a Tuple out of a bag, this Tuple will contain two ints.  The first int is the original number, and the second int is the last multiple of that number.  So we could load our bag with the initial values (let’s say we want to know the last multiple of each of 2, 3, 5, and 7 under 100. 1: var bag = new ConcurrentBag<Tuple<int, int>> 2: { 3: Tuple.Create(2, 1), 4: Tuple.Create(3, 1), 5: Tuple.Create(5, 1), 6: Tuple.Create(7, 1) 7: }; Then we can create a method that given the bag, will take out an item, apply the multiplier again, 1: public static void FindHighestPowerUnder(ConcurrentBag<Tuple<int,int>> bag, int threshold) 2: { 3: Tuple<int,int> pair; 4:  5: // while there are items to take, this will prefer local first, then steal if no local 6: while (bag.TryTake(out pair)) 7: { 8: // look at next power 9: var result = Math.Pow(pair.Item1, pair.Item2 + 1); 10:  11: if (result < threshold) 12: { 13: // if smaller than threshold bump power by 1 14: bag.Add(Tuple.Create(pair.Item1, pair.Item2 + 1)); 15: } 16: else 17: { 18: // otherwise, we're done 19: Console.WriteLine("Highest power of {0} under {3} is {0}^{1} = {2}.", 20: pair.Item1, pair.Item2, Math.Pow(pair.Item1, pair.Item2), threshold); 21: } 22: } 23: } Now that we have this, we can load up this method as an Action into our Tasks and run it: 1: // create array of tasks, start all, wait for all 2: var tasks = new[] 3: { 4: new Task(() => FindHighestPowerUnder(bag, 100)), 5: new Task(() => FindHighestPowerUnder(bag, 100)), 6: }; 7:  8: Array.ForEach(tasks, t => t.Start()); 9:  10: Task.WaitAll(tasks); Totally contrived, I know, but keep in mind the main point!  When you have a thread or task that operates on an item, and then puts it back for further consumption – or decomposes an item into further sub-items to be processed – you should consider a ConcurrentBag as the thread-local lists will allow for quick processing.  However, if you need ordering or if your processes are dedicated producers or consumers, this collection is not ideal.  As with anything, you should performance test as your mileage will vary depending on your situation! BlockingCollection<T> – A producers & consumers pattern collection The BlockingCollection<T> can be treated like a collection in its own right, but in reality it adds a producers and consumers paradigm to any collection that implements the interface IProducerConsumerCollection<T>.  If you don’t specify one at the time of construction, it will use a ConcurrentQueue<T> as its underlying store. If you don’t want to use the ConcurrentQueue, the ConcurrentStack and ConcurrentBag also implement the interface (though ConcurrentDictionary does not).  In addition, you are of course free to create your own implementation of the interface. So, for those who don’t remember the producers and consumers classical computer-science problem, the gist of it is that you have one (or more) processes that are creating items (producers) and one (or more) processes that are consuming these items (consumers).  Now, the crux of the problem is that there is a bin (queue) where the produced items are placed, and typically that bin has a limited size.  Thus if a producer creates an item, but there is no space to store it, it must wait until an item is consumed.  Also if a consumer goes to consume an item and none exists, it must wait until an item is produced. The BlockingCollection makes it trivial to implement any standard producers/consumers process set by providing that “bin” where the items can be produced into and consumed from with the appropriate blocking operations.  In addition, you can specify whether the bin should have a limited size or can be (theoretically) unbounded, and you can specify timeouts on the blocking operations. As far as your choice of “bin”, for the most part the ConcurrentQueue is the right choice because it is fairly light and maximizes fairness by ordering items so that they are consumed in the same order they are produced.  You can use the concurrent bag or stack, of course, but your ordering would be random-ish in the case of the former and LIFO in the case of the latter. So let’s look at some of the methods of note in BlockingCollection: BoundedCapacity returns capacity of the “bin” If the bin is unbounded, the capacity is int.MaxValue. Count returns an internally-kept count of items This makes it O(1), but if you modify underlying collection directly (not recommended) it is unreliable. CompleteAdding() is used to cut off further adds. This sets IsAddingCompleted and begins to wind down consumers once empty. IsAddingCompleted is true when producers are “done”. Once you are done producing, should complete the add process to alert consumers. IsCompleted is true when producers are “done” and “bin” is empty. Once you mark the producers done, and all items removed, this will be true. Add() is a blocking add to collection. If bin is full, will wait till space frees up Take() is a blocking remove from collection. If bin is empty, will wait until item is produced or adding is completed. GetConsumingEnumerable() is used to iterate and consume items. Unlike the standard enumerator, this one consumes the items instead of iteration. TryAdd() attempts add but does not block completely If adding would block, returns false instead, can specify TimeSpan to wait before stopping. TryTake() attempts to take but does not block completely Like TryAdd(), if taking would block, returns false instead, can specify TimeSpan to wait. Note the use of CompleteAdding() to signal the BlockingCollection that nothing else should be added.  This means that any attempts to TryAdd() or Add() after marked completed will throw an InvalidOperationException.  In addition, once adding is complete you can still continue to TryTake() and Take() until the bin is empty, and then Take() will throw the InvalidOperationException and TryTake() will return false. So let’s create a simple program to try this out.  Let’s say that you have one process that will be producing items, but a slower consumer process that handles them.  This gives us a chance to peek inside what happens when the bin is bounded (by default, the bin is NOT bounded). 1: var bin = new BlockingCollection<int>(5); Now, we create a method to produce items: 1: public static void ProduceItems(BlockingCollection<int> bin, int numToProduce) 2: { 3: for (int i = 0; i < numToProduce; i++) 4: { 5: // try for 10 ms to add an item 6: while (!bin.TryAdd(i, TimeSpan.FromMilliseconds(10))) 7: { 8: Console.WriteLine("Bin is full, retrying..."); 9: } 10: } 11:  12: // once done producing, call CompleteAdding() 13: Console.WriteLine("Adding is completed."); 14: bin.CompleteAdding(); 15: } And one to consume them: 1: public static void ConsumeItems(BlockingCollection<int> bin) 2: { 3: // This will only be true if CompleteAdding() was called AND the bin is empty. 4: while (!bin.IsCompleted) 5: { 6: int item; 7:  8: if (!bin.TryTake(out item, TimeSpan.FromMilliseconds(10))) 9: { 10: Console.WriteLine("Bin is empty, retrying..."); 11: } 12: else 13: { 14: Console.WriteLine("Consuming item {0}.", item); 15: Thread.Sleep(TimeSpan.FromMilliseconds(20)); 16: } 17: } 18: } Then we can fire them off: 1: // create one producer and two consumers 2: var tasks = new[] 3: { 4: new Task(() => ProduceItems(bin, 20)), 5: new Task(() => ConsumeItems(bin)), 6: new Task(() => ConsumeItems(bin)), 7: }; 8:  9: Array.ForEach(tasks, t => t.Start()); 10:  11: Task.WaitAll(tasks); Notice that the producer is faster than the consumer, thus it should be hitting a full bin often and displaying the message after it times out on TryAdd(). 1: Consuming item 0. 2: Consuming item 1. 3: Bin is full, retrying... 4: Bin is full, retrying... 5: Consuming item 3. 6: Consuming item 2. 7: Bin is full, retrying... 8: Consuming item 4. 9: Consuming item 5. 10: Bin is full, retrying... 11: Consuming item 6. 12: Consuming item 7. 13: Bin is full, retrying... 14: Consuming item 8. 15: Consuming item 9. 16: Bin is full, retrying... 17: Consuming item 10. 18: Consuming item 11. 19: Bin is full, retrying... 20: Consuming item 12. 21: Consuming item 13. 22: Bin is full, retrying... 23: Bin is full, retrying... 24: Consuming item 14. 25: Adding is completed. 26: Consuming item 15. 27: Consuming item 16. 28: Consuming item 17. 29: Consuming item 19. 30: Consuming item 18. Also notice that once CompleteAdding() is called and the bin is empty, the IsCompleted property returns true, and the consumers will exit. Summary The ConcurrentBag is an interesting collection that can be used to optimize concurrency scenarios where tasks or threads both produce and consume items.  In this way, it will choose to consume its own work if available, and then steal if not.  However, in situations where you want fair consumption or ordering, or in situations where the producers and consumers are distinct processes, the bag is not optimal. The BlockingCollection is a great wrapper around all of the concurrent queue, stack, and bag that allows you to add producer and consumer semantics easily including waiting when the bin is full or empty. That’s the end of my dive into the concurrent collections.  I’d also strongly recommend, once again, you read this excellent Microsoft white paper that goes into much greater detail on the efficiencies you can gain using these collections judiciously (here). Tweet Technorati Tags: C#,.NET,Concurrent Collections,Little Wonders

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  • C++ Little Wonders: The C++11 auto keyword redux

    - by James Michael Hare
    I’ve decided to create a sub-series of my Little Wonders posts to focus on C++.  Just like their C# counterparts, these posts will focus on those features of the C++ language that can help improve code by making it easier to write and maintain.  The index of the C# Little Wonders can be found here. This has been a busy week with a rollout of some new website features here at my work, so I don’t have a big post for this week.  But I wanted to write something up, and since lately I’ve been renewing my C++ skills in a separate project, it seemed like a good opportunity to start a C++ Little Wonders series.  Most of my development work still tends to focus on C#, but it was great to get back into the saddle and renew my C++ knowledge.  Today I’m going to focus on a new feature in C++11 (formerly known as C++0x, which is a major move forward in the C++ language standard).  While this small keyword can seem so trivial, I feel it is a big step forward in improving readability in C++ programs. The auto keyword If you’ve worked on C++ for a long time, you probably have some passing familiarity with the old auto keyword as one of those rarely used C++ keywords that was almost never used because it was the default. That is, in the code below (before C++11): 1: int foo() 2: { 3: // automatic variables (allocated and deallocated on stack) 4: int x; 5: auto int y; 6:  7: // static variables (retain their value across calls) 8: static int z; 9:  10: return 0; 11: } The variable x is assumed to be auto because that is the default, thus it is unnecessary to specify it explicitly as in the declaration of y below that.  Basically, an auto variable is one that is allocated and de-allocated on the stack automatically.  Contrast this to static variables, that are allocated statically and exist across the lifetime of the program. Because auto was so rarely (if ever) used since it is the norm, they decided to remove it for this purpose and give it new meaning in C++11.  The new meaning of auto: implicit typing Now, if your compiler supports C++ 11 (or at least a good subset of C++11 or 0x) you can take advantage of type inference in C++.  For those of you from the C# world, this means that the auto keyword in C++ now behaves a lot like the var keyword in C#! For example, many of us have had to declare those massive type declarations for an iterator before.  Let’s say we have a std::map of std::string to int which will map names to ages: 1: std::map<std::string, int> myMap; And then let’s say we want to find the age of a given person: 1: // Egad that's a long type... 2: std::map<std::string, int>::const_iterator pos = myMap.find(targetName); Notice that big ugly type definition to declare variable pos?  Sure, we could shorten this by creating a typedef of our specific map type if we wanted, but now with the auto keyword there’s no need: 1: // much shorter! 2: auto pos = myMap.find(targetName); The auto now tells the compiler to determine what type pos should be based on what it’s being assigned to.  This is not dynamic typing, it still determines the type as if it were explicitly declared and once declared that type cannot be changed.  That is, this is invalid: 1: // x is type int 2: auto x = 42; 3:  4: // can't assign string to int 5: x = "Hello"; Once the compiler determines x is type int it is exactly as if we typed int x = 42; instead, so don’t' confuse it with dynamic typing, it’s still very type-safe. An interesting feature of the auto keyword is that you can modify the inferred type: 1: // declare method that returns int* 2: int* GetPointer(); 3:  4: // p1 is int*, auto inferred type is int 5: auto *p1 = GetPointer(); 6:  7: // ps is int*, auto inferred type is int* 8: auto p2 = GetPointer(); Notice in both of these cases, p1 and p2 are determined to be int* but in each case the inferred type was different.  because we declared p1 as auto *p1 and GetPointer() returns int*, it inferred the type int was needed to complete the declaration.  In the second case, however, we declared p2 as auto p2 which means the inferred type was int*.  Ultimately, this make p1 and p2 the same type, but which type is inferred makes a difference, if you are chaining multiple inferred declarations together.  In these cases, the inferred type of each must match the first: 1: // Type inferred is int 2: // p1 is int* 3: // p2 is int 4: // p3 is int& 5: auto *p1 = GetPointer(), p2 = 42, &p3 = p2; Note that this works because the inferred type was int, if the inferred type was int* instead: 1: // syntax error, p1 was inferred to be int* so p2 and p3 don't make sense 2: auto p1 = GetPointer(), p2 = 42, &p3 = p2; You could also use const or static to modify the inferred type: 1: // inferred type is an int, theAnswer is a const int 2: const auto theAnswer = 42; 3:  4: // inferred type is double, Pi is a static double 5: static auto Pi = 3.1415927; Thus in the examples above it inferred the types int and double respectively, which were then modified to const and static. Summary The auto keyword has gotten new life in C++11 to allow you to infer the type of a variable from it’s initialization.  This simple little keyword can be used to cut down large declarations for complex types into a much more readable form, where appropriate.   Technorati Tags: C++, C++11, Little Wonders, auto

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  • Paper on Linux memory access techniques sought

    - by James
    Over on stackoverflow someone posted a link to a paper written by a Linux kernel engineer about how to use computers and RAM. He started off by explaining how RAM works (right down to the flip-flops) and then went on to discuss performance problems associated with operations on matrices (column vs row accesses), offered solutions and then dealt with some stuff MMX instructions can do. Sorry it's a bit vague but I can't find it anywhere. I think the guy had a Scandinavian name, possibly Anders

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  • WebLogic Server JMS WLST Script – Who is Connected To My Server

    - by james.bayer
    Ever want to know who was connected to your WebLogic Server instance for troubleshooting?  An email exchange about this topic and JMS came up this week, and I’ve heard it come up once or twice before too.  Sometimes it’s interesting or helpful to know the list of JMS clients (IP Addresses, JMS Destinations, message counts) that are connected to a particular JMS server.  This can be helpful for troubleshooting.  Tom Barnes from the WebLogic Server JMS team provided some helpful advice: The JMS connection runtime mbean has “getHostAddress”, which returns the host address of the connecting client JVM as a string.  A connection runtime can contain session runtimes, which in turn can contain consumer runtimes.  The consumer runtime, in turn has a “getDestinationName” and “getMemberDestinationName”.  I think that this means you could write a WLST script, for example, to dump all consumers, their destinations, plus their parent session’s parent connection’s host addresses.    Note that the client runtime mbeans (connection, session, and consumer) won’t necessarily be hosted on the same JVM as a destination that’s in the same cluster (client messages route from their connection host to their ultimate destination in the same cluster). Writing the Script So armed with this information, I decided to take the challenge and see if I could write a WLST script to do this.  It’s always helpful to have the WebLogic Server MBean Reference handy for activities like this.  This one is focused on JMS Consumers and I only took a subset of the information available, but it could be modified easily to do Producers.  I haven’t tried this on a more complex environment, but it works in my simple sandbox case, so it should give you the general idea. # Better to use Secure Config File approach for login as shown here http://buttso.blogspot.com/2011/02/using-secure-config-files-with-weblogic.html connect('weblogic','welcome1','t3://localhost:7001')   # Navigate to the Server Runtime and get the Server Name serverRuntime() serverName = cmo.getName()   # Multiple JMS Servers could be hosted by a single WLS server cd('JMSRuntime/' + serverName + '.jms' ) jmsServers=cmo.getJMSServers()   # Find the list of all JMSServers for this server namesOfJMSServers = '' for jmsServer in jmsServers: namesOfJMSServers = jmsServer.getName() + ' '   # Count the number of connections jmsConnections=cmo.getConnections() print str(len(jmsConnections)) + ' JMS Connections found for ' + serverName + ' with JMSServers ' + namesOfJMSServers   # Recurse the MBean tree for each connection and pull out some information about consumers for jmsConnection in jmsConnections: try: print 'JMS Connection:' print ' Host Address = ' + jmsConnection.getHostAddress() print ' ClientID = ' + str( jmsConnection.getClientID() ) print ' Sessions Current = ' + str( jmsConnection.getSessionsCurrentCount() ) jmsSessions = jmsConnection.getSessions() for jmsSession in jmsSessions: jmsConsumers = jmsSession.getConsumers() for jmsConsumer in jmsConsumers: print ' Consumer:' print ' Name = ' + jmsConsumer.getName() print ' Messages Received = ' + str(jmsConsumer.getMessagesReceivedCount()) print ' Member Destination Name = ' + jmsConsumer.getMemberDestinationName() except: print 'Error retrieving JMS Consumer Information' dumpStack() # Cleanup disconnect() exit() Example Output I expect the output to look something like this and loop through all the connections, this is just the first one: 1 JMS Connections found for AdminServer with JMSServers myJMSServer JMS Connection:   Host Address = 127.0.0.1   ClientID = None   Sessions Current = 16    Consumer:      Name = consumer40      Messages Received = 1      Member Destination Name = myJMSModule!myQueue Notice that it has the IP Address of the client.  There are 16 Sessions open because I’m using an MDB, which defaults to 16 connections, so this matches what I expect.  Let’s see what the full output actually looks like: D:\Oracle\fmw11gr1ps3\user_projects\domains\offline_domain>java weblogic.WLST d:\temp\jms.py   Initializing WebLogic Scripting Tool (WLST) ...   Welcome to WebLogic Server Administration Scripting Shell   Type help() for help on available commands   Connecting to t3://localhost:7001 with userid weblogic ... Successfully connected to Admin Server 'AdminServer' that belongs to domain 'offline_domain'.   Warning: An insecure protocol was used to connect to the server. To ensure on-the-wire security, the SSL port or Admin port should be used instead.   Location changed to serverRuntime tree. This is a read-only tree with ServerRuntimeMBean as the root. For more help, use help(serverRuntime)   1 JMS Connections found for AdminServer with JMSServers myJMSServer JMS Connection: Host Address = 127.0.0.1 ClientID = None Sessions Current = 16 Consumer: Name = consumer40 Messages Received = 2 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer34 Messages Received = 2 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer37 Messages Received = 2 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer16 Messages Received = 2 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer46 Messages Received = 2 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer49 Messages Received = 2 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer43 Messages Received = 1 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer55 Messages Received = 1 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer25 Messages Received = 1 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer22 Messages Received = 1 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer19 Messages Received = 1 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer52 Messages Received = 1 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer31 Messages Received = 1 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer58 Messages Received = 1 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer28 Messages Received = 1 Member Destination Name = myJMSModule!myQueue Consumer: Name = consumer61 Messages Received = 1 Member Destination Name = myJMSModule!myQueue Disconnected from weblogic server: AdminServer     Exiting WebLogic Scripting Tool. Thanks to Tom Barnes for the hints and the inspiration to write this up. Image of telephone switchboard courtesy of http://www.JoeTourist.net/ JoeTourist InfoSystems

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  • C#/.NET Little Wonders: Fun With Enum Methods

    - by James Michael Hare
    Once again lets dive into the Little Wonders of .NET, those small things in the .NET languages and BCL classes that make development easier by increasing readability, maintainability, and/or performance. So probably every one of us has used an enumerated type at one time or another in a C# program.  The enumerated types we create are a great way to represent that a value can be one of a set of discrete values (or a combination of those values in the case of bit flags). But the power of enum types go far beyond simple assignment and comparison, there are many methods in the Enum class (that all enum types “inherit” from) that can give you even more power when dealing with them. IsDefined() – check if a given value exists in the enum Are you reading a value for an enum from a data source, but are unsure if it is actually a valid value or not?  Casting won’t tell you this, and Parse() isn’t guaranteed to balk either if you give it an int or a combination of flags.  So what can we do? Let’s assume we have a small enum like this for result codes we want to return back from our business logic layer: 1: public enum ResultCode 2: { 3: Success, 4: Warning, 5: Error 6: } In this enum, Success will be zero (unless given another value explicitly), Warning will be one, and Error will be two. So what happens if we have code like this where perhaps we’re getting the result code from another data source (could be database, could be web service, etc)? 1: public ResultCode PerformAction() 2: { 3: // set up and call some method that returns an int. 4: int result = ResultCodeFromDataSource(); 5:  6: // this will suceed even if result is < 0 or > 2. 7: return (ResultCode) result; 8: } So what happens if result is –1 or 4?  Well, the cast does not fail, so what we end up with would be an instance of a ResultCode that would have a value that’s outside of the bounds of the enum constants we defined. This means if you had a block of code like: 1: switch (result) 2: { 3: case ResultType.Success: 4: // do success stuff 5: break; 6:  7: case ResultType.Warning: 8: // do warning stuff 9: break; 10:  11: case ResultType.Error: 12: // do error stuff 13: break; 14: } That you would hit none of these blocks (which is a good argument for always having a default in a switch by the way). So what can you do?  Well, there is a handy static method called IsDefined() on the Enum class which will tell you if an enum value is defined.  1: public ResultCode PerformAction() 2: { 3: int result = ResultCodeFromDataSource(); 4:  5: if (!Enum.IsDefined(typeof(ResultCode), result)) 6: { 7: throw new InvalidOperationException("Enum out of range."); 8: } 9:  10: return (ResultCode) result; 11: } In fact, this is often recommended after you Parse() or cast a value to an enum as there are ways for values to get past these methods that may not be defined. If you don’t like the syntax of passing in the type of the enum, you could clean it up a bit by creating an extension method instead that would allow you to call IsDefined() off any isntance of the enum: 1: public static class EnumExtensions 2: { 3: // helper method that tells you if an enum value is defined for it's enumeration 4: public static bool IsDefined(this Enum value) 5: { 6: return Enum.IsDefined(value.GetType(), value); 7: } 8: }   HasFlag() – an easier way to see if a bit (or bits) are set Most of us who came from the land of C programming have had to deal extensively with bit flags many times in our lives.  As such, using bit flags may be almost second nature (for a quick refresher on bit flags in enum types see one of my old posts here). However, in higher-level languages like C#, the need to manipulate individual bit flags is somewhat diminished, and the code to check for bit flag enum values may be obvious to an advanced developer but cryptic to a novice developer. For example, let’s say you have an enum for a messaging platform that contains bit flags: 1: // usually, we pluralize flags enum type names 2: [Flags] 3: public enum MessagingOptions 4: { 5: None = 0, 6: Buffered = 0x01, 7: Persistent = 0x02, 8: Durable = 0x04, 9: Broadcast = 0x08 10: } We can combine these bit flags using the bitwise OR operator (the ‘|’ pipe character): 1: // combine bit flags using 2: var myMessenger = new Messenger(MessagingOptions.Buffered | MessagingOptions.Broadcast); Now, if we wanted to check the flags, we’d have to test then using the bit-wise AND operator (the ‘&’ character): 1: if ((options & MessagingOptions.Buffered) == MessagingOptions.Buffered) 2: { 3: // do code to set up buffering... 4: // ... 5: } While the ‘|’ for combining flags is easy enough to read for advanced developers, the ‘&’ test tends to be easy for novice developers to get wrong.  First of all you have to AND the flag combination with the value, and then typically you should test against the flag combination itself (and not just for a non-zero)!  This is because the flag combination you are testing with may combine multiple bits, in which case if only one bit is set, the result will be non-zero but not necessarily all desired bits! Thanks goodness in .NET 4.0 they gave us the HasFlag() method.  This method can be called from an enum instance to test to see if a flag is set, and best of all you can avoid writing the bit wise logic yourself.  Not to mention it will be more readable to a novice developer as well: 1: if (options.HasFlag(MessagingOptions.Buffered)) 2: { 3: // do code to set up buffering... 4: // ... 5: } It is much more concise and unambiguous, thus increasing your maintainability and readability. It would be nice to have a corresponding SetFlag() method, but unfortunately generic types don’t allow you to specialize on Enum, which makes it a bit more difficult.  It can be done but you have to do some conversions to numeric and then back to the enum which makes it less of a payoff than having the HasFlag() method.  But if you want to create it for symmetry, it would look something like this: 1: public static T SetFlag<T>(this Enum value, T flags) 2: { 3: if (!value.GetType().IsEquivalentTo(typeof(T))) 4: { 5: throw new ArgumentException("Enum value and flags types don't match."); 6: } 7:  8: // yes this is ugly, but unfortunately we need to use an intermediate boxing cast 9: return (T)Enum.ToObject(typeof (T), Convert.ToUInt64(value) | Convert.ToUInt64(flags)); 10: } Note that since the enum types are value types, we need to assign the result to something (much like string.Trim()).  Also, you could chain several SetFlag() operations together or create one that takes a variable arg list if desired. Parse() and ToString() – transitioning from string to enum and back Sometimes, you may want to be able to parse an enum from a string or convert it to a string - Enum has methods built in to let you do this.  Now, many may already know this, but may not appreciate how much power are in these two methods. For example, if you want to parse a string as an enum, it’s easy and works just like you’d expect from the numeric types: 1: string optionsString = "Persistent"; 2:  3: // can use Enum.Parse, which throws if finds something it doesn't like... 4: var result = (MessagingOptions)Enum.Parse(typeof (MessagingOptions), optionsString); 5:  6: if (result == MessagingOptions.Persistent) 7: { 8: Console.WriteLine("It worked!"); 9: } Note that Enum.Parse() will throw if it finds a value it doesn’t like.  But the values it likes are fairly flexible!  You can pass in a single value, or a comma separated list of values for flags and it will parse them all and set all bits: 1: // for string values, can have one, or comma separated. 2: string optionsString = "Persistent, Buffered"; 3:  4: var result = (MessagingOptions)Enum.Parse(typeof (MessagingOptions), optionsString); 5:  6: if (result.HasFlag(MessagingOptions.Persistent) && result.HasFlag(MessagingOptions.Buffered)) 7: { 8: Console.WriteLine("It worked!"); 9: } Or you can parse in a string containing a number that represents a single value or combination of values to set: 1: // 3 is the combination of Buffered (0x01) and Persistent (0x02) 2: var optionsString = "3"; 3:  4: var result = (MessagingOptions) Enum.Parse(typeof (MessagingOptions), optionsString); 5:  6: if (result.HasFlag(MessagingOptions.Persistent) && result.HasFlag(MessagingOptions.Buffered)) 7: { 8: Console.WriteLine("It worked again!"); 9: } And, if you really aren’t sure if the parse will work, and don’t want to handle an exception, you can use TryParse() instead: 1: string optionsString = "Persistent, Buffered"; 2: MessagingOptions result; 3:  4: // try parse returns true if successful, and takes an out parm for the result 5: if (Enum.TryParse(optionsString, out result)) 6: { 7: if (result.HasFlag(MessagingOptions.Persistent) && result.HasFlag(MessagingOptions.Buffered)) 8: { 9: Console.WriteLine("It worked!"); 10: } 11: } So we covered parsing a string to an enum, what about reversing that and converting an enum to a string?  The ToString() method is the obvious and most basic choice for most of us, but did you know you can pass a format string for enum types that dictate how they are written as a string?: 1: MessagingOptions value = MessagingOptions.Buffered | MessagingOptions.Persistent; 2:  3: // general format, which is the default, 4: Console.WriteLine("Default : " + value); 5: Console.WriteLine("G (default): " + value.ToString("G")); 6:  7: // Flags format, even if type does not have Flags attribute. 8: Console.WriteLine("F (flags) : " + value.ToString("F")); 9:  10: // integer format, value as number. 11: Console.WriteLine("D (num) : " + value.ToString("D")); 12:  13: // hex format, value as hex 14: Console.WriteLine("X (hex) : " + value.ToString("X")); Which displays: 1: Default : Buffered, Persistent 2: G (default): Buffered, Persistent 3: F (flags) : Buffered, Persistent 4: D (num) : 3 5: X (hex) : 00000003 Now, you may not really see a difference here between G and F because I used a [Flags] enum, the difference is that the “F” option treats the enum as if it were flags even if the [Flags] attribute is not present.  Let’s take a non-flags enum like the ResultCode used earlier: 1: // yes, we can do this even if it is not [Flags] enum. 2: ResultCode value = ResultCode.Warning | ResultCode.Error; And if we run that through the same formats again we get: 1: Default : 3 2: G (default): 3 3: F (flags) : Warning, Error 4: D (num) : 3 5: X (hex) : 00000003 Notice that since we had multiple values combined, but it was not a [Flags] marked enum, the G and default format gave us a number instead of a value name.  This is because the value was not a valid single-value constant of the enum.  However, using the F flags format string, it broke out the value into its component flags even though it wasn’t marked [Flags]. So, if you want to get an enum to display appropriately for whether or not it has the [Flags] attribute, use G which is the default.  If you always want it to attempt to break down the flags, use F.  For numeric output, obviously D or  X are the best choice depending on whether you want decimal or hex. Summary Hopefully, you learned a couple of new tricks with using the Enum class today!  I’ll add more little wonders as I think of them and thanks for all the invaluable input!   Technorati Tags: C#,.NET,Little Wonders,Enum,BlackRabbitCoder

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  • Business/Development Liaison Wanting To Enhance Understanding In Programming

    - by James Alexander
    I lead software development for a team of of about 20 devs and we're primarily a .net/sql server shop. We've recently created a new role in our organization for a more business like role to assist in prioritization of development and this business liaison has asked me if there are any books or resources he could use to better understand software concepts in a meaningful way. Any suggestions or advice would be greatly appreciated.

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  • Publish Static Content to WebLogic

    - by James Taylor
    Most people know WebLogic has a built in web server. Typically this is not an issue as you deploy java applications and WebLogic publishes to the web. But what if you just want to display a simple static HTML page. In WebLogic you can develop a simple web application to display static HTML content. In this example I used WLS 10.3.3. I want to display 2 files, an HTML file, and an xsd for reference. Create a directory of your choice, this is what I will call the document root. mkdir /u01/oracle/doc_root Copy the static files to this directory  In the document root directory created in step 1 create the directory WEB-INF mkdir WEB-INF In the WEB-INF directory create a file called web.xml with the following content <?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE web-app PUBLIC "-//Sun Microsystems, Inc.//DTD Web Application 2.3//EN" "http://java.sun.com/j2ee/dtds/web-app_2_3.dtd"> <web-app> </web-app> Login to the WebLogic console to deploy application Click on Deployments Click on Lock & Edit Click Install and set the path to the directory created in step 1 Leave default "Install this deployment as an application" and click Next Select a Managed Server to deploy to and click Next Accept the defaults and click Finish  Deployment completes successfully, now click the Activate Changes You should now see the application started in the deployments You can now access your static content via the following URL http://localhost:7001/doc_root/helloworld.html

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  • wcf http 504: Working on a mystery

    - by James Fleming
    Ok,  So you're here because you've been trying to solve the mystery of why you're getting a 504 error. If you've made it to this lonely corner of the Internet, then the advice you're getting from other bloggers isn't the answer you are after. It wasn't the answer I needed either, so once I did solve my problem, I thought I'd share the answer with you. For starters, if by some miracle, you landed here first you may not already know that the 504 error is NOT coming from IIS or Casini, that response code is coming from Fiddler. HTTP/1.1 504 Fiddler - Receive Failure Content-Type: text/html Connection: close Timestamp: 09:43:05.193 ReadResponse() failed: The server did not return a response for this request.       The take away here is Fiddler won't help you with the diagnosis and any further digging in that direction is a red herring. Assuming you've dug around a bit, you may have arrived at posts which suggest you may be getting the error because you're trying to hump too much data over the wire, and have an urgent need to employ an anti-pattern: due to a special case: http://delphimike.blogspot.com/2010/01/error-504-in-wcfnet-35.html Or perhaps you're experiencing wonky behavior using WCF-CustomIsolated Adapter on Windows Server 2008 64bit environment, in which case the rather fly MVP Dwight Goins' advice is what you need. http://dgoins.wordpress.com/2009/12/18/64bit-wcf-custom-isolated-%E2%80%93-rest-%E2%80%93-%E2%80%9C504%E2%80%9D-response/ For me, none of that was helpful. I could perform a get on a single record  http://localhost:8783/Criterion/Skip(0)/Take(1) but I couldn't get more than one record in my collection as in:  http://localhost:8783/Criterion/Skip(0)/Take(2) I didn't have a big payload, or a large number of objects (as you can see by the size of one record below) - - A-1B f5abd850-ec52-401a-8bac-bcea22c74138 .biological/legal mother This item refers to the supervisor’s evaluation of the caseworker’s ability to involve the biological/legal mother in the permanency planning process. 75d8ecb7-91df-475f-aa17-26367aeb8b21 false true Admin account 2010-01-06T17:58:24.88 1.20 764a2333-f445-4793-b54d-1c3084116daa So while I was able to retrieve one record without a hitch (thus the record above) I wasn't able to return multiple records. I confirmed I could get each record individually, (Skip(1)/Take(1))so it stood to reason the problem wasn't with the data at all, so I suspected a serialization error. The first step to resolving this was to enable WCF Tracing. Instructions on how to set it up are here: http://msdn.microsoft.com/en-us/library/ms733025.aspx. The tracing log led me to the solution. The use of type 'Application.Survey.Model.Criterion' as a get-only collection is not supported with NetDataContractSerializer.  Consider marking the type with the CollectionDataContractAttribute attribute or the SerializableAttribute attribute or adding a setter to the property. So I was wrong (but close!). The problem was a deserializing issue in trying to recreate my read only collection. http://msdn.microsoft.com/en-us/library/aa347850.aspx#Y1455 So looking at my underlying model, I saw I did have a read only collection. Adding a setter was all it took.         public virtual ICollection<string> GoverningResponses         {             get             {                 if (!string.IsNullOrEmpty(GoverningResponse))                 {                     return GoverningResponse.Split(';');                 }                 else                     return null;             }                  } Hope this helps. If it does, post a comment.

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  • C#/.NET Little Wonders: The Predicate, Comparison, and Converter Generic 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. In the last three weeks, we examined the Action family of delegates (and delegates in general), the Func family of delegates, and the EventHandler family of delegates and how they can be used to support generic, reusable algorithms and classes. This week I will be completing my series on the generic delegates in the .NET Framework with a discussion of three more, somewhat less used, generic delegates: Predicate<T>, Comparison<T>, and Converter<TInput, TOutput>. These are older generic delegates that were introduced in .NET 2.0, mostly for use in the Array and List<T> classes.  Though older, it’s good to have an understanding of them and their intended purpose.  In addition, you can feel free to use them yourself, though obviously you can also use the equivalents from the Func family of delegates instead. Predicate<T> – delegate for determining matches The Predicate<T> delegate was a very early delegate developed in the .NET 2.0 Framework to determine if an item was a match for some condition in a List<T> or T[].  The methods that tend to use the Predicate<T> include: Find(), FindAll(), FindLast() Uses the Predicate<T> delegate to finds items, in a list/array of type T, that matches the given predicate. FindIndex(), FindLastIndex() Uses the Predicate<T> delegate to find the index of an item, of in a list/array of type T, that matches the given predicate. The signature of the Predicate<T> delegate (ignoring variance for the moment) is: 1: public delegate bool Predicate<T>(T obj); So, this is a delegate type that supports any method taking an item of type T and returning bool.  In addition, there is a semantic understanding that this predicate is supposed to be examining the item supplied to see if it matches a given criteria. 1: // finds first even number (2) 2: var firstEven = Array.Find(numbers, n => (n % 2) == 0); 3:  4: // finds all odd numbers (1, 3, 5, 7, 9) 5: var allEvens = Array.FindAll(numbers, n => (n % 2) == 1); 6:  7: // find index of first multiple of 5 (4) 8: var firstFiveMultiplePos = Array.FindIndex(numbers, n => (n % 5) == 0); This delegate has typically been succeeded in LINQ by the more general Func family, so that Predicate<T> and Func<T, bool> are logically identical.  Strictly speaking, though, they are different types, so a delegate reference of type Predicate<T> cannot be directly assigned to a delegate reference of type Func<T, bool>, though the same method can be assigned to both. 1: // SUCCESS: the same lambda can be assigned to either 2: Predicate<DateTime> isSameDayPred = dt => dt.Date == DateTime.Today; 3: Func<DateTime, bool> isSameDayFunc = dt => dt.Date == DateTime.Today; 4:  5: // ERROR: once they are assigned to a delegate type, they are strongly 6: // typed and cannot be directly assigned to other delegate types. 7: isSameDayPred = isSameDayFunc; When you assign a method to a delegate, all that is required is that the signature matches.  This is why the same method can be assigned to either delegate type since their signatures are the same.  However, once the method has been assigned to a delegate type, it is now a strongly-typed reference to that delegate type, and it cannot be assigned to a different delegate type (beyond the bounds of variance depending on Framework version, of course). Comparison<T> – delegate for determining order Just as the Predicate<T> generic delegate was birthed to give Array and List<T> the ability to perform type-safe matching, the Comparison<T> was birthed to give them the ability to perform type-safe ordering. The Comparison<T> is used in Array and List<T> for: Sort() A form of the Sort() method that takes a comparison delegate; this is an alternate way to custom sort a list/array from having to define custom IComparer<T> classes. The signature for the Comparison<T> delegate looks like (without variance): 1: public delegate int Comparison<T>(T lhs, T rhs); The goal of this delegate is to compare the left-hand-side to the right-hand-side and return a negative number if the lhs < rhs, zero if they are equal, and a positive number if the lhs > rhs.  Generally speaking, null is considered to be the smallest value of any reference type, so null should always be less than non-null, and two null values should be considered equal. In most sort/ordering methods, you must specify an IComparer<T> if you want to do custom sorting/ordering.  The Array and List<T> types, however, also allow for an alternative Comparison<T> delegate to be used instead, essentially, this lets you perform the custom sort without having to have the custom IComparer<T> class defined. It should be noted, however, that the LINQ OrderBy(), and ThenBy() family of methods do not support the Comparison<T> delegate (though one could easily add their own extension methods to create one, or create an IComparer() factory class that generates one from a Comparison<T>). So, given this delegate, we could use it to perform easy sorts on an Array or List<T> based on custom fields.  Say for example we have a data class called Employee with some basic employee information: 1: public sealed class Employee 2: { 3: public string Name { get; set; } 4: public int Id { get; set; } 5: public double Salary { get; set; } 6: } And say we had a List<Employee> that contained data, such as: 1: var employees = new List<Employee> 2: { 3: new Employee { Name = "John Smith", Id = 2, Salary = 37000.0 }, 4: new Employee { Name = "Jane Doe", Id = 1, Salary = 57000.0 }, 5: new Employee { Name = "John Doe", Id = 5, Salary = 60000.0 }, 6: new Employee { Name = "Jane Smith", Id = 3, Salary = 59000.0 } 7: }; Now, using the Comparison<T> delegate form of Sort() on the List<Employee>, we can sort our list many ways: 1: // sort based on employee ID 2: employees.Sort((lhs, rhs) => Comparer<int>.Default.Compare(lhs.Id, rhs.Id)); 3:  4: // sort based on employee name 5: employees.Sort((lhs, rhs) => string.Compare(lhs.Name, rhs.Name)); 6:  7: // sort based on salary, descending (note switched lhs/rhs order for descending) 8: employees.Sort((lhs, rhs) => Comparer<double>.Default.Compare(rhs.Salary, lhs.Salary)); So again, you could use this older delegate, which has a lot of logical meaning to it’s name, or use a generic delegate such as Func<T, T, int> to implement the same sort of behavior.  All this said, one of the reasons, in my opinion, that Comparison<T> isn’t used too often is that it tends to need complex lambdas, and the LINQ ability to order based on projections is much easier to use, though the Array and List<T> sorts tend to be more efficient if you want to perform in-place ordering. Converter<TInput, TOutput> – delegate to convert elements The Converter<TInput, TOutput> delegate is used by the Array and List<T> delegate to specify how to convert elements from an array/list of one type (TInput) to another type (TOutput).  It is used in an array/list for: ConvertAll() Converts all elements from a List<TInput> / TInput[] to a new List<TOutput> / TOutput[]. The delegate signature for Converter<TInput, TOutput> is very straightforward (ignoring variance): 1: public delegate TOutput Converter<TInput, TOutput>(TInput input); So, this delegate’s job is to taken an input item (of type TInput) and convert it to a return result (of type TOutput).  Again, this is logically equivalent to a newer Func delegate with a signature of Func<TInput, TOutput>.  In fact, the latter is how the LINQ conversion methods are defined. So, we could use the ConvertAll() syntax to convert a List<T> or T[] to different types, such as: 1: // get a list of just employee IDs 2: var empIds = employees.ConvertAll(emp => emp.Id); 3:  4: // get a list of all emp salaries, as int instead of double: 5: var empSalaries = employees.ConvertAll(emp => (int)emp.Salary); Note that the expressions above are logically equivalent to using LINQ’s Select() method, which gives you a lot more power: 1: // get a list of just employee IDs 2: var empIds = employees.Select(emp => emp.Id).ToList(); 3:  4: // get a list of all emp salaries, as int instead of double: 5: var empSalaries = employees.Select(emp => (int)emp.Salary).ToList(); The only difference with using LINQ is that many of the methods (including Select()) are deferred execution, which means that often times they will not perform the conversion for an item until it is requested.  This has both pros and cons in that you gain the benefit of not performing work until it is actually needed, but on the flip side if you want the results now, there is overhead in the behind-the-scenes work that support deferred execution (it’s supported by the yield return / yield break keywords in C# which define iterators that maintain current state information). In general, the new LINQ syntax is preferred, but the older Array and List<T> ConvertAll() methods are still around, as is the Converter<TInput, TOutput> delegate. Sidebar: Variance support update in .NET 4.0 Just like our descriptions of Func and Action, these three early generic delegates also support more variance in assignment as of .NET 4.0.  Their new signatures are: 1: // comparison is contravariant on type being compared 2: public delegate int Comparison<in T>(T lhs, T rhs); 3:  4: // converter is contravariant on input and covariant on output 5: public delegate TOutput Contravariant<in TInput, out TOutput>(TInput input); 6:  7: // predicate is contravariant on input 8: public delegate bool Predicate<in T>(T obj); Thus these delegates can now be assigned to delegates allowing for contravariance (going to a more derived type) or covariance (going to a less derived type) based on whether the parameters are input or output, respectively. Summary Today, we wrapped up our generic delegates discussion by looking at three lesser-used delegates: Predicate<T>, Comparison<T>, and Converter<TInput, TOutput>.  All three of these tend to be replaced by their more generic Func equivalents in LINQ, but that doesn’t mean you shouldn’t understand what they do or can’t use them for your own code, as they do contain semantic meanings in their names that sometimes get lost in the more generic Func name.   Tweet Technorati Tags: C#,CSharp,.NET,Little Wonders,delegates,generics,Predicate,Converter,Comparison

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  • Review: A Quick Look at Reflector

    - by James Michael Hare
    I, like many, was disappointed when I heard that Reflector 7 was not free, and perhaps that’s why I waited so long to try it and just kept using my version 6 (which continues to be free).  But though I resisted for so long, I longed for the better features that were being developed, and began to wonder if I should upgrade.  Thus, I began to look into the features being offered in Reflector 7.5 to see what was new. Multiple Editions Reflector 7.5 comes in three flavors, each building on the features of the previous version: Standard – Contains just the Standalone application ($70) VS – Same as Standard but adds Reflector Object Browser for Visual Studio ($130) VSPro – Same as VS but adds ability to set breakpoints and step into decompiled code ($190) So let’s examine each of these features. The Standalone Application (Standard, VS, VSPro editions) Popping open Reflector 7.5 and looking at the GUI, we see much of the same familiar features, with a few new ones as well: Most notably, the disassembler window now has a tabbed window with navigation buttons.  This makes it much easier to back out of a deep-dive into many layers of decompiled code back to a previous point. Also, there is now an analyzer which can be used to determine dependencies for a given method, property, type, etc. For example, if we select System.Net.Sockets.TcpClient and hit the Analyze button, we’d see a window with the following nodes we could expand: This gives us the ability to see what a given type uses, what uses it, who exposes it, and who instantiates it. Now obviously, for low-level types (like DateTime) this list would be enormous, but this can give a lot of information on how a given type is connected to the larger code ecosystem. One of the other things I like about using Reflector 7.5 is that it does a much better job of displaying iterator blocks than Reflector 6 did. For example, if you were to take a look at the Enumerable.Cast() extension method in System.Linq, and dive into the CastIterator in Reflector 6, you’d see this: But now, in Reflector 7.5, we see the iterator logic much more clearly: This is a big improvement in the quality of their code disassembler and for me was one of the main reasons I decided to take the plunge and get version 7.5. The Reflector Object Browser (VS, VSPro editions) If you have the .NET Reflector VS or VSPro editions, you’ll find you have in Visual Studio a Reflector Object Browser window available where you can select and decompile any assembly right in Visual Studio. For example, if you want to take a peek at how System.Collections.Generic.List<T> works, you can either select List<T> in the Reflector Object Browser, or even simpler just select a usage of it in your code and CTRL + Click to dive in. – And it takes you right to a source window with the decompiled source: Setting Breakpoints and Stepping Into Decompiled Code (VSPro) If you have the VSPro edition, in addition to all the things said above, you also get the additional ability to set breakpoints in this decompiled code and step through it as if it were your own code: This can be a handy feature when you need to see why your code’s use of a BCL or other third-party library isn’t working as you expect. Summary Yes, Reflector is no longer free, and yes, that’s a bit of a bummer. But it always was and still is a very fine tool. If you still have Reflector 6, you aren’t forced to upgrade any longer, but getting the nicer disassembler (especially for iterator blocks) and the handy VS integration is worth at least considering upgrading for.  So I leave it up to you, these are some of the features of Reflector 7.5, what’s your thoughts? Technorati Tags: .NET,Reflector

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  • C#/.NET &ndash; Finding an Item&rsquo;s Index in IEnumerable&lt;T&gt;

    - by James Michael Hare
    Sorry for the long blogging hiatus.  First it was, of course, the holidays hustle and bustle, then my brother and his wife gave birth to their son, so I’ve been away from my blogging for two weeks. Background: Finding an item’s index in List<T> is easy… Many times in our day to day programming activities, we want to find the index of an item in a collection.  Now, if we have a List<T> and we’re looking for the item itself this is trivial: 1: // assume have a list of ints: 2: var list = new List<int> { 1, 13, 42, 64, 121, 77, 5, 99, 132 }; 3:  4: // can find the exact item using IndexOf() 5: var pos = list.IndexOf(64); This will return the position of the item if it’s found, or –1 if not.  It’s easy to see how this works for primitive types where equality is well defined.  For complex types, however, it will attempt to compare them using EqualityComparer<T>.Default which, in a nutshell, relies on the object’s Equals() method. So what if we want to search for a condition instead of equality?  That’s also easy in a List<T> with the FindIndex() method: 1: // assume have a list of ints: 2: var list = new List<int> { 1, 13, 42, 64, 121, 77, 5, 99, 132 }; 3:  4: // finds index of first even number or -1 if not found. 5: var pos = list.FindIndex(i => i % 2 == 0);   Problem: Finding an item’s index in IEnumerable<T> is not so easy... This is all well and good for lists, but what if we want to do the same thing for IEnumerable<T>?  A collection of IEnumerable<T> has no indexing, so there’s no direct method to find an item’s index.  LINQ, as powerful as it is, gives us many tools to get us this information, but not in one step.  As with almost any problem involving collections, there are several ways to accomplish the same goal.  And once again as with almost any problem involving collections, the choice of the solution somewhat depends on the situation. So let’s look at a few possible alternatives.  I’m going to express each of these as extension methods for simplicity and consistency. Solution: The TakeWhile() and Count() combo One of the things you can do is to perform a TakeWhile() on the list as long as your find condition is not true, and then do a Count() of the items it took.  The only downside to this method is that if the item is not in the list, the index will be the full Count() of items, and not –1.  So if you don’t know the size of the list beforehand, this can be confusing. 1: // a collection of extra extension methods off IEnumerable<T> 2: public static class EnumerableExtensions 3: { 4: // Finds an item in the collection, similar to List<T>.FindIndex() 5: public static int FindIndex<T>(this IEnumerable<T> list, Predicate<T> finder) 6: { 7: // note if item not found, result is length and not -1! 8: return list.TakeWhile(i => !finder(i)).Count(); 9: } 10: } Personally, I don’t like switching the paradigm of not found away from –1, so this is one of my least favorites.  Solution: Select with index Many people don’t realize that there is an alternative form of the LINQ Select() method that will provide you an index of the item being selected: 1: list.Select( (item,index) => do something here with the item and/or index... ) This can come in handy, but must be treated with care.  This is because the index provided is only as pertains to the result of previous operations (if any).  For example: 1: // assume have a list of ints: 2: var list = new List<int> { 1, 13, 42, 64, 121, 77, 5, 99, 132 }; 3:  4: // you'd hope this would give you the indexes of the even numbers 5: // which would be 2, 3, 8, but in reality it gives you 0, 1, 2 6: list.Where(item => item % 2 == 0).Select((item,index) => index); The reason the example gives you the collection { 0, 1, 2 } is because the where clause passes over any items that are odd, and therefore only the even items are given to the select and only they are given indexes. Conversely, we can’t select the index and then test the item in a Where() clause, because then the Where() clause would be operating on the index and not the item! So, what we have to do is to select the item and index and put them together in an anonymous type.  It looks ugly, but it works: 1: // extensions defined on IEnumerable<T> 2: public static class EnumerableExtensions 3: { 4: // finds an item in a collection, similar to List<T>.FindIndex() 5: public static int FindIndex<T>(this IEnumerable<T> list, Predicate<T> finder) 6: { 7: // if you don't name the anonymous properties they are the variable names 8: return list.Select((item, index) => new { item, index }) 9: .Where(p => finder(p.item)) 10: .Select(p => p.index + 1) 11: .FirstOrDefault() - 1; 12: } 13: }     So let’s look at this, because i know it’s convoluted: First Select() joins the items and their indexes into an anonymous type. Where() filters that list to only the ones matching the predicate. Second Select() picks the index of the matches and adds 1 – this is to distinguish between not found and first item. FirstOrDefault() returns the first item found from the previous clauses or default (zero) if not found. Subtract one so that not found (zero) will be –1, and first item (one) will be zero. The bad thing is, this is ugly as hell and creates anonymous objects for each item tested until it finds the match.  This concerns me a bit but we’ll defer judgment until compare the relative performances below. Solution: Convert ToList() and use FindIndex() This solution is easy enough.  We know any IEnumerable<T> can be converted to List<T> using the LINQ extension method ToList(), so we can easily convert the collection to a list and then just use the FindIndex() method baked into List<T>. 1: // a collection of extension methods for IEnumerable<T> 2: public static class EnumerableExtensions 3: { 4: // find the index of an item in the collection similar to List<T>.FindIndex() 5: public static int FindIndex<T>(this IEnumerable<T> list, Predicate<T> finder) 6: { 7: return list.ToList().FindIndex(finder); 8: } 9: } This solution is simplicity itself!  It is very concise and elegant and you need not worry about anyone misinterpreting what it’s trying to do (as opposed to the more convoluted LINQ methods above). But the main thing I’m concerned about here is the performance hit to allocate the List<T> in the ToList() call, but once again we’ll explore that in a second. Solution: Roll your own FindIndex() for IEnumerable<T> Of course, you can always roll your own FindIndex() method for IEnumerable<T>.  It would be a very simple for loop which scans for the item and counts as it goes.  There’s many ways to do this, but one such way might look like: 1: // extension methods for IEnumerable<T> 2: public static class EnumerableExtensions 3: { 4: // Finds an item matching a predicate in the enumeration, much like List<T>.FindIndex() 5: public static int FindIndex<T>(this IEnumerable<T> list, Predicate<T> finder) 6: { 7: int index = 0; 8: foreach (var item in list) 9: { 10: if (finder(item)) 11: { 12: return index; 13: } 14:  15: index++; 16: } 17:  18: return -1; 19: } 20: } Well, it’s not quite simplicity, and those less familiar with LINQ may prefer it since it doesn’t include all of the lambdas and behind the scenes iterators that come with deferred execution.  But does having this long, blown out method really gain us much in performance? Comparison of Proposed Solutions So we’ve now seen four solutions, let’s analyze their collective performance.  I took each of the four methods described above and run them over 100,000 iterations of lists of size 10, 100, 1000, and 10000 and here’s the performance results.  Then I looked for targets at the begining of the list (best case), middle of the list (the average case) and not in the list (worst case as must scan all of the list). Each of the times below is the average time in milliseconds for one execution as computer over the 100,000 iterations: Searches Matching First Item (Best Case)   10 100 1000 10000 TakeWhile 0.0003 0.0003 0.0003 0.0003 Select 0.0005 0.0005 0.0005 0.0005 ToList 0.0002 0.0003 0.0013 0.0121 Manual 0.0001 0.0001 0.0001 0.0001   Searches Matching Middle Item (Average Case)   10 100 1000 10000 TakeWhile 0.0004 0.0020 0.0191 0.1889 Select 0.0008 0.0042 0.0387 0.3802 ToList 0.0002 0.0007 0.0057 0.0562 Manual 0.0002 0.0013 0.0129 0.1255   Searches Where Not Found (Worst Case)   10 100 1000 10000 TakeWhile 0.0006 0.0039 0.0381 0.3770 Select 0.0012 0.0081 0.0758 0.7583 ToList 0.0002 0.0012 0.0100 0.0996 Manual 0.0003 0.0026 0.0253 0.2514   Notice something interesting here, you’d think the “roll your own” loop would be the most efficient, but it only wins when the item is first (or very close to it) regardless of list size.  In almost all other cases though and in particular the average case and worst case, the ToList()/FindIndex() combo wins for performance, even though it is creating some temporary memory to hold the List<T>.  If you examine the algorithm, the reason why is most likely because once it’s in a ToList() form, internally FindIndex() scans the internal array which is much more efficient to iterate over.  Thus, it takes a one time performance hit (not including any GC impact) to create the List<T> but after that the performance is much better. Summary If you’re concerned about too many throw-away objects, you can always roll your own FindIndex() method, but for sheer simplicity and overall performance, using the ToList()/FindIndex() combo performs best on nearly all list sizes in the average and worst cases.    Technorati Tags: C#,.NET,Litte Wonders,BlackRabbitCoder,Software,LINQ,List

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  • C#/.NET Little Wonders: The Timeout static class

    - 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. When I started the “Little Wonders” series, I really wanted to pay homage to parts of the .NET Framework that are often small but can help in big ways.  The item I have to discuss today really is a very small item in the .NET BCL, but once again I feel it can help make the intention of code much clearer and thus is worthy of note. The Problem - Magic numbers aren’t very readable or maintainable In my first Little Wonders Post (Five Little Wonders That Make Code Better) I mention the TimeSpan factory methods which, I feel, really help the readability of constructed TimeSpan instances. Just to quickly recap that discussion, ask yourself what the TimeSpan specified in each case below is 1: // Five minutes? Five Seconds? 2: var fiveWhat1 = new TimeSpan(0, 0, 5); 3: var fiveWhat2 = new TimeSpan(0, 0, 5, 0); 4: var fiveWhat3 = new TimeSpan(0, 0, 5, 0, 0); You’d think they’d all be the same unit of time, right?  After all, most overloads tend to tack additional arguments on the end.  But this is not the case with TimeSpan, where the constructor forms are:     TimeSpan(int hours, int minutes, int seconds);     TimeSpan(int days, int hours, int minutes, int seconds);     TimeSpan(int days, int hours, int minutes, int seconds, int milliseconds); Notice how in the 4 and 5 parameter version we suddenly have the parameter days slipping in front of hours?  This can make reading constructors like those above much harder.  Fortunately, there are TimeSpan factory methods to help make your intention crystal clear: 1: // Ah! Much clearer! 2: var fiveSeconds = TimeSpan.FromSeconds(5); These are great because they remove all ambiguity from the reader!  So in short, magic numbers in constructors and methods can be ambiguous, and anything we can do to clean up the intention of the developer will make the code much easier to read and maintain. Timeout – Readable identifiers for infinite timeout values In a similar way to TimeSpan, let’s consider specifying timeouts for some of .NET’s (or our own) many methods that allow you to specify timeout periods. For example, in the TPL Task class, there is a family of Wait() methods that can take TimeSpan or int for timeouts.  Typically, if you want to specify an infinite timeout, you’d just call the version that doesn’t take a timeout parameter at all: 1: myTask.Wait(); // infinite wait But there are versions that take the int or TimeSpan for timeout as well: 1: // Wait for 100 ms 2: myTask.Wait(100); 3:  4: // Wait for 5 seconds 5: myTask.Wait(TimeSpan.FromSeconds(5); Now, if we want to specify an infinite timeout to wait on the Task, we could pass –1 (or a TimeSpan set to –1 ms), which what the .NET BCL methods with timeouts use to represent an infinite timeout: 1: // Also infinite timeouts, but harder to read/maintain 2: myTask.Wait(-1); 3: myTask.Wait(TimeSpan.FromMilliseconds(-1)); However, these are not as readable or maintainable.  If you were writing this code, you might make the mistake of thinking 0 or int.MaxValue was an infinite timeout, and you’d be incorrect.  Also, reading the code above it isn’t as clear that –1 is infinite unless you happen to know that is the specified behavior. To make the code like this easier to read and maintain, there is a static class called Timeout in the System.Threading namespace which contains definition for infinite timeouts specified as both int and TimeSpan forms: Timeout.Infinite An integer constant with a value of –1 Timeout.InfiniteTimeSpan A static readonly TimeSpan which represents –1 ms (only available in .NET 4.5+) This makes our calls to Task.Wait() (or any other calls with timeouts) much more clear: 1: // intention to wait indefinitely is quite clear now 2: myTask.Wait(Timeout.Infinite); 3: myTask.Wait(Timeout.InfiniteTimeSpan); But wait, you may say, why would we care at all?  Why not use the version of Wait() that takes no arguments?  Good question!  When you’re directly calling the method with an infinite timeout that’s what you’d most likely do, but what if you are just passing along a timeout specified by a caller from higher up?  Or perhaps storing a timeout value from a configuration file, and want to default it to infinite? For example, perhaps you are designing a communications module and want to be able to shutdown gracefully, but if you can’t gracefully finish in a specified amount of time you want to force the connection closed.  You could create a Shutdown() method in your class, and take a TimeSpan or an int for the amount of time to wait for a clean shutdown – perhaps waiting for client to acknowledge – before terminating the connection.  So, assume we had a pub/sub system with a class to broadcast messages: 1: // Some class to broadcast messages to connected clients 2: public class Broadcaster 3: { 4: // ... 5:  6: // Shutdown connection to clients, wait for ack back from clients 7: // until all acks received or timeout, whichever happens first 8: public void Shutdown(int timeout) 9: { 10: // Kick off a task here to send shutdown request to clients and wait 11: // for the task to finish below for the specified time... 12:  13: if (!shutdownTask.Wait(timeout)) 14: { 15: // If Wait() returns false, we timed out and task 16: // did not join in time. 17: } 18: } 19: } We could even add an overload to allow us to use TimeSpan instead of int, to give our callers the flexibility to specify timeouts either way: 1: // overload to allow them to specify Timeout in TimeSpan, would 2: // just call the int version passing in the TotalMilliseconds... 3: public void Shutdown(TimeSpan timeout) 4: { 5: Shutdown(timeout.TotalMilliseconds); 6: } Notice in case of this class, we don’t assume the caller wants infinite timeouts, we choose to rely on them to tell us how long to wait.  So now, if they choose an infinite timeout, they could use the –1, which is more cryptic, or use Timeout class to make the intention clear: 1: // shutdown the broadcaster, waiting until all clients ack back 2: // without timing out. 3: myBroadcaster.Shutdown(Timeout.Infinite); We could even add a default argument using the int parameter version so that specifying no arguments to Shutdown() assumes an infinite timeout: 1: // Modified original Shutdown() method to add a default of 2: // Timeout.Infinite, works because Timeout.Infinite is a compile 3: // time constant. 4: public void Shutdown(int timeout = Timeout.Infinite) 5: { 6: // same code as before 7: } Note that you can’t default the ShutDown(TimeSpan) overload with Timeout.InfiniteTimeSpan since it is not a compile-time constant.  The only acceptable default for a TimeSpan parameter would be default(TimeSpan) which is zero milliseconds, which specified no wait, not infinite wait. Summary While Timeout.Infinite and Timeout.InfiniteTimeSpan are not earth-shattering classes in terms of functionality, they do give you very handy and readable constant values that you can use in your programs to help increase readability and maintainability when specifying infinite timeouts for various timeouts in the BCL and your own applications. Technorati Tags: C#,CSharp,.NET,Little Wonders,Timeout,Task

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  • Of C# Iterators and Performance

    - by James Michael Hare
    Some of you reading this will be wondering, "what is an iterator" and think I'm locked in the world of C++.  Nope, I'm talking C# iterators.  No, not enumerators, iterators.   So, for those of you who do not know what iterators are in C#, I will explain it in summary, and for those of you who know what iterators are but are curious of the performance impacts, I will explore that as well.   Iterators have been around for a bit now, and there are still a bunch of people who don't know what they are or what they do.  I don't know how many times at work I've had a code review on my code and have someone ask me, "what's that yield word do?"   Basically, this post came to me as I was writing some extension methods to extend IEnumerable<T> -- I'll post some of the fun ones in a later post.  Since I was filtering the resulting list down, I was using the standard C# iterator concept; but that got me wondering: what are the performance implications of using an iterator versus returning a new enumeration?   So, to begin, let's look at a couple of methods.  This is a new (albeit contrived) method called Every(...).  The goal of this method is to access and enumeration and return every nth item in the enumeration (including the first).  So Every(2) would return items 0, 2, 4, 6, etc.   Now, if you wanted to write this in the traditional way, you may come up with something like this:       public static IEnumerable<T> Every<T>(this IEnumerable<T> list, int interval)     {         List<T> newList = new List<T>();         int count = 0;           foreach (var i in list)         {             if ((count++ % interval) == 0)             {                 newList.Add(i);             }         }           return newList;     }     So basically this method takes any IEnumerable<T> and returns a new IEnumerable<T> that contains every nth item.  Pretty straight forward.   The problem?  Well, Every<T>(...) will construct a list containing every nth item whether or not you care.  What happens if you were searching this result for a certain item and find that item after five tries?  You would have generated the rest of the list for nothing.   Enter iterators.  This C# construct uses the yield keyword to effectively defer evaluation of the next item until it is asked for.  This can be very handy if the evaluation itself is expensive or if there's a fair chance you'll never want to fully evaluate a list.   We see this all the time in Linq, where many expressions are chained together to do complex processing on a list.  This would be very expensive if each of these expressions evaluated their entire possible result set on call.    Let's look at the same example function, this time using an iterator:       public static IEnumerable<T> Every<T>(this IEnumerable<T> list, int interval)     {         int count = 0;         foreach (var i in list)         {             if ((count++ % interval) == 0)             {                 yield return i;             }         }     }   Notice it does not create a new return value explicitly, the only evidence of a return is the "yield return" statement.  What this means is that when an item is requested from the enumeration, it will enter this method and evaluate until it either hits a yield return (in which case that item is returned) or until it exits the method or hits a yield break (in which case the iteration ends.   Behind the scenes, this is all done with a class that the CLR creates behind the scenes that keeps track of the state of the iteration, so that every time the next item is asked for, it finds that item and then updates the current position so it knows where to start at next time.   It doesn't seem like a big deal, does it?  But keep in mind the key point here: it only returns items as they are requested. Thus if there's a good chance you will only process a portion of the return list and/or if the evaluation of each item is expensive, an iterator may be of benefit.   This is especially true if you intend your methods to be chainable similar to the way Linq methods can be chained.    For example, perhaps you have a List<int> and you want to take every tenth one until you find one greater than 10.  We could write that as:       List<int> someList = new List<int>();         // fill list here         someList.Every(10).TakeWhile(i => i <= 10);     Now is the difference more apparent?  If we use the first form of Every that makes a copy of the list.  It's going to copy the entire list whether we will need those items or not, that can be costly!    With the iterator version, however, it will only take items from the list until it finds one that is > 10, at which point no further items in the list are evaluated.   So, sounds neat eh?  But what's the cost is what you're probably wondering.  So I ran some tests using the two forms of Every above on lists varying from 5 to 500,000 integers and tried various things.    Now, iteration isn't free.  If you are more likely than not to iterate the entire collection every time, iterator has some very slight overhead:   Copy vs Iterator on 100% of Collection (10,000 iterations) Collection Size Num Iterated Type Total ms 5 5 Copy 5 5 5 Iterator 5 50 50 Copy 28 50 50 Iterator 27 500 500 Copy 227 500 500 Iterator 247 5000 5000 Copy 2266 5000 5000 Iterator 2444 50,000 50,000 Copy 24,443 50,000 50,000 Iterator 24,719 500,000 500,000 Copy 250,024 500,000 500,000 Iterator 251,521   Notice that when iterating over the entire produced list, the times for the iterator are a little better for smaller lists, then getting just a slight bit worse for larger lists.  In reality, given the number of items and iterations, the result is near negligible, but just to show that iterators come at a price.  However, it should also be noted that the form of Every that returns a copy will have a left-over collection to garbage collect.   However, if we only partially evaluate less and less through the list, the savings start to show and make it well worth the overhead.  Let's look at what happens if you stop looking after 80% of the list:   Copy vs Iterator on 80% of Collection (10,000 iterations) Collection Size Num Iterated Type Total ms 5 4 Copy 5 5 4 Iterator 5 50 40 Copy 27 50 40 Iterator 23 500 400 Copy 215 500 400 Iterator 200 5000 4000 Copy 2099 5000 4000 Iterator 1962 50,000 40,000 Copy 22,385 50,000 40,000 Iterator 19,599 500,000 400,000 Copy 236,427 500,000 400,000 Iterator 196,010       Notice that the iterator form is now operating quite a bit faster.  But the savings really add up if you stop on average at 50% (which most searches would typically do):     Copy vs Iterator on 50% of Collection (10,000 iterations) Collection Size Num Iterated Type Total ms 5 2 Copy 5 5 2 Iterator 4 50 25 Copy 25 50 25 Iterator 16 500 250 Copy 188 500 250 Iterator 126 5000 2500 Copy 1854 5000 2500 Iterator 1226 50,000 25,000 Copy 19,839 50,000 25,000 Iterator 12,233 500,000 250,000 Copy 208,667 500,000 250,000 Iterator 122,336   Now we see that if we only expect to go on average 50% into the results, we tend to shave off around 40% of the time.  And this is only for one level deep.  If we are using this in a chain of query expressions it only adds to the savings.   So my recommendation?  If you have a resonable expectation that someone may only want to partially consume your enumerable result, I would always tend to favor an iterator.  The cost if they iterate the whole thing does not add much at all -- and if they consume only partially, you reap some really good performance gains.   Next time I'll discuss some of my favorite extensions I've created to make development life a little easier and maintainability a little better.

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  • Analysis Services (SSAS) - Unexpected Internal Error when processing (ProcessUpdate). Workaround/Resolution

    - by James Rogers
    Many implementations require the use of ProcessUpdate to support Type 1 slowly changing dimensions. ProcessUpdate drops all of the affected indexes and aggregations in partitions affected by data that changes in the Dimension on which the ProcessUpdate is being performed. Twice now I have had situations where the processing fails with "Internal error: An unexpected exception occurred." Any subsequent ProcessUpdate processing will also fail with the same error. In talking with Microsoft the issue is corrupt indexes for the Dimension(s) being processed in the partitions of the affected measure group. I cannot guarantee that the following will correct your problem but it did in my case and saved us quite a bit of down time.   Workaround: ProcessIndexes on the entire cube that is being processed and throwing the error. This corrected the problem on both 2008 and 2008 R2.   Pros:  Does not require a complete rebuild of the data (ProcessFull) for either the Dimension or Cube. User access can continue while this ProcessIndexes in underway.   Cons: Can take a long time, especially on large cubes with many partitions, dimensions and/or aggregations. Query Performance is usually severely impacted due to the memory and CPU requirements for Aggregation and Index building   <Batch http://schemas.microsoft.com/analysisservices/2003/engine"http://schemas.microsoft.com/analysisservices/2003/engine">  <Parallel>     <Process xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ddl2="http://schemas.microsoft.com/analysisservices/2003/engine/2" xmlns:ddl2_2="http://schemas.microsoft.com/analysisservices/2003/engine/2/2" xmlns:ddl100_100="http://schemas.microsoft.com/analysisservices/2008/engine/100/100" xmlns:ddl200="http://schemas.microsoft.com/analysisservices/2010/engine/200" xmlns:ddl200_200="http://schemas.microsoft.com/analysisservices/2010/engine/200/200">       <Object>         <DatabaseID>MyDatabase</DatabaseID>         <CubeID>MyCube</CubeID>       </Object>       <Type>ProcessIndexes</Type>       <WriteBackTableCreation>UseExisting</WriteBackTableCreation>     </Process>  </Parallel> </Batch>   The cube where the corruption exists can be found by having Profiler running while the ProcessUpdate is executing. The first partition that displays the "The Job has ended in failure." message in the TextData column will be part of the cube/measuregroup that has the corruption. You can try to run ProcessIndexes on just that measure group. This may correct the problem and save additional time if you have other large measure groups in the cube that are not affected by the corruption.   Remember to execute your normal ProcessUpdate batch after the successful completion of the ProcessIndexes. The ProcessIndexes does not pick up data changes.   Things that did not work: ProcessClearIndexes - why this doesn't work and ProcessIndexes does is unclear at this point. ProcessFull on the partition in question. In my latest case, this would clear up the problem for that partition. However, the next partition the ProcessUpdate touched that had data in it would generate and error. This leads me to believe the corruption problem will exist in all partitions in the affected measure group that have data in them.   NOTE: I experience this problem in both a SQL 2008 and SQL 2008 R2 Analysis Services environment, on separate built from the same relational database. This leads me to believe that some data condition in the tables used for the Dimension processing caused the corruption since the two environments were on physically separate hardware. I am waiting on Microsoft to analyze the dumps to give us more insight into what actually caused the corruption and will update this post accordingly.

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  • Detecting 404 errors after a new site design

    - by James Crowley
    We recently re-designed Developer Fusion and as part of that we needed to ensure that any external links were not broken in the process. In order to monitor this, we used the awesome LogParser tool. All you need to do is open up a command prompt, navigate to the directory with your web site's log files in, and run a query like this: "c:\program files (x86)\log parser 2.2\logparser" "SELECT top 500 cs-uri-stem,count(*) FROM u_ex*.log WHERE sc-status=404 GROUP BY cs-uri-stem order by count(*) desc" -rtp:-1 topMissingUrls.txt And you've got a text file with the top 500 requested URLs that are returning 404. Simple!

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  • Is there a way to update all Java related alternatives?

    - by James McMahon
    Is there a way to quickly switch over all the Java related alternatives using update-alternatives? For instance, if want to switch Java over to 7, I run sudo update-alternatives --config java and select the Java 7 OpenJdk. But if I run update-alternatives --get-selections | grep java I get the following, appletviewer auto /usr/lib/jvm/java-6-openjdk-amd64/bin/appletviewer extcheck auto /usr/lib/jvm/java-6-openjdk-amd64/bin/extcheck idlj auto /usr/lib/jvm/java-6-openjdk-amd64/bin/idlj itweb-settings auto /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/itweb-settings jar auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jar jarsigner auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jarsigner java manual /usr/lib/jvm/java-7-openjdk-amd64/jre/bin/java javac auto /usr/lib/jvm/java-6-openjdk-amd64/bin/javac javadoc auto /usr/lib/jvm/java-6-openjdk-amd64/bin/javadoc javah auto /usr/lib/jvm/java-6-openjdk-amd64/bin/javah javap auto /usr/lib/jvm/java-6-openjdk-amd64/bin/javap javaws auto /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/javaws jconsole auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jconsole jdb auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jdb jexec auto /usr/lib/jvm/java-6-openjdk-amd64/jre/lib/jexec jhat auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jhat jinfo auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jinfo jmap auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jmap jps auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jps jrunscript auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jrunscript jsadebugd auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jsadebugd jstack auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jstack jstat auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jstat jstatd auto /usr/lib/jvm/java-6-openjdk-amd64/bin/jstatd keytool auto /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/keytool native2ascii auto /usr/lib/jvm/java-6-openjdk-amd64/bin/native2ascii orbd auto /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/orbd pack200 auto /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/pack200 policytool auto /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/policytool rmic auto /usr/lib/jvm/java-6-openjdk-amd64/bin/rmic rmid auto /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/rmid rmiregistry auto /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/rmiregistry schemagen auto /usr/lib/jvm/java-6-openjdk-amd64/bin/schemagen serialver auto /usr/lib/jvm/java-6-openjdk-amd64/bin/serialver servertool auto /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/servertool tnameserv auto /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/tnameserv unpack200 auto /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/unpack200 wsgen auto /usr/lib/jvm/java-6-openjdk-amd64/bin/wsgen wsimport auto /usr/lib/jvm/java-6-openjdk-amd64/bin/wsimport xjc auto /usr/lib/jvm/java-6-openjdk-amd64/bin/xjc As you can see, my Java alternative was switched over to 7, but every other alternative based on OpenJDK 6 was not switched over. Sure I could switch each one manually or write a script to do so, but I assume there is a better way to accomplish this.

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  • Managing Personal Projects As Solo Developer - Getting out of depth and failing projects

    - by James Jeffery
    I need some advice on project management. I start a project, and often times it will a large project for a solo developer. Usually its a web project. I handle everything from the UI, to the JS, PHP, server management etc. Half way in I feel out of my depth. I lose where I am, so I spend a couple of days away from the project to avoid the stress and before you know it, it becomes another unfinished project. I try to use frameworks and code libraries to make my developments easier on myself. Sometimes I will complete a project so it "works" and then go back and handle errors, design the UI properly and stuff. But without fail I will always end up out of my depth. I've though about outsourcing tasks such as the UI, and the behaviour, and focusing just on the PHP - which I feel is my strong point. But then pride kicks in, and I don't feel at one with a project I haven't completed myself. Does this make sense? I am sure there are many others who have felt like this either at home, or at work, and I would love some advice on managing my projects better.

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  • C#: Why Decorate When You Can Intercept

    - by James Michael Hare
    We've all heard of the old Decorator Design Pattern (here) or used it at one time or another either directly or indirectly.  A decorator is a class that wraps a given abstract class or interface and presents the same (or a superset) public interface but "decorated" with additional functionality.   As a really simplistic example, consider the System.IO.BufferedStream, it itself is a descendent of System.IO.Stream and wraps the given stream with buffering logic while still presenting System.IO.Stream's public interface:   1: Stream buffStream = new BufferedStream(rawStream); Now, let's take a look at a custom-code example.  Let's say that we have a class in our data access layer that retrieves a list of products from a database:  1: // a class that handles our CRUD operations for products 2: public class ProductDao 3: { 4: ... 5:  6: // a method that would retrieve all available products 7: public IEnumerable<Product> GetAvailableProducts() 8: { 9: var results = new List<Product>(); 10:  11: // must create the connection 12: using (var con = _factory.CreateConnection()) 13: { 14: con.ConnectionString = _productsConnectionString; 15: con.Open(); 16:  17: // create the command 18: using (var cmd = _factory.CreateCommand()) 19: { 20: cmd.Connection = con; 21: cmd.CommandText = _getAllProductsStoredProc; 22: cmd.CommandType = CommandType.StoredProcedure; 23:  24: // get a reader and pass back all results 25: using (var reader = cmd.ExecuteReader()) 26: { 27: while(reader.Read()) 28: { 29: results.Add(new Product 30: { 31: Name = reader["product_name"].ToString(), 32: ... 33: }); 34: } 35: } 36: } 37: }            38:  39: return results; 40: } 41: } Yes, you could use EF or any myriad other choices for this sort of thing, but the germaine point is that you have some operation that takes a non-trivial amount of time.  What if, during the production day I notice that my application is performing slowly and I want to see how much of that slowness is in the query versus my code.  Well, I could easily wrap the logic block in a System.Diagnostics.Stopwatch and log the results to log4net or other logging flavor of choice: 1:     // a class that handles our CRUD operations for products 2:     public class ProductDao 3:     { 4:         private static readonly ILog _log = LogManager.GetLogger(typeof(ProductDao)); 5:         ... 6:         7:         // a method that would retrieve all available products 8:         public IEnumerable<Product> GetAvailableProducts() 9:         { 10:             var results = new List<Product>(); 11:             var timer = Stopwatch.StartNew(); 12:             13:             // must create the connection 14:             using (var con = _factory.CreateConnection()) 15:             { 16:                 con.ConnectionString = _productsConnectionString; 17:                 18:                 // and all that other DB code... 19:                 ... 20:             } 21:             22:             timer.Stop(); 23:             24:             if (timer.ElapsedMilliseconds > 5000) 25:             { 26:                 _log.WarnFormat("Long query in GetAvailableProducts() took {0} ms", 27:                     timer.ElapsedMillseconds); 28:             } 29:             30:             return results; 31:         } 32:     } In my eye, this is very ugly.  It violates Single Responsibility Principle (SRP), which says that a class should only ever have one responsibility, where responsibility is often defined as a reason to change.  This class (and in particular this method) has two reasons to change: If the method of retrieving products changes. If the method of logging changes. Well, we could “simplify” this using the Decorator Design Pattern (here).  If we followed the pattern to the letter, we'd need to create a base decorator that implements the DAOs public interface and forwards to the wrapped instance.  So let's assume we break out the ProductDAO interface into IProductDAO using your refactoring tool of choice (Resharper is great for this). Now, ProductDao will implement IProductDao and get rid of all logging logic: 1:     public class ProductDao : IProductDao 2:     { 3:         // this reverts back to original version except for the interface added 4:     } 5:  And we create the base Decorator that also implements the interface and forwards all calls: 1:     public class ProductDaoDecorator : IProductDao 2:     { 3:         private readonly IProductDao _wrappedDao; 4:         5:         // constructor takes the dao to wrap 6:         public ProductDaoDecorator(IProductDao wrappedDao) 7:         { 8:             _wrappedDao = wrappedDao; 9:         } 10:         11:         ... 12:         13:         // and then all methods just forward their calls 14:         public IEnumerable<Product> GetAvailableProducts() 15:         { 16:             return _wrappedDao.GetAvailableProducts(); 17:         } 18:     } This defines our base decorator, then we can create decorators that add items of interest, and for any methods we don't decorate, we'll get the default behavior which just forwards the call to the wrapper in the base decorator: 1:     public class TimedThresholdProductDaoDecorator : ProductDaoDecorator 2:     { 3:         private static readonly ILog _log = LogManager.GetLogger(typeof(TimedThresholdProductDaoDecorator)); 4:         5:         public TimedThresholdProductDaoDecorator(IProductDao wrappedDao) : 6:             base(wrappedDao) 7:         { 8:         } 9:         10:         ... 11:         12:         public IEnumerable<Product> GetAvailableProducts() 13:         { 14:             var timer = Stopwatch.StartNew(); 15:             16:             var results = _wrapped.GetAvailableProducts(); 17:             18:             timer.Stop(); 19:             20:             if (timer.ElapsedMilliseconds > 5000) 21:             { 22:                 _log.WarnFormat("Long query in GetAvailableProducts() took {0} ms", 23:                     timer.ElapsedMillseconds); 24:             } 25:             26:             return results; 27:         } 28:     } Well, it's a bit better.  Now the logging is in its own class, and the database logic is in its own class.  But we've essentially multiplied the number of classes.  We now have 3 classes and one interface!  Now if you want to do that same logging decorating on all your DAOs, imagine the code bloat!  Sure, you can simplify and avoid creating the base decorator, or chuck it all and just inherit directly.  But regardless all of these have the problem of tying the logging logic into the code itself. Enter the Interceptors.  Things like this to me are a perfect example of when it's good to write an Interceptor using your class library of choice.  Sure, you could design your own perfectly generic decorator with delegates and all that, but personally I'm a big fan of Castle's Dynamic Proxy (here) which is actually used by many projects including Moq. What DynamicProxy allows you to do is intercept calls into any object by wrapping it with a proxy on the fly that intercepts the method and allows you to add functionality.  Essentially, the code would now look like this using DynamicProxy: 1: // Note: I like hiding DynamicProxy behind the scenes so users 2: // don't have to explicitly add reference to Castle's libraries. 3: public static class TimeThresholdInterceptor 4: { 5: // Our logging handle 6: private static readonly ILog _log = LogManager.GetLogger(typeof(TimeThresholdInterceptor)); 7:  8: // Handle to Castle's proxy generator 9: private static readonly ProxyGenerator _generator = new ProxyGenerator(); 10:  11: // generic form for those who prefer it 12: public static object Create<TInterface>(object target, TimeSpan threshold) 13: { 14: return Create(typeof(TInterface), target, threshold); 15: } 16:  17: // Form that uses type instead 18: public static object Create(Type interfaceType, object target, TimeSpan threshold) 19: { 20: return _generator.CreateInterfaceProxyWithTarget(interfaceType, target, 21: new TimedThreshold(threshold, level)); 22: } 23:  24: // The interceptor that is created to intercept the interface calls. 25: // Hidden as a private inner class so not exposing Castle libraries. 26: private class TimedThreshold : IInterceptor 27: { 28: // The threshold as a positive timespan that triggers a log message. 29: private readonly TimeSpan _threshold; 30:  31: // interceptor constructor 32: public TimedThreshold(TimeSpan threshold) 33: { 34: _threshold = threshold; 35: } 36:  37: // Intercept functor for each method invokation 38: public void Intercept(IInvocation invocation) 39: { 40: // time the method invocation 41: var timer = Stopwatch.StartNew(); 42:  43: // the Castle magic that tells the method to go ahead 44: invocation.Proceed(); 45:  46: timer.Stop(); 47:  48: // check if threshold is exceeded 49: if (timer.Elapsed > _threshold) 50: { 51: _log.WarnFormat("Long execution in {0} took {1} ms", 52: invocation.Method.Name, 53: timer.ElapsedMillseconds); 54: } 55: } 56: } 57: } Yes, it's a bit longer, but notice that: This class ONLY deals with logging long method calls, no DAO interface leftovers. This class can be used to time ANY class that has an interface or virtual methods. Personally, I like to wrap and hide the usage of DynamicProxy and IInterceptor so that anyone who uses this class doesn't need to know to add a Castle library reference.  As far as they are concerned, they're using my interceptor.  If I change to a new library if a better one comes along, they're insulated. Now, all we have to do to use this is to tell it to wrap our ProductDao and it does the rest: 1: // wraps a new ProductDao with a timing interceptor with a threshold of 5 seconds 2: IProductDao dao = TimeThresholdInterceptor.Create<IProductDao>(new ProductDao(), 5000); Automatic decoration of all methods!  You can even refine the proxy so that it only intercepts certain methods. This is ideal for so many things.  These are just some of the interceptors we've dreamed up and use: Log parameters and returns of methods to XML for auditing. Block invocations to methods and return default value (stubbing). Throw exception if certain methods are called (good for blocking access to deprecated methods). Log entrance and exit of a method and the duration. Log a message if a method takes more than a given time threshold to execute. Whether you use DynamicProxy or some other technology, I hope you see the benefits this adds.  Does it completely eliminate all need for the Decorator pattern?  No, there may still be cases where you want to decorate a particular class with functionality that doesn't apply to the world at large. But for all those cases where you are using Decorator to add functionality that's truly generic.  I strongly suggest you give this a try!

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  • C#: LINQ vs foreach - Round 1.

    - by James Michael Hare
    So I was reading Peter Kellner's blog entry on Resharper 5.0 and its LINQ refactoring and thought that was very cool.  But that raised a point I had always been curious about in my head -- which is a better choice: manual foreach loops or LINQ?    The answer is not really clear-cut.  There are two sides to any code cost arguments: performance and maintainability.  The first of these is obvious and quantifiable.  Given any two pieces of code that perform the same function, you can run them side-by-side and see which piece of code performs better.   Unfortunately, this is not always a good measure.  Well written assembly language outperforms well written C++ code, but you lose a lot in maintainability which creates a big techncial debt load that is hard to offset as the application ages.  In contrast, higher level constructs make the code more brief and easier to understand, hence reducing technical cost.   Now, obviously in this case we're not talking two separate languages, we're comparing doing something manually in the language versus using a higher-order set of IEnumerable extensions that are in the System.Linq library.   Well, before we discuss any further, let's look at some sample code and the numbers.  First, let's take a look at the for loop and the LINQ expression.  This is just a simple find comparison:       // find implemented via LINQ     public static bool FindViaLinq(IEnumerable<int> list, int target)     {         return list.Any(item => item == target);     }         // find implemented via standard iteration     public static bool FindViaIteration(IEnumerable<int> list, int target)     {         foreach (var i in list)         {             if (i == target)             {                 return true;             }         }           return false;     }   Okay, looking at this from a maintainability point of view, the Linq expression is definitely more concise (8 lines down to 1) and is very readable in intention.  You don't have to actually analyze the behavior of the loop to determine what it's doing.   So let's take a look at performance metrics from 100,000 iterations of these methods on a List<int> of varying sizes filled with random data.  For this test, we fill a target array with 100,000 random integers and then run the exact same pseudo-random targets through both searches.                       List<T> On 100,000 Iterations     Method      Size     Total (ms)  Per Iteration (ms)  % Slower     Any         10       26          0.00046             30.00%     Iteration   10       20          0.00023             -     Any         100      116         0.00201             18.37%     Iteration   100      98          0.00118             -     Any         1000     1058        0.01853             16.78%     Iteration   1000     906         0.01155             -     Any         10,000   10,383      0.18189             17.41%     Iteration   10,000   8843        0.11362             -     Any         100,000  104,004     1.8297              18.27%     Iteration   100,000  87,941      1.13163             -   The LINQ expression is running about 17% slower for average size collections and worse for smaller collections.  Presumably, this is due to the overhead of the state machine used to track the iterators for the yield returns in the LINQ expressions, which seems about right in a tight loop such as this.   So what about other LINQ expressions?  After all, Any() is one of the more trivial ones.  I decided to try the TakeWhile() algorithm using a Count() to get the position stopped like the sample Pete was using in his blog that Resharper refactored for him into LINQ:       // Linq form     public static int GetTargetPosition1(IEnumerable<int> list, int target)     {         return list.TakeWhile(item => item != target).Count();     }       // traditionally iterative form     public static int GetTargetPosition2(IEnumerable<int> list, int target)     {         int count = 0;           foreach (var i in list)         {             if(i == target)             {                 break;             }               ++count;         }           return count;     }   Once again, the LINQ expression is much shorter, easier to read, and should be easier to maintain over time, reducing the cost of technical debt.  So I ran these through the same test data:                       List<T> On 100,000 Iterations     Method      Size     Total (ms)  Per Iteration (ms)  % Slower     TakeWhile   10       41          0.00041             128%     Iteration   10       18          0.00018             -     TakeWhile   100      171         0.00171             88%     Iteration   100      91          0.00091             -     TakeWhile   1000     1604        0.01604             94%     Iteration   1000     825         0.00825             -     TakeWhile   10,000   15765       0.15765             92%     Iteration   10,000   8204        0.08204             -     TakeWhile   100,000  156950      1.5695              92%     Iteration   100,000  81635       0.81635             -     Wow!  I expected some overhead due to the state machines iterators produce, but 90% slower?  That seems a little heavy to me.  So then I thought, well, what if TakeWhile() is not the right tool for the job?  The problem is TakeWhile returns each item for processing using yield return, whereas our for-loop really doesn't care about the item beyond using it as a stop condition to evaluate. So what if that back and forth with the iterator state machine is the problem?  Well, we can quickly create an (albeit ugly) lambda that uses the Any() along with a count in a closure (if a LINQ guru knows a better way PLEASE let me know!), after all , this is more consistent with what we're trying to do, we're trying to find the first occurence of an item and halt once we find it, we just happen to be counting on the way.  This mostly matches Any().       // a new method that uses linq but evaluates the count in a closure.     public static int TakeWhileViaLinq2(IEnumerable<int> list, int target)     {         int count = 0;         list.Any(item =>             {                 if(item == target)                 {                     return true;                 }                   ++count;                 return false;             });         return count;     }     Now how does this one compare?                         List<T> On 100,000 Iterations     Method         Size     Total (ms)  Per Iteration (ms)  % Slower     TakeWhile      10       41          0.00041             128%     Any w/Closure  10       23          0.00023             28%     Iteration      10       18          0.00018             -     TakeWhile      100      171         0.00171             88%     Any w/Closure  100      116         0.00116             27%     Iteration      100      91          0.00091             -     TakeWhile      1000     1604        0.01604             94%     Any w/Closure  1000     1101        0.01101             33%     Iteration      1000     825         0.00825             -     TakeWhile      10,000   15765       0.15765             92%     Any w/Closure  10,000   10802       0.10802             32%     Iteration      10,000   8204        0.08204             -     TakeWhile      100,000  156950      1.5695              92%     Any w/Closure  100,000  108378      1.08378             33%     Iteration      100,000  81635       0.81635             -     Much better!  It seems that the overhead of TakeAny() returning each item and updating the state in the state machine is drastically reduced by using Any() since Any() iterates forward until it finds the value we're looking for -- for the task we're attempting to do.   So the lesson there is, make sure when you use a LINQ expression you're choosing the best expression for the job, because if you're doing more work than you really need, you'll have a slower algorithm.  But this is true of any choice of algorithm or collection in general.     Even with the Any() with the count in the closure it is still about 30% slower, but let's consider that angle carefully.  For a list of 100,000 items, it was the difference between 1.01 ms and 0.82 ms roughly in a List<T>.  That's really not that bad at all in the grand scheme of things.  Even running at 90% slower with TakeWhile(), for the vast majority of my projects, an extra millisecond to save potential errors in the long term and improve maintainability is a small price to pay.  And if your typical list is 1000 items or less we're talking only microseconds worth of difference.   It's like they say: 90% of your performance bottlenecks are in 2% of your code, so over-optimizing almost never pays off.  So personally, I'll take the LINQ expression wherever I can because they will be easier to read and maintain (thus reducing technical debt) and I can rely on Microsoft's development to have coded and unit tested those algorithm fully for me instead of relying on a developer to code the loop logic correctly.   If something's 90% slower, yes, it's worth keeping in mind, but it's really not until you start get magnitudes-of-order slower (10x, 100x, 1000x) that alarm bells should really go off.  And if I ever do need that last millisecond of performance?  Well then I'll optimize JUST THAT problem spot.  To me it's worth it for the readability, speed-to-market, and maintainability.

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  • C#/.NET Little Wonders: Using &lsquo;default&rsquo; to Get Default Values

    - 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. Today’s little wonder is another of those small items that can help a lot in certain situations, especially when writing generics.  In particular, it is useful in determining what the default value of a given type would be. The Problem: what’s the default value for a generic type? There comes a time when you’re writing generic code where you may want to set an item of a given generic type.  Seems simple enough, right?  We’ll let’s see! Let’s say we want to query a Dictionary<TKey, TValue> for a given key and get back the value, but if the key doesn’t exist, we’d like a default value instead of throwing an exception. So, for example, we might have a the following dictionary defined: 1: var lookup = new Dictionary<int, string> 2: { 3: { 1, "Apple" }, 4: { 2, "Orange" }, 5: { 3, "Banana" }, 6: { 4, "Pear" }, 7: { 9, "Peach" } 8: }; And using those definitions, perhaps we want to do something like this: 1: // assume a default 2: string value = "Unknown"; 3:  4: // if the item exists in dictionary, get its value 5: if (lookup.ContainsKey(5)) 6: { 7: value = lookup[5]; 8: } But that’s inefficient, because then we’re double-hashing (once for ContainsKey() and once for the indexer).  Well, to avoid the double-hashing, we could use TryGetValue() instead: 1: string value; 2:  3: // if key exists, value will be put in value, if not default it 4: if (!lookup.TryGetValue(5, out value)) 5: { 6: value = "Unknown"; 7: } But the “flow” of using of TryGetValue() can get clunky at times when you just want to assign either the value or a default to a variable.  Essentially it’s 3-ish lines (depending on formatting) for 1 assignment.  So perhaps instead we’d like to write an extension method to support a cleaner interface that will return a default if the item isn’t found: 1: public static class DictionaryExtensions 2: { 3: public static TValue GetValueOrDefault<TKey, TValue>(this Dictionary<TKey, TValue> dict, 4: TKey key, TValue defaultIfNotFound) 5: { 6: TValue value; 7:  8: // value will be the result or the default for TValue 9: if (!dict.TryGetValue(key, out value)) 10: { 11: value = defaultIfNotFound; 12: } 13:  14: return value; 15: } 16: } 17:  So this creates an extension method on Dictionary<TKey, TValue> that will attempt to get a value using the given key, and will return the defaultIfNotFound as a stand-in if the key does not exist. This code compiles, fine, but what if we would like to go one step further and allow them to specify a default if not found, or accept the default for the type?  Obviously, we could overload the method to take the default or not, but that would be duplicated code and a bit heavy for just specifying a default.  It seems reasonable that we could set the not found value to be either the default for the type, or the specified value. So what if we defaulted the type to null? 1: public static TValue GetValueOrDefault<TKey, TValue>(this Dictionary<TKey, TValue> dict, 2: TKey key, TValue defaultIfNotFound = null) // ... No, this won’t work, because only reference types (and Nullable<T> wrapped types due to syntactical sugar) can be assigned to null.  So what about a calling parameterless constructor? 1: public static TValue GetValueOrDefault<TKey, TValue>(this Dictionary<TKey, TValue> dict, 2: TKey key, TValue defaultIfNotFound = new TValue()) // ... No, this won’t work either for several reasons.  First, we’d expect a reference type to return null, not an “empty” instance.  Secondly, not all reference types have a parameter-less constructor (string for example does not).  And finally, a constructor cannot be determined at compile-time, while default values can. The Solution: default(T) – returns the default value for type T Many of us know the default keyword for its uses in switch statements as the default case.  But it has another use as well: it can return us the default value for a given type.  And since it generates the same defaults that default field initialization uses, it can be determined at compile-time as well. For example: 1: var x = default(int); // x is 0 2:  3: var y = default(bool); // y is false 4:  5: var z = default(string); // z is null 6:  7: var t = default(TimeSpan); // t is a TimeSpan with Ticks == 0 8:  9: var n = default(int?); // n is a Nullable<int> with HasValue == false Notice that for numeric types the default is 0, and for reference types the default is null.  In addition, for struct types, the value is a default-constructed struct – which simply means a struct where every field has their default value (hence 0 Ticks for TimeSpan, etc.). So using this, we could modify our code to this: 1: public static class DictionaryExtensions 2: { 3: public static TValue GetValueOrDefault<TKey, TValue>(this Dictionary<TKey, TValue> dict, 4: TKey key, TValue defaultIfNotFound = default(TValue)) 5: { 6: TValue value; 7:  8: // value will be the result or the default for TValue 9: if (!dict.TryGetValue(key, out value)) 10: { 11: value = defaultIfNotFound; 12: } 13:  14: return value; 15: } 16: } Now, if defaultIfNotFound is unspecified, it will use default(TValue) which will be the default value for whatever value type the dictionary holds.  So let’s consider how we could use this: 1: lookup.GetValueOrDefault(1); // returns “Apple” 2:  3: lookup.GetValueOrDefault(5); // returns null 4:  5: lookup.GetValueOrDefault(5, “Unknown”); // returns “Unknown” 6:  Again, do not confuse a parameter-less constructor with the default value for a type.  Remember that the default value for any type is the compile-time default for any instance of that type (0 for numeric, false for bool, null for reference types, and struct will all default fields for struct).  Consider the difference: 1: // both zero 2: int i1 = default(int); 3: int i2 = new int(); 4:  5: // both “zeroed” structs 6: var dt1 = default(DateTime); 7: var dt2 = new DateTime(); 8:  9: // sb1 is null, sb2 is an “empty” string builder 10: var sb1 = default(StringBuilder()); 11: var sb2 = new StringBuilder(); So in the above code, notice that the value types all resolve the same whether using default or parameter-less construction.  This is because a value type is never null (even Nullable<T> wrapped types are never “null” in a reference sense), they will just by default contain fields with all default values. However, for reference types, the default is null and not a constructed instance.  Also it should be noted that not all classes have parameter-less constructors (string, for instance, doesn’t have one – and doesn’t need one). Summary Whenever you need to get the default value for a type, especially a generic type, consider using the default keyword.  This handy word will give you the default value for the given type at compile-time, which can then be used for initialization, optional parameters, etc. Technorati Tags: C#,CSharp,.NET,Little Wonders,default

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  • C#: Does an IDisposable in a Halted Iterator Dispose?

    - by James Michael Hare
    If that sounds confusing, let me give you an example. Let's say you expose a method to read a database of products, and instead of returning a List<Product> you return an IEnumerable<Product> in iterator form (yield return). This accomplishes several good things: The IDataReader is not passed out of the Data Access Layer which prevents abstraction leak and resource leak potentials. You don't need to construct a full List<Product> in memory (which could be very big) if you just want to forward iterate once. If you only want to consume up to a certain point in the list, you won't incur the database cost of looking up the other items. This could give us an example like: 1: // a sample data access object class to do standard CRUD operations. 2: public class ProductDao 3: { 4: private DbProviderFactory _factory = SqlClientFactory.Instance 5:  6: // a method that would retrieve all available products 7: public IEnumerable<Product> GetAvailableProducts() 8: { 9: // must create the connection 10: using (var con = _factory.CreateConnection()) 11: { 12: con.ConnectionString = _productsConnectionString; 13: con.Open(); 14:  15: // create the command 16: using (var cmd = _factory.CreateCommand()) 17: { 18: cmd.Connection = con; 19: cmd.CommandText = _getAllProductsStoredProc; 20: cmd.CommandType = CommandType.StoredProcedure; 21:  22: // get a reader and pass back all results 23: using (var reader = cmd.ExecuteReader()) 24: { 25: while(reader.Read()) 26: { 27: yield return new Product 28: { 29: Name = reader["product_name"].ToString(), 30: ... 31: }; 32: } 33: } 34: } 35: } 36: } 37: } The database details themselves are irrelevant. I will say, though, that I'm a big fan of using the System.Data.Common classes instead of your provider specific counterparts directly (SqlCommand, OracleCommand, etc). This lets you mock your data sources easily in unit testing and also allows you to swap out your provider in one line of code. In fact, one of the shared components I'm most proud of implementing was our group's DatabaseUtility library that simplifies all the database access above into one line of code in a thread-safe and provider-neutral way. I went with my own flavor instead of the EL due to the fact I didn't want to force internal company consumers to use the EL if they didn't want to, and it made it easy to allow them to mock their database for unit testing by providing a MockCommand, MockConnection, etc that followed the System.Data.Common model. One of these days I'll blog on that if anyone's interested. Regardless, you often have situations like the above where you are consuming and iterating through a resource that must be closed once you are finished iterating. For the reasons stated above, I didn't want to return IDataReader (that would force them to remember to Dispose it), and I didn't want to return List<Product> (that would force them to hold all products in memory) -- but the first time I wrote this, I was worried. What if you never consume the last item and exit the loop? Are the reader, command, and connection all disposed correctly? Of course, I was 99.999999% sure the creators of C# had already thought of this and taken care of it, but inspection in Reflector was difficult due to the nature of the state machines yield return generates, so I decided to try a quick example program to verify whether or not Dispose() will be called when an iterator is broken from outside the iterator itself -- i.e. before the iterator reports there are no more items. So I wrote a quick Sequencer class with a Dispose() method and an iterator for it. Yes, it is COMPLETELY contrived: 1: // A disposable sequence of int -- yes this is completely contrived... 2: internal class Sequencer : IDisposable 3: { 4: private int _i = 0; 5: private readonly object _mutex = new object(); 6:  7: // Constructs an int sequence. 8: public Sequencer(int start) 9: { 10: _i = start; 11: } 12:  13: // Gets the next integer 14: public int GetNext() 15: { 16: lock (_mutex) 17: { 18: return _i++; 19: } 20: } 21:  22: // Dispose the sequence of integers. 23: public void Dispose() 24: { 25: // force output immediately (flush the buffer) 26: Console.WriteLine("Disposed with last sequence number of {0}!", _i); 27: Console.Out.Flush(); 28: } 29: } And then I created a generator (infinite-loop iterator) that did the using block for auto-Disposal: 1: // simply defines an extension method off of an int to start a sequence 2: public static class SequencerExtensions 3: { 4: // generates an infinite sequence starting at the specified number 5: public static IEnumerable<int> GetSequence(this int starter) 6: { 7: // note the using here, will call Dispose() when block terminated. 8: using (var seq = new Sequencer(starter)) 9: { 10: // infinite loop on this generator, means must be bounded by caller! 11: while(true) 12: { 13: yield return seq.GetNext(); 14: } 15: } 16: } 17: } This is really the same conundrum as the database problem originally posed. Here we are using iteration (yield return) over a large collection (infinite sequence of integers). If we cut the sequence short by breaking iteration, will that using block exit and hence, Dispose be called? Well, let's see: 1: // The test program class 2: public class IteratorTest 3: { 4: // The main test method. 5: public static void Main() 6: { 7: Console.WriteLine("Going to consume 10 of infinite items"); 8: Console.Out.Flush(); 9:  10: foreach(var i in 0.GetSequence()) 11: { 12: // could use TakeWhile, but wanted to output right at break... 13: if(i >= 10) 14: { 15: Console.WriteLine("Breaking now!"); 16: Console.Out.Flush(); 17: break; 18: } 19:  20: Console.WriteLine(i); 21: Console.Out.Flush(); 22: } 23:  24: Console.WriteLine("Done with loop."); 25: Console.Out.Flush(); 26: } 27: } So, what do we see? Do we see the "Disposed" message from our dispose, or did the Dispose get skipped because from an "eyeball" perspective we should be locked in that infinite generator loop? Here's the results: 1: Going to consume 10 of infinite items 2: 0 3: 1 4: 2 5: 3 6: 4 7: 5 8: 6 9: 7 10: 8 11: 9 12: Breaking now! 13: Disposed with last sequence number of 11! 14: Done with loop. Yes indeed, when we break the loop, the state machine that C# generates for yield iterate exits the iteration through the using blocks and auto-disposes the IDisposable correctly. I must admit, though, the first time I wrote one, I began to wonder and that led to this test. If you've never seen iterators before (I wrote a previous entry here) the infinite loop may throw you, but you have to keep in mind it is not a linear piece of code, that every time you hit a "yield return" it cedes control back to the state machine generated for the iterator. And this state machine, I'm happy to say, is smart enough to clean up the using blocks correctly. I suspected those wily guys and gals at Microsoft engineered it well, and I wasn't disappointed. But, I've been bitten by assumptions before, so it's good to test and see. Yes, maybe you knew it would or figured it would, but isn't it nice to know? And as those campy 80s G.I. Joe cartoon public service reminders always taught us, "Knowing is half the battle...". Technorati Tags: C#,.NET

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  • Aggregating cache data from OCEP in CQL

    - by Manju James
    There are several use cases where OCEP applications need to join stream data with external data, such as data available in a Coherence cache. OCEP’s streaming language, CQL, supports simple cache-key based joins of stream data with data in Coherence (more complex queries will be supported in a future release). However, there are instances where you may need to aggregate the data in Coherence based on input data from a stream. This blog describes a sample that does just that. For our sample, we will use a simplified credit card fraud detection use case. The input to this sample application is a stream of credit card transaction data. The input stream contains information like the credit card ID, transaction time and transaction amount. The purpose of this application is to detect suspicious transactions and send out a warning event. For the sake of simplicity, we will assume that all transactions with amounts greater than $1000 are suspicious. The transaction history is available in a Coherence distributed cache. For every suspicious transaction detected, a warning event must be sent with maximum amount, total amount and total number of transactions over the past 30 days, as shown in the diagram below. Application Input Stream input to the EPN contains events of type CCTransactionEvent. This input has to be joined with the cache with all credit card transactions. The cache is configured in the EPN as shown below: <wlevs:caching-system id="CohCacheSystem" provider="coherence"/> <wlevs:cache id="CCTransactionsCache" value-type="CCTransactionEvent" key-properties="cardID, transactionTime" caching-system="CohCacheSystem"> </wlevs:cache> Application Output The output that must be produced by the application is a fraud warning event. This event is configured in the spring file as shown below. Source for cardHistory property can be seen here. <wlevs:event-type type-name="FraudWarningEvent"> <wlevs:properties type="tuple"> <wlevs:property name="cardID" type="CHAR"/> <wlevs:property name="transactionTime" type="BIGINT"/> <wlevs:property name="transactionAmount" type="DOUBLE"/> <wlevs:property name="cardHistory" type="OBJECT"/> </wlevs:properties </wlevs:event-type> Cache Data Aggregation using Java Cartridge In the output warning event, cardHistory property contains data from the cache aggregated over the past 30 days. To get this information, we use a java cartridge method. This method uses Coherence’s query API on credit card transactions cache to get the required information. Therefore, the java cartridge method requires a reference to the cache. This may be set up by configuring it in the spring context file as shown below: <bean class="com.oracle.cep.ccfraud.CCTransactionsAggregator"> <property name="cache" ref="CCTransactionsCache"/> </bean> This is used by the java class to set a static property: public void setCache(Map cache) { s_cache = (NamedCache) cache; } The code snippet below shows how the total of all the transaction amounts in the past 30 days is computed. Rest of the information required by CardHistory object is calculated in a similar manner. Complete source of this class can be found here. To find out more information about using Coherence's API to query a cache, please refer Coherence Developer’s Guide. public static CreditHistoryData(String cardID) { … Filter filter = QueryHelper.createFilter("cardID = :cardID and transactionTime :transactionTime", map); CardHistoryData history = new CardHistoryData(); Double sum = (Double) s_cache.aggregate(filter, new DoubleSum("getTransactionAmount")); history.setTotalAmount(sum); … return history; } The java cartridge method is used from CQL as seen below: select cardID, transactionTime, transactionAmount, CCTransactionsAggregator.execute(cardID) as cardHistory from inputChannel where transactionAmount1000 This produces a warning event, with history data, for every credit card transaction over $1000. That is all there is to it. The complete source for the sample application, along with the configuration files, is available here. In the sample, I use a simple java bean to load the cache with initial transaction history data. An input adapter is used to create and send transaction events for the input stream.

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