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  • Object reference not set to an instance of an object- Linked List Example

    - by Zoro Roronoa
    I am seeing following errors : Object reference not set to an instance of an object! Check to determinate if the object is null before calling the method! I'am new with C#,and I made a program for Sorted Linked Lists. Here is the code where the error comes! public void Insert(double data) { Link newLink = new Link(data); Link current = first; Link previous = null; if (first == null) { first = newLink; } else { while (data > current.DData && current != null) { previous = current; current = current.Next; } previous.Next = newLink; newLink.Next = current; } } It says that the current referenc is null while (data current.DData && current != null), but I assigned it current = first; Please Help ! The rest is the complete code of the Program! class Link { double dData; Link next=null; public Link Next { get { return next; } set { next = value; } } public double DData { get { return dData; } set { dData = value; } } public Link(double dData) { this.dData = dData; } public void DisplayLink() { Console.WriteLine("Link : "+ dData); } } class SortedList { Link first; public SortedList() { first = null; } public bool IsEmpty() { return (this.first == null); } public void Insert(double data) { Link newLink = new Link(data); Link current = first; Link previous = null; if (first == null) { first = newLink; } else { while (data > current.DData && current != null) { previous = current; current = current.Next; } previous.Next = newLink; newLink.Next = current; } } public Link Remove() { Link temp = first; first = first.Next; return temp; } public void DisplayList() { Link current; current = first; Console.WriteLine("Display the List!"); while (current != null) { current.DisplayLink(); current = current.Next; } } } class SortedListApp { public void TestSortedList() { SortedList newList = new SortedList(); newList.Insert(20); newList.Insert(22); newList.Insert(100); newList.Insert(1000); newList.Insert(15); newList.Insert(11); newList.DisplayList(); newList.Remove(); newList.DisplayList(); } }

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  • Java - Syntax Question: What is <? super T>

    - by aloh
    I'm having trouble understanding the following syntax: public class SortedList< T extends Comparable< ? super T> > extends LinkedList< T > I see that class SortedList extends LinkedList. I just don't know what T extends Comparable< ? super T> means. My understanding of it so far is that type T must be a type that implements Comparable...but what is "< ? super T "?

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  • Most efficient way of creating tree from adjacency list

    - by Jeff Meatball Yang
    I have an adjacency list of objects (rows loaded from SQL database with the key and it's parent key) that I need to use to build an unordered tree. It's guaranteed to not have cycles. This is taking wayyy too long (processed only ~3K out of 870K nodes in about 5 minutes). Running on my workstation Core 2 Duo with plenty of RAM. Any ideas on how to make this faster? public class StampHierarchy { private StampNode _root; private SortedList<int, StampNode> _keyNodeIndex; // takes a list of nodes and builds a tree // starting at _root private void BuildHierarchy(List<StampNode> nodes) { Stack<StampNode> processor = new Stack<StampNode>(); _keyNodeIndex = new SortedList<int, StampNode>(nodes.Count); // find the root _root = nodes.Find(n => n.Parent == 0); // find children... processor.Push(_root); while (processor.Count != 0) { StampNode current = processor.Pop(); // keep a direct link to the node via the key _keyNodeIndex.Add(current.Key, current); // add children current.Children.AddRange(nodes.Where(n => n.Parent == current.Key)); // queue the children foreach (StampNode child in current.Children) { processor.Push(child); nodes.Remove(child); // thought this might help the Where above } } } } public class StampNode { // properties: int Key, int Parent, string Name, List<StampNode> Children }

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  • Fun With the Chrome JavaScript Console and the Pluralsight Website

    - by Steve Michelotti
    Originally posted on: http://geekswithblogs.net/michelotti/archive/2013/07/24/fun-with-the-chrome-javascript-console-and-the-pluralsight-website.aspxI’m currently working on my third course for Pluralsight. Everyone already knows that Scott Allen is a “dominating force” for Pluralsight but I was curious how many courses other authors have published as well. The Pluralsight Authors page - http://pluralsight.com/training/Authors – shows all 146 authors and you can click on any author’s page to see how many (and which) courses they have authored. The problem is: I don’t want to have to click into 146 pages to get a count for each author. With this in mind, I figured I could write a little JavaScript using the Chrome JavaScript console to do some “detective work.” My first step was to figure out how the HTML was structured on this page so I could do some screen-scraping. Right-click the first author - “Inspect Element”. I can see there is a primary <div> with a class of “main” which contains all the authors. Each author is in an <h3> with an <a> tag containing their name and link to their page:     This web page already has jQuery loaded so I can use $ directly from the console. This allows me to just use jQuery to inspect items on the current page. Notice this is a multi-line command. In order to use multiple lines in the console you have to press SHIFT-ENTER to go to the next line:     Now I can see I’m extracting data just fine. At this point I want to follow each URL. Then I want to screen-scrape this next page to see how many courses each author has done. Let’s take a look at the author detail page:       I can see we have a table (with a css class of “course”) that contains rows for each course authored. This means I can get the number of courses pretty easily like this:     Now I can put this all together. Back on the authors page, I want to follow each URL, extract the returned HTML, and grab the count. In the code below, I simply use the jQuery $.get() method to get the author detail page and the “data” variable that is in the callback contains the HTML. A nice feature of jQuery is that I can simply put this HTML string inside of $() and I can use jQuery selectors directly on it in conjunction with the find() method:     Now I’m getting somewhere. I have every Pluralsight author and how many courses each one has authored. But that’s not quite what I’m after – what I want to see are the authors that have the MOST courses in the library. What I’d like to do is to put all of the data in an array and then sort that array descending by number of courses. I can add an item to the array after each author detail page is returned but the catch here is that I can’t perform the sort operation until ALL of the author detail pages have executed. The jQuery $.get() method is naturally an async method so I essentially have 146 async calls and I don’t want to perform my sort action until ALL have completed (side note: don’t run this script too many times or the Pluralsight servers might think your an evil hacker attempting a DoS attack and deny you). My C# brain wants to use a WaitHandle WaitAll() method here but this is JavaScript. I was able to do this by using the jQuery Deferred() object. I create a new deferred object for each request and push it onto a deferred array. After each request is complete, I signal completion by calling the resolve() method. Finally, I use a $.when.apply() method to execute my descending sort operation once all requests are complete. Here is my complete console command: 1: var authorList = [], 2: defList = []; 3: $(".main h3 a").each(function() { 4: var def = $.Deferred(); 5: defList.push(def); 6: var authorName = $(this).text(); 7: var authorUrl = $(this).attr('href'); 8: $.get(authorUrl, function(data) { 9: var courseCount = $(data).find("table.course tbody tr").length; 10: authorList.push({ name: authorName, numberOfCourses: courseCount }); 11: def.resolve(); 12: }); 13: }); 14: $.when.apply($, defList).then(function() { 15: console.log("*Everything* is complete"); 16: var sortedList = authorList.sort(function(obj1, obj2) { 17: return obj2.numberOfCourses - obj1.numberOfCourses; 18: }); 19: for (var i = 0; i < sortedList.length; i++) { 20: console.log(authorList[i]); 21: } 22: });   And here are the results:     WOW! John Sonmez has 44 courses!! And Matt Milner has 29! I guess Scott Allen isn’t the only “dominating force”. I would have assumed Scott Allen was #1 but he comes in as #3 in total course count (of course Scott has 11 courses in the Top 50, and 14 in the Top 100 which is incredible!). Given that I’m in the middle of producing only my third course, I better get to work!

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  • Performance comparison of Dictionaries

    - by Hun1Ahpu
    I'm interested in performance values (big-O analysis) of Lookup and Insert operation for .Net Dictionaries: HashTable, SortedList, StringDictionary, ListDictionary, HybridDictionary, NameValueCollection Link to a web page with the answer works for me too.

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  • How do you sort a C# dictionary by value?

    - by kurious
    I often have a Dictionary of keys & values and need to sort it by value. For example, I have a hash of words and their frequencies, and want to order them by frequency. There's SortedList which is good for a single value (frequency), but I want to map it back to the word. SortedDictionary orders by key, not value. Some resort to a custom class, but what's the cleanest way?

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  • C#/.NET Little Wonders: The Useful But Overlooked Sets

    - by James Michael Hare
    Once again we consider some of the lesser known classes and keywords of C#.  Today we will be looking at two set implementations in the System.Collections.Generic namespace: HashSet<T> and SortedSet<T>.  Even though most people think of sets as mathematical constructs, they are actually very useful classes that can be used to help make your application more performant if used appropriately. A Background From Math In mathematical terms, a set is an unordered collection of unique items.  In other words, the set {2,3,5} is identical to the set {3,5,2}.  In addition, the set {2, 2, 4, 1} would be invalid because it would have a duplicate item (2).  In addition, you can perform set arithmetic on sets such as: Intersections: The intersection of two sets is the collection of elements common to both.  Example: The intersection of {1,2,5} and {2,4,9} is the set {2}. Unions: The union of two sets is the collection of unique items present in either or both set.  Example: The union of {1,2,5} and {2,4,9} is {1,2,4,5,9}. Differences: The difference of two sets is the removal of all items from the first set that are common between the sets.  Example: The difference of {1,2,5} and {2,4,9} is {1,5}. Supersets: One set is a superset of a second set if it contains all elements that are in the second set. Example: The set {1,2,5} is a superset of {1,5}. Subsets: One set is a subset of a second set if all the elements of that set are contained in the first set. Example: The set {1,5} is a subset of {1,2,5}. If We’re Not Doing Math, Why Do We Care? Now, you may be thinking: why bother with the set classes in C# if you have no need for mathematical set manipulation?  The answer is simple: they are extremely efficient ways to determine ownership in a collection. For example, let’s say you are designing an order system that tracks the price of a particular equity, and once it reaches a certain point will trigger an order.  Now, since there’s tens of thousands of equities on the markets, you don’t want to track market data for every ticker as that would be a waste of time and processing power for symbols you don’t have orders for.  Thus, we just want to subscribe to the stock symbol for an equity order only if it is a symbol we are not already subscribed to. Every time a new order comes in, we will check the list of subscriptions to see if the new order’s stock symbol is in that list.  If it is, great, we already have that market data feed!  If not, then and only then should we subscribe to the feed for that symbol. So far so good, we have a collection of symbols and we want to see if a symbol is present in that collection and if not, add it.  This really is the essence of set processing, but for the sake of comparison, let’s say you do a list instead: 1: // class that handles are order processing service 2: public sealed class OrderProcessor 3: { 4: // contains list of all symbols we are currently subscribed to 5: private readonly List<string> _subscriptions = new List<string>(); 6:  7: ... 8: } Now whenever you are adding a new order, it would look something like: 1: public PlaceOrderResponse PlaceOrder(Order newOrder) 2: { 3: // do some validation, of course... 4:  5: // check to see if already subscribed, if not add a subscription 6: if (!_subscriptions.Contains(newOrder.Symbol)) 7: { 8: // add the symbol to the list 9: _subscriptions.Add(newOrder.Symbol); 10: 11: // do whatever magic is needed to start a subscription for the symbol 12: } 13:  14: // place the order logic! 15: } What’s wrong with this?  In short: performance!  Finding an item inside a List<T> is a linear - O(n) – operation, which is not a very performant way to find if an item exists in a collection. (I used to teach algorithms and data structures in my spare time at a local university, and when you began talking about big-O notation you could immediately begin to see eyes glossing over as if it was pure, useless theory that would not apply in the real world, but I did and still do believe it is something worth understanding well to make the best choices in computer science). Let’s think about this: a linear operation means that as the number of items increases, the time that it takes to perform the operation tends to increase in a linear fashion.  Put crudely, this means if you double the collection size, you might expect the operation to take something like the order of twice as long.  Linear operations tend to be bad for performance because they mean that to perform some operation on a collection, you must potentially “visit” every item in the collection.  Consider finding an item in a List<T>: if you want to see if the list has an item, you must potentially check every item in the list before you find it or determine it’s not found. Now, we could of course sort our list and then perform a binary search on it, but sorting is typically a linear-logarithmic complexity – O(n * log n) - and could involve temporary storage.  So performing a sort after each add would probably add more time.  As an alternative, we could use a SortedList<TKey, TValue> which sorts the list on every Add(), but this has a similar level of complexity to move the items and also requires a key and value, and in our case the key is the value. This is why sets tend to be the best choice for this type of processing: they don’t rely on separate keys and values for ordering – so they save space – and they typically don’t care about ordering – so they tend to be extremely performant.  The .NET BCL (Base Class Library) has had the HashSet<T> since .NET 3.5, but at that time it did not implement the ISet<T> interface.  As of .NET 4.0, HashSet<T> implements ISet<T> and a new set, the SortedSet<T> was added that gives you a set with ordering. HashSet<T> – For Unordered Storage of Sets When used right, HashSet<T> is a beautiful collection, you can think of it as a simplified Dictionary<T,T>.  That is, a Dictionary where the TKey and TValue refer to the same object.  This is really an oversimplification, but logically it makes sense.  I’ve actually seen people code a Dictionary<T,T> where they store the same thing in the key and the value, and that’s just inefficient because of the extra storage to hold both the key and the value. As it’s name implies, the HashSet<T> uses a hashing algorithm to find the items in the set, which means it does take up some additional space, but it has lightning fast lookups!  Compare the times below between HashSet<T> and List<T>: Operation HashSet<T> List<T> Add() O(1) O(1) at end O(n) in middle Remove() O(1) O(n) Contains() O(1) O(n)   Now, these times are amortized and represent the typical case.  In the very worst case, the operations could be linear if they involve a resizing of the collection – but this is true for both the List and HashSet so that’s a less of an issue when comparing the two. The key thing to note is that in the general case, HashSet is constant time for adds, removes, and contains!  This means that no matter how large the collection is, it takes roughly the exact same amount of time to find an item or determine if it’s not in the collection.  Compare this to the List where almost any add or remove must rearrange potentially all the elements!  And to find an item in the list (if unsorted) you must search every item in the List. So as you can see, if you want to create an unordered collection and have very fast lookup and manipulation, the HashSet is a great collection. And since HashSet<T> implements ICollection<T> and IEnumerable<T>, it supports nearly all the same basic operations as the List<T> and can use the System.Linq extension methods as well. All we have to do to switch from a List<T> to a HashSet<T>  is change our declaration.  Since List and HashSet support many of the same members, chances are we won’t need to change much else. 1: public sealed class OrderProcessor 2: { 3: private readonly HashSet<string> _subscriptions = new HashSet<string>(); 4:  5: // ... 6:  7: public PlaceOrderResponse PlaceOrder(Order newOrder) 8: { 9: // do some validation, of course... 10: 11: // check to see if already subscribed, if not add a subscription 12: if (!_subscriptions.Contains(newOrder.Symbol)) 13: { 14: // add the symbol to the list 15: _subscriptions.Add(newOrder.Symbol); 16: 17: // do whatever magic is needed to start a subscription for the symbol 18: } 19: 20: // place the order logic! 21: } 22:  23: // ... 24: } 25: Notice, we didn’t change any code other than the declaration for _subscriptions to be a HashSet<T>.  Thus, we can pick up the performance improvements in this case with minimal code changes. SortedSet<T> – Ordered Storage of Sets Just like HashSet<T> is logically similar to Dictionary<T,T>, the SortedSet<T> is logically similar to the SortedDictionary<T,T>. The SortedSet can be used when you want to do set operations on a collection, but you want to maintain that collection in sorted order.  Now, this is not necessarily mathematically relevant, but if your collection needs do include order, this is the set to use. So the SortedSet seems to be implemented as a binary tree (possibly a red-black tree) internally.  Since binary trees are dynamic structures and non-contiguous (unlike List and SortedList) this means that inserts and deletes do not involve rearranging elements, or changing the linking of the nodes.  There is some overhead in keeping the nodes in order, but it is much smaller than a contiguous storage collection like a List<T>.  Let’s compare the three: Operation HashSet<T> SortedSet<T> List<T> Add() O(1) O(log n) O(1) at end O(n) in middle Remove() O(1) O(log n) O(n) Contains() O(1) O(log n) O(n)   The MSDN documentation seems to indicate that operations on SortedSet are O(1), but this seems to be inconsistent with its implementation and seems to be a documentation error.  There’s actually a separate MSDN document (here) on SortedSet that indicates that it is, in fact, logarithmic in complexity.  Let’s put it in layman’s terms: logarithmic means you can double the collection size and typically you only add a single extra “visit” to an item in the collection.  Take that in contrast to List<T>’s linear operation where if you double the size of the collection you double the “visits” to items in the collection.  This is very good performance!  It’s still not as performant as HashSet<T> where it always just visits one item (amortized), but for the addition of sorting this is a good thing. Consider the following table, now this is just illustrative data of the relative complexities, but it’s enough to get the point: Collection Size O(1) Visits O(log n) Visits O(n) Visits 1 1 1 1 10 1 4 10 100 1 7 100 1000 1 10 1000   Notice that the logarithmic – O(log n) – visit count goes up very slowly compare to the linear – O(n) – visit count.  This is because since the list is sorted, it can do one check in the middle of the list, determine which half of the collection the data is in, and discard the other half (binary search).  So, if you need your set to be sorted, you can use the SortedSet<T> just like the HashSet<T> and gain sorting for a small performance hit, but it’s still faster than a List<T>. Unique Set Operations Now, if you do want to perform more set-like operations, both implementations of ISet<T> support the following, which play back towards the mathematical set operations described before: IntersectWith() – Performs the set intersection of two sets.  Modifies the current set so that it only contains elements also in the second set. UnionWith() – Performs a set union of two sets.  Modifies the current set so it contains all elements present both in the current set and the second set. ExceptWith() – Performs a set difference of two sets.  Modifies the current set so that it removes all elements present in the second set. IsSupersetOf() – Checks if the current set is a superset of the second set. IsSubsetOf() – Checks if the current set is a subset of the second set. For more information on the set operations themselves, see the MSDN description of ISet<T> (here). What Sets Don’t Do Don’t get me wrong, sets are not silver bullets.  You don’t really want to use a set when you want separate key to value lookups, that’s what the IDictionary implementations are best for. Also sets don’t store temporal add-order.  That is, if you are adding items to the end of a list all the time, your list is ordered in terms of when items were added to it.  This is something the sets don’t do naturally (though you could use a SortedSet with an IComparer with a DateTime but that’s overkill) but List<T> can. Also, List<T> allows indexing which is a blazingly fast way to iterate through items in the collection.  Iterating over all the items in a List<T> is generally much, much faster than iterating over a set. Summary Sets are an excellent tool for maintaining a lookup table where the item is both the key and the value.  In addition, if you have need for the mathematical set operations, the C# sets support those as well.  The HashSet<T> is the set of choice if you want the fastest possible lookups but don’t care about order.  In contrast the SortedSet<T> will give you a sorted collection at a slight reduction in performance.   Technorati Tags: C#,.Net,Little Wonders,BlackRabbitCoder,ISet,HashSet,SortedSet

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  • SortList duplicated key, but it shouldn't

    - by Luca
    I have a class which implements IList interface. I requires a "sorted view" of this list, but without modifying it (I cannot sort directly the IList class). These view shall be updated when the original list is modified, keeping items sorted. So, I've introduced a SortList creation method which create a SortList which has a comparer for the specific object contained in the original list. Here is the snippet of code: public class MyList<T> : ICollection, IList<T> { ... public SortedList CreateSortView(string property) { try { Lock(); SortListView sortView; if (mSortListViews.ContainsKey(property) == false) { // Create sorted view sortView = new SortListView(property, Count); mSortListViews.Add(property, sortView); foreach (T item in Items) sortView.Add(item); } else sortView = mSortListViews[property]; sortView.ReferenceCount++; return (sortView); } finally { Unlock(); } } public void DeleteSortView(string property) { try { Lock(); // Unreference sorted view mSortListViews[property].ReferenceCount--; // Remove sorted view if (mSortListViews[property].ReferenceCount == 0) mSortListViews.Remove(property); } finally { Unlock(); } } protected class SortListView : SortedList { /// <summary> /// /// </summary> /// <param name="property"></param> /// <param name="capacity"></param> public SortListView(string property, int capacity) : base(new GenericPropertyComparer(typeof(T).GetProperty(property, BindingFlags.Instance | BindingFlags.Public)), capacity) { } /// <summary> /// Reference count. /// </summary> public int ReferenceCount = 0; /// <summary> /// /// </summary> /// <param name="item"></param> public void Add(T item) { Add(item, item); } /// <summary> /// /// </summary> /// <param name="item"></param> public void Remove(T item) { // Base implementation base.Remove(item); } /// <summary> /// Compare object on a generic property. /// </summary> class GenericPropertyComparer : IComparer { #region Constructors /// <summary> /// Construct a GenericPropertyComparer specifying the property to compare. /// </summary> /// <param name="property"> /// A <see cref="PropertyInfo"/> which specify the property to be compared. /// </param> /// <remarks> /// The <paramref name="property"/> parameter imply that the compared objects have the specified property. The property /// must be readable, and its type must implement the IComparable interface. /// </remarks> public GenericPropertyComparer(PropertyInfo property) { if (property == null) throw new ArgumentException("property doesn't specify a valid property"); if (property.CanRead == false) throw new ArgumentException("property specify a write-only property"); if (property.PropertyType.GetInterface("IComparable") == null) throw new ArgumentException("property type doesn't IComparable"); mSortingProperty = property; } #endregion #region IComparer Implementation public int Compare(object x, object y) { IComparable propX = (IComparable)mSortingProperty.GetValue(x, null); IComparable propY = (IComparable)mSortingProperty.GetValue(y, null); return (propX.CompareTo(propY)); } /// <summary> /// Sorting property. /// </summary> private PropertyInfo mSortingProperty = null; #endregion } } /// <summary> /// Sorted views of this ReactList. /// </summary> private Dictionary<string, SortListView> mSortListViews = new Dictionary<string, SortListView>(); } Practically, class users request to create a SortListView specifying the name of property which determine the sorting, and using the reflection each SortListView defined a IComparer which keep sorted the items. Whenever an item is added or removed from the original list, every created SortListView will be updated with the same operation. This seems good at first chance, but it creates me problems since it give me the following exception when adding items to the SortList: System.ArgumentException: Item has already been added. Key in dictionary: 'PowerShell_ISE [C:\Windows\sysWOW64\WindowsPowerShell\v1.0\PowerShell_ISE.exe]' Key being added: 'PowerShell_ISE [C:\Windows\system32\WindowsPowerShell\v1.0\PowerShell_ISE.exe]' As you can see from the exception message, thrown by SortedListView.Add(object), the string representation of the key (the list item object) is different (note the path of the executable). Why SortList give me that exception? To solve this I tried to implement a GetHashCode implementation for the underlying object, but without success: public override int GetHashCode() { return ( base.GetHashCode() ^ mApplicationName.GetHashCode() ^ mApplicationPath.GetHashCode() ^ mCommandLine.GetHashCode() ^ mWorkingDirectory.GetHashCode() ); }

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  • What is a great resource for learning about the implementation details of .NET generic collections?

    - by Jimmy W
    Hi all, I'm interested in understanding the underlying implementation details of generic collections in .NET. What I have in mind are details such as how the collections are stored, how each member of a collection is accessed by the CLR, etc. For collections that are analogous to traditional data structures, such as LinkedList and Dictionary, I think I have an understanding of what's going on underneath. However, I'm not as certain about collections like List (how is set up such that it is both indexable and expandable?) and SortedList, so any leads as to what I could look up to learn more about them would be greatly appreciated.

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  • Dynamic Paging and Sorting

    - by Ricardo Peres
    Since .NET 3.5 brought us LINQ and expressions, I became a great fan of these technologies. There are times, however, when strong typing cannot be used - for example, when you are developing an ObjectDataSource and you need to do paging having just a column name, a page index and a page size, so I set out to fix this. Yes, I know about Dynamic LINQ, and even talked on it previously, but there's no need to add this extra assembly. So, without further delay, here's the code, in both generic and non-generic versions: public static IList ApplyPagingAndSorting(IEnumerable enumerable, Type elementType, Int32 pageSize, Int32 pageIndex, params String [] orderByColumns) { MethodInfo asQueryableMethod = typeof(Queryable).GetMethods(BindingFlags.Static | BindingFlags.Public).Where(m = (m.Name == "AsQueryable") && (m.ContainsGenericParameters == false)).Single(); IQueryable query = (enumerable is IQueryable) ? (enumerable as IQueryable) : asQueryableMethod.Invoke(null, new Object [] { enumerable }) as IQueryable; if ((orderByColumns != null) && (orderByColumns.Length 0)) { PropertyInfo orderByProperty = elementType.GetProperty(orderByColumns [ 0 ]); MemberExpression member = Expression.MakeMemberAccess(Expression.Parameter(elementType, "n"), orderByProperty); LambdaExpression orderBy = Expression.Lambda(member, member.Expression as ParameterExpression); MethodInfo orderByMethod = typeof(Queryable).GetMethods(BindingFlags.Public | BindingFlags.Static).Where(m = m.Name == "OrderBy").ToArray() [ 0 ].MakeGenericMethod(elementType, orderByProperty.PropertyType); query = orderByMethod.Invoke(null, new Object [] { query, orderBy }) as IQueryable; if (orderByColumns.Length 1) { MethodInfo thenByMethod = typeof(Queryable).GetMethods(BindingFlags.Public | BindingFlags.Static).Where(m = m.Name == "ThenBy").ToArray() [ 0 ].MakeGenericMethod(elementType, orderByProperty.PropertyType); PropertyInfo thenByProperty = null; MemberExpression thenByMember = null; LambdaExpression thenBy = null; for (Int32 i = 1; i 0) { MethodInfo takeMethod = typeof(Queryable).GetMethod("Take", BindingFlags.Public | BindingFlags.Static).MakeGenericMethod(elementType); MethodInfo skipMethod = typeof(Queryable).GetMethod("Skip", BindingFlags.Public | BindingFlags.Static).MakeGenericMethod(elementType); query = skipMethod.Invoke(null, new Object [] { query, pageSize * pageIndex }) as IQueryable; query = takeMethod.Invoke(null, new Object [] { query, pageSize }) as IQueryable; } MethodInfo toListMethod = typeof(Enumerable).GetMethod("ToList", BindingFlags.Static | BindingFlags.Public).MakeGenericMethod(elementType); IList list = toListMethod.Invoke(null, new Object [] { query }) as IList; return (list); } public static List ApplyPagingAndSorting(IEnumerable enumerable, Int32 pageSize, Int32 pageIndex, params String [] orderByColumns) { return (ApplyPagingAndSorting(enumerable, typeof(T), pageSize, pageIndex, orderByColumns) as List); } List list = new List { new DateTime(2010, 1, 1), new DateTime(1999, 1, 12), new DateTime(1900, 10, 10), new DateTime(1900, 2, 20), new DateTime(2012, 5, 5), new DateTime(2012, 1, 20) }; List sortedList = ApplyPagingAndSorting(list, 3, 0, "Year", "Month", "Day"); SyntaxHighlighter.config.clipboardSwf = 'http://alexgorbatchev.com/pub/sh/2.0.320/scripts/clipboard.swf'; SyntaxHighlighter.brushes.CSharp.aliases = ['c#', 'c-sharp', 'csharp']; SyntaxHighlighter.all();

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  • Generic Dictionary and generating a hashcode for multi-part key

    - by Andrew
    I have an object that has a multi-part key and I am struggling to find a suitable way override GetHashCode. An example of what the class looks like is. public class wibble{ public int keypart1 {get; set;} public int keypart2 {get; set;} public int keypart3 {get; set;} public int keypart4 {get; set;} public int keypart5 {get; set;} public int keypart6 {get; set;} public int keypart7 {get; set;} public single value {get; set;} } Note in just about every instance of the class no more than 2 or 3 of the keyparts would have a value greater than 0. Any ideas on how best to generate a unique hashcode in this situation? I have also been playing around with creating a key that is not unique, but spreads the objects evenly between the dictionaries buckets and then storing objects with matched hashes in a List< or LinkedList< or SortedList<. Any thoughts on this?

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  • What Qt container class to use for a sorted list?

    - by Dave
    Part of my application involves rendering audio waveforms. The user will be able to zoom in/out of the waveform. Starting at fully zoomed-out, I only want to sample the audio at the necessary internals to draw the waveform at the given resolution. Then, when they zoom in, asynchronously resample the "missing points" and provide a clearer waveform. (Think Google Maps.) I'm not sure the best data structure to use in Qt world. Ideally, I would like to store data samples sorted by time, but with the ability to fill-in points as needed. So, for example, the data points might initially look like: data[0 ms] = 10 data[10 ms] = 32 data[20 ms] = 21 ... But when they zoom in, I would get more points as necessary, perhaps: data[0 ms] = 10 data[2 ms] = 11 data[4 ms] = 18 data[6 ms] = 30 data[10 ms] = 32 data[20 ms] = 21 ... Note that the values in brackets are lookup values (milliseconds), not array indices. In .Net I might have used a SortedList<int, int>. What would be the best class to use in Qt? Or should I use a STL container?

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  • Why enumerator structs are a really bad idea

    - by Simon Cooper
    If you've ever poked around the .NET class libraries in Reflector, I'm sure you would have noticed that the generic collection classes all have implementations of their IEnumerator as a struct rather than a class. As you will see, this design decision has some rather unfortunate side effects... As is generally known in the .NET world, mutable structs are a Very Bad Idea; and there are several other blogs around explaining this (Eric Lippert's blog post explains the problem quite well). In the BCL, the generic collection enumerators are all mutable structs, as they need to keep track of where they are in the collection. This bit me quite hard when I was coding a wrapper around a LinkedList<int>.Enumerator. It boils down to this code: sealed class EnumeratorWrapper : IEnumerator<int> { private readonly LinkedList<int>.Enumerator m_Enumerator; public EnumeratorWrapper(LinkedList<int> linkedList) { m_Enumerator = linkedList.GetEnumerator(); } public int Current { get { return m_Enumerator.Current; } } object System.Collections.IEnumerator.Current { get { return Current; } } public bool MoveNext() { return m_Enumerator.MoveNext(); } public void Reset() { ((System.Collections.IEnumerator)m_Enumerator).Reset(); } public void Dispose() { m_Enumerator.Dispose(); } } The key line here is the MoveNext method. When I initially coded this, I thought that the call to m_Enumerator.MoveNext() would alter the enumerator state in the m_Enumerator class variable and so the enumeration would proceed in an orderly fashion through the collection. However, when I ran this code it went into an infinite loop - the m_Enumerator.MoveNext() call wasn't actually changing the state in the m_Enumerator variable at all, and my code was looping forever on the first collection element. It was only after disassembling that method that I found out what was going on The MoveNext method above results in the following IL: .method public hidebysig newslot virtual final instance bool MoveNext() cil managed { .maxstack 1 .locals init ( [0] bool CS$1$0000, [1] valuetype [System]System.Collections.Generic.LinkedList`1/Enumerator CS$0$0001) L_0000: nop L_0001: ldarg.0 L_0002: ldfld valuetype [System]System.Collections.Generic.LinkedList`1/Enumerator EnumeratorWrapper::m_Enumerator L_0007: stloc.1 L_0008: ldloca.s CS$0$0001 L_000a: call instance bool [System]System.Collections.Generic.LinkedList`1/Enumerator::MoveNext() L_000f: stloc.0 L_0010: br.s L_0012 L_0012: ldloc.0 L_0013: ret } Here, the important line is 0002 - m_Enumerator is accessed using the ldfld operator, which does the following: Finds the value of a field in the object whose reference is currently on the evaluation stack. So, what the MoveNext method is doing is the following: public bool MoveNext() { LinkedList<int>.Enumerator CS$0$0001 = this.m_Enumerator; bool CS$1$0000 = CS$0$0001.MoveNext(); return CS$1$0000; } The enumerator instance being modified by the call to MoveNext is the one stored in the CS$0$0001 variable on the stack, and not the one in the EnumeratorWrapper class instance. Hence why the state of m_Enumerator wasn't getting updated. Hmm, ok. Well, why is it doing this? If you have a read of Eric Lippert's blog post about this issue, you'll notice he quotes a few sections of the C# spec. In particular, 7.5.4: ...if the field is readonly and the reference occurs outside an instance constructor of the class in which the field is declared, then the result is a value, namely the value of the field I in the object referenced by E. And my m_Enumerator field is readonly! Indeed, if I remove the readonly from the class variable then the problem goes away, and the code works as expected. The IL confirms this: .method public hidebysig newslot virtual final instance bool MoveNext() cil managed { .maxstack 1 .locals init ( [0] bool CS$1$0000) L_0000: nop L_0001: ldarg.0 L_0002: ldflda valuetype [System]System.Collections.Generic.LinkedList`1/Enumerator EnumeratorWrapper::m_Enumerator L_0007: call instance bool [System]System.Collections.Generic.LinkedList`1/Enumerator::MoveNext() L_000c: stloc.0 L_000d: br.s L_000f L_000f: ldloc.0 L_0010: ret } Notice on line 0002, instead of the ldfld we had before, we've got a ldflda, which does this: Finds the address of a field in the object whose reference is currently on the evaluation stack. Instead of loading the value, we're loading the address of the m_Enumerator field. So now the call to MoveNext modifies the enumerator stored in the class rather than on the stack, and everything works as expected. Previously, I had thought enumerator structs were an odd but interesting feature of the BCL that I had used in the past to do linked list slices. However, effects like this only underline how dangerous mutable structs are, and I'm at a loss to explain why the enumerators were implemented as structs in the first place. (interestingly, the SortedList<TKey, TValue> enumerator is a struct but is private, which makes it even more odd - the only way it can be accessed is as a boxed IEnumerator!). I would love to hear people's theories as to why the enumerators are implemented in such a fashion. And bonus points if you can explain why LinkedList<int>.Enumerator.Reset is an explicit implementation but Dispose is implicit... Note to self: never ever ever code a mutable struct.

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  • Editing a Gridview row with drop-down lists gets too wide - how can I use popup panels instead?

    - by David
    I have a series of GridViews in a Tab Panel - databound to a generic List of Business Objects. The columns in the Gridview are all similar to the following: <asp:TemplateField HeaderText="Company" SortExpression="Company.ShortName"> <ItemTemplate> <asp:Label ID="lblCompany" runat="server" Text='<%# Bind("Company.ShortName") %>'></asp:Label> </ItemTemplate> <EditItemTemplate> <asp:DropDownList ID="ddlCompany" runat="server"></asp:DropDownList> </EditItemTemplate> </asp:TemplateField> The GridView generates the "Edit" link at the beginning of the row, all the events fire ok. The problem is that the data is getting long. When in 'display mode', it's fine because the GridView control is smart enough to break some text into multiple lines (in particular Project, Title and Worker names can get pretty long). The problem come in editing mode. Drop-down lists DON'T break entries into multiple lines (for obvious reasons). Going into Edit ode on a row in the Gridview can make the Griview expand horizontally to twice the screen size (blowing through the width limits in the Master page and CSS but that's only a related problem). What I need is something like the ModalPopup - but trying to tie it to an ID in an EditItemTemplate gives me errors when the page renders (because the 'ddlXXXX' doesn't exist at the time). In addition I don't know how to dynamically populate the panel so that I can get a response from it (like the ID of the Company they selected). I'm also trying to avoid javascript and would like this to be a 'pure' aspx/code-behind solution (for simplicity's sake among others). All the examples I find are of Modal Popups with the panels pre-defined. Even if it (the popup panel) were something like a list of checkboxes, it could be databound to the SortedList I have ready to go and an OK/Cancel button combination to accept or ignore things. I'm just not sure of what goes where. I'm open to suggestions. Thanks in advance. EDIT: Final solution looks as follows: <asp:TemplateField HeaderText="Company" SortExpression="Company.ShortName"> <ItemTemplate> <asp:Label ID="lblCompany" runat="server" Text='<%# Bind("Company.ShortName") %>'></asp:Label> </ItemTemplate> <EditItemTemplate> <asp:LinkButton ID="lnkCompany" runat="server" Text='<%# Bind("Company.ShortName") %>'></asp:LinkButton> <asp:Panel ID="pnlCompany" runat="server" style="display:none"> <div> <asp:DropDownList ID="ddlCompany" runat="server" ></asp:DropDownList> <br/> <asp:ImageButton ID="btnOKCo" runat="server" ImageUrl="~/Images/greencheck.gif" OnCommand="PopupButton_Command" CommandName="SelectCO" /> <asp:ImageButton ID="btnCxlCo" runat="server" ImageUrl="~/Images/RedX.gif" /> </div> </asp:Panel> <cc1:ModalPopupExtender ID="mpeCompany" runat="server" TargetControlID="lnkCompany" PopupControlID="pnlCompany" BackgroundCssClass="modalBackground" CancelControlID="btnCxlCo" DropShadow="true" PopupDragHandleControlID="pnlCompany" /> </EditItemTemplate> </asp:TemplateField> And in the code-behind, lstIDLabor is the generic List of data lines (of which Company is one of the properties that is also a business object) that is bound to the GridView: Sub PopupButton_Command(ByVal sender As Object, ByVal e As CommandEventArgs) Dim intRow As Integer Dim intVal As Integer RestoreFromSessionVariables() Select Case e.CommandName Case "SelectCO" intRow = grdIDCostLabor.EditIndex Dim ddlCo As DropDownList = CType(grdIDCost.Rows(intRow).FindControl("ddlCompany"), DropDownList) intVal = ddlCo.SelectedValue lstIDLabor(intRow).CompanyID = intVal lstIDLabor(intRow).Company = Company.Read(intVal) Case Else ' End Select MakeSessionVariables() BindGrids() End Sub

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  • Revisiting ANTS Performance Profiler 7.4

    - by James Michael Hare
    Last year, I did a small review on the ANTS Performance Profiler 6.3, now that it’s a year later and a major version number higher, I thought I’d revisit the review and revise my last post. This post will take the same examples as the original post and update them to show what’s new in version 7.4 of the profiler. Background A performance profiler’s main job is to keep track of how much time is typically spent in each unit of code. This helps when we have a program that is not running at the performance we expect, and we want to know where the program is experiencing issues. There are many profilers out there of varying capabilities. Red Gate’s typically seem to be the very easy to “jump in” and get started with very little training required. So let’s dig into the Performance Profiler. I’ve constructed a very crude program with some obvious inefficiencies. It’s a simple program that generates random order numbers (or really could be any unique identifier), adds it to a list, sorts the list, then finds the max and min number in the list. Ignore the fact it’s very contrived and obviously inefficient, we just want to use it as an example to show off the tool: 1: // our test program 2: public static class Program 3: { 4: // the number of iterations to perform 5: private static int _iterations = 1000000; 6: 7: // The main method that controls it all 8: public static void Main() 9: { 10: var list = new List<string>(); 11: 12: for (int i = 0; i < _iterations; i++) 13: { 14: var x = GetNextId(); 15: 16: AddToList(list, x); 17: 18: var highLow = GetHighLow(list); 19: 20: if ((i % 1000) == 0) 21: { 22: Console.WriteLine("{0} - High: {1}, Low: {2}", i, highLow.Item1, highLow.Item2); 23: Console.Out.Flush(); 24: } 25: } 26: } 27: 28: // gets the next order id to process (random for us) 29: public static string GetNextId() 30: { 31: var random = new Random(); 32: var num = random.Next(1000000, 9999999); 33: return num.ToString(); 34: } 35: 36: // add it to our list - very inefficiently! 37: public static void AddToList(List<string> list, string item) 38: { 39: list.Add(item); 40: list.Sort(); 41: } 42: 43: // get high and low of order id range - very inefficiently! 44: public static Tuple<int,int> GetHighLow(List<string> list) 45: { 46: return Tuple.Create(list.Max(s => Convert.ToInt32(s)), list.Min(s => Convert.ToInt32(s))); 47: } 48: } So let’s run it through the profiler and see what happens! Visual Studio Integration First, let’s look at how the ANTS profilers integrate with Visual Studio’s menu system. Once you install the ANTS profilers, you will get an ANTS menu item with several options: Notice that you can either Profile Performance or Launch ANTS Performance Profiler. These sound similar but achieve two slightly different actions: Profile Performance: this immediately launches the profiler with all defaults selected to profile the active project in Visual Studio. Launch ANTS Performance Profiler: this launches the profiler much the same way as starting it from the Start Menu. The profiler will pre-populate the application and path information, but allow you to change the settings before beginning the profile run. So really, the main difference is that Profile Performance immediately begins profiling with the default selections, where Launch ANTS Performance Profiler allows you to change the defaults and attach to an already-running application. Let’s Fire it Up! So when you fire up ANTS either via Start Menu or Launch ANTS Performance Profiler menu in Visual Studio, you are presented with a very simple dialog to get you started: Notice you can choose from many different options for application type. You can profile executables, services, web applications, or just attach to a running process. In fact, in version 7.4 we see two new options added: ASP.NET Web Application (IIS Express) SharePoint web application (IIS) So this gives us an additional way to profile ASP.NET applications and the ability to profile SharePoint applications as well. You can also choose your level of detail in the Profiling Mode drop down. If you choose Line-Level and method-level timings detail, you will get a lot more detail on the method durations, but this will also slow down profiling somewhat. If you really need the profiler to be as unintrusive as possible, you can change it to Sample method-level timings. This is performing very light profiling, where basically the profiler collects timings of a method by examining the call-stack at given intervals. Which method you choose depends a lot on how much detail you need to find the issue and how sensitive your program issues are to timing. So for our example, let’s just go with the line and method timing detail. So, we check that all the options are correct (if you launch from VS2010, the executable and path are filled in already), and fire it up by clicking the [Start Profiling] button. Profiling the Application Once you start profiling the application, you will see a real-time graph of CPU usage that will indicate how much your application is using the CPU(s) on your system. During this time, you can select segments of the graph and bookmark them, giving them mnemonic names. This can be useful if you want to compare performance in one part of the run to another part of the run. Notice that once you select a block, it will give you the call tree breakdown for that selection only, and the relative performance of those calls. Once you feel you have collected enough information, you can click [Stop Profiling] to stop the application run and information collection and begin a more thorough analysis. Analyzing Method Timings So now that we’ve halted the run, we can look around the GUI and see what we can see. By default, the times are shown in terms of percentage of time of the total run of the application, though you can change it in the View menu item to milliseconds, ticks, or seconds as well. This won’t affect the percentages of methods, it only affects what units the times are shown. Notice also that the major hotspot seems to be in a method without source, ANTS Profiler will filter these out by default, but you can right-click on the line and remove the filter to see more detail. This proves especially handy when a bottleneck is due to a method in the BCL. So now that we’ve removed the filter, we see a bit more detail: In addition, ANTS Performance Profiler gives you the ability to decompile the methods without source so that you can dive even deeper, though typically this isn’t necessary for our purposes. When looking at timings, there are generally two types of timings for each method call: Time: This is the time spent ONLY in this method, not including calls this method makes to other methods. Time With Children: This is the total of time spent in both this method AND including calls this method makes to other methods. In other words, the Time tells you how much work is being done exclusively in this method, and the Time With Children tells you how much work is being done inclusively in this method and everything it calls. You can also choose to display the methods in a tree or in a grid. The tree view is the default and it shows the method calls arranged in terms of the tree representing all method calls and the parent method that called them, etc. This is useful for when you find a hot-spot method, you can see who is calling it to determine if the problem is the method itself, or if it is being called too many times. The grid method represents each method only once with its totals and is useful for quickly seeing what method is the trouble spot. In addition, you can choose to display Methods with source which are generally the methods you wrote (as opposed to native or BCL code), or Any Method which shows not only your methods, but also native calls, JIT overhead, synchronization waits, etc. So these are just two ways of viewing the same data, and you’re free to choose the organization that best suits what information you are after. Analyzing Method Source If we look at the timings above, we see that our AddToList() method (and in particular, it’s call to the List<T>.Sort() method in the BCL) is the hot-spot in this analysis. If ANTS sees a method that is consuming the most time, it will flag it as a hot-spot to help call out potential areas of concern. This doesn’t mean the other statistics aren’t meaningful, but that the hot-spot is most likely going to be your biggest bang-for-the-buck to concentrate on. So let’s select the AddToList() method, and see what it shows in the source window below: Notice the source breakout in the bottom pane when you select a method (from either tree or grid view). This shows you the timings in this method per line of code. This gives you a major indicator of where the trouble-spot in this method is. So in this case, we see that performing a Sort() on the List<T> after every Add() is killing our performance! Of course, this was a very contrived, duh moment, but you’d be surprised how many performance issues become duh moments. Note that this one line is taking up 86% of the execution time of this application! If we eliminate this bottleneck, we should see drastic improvement in the performance. So to fix this, if we still wanted to maintain the List<T> we’d have many options, including: delay Sort() until after all Add() methods, using a SortedSet, SortedList, or SortedDictionary depending on which is most appropriate, or forgoing the sorting all together and using a Dictionary. Rinse, Repeat! So let’s just change all instances of List<string> to SortedSet<string> and run this again through the profiler: Now we see the AddToList() method is no longer our hot-spot, but now the Max() and Min() calls are! This is good because we’ve eliminated one hot-spot and now we can try to correct this one as well. As before, we can then optimize this part of the code (possibly by taking advantage of the fact the list is now sorted and returning the first and last elements). We can then rinse and repeat this process until we have eliminated as many bottlenecks as possible. Calls by Web Request Another feature that was added recently is the ability to view .NET methods grouped by the HTTP requests that caused them to run. This can be helpful in determining which pages, web services, etc. are causing hot spots in your web applications. Summary If you like the other ANTS tools, you’ll like the ANTS Performance Profiler as well. It is extremely easy to use with very little product knowledge required to get up and running. There are profilers built into the higher product lines of Visual Studio, of course, which are also powerful and easy to use. But for quickly jumping in and finding hot spots rapidly, Red Gate’s Performance Profiler 7.4 is an excellent choice. Technorati Tags: Influencers,ANTS,Performance Profiler,Profiler

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  • C#/.NET Little Wonders: Tuples and Tuple Factory Methods

    - 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 really help improve your code by making it easier to write and maintain.  This week, we look at the System.Tuple class and the handy factory methods for creating a Tuple by inferring the types. What is a Tuple? The System.Tuple is a class that tends to inspire a reaction in one of two ways: love or hate.  Simply put, a Tuple is a data structure that holds a specific number of items of a specific type in a specific order.  That is, a Tuple<int, string, int> is a tuple that contains exactly three items: an int, followed by a string, followed by an int.  The sequence is important not only to distinguish between two members of the tuple with the same type, but also for comparisons between tuples.  Some people tend to love tuples because they give you a quick way to combine multiple values into one result.  This can be handy for returning more than one value from a method (without using out or ref parameters), or for creating a compound key to a Dictionary, or any other purpose you can think of.  They can be especially handy when passing a series of items into a call that only takes one object parameter, such as passing an argument to a thread's startup routine.  In these cases, you do not need to define a class, simply create a tuple containing the types you wish to return, and you are ready to go? On the other hand, there are some people who see tuples as a crutch in object-oriented design.  They may view the tuple as a very watered down class with very little inherent semantic meaning.  As an example, what if you saw this in a piece of code: 1: var x = new Tuple<int, int>(2, 5); What are the contents of this tuple?  If the tuple isn't named appropriately, and if the contents of each member are not self evident from the type this can be a confusing question.  The people who tend to be against tuples would rather you explicitly code a class to contain the values, such as: 1: public sealed class RetrySettings 2: { 3: public int TimeoutSeconds { get; set; } 4: public int MaxRetries { get; set; } 5: } Here, the meaning of each int in the class is much more clear, but it's a bit more work to create the class and can clutter a solution with extra classes. So, what's the correct way to go?  That's a tough call.  You will have people who will argue quite well for one or the other.  For me, I consider the Tuple to be a tool to make it easy to collect values together easily.  There are times when I just need to combine items for a key or a result, in which case the tuple is short lived and so the meaning isn't easily lost and I feel this is a good compromise.  If the scope of the collection of items, though, is more application-wide I tend to favor creating a full class. Finally, it should be noted that tuples are immutable.  That means they are assigned a value at construction, and that value cannot be changed.  Now, of course if the tuple contains an item of a reference type, this means that the reference is immutable and not the item referred to. Tuples from 1 to N Tuples come in all sizes, you can have as few as one element in your tuple, or as many as you like.  However, since C# generics can't have an infinite generic type parameter list, any items after 7 have to be collapsed into another tuple, as we'll show shortly. So when you declare your tuple from sizes 1 (a 1-tuple or singleton) to 7 (a 7-tuple or septuple), simply include the appropriate number of type arguments: 1: // a singleton tuple of integer 2: Tuple<int> x; 3:  4: // or more 5: Tuple<int, double> y; 6:  7: // up to seven 8: Tuple<int, double, char, double, int, string, uint> z; Anything eight and above, and we have to nest tuples inside of tuples.  The last element of the 8-tuple is the generic type parameter Rest, this is special in that the Tuple checks to make sure at runtime that the type is a Tuple.  This means that a simple 8-tuple must nest a singleton tuple (one of the good uses for a singleton tuple, by the way) for the Rest property. 1: // an 8-tuple 2: Tuple<int, int, int, int, int, double, char, Tuple<string>> t8; 3:  4: // an 9-tuple 5: Tuple<int, int, int, int, double, int, char, Tuple<string, DateTime>> t9; 6:  7: // a 16-tuple 8: Tuple<int, int, int, int, int, int, int, Tuple<int, int, int, int, int, int, int, Tuple<int,int>>> t14; Notice that on the 14-tuple we had to have a nested tuple in the nested tuple.  Since the tuple can only support up to seven items, and then a rest element, that means that if the nested tuple needs more than seven items you must nest in it as well.  Constructing tuples Constructing tuples is just as straightforward as declaring them.  That said, you have two distinct ways to do it.  The first is to construct the tuple explicitly yourself: 1: var t3 = new Tuple<int, string, double>(1, "Hello", 3.1415927); This creates a triple that has an int, string, and double and assigns the values 1, "Hello", and 3.1415927 respectively.  Make sure the order of the arguments supplied matches the order of the types!  Also notice that we can't half-assign a tuple or create a default tuple.  Tuples are immutable (you can't change the values once constructed), so thus you must provide all values at construction time. Another way to easily create tuples is to do it implicitly using the System.Tuple static class's Create() factory methods.  These methods (much like C++'s std::make_pair method) will infer the types from the method call so you don't have to type them in.  This can dramatically reduce the amount of typing required especially for complex tuples! 1: // this 4-tuple is typed Tuple<int, double, string, char> 2: var t4 = Tuple.Create(42, 3.1415927, "Love", 'X'); Notice how much easier it is to use the factory methods and infer the types?  This can cut down on typing quite a bit when constructing tuples.  The Create() factory method can construct from a 1-tuple (singleton) to an 8-tuple (octuple), which of course will be a octuple where the last item is a singleton as we described before in nested tuples. Accessing tuple members Accessing a tuple's members is simplicity itself… mostly.  The properties for accessing up to the first seven items are Item1, Item2, …, Item7.  If you have an octuple or beyond, the final property is Rest which will give you the nested tuple which you can then access in a similar matter.  Once again, keep in mind that these are read-only properties and cannot be changed. 1: // for septuples and below, use the Item properties 2: var t1 = Tuple.Create(42, 3.14); 3:  4: Console.WriteLine("First item is {0} and second is {1}", 5: t1.Item1, t1.Item2); 6:  7: // for octuples and above, use Rest to retrieve nested tuple 8: var t9 = new Tuple<int, int, int, int, int, int, int, 9: Tuple<int, int>>(1,2,3,4,5,6,7,Tuple.Create(8,9)); 10:  11: Console.WriteLine("The 8th item is {0}", t9.Rest.Item1); Tuples are IStructuralComparable and IStructuralEquatable Most of you know about IComparable and IEquatable, what you may not know is that there are two sister interfaces to these that were added in .NET 4.0 to help support tuples.  These IStructuralComparable and IStructuralEquatable make it easy to compare two tuples for equality and ordering.  This is invaluable for sorting, and makes it easy to use tuples as a compound-key to a dictionary (one of my favorite uses)! Why is this so important?  Remember when we said that some folks think tuples are too generic and you should define a custom class?  This is all well and good, but if you want to design a custom class that can automatically order itself based on its members and build a hash code for itself based on its members, it is no longer a trivial task!  Thankfully the tuple does this all for you through the explicit implementations of these interfaces. For equality, two tuples are equal if all elements are equal between the two tuples, that is if t1.Item1 == t2.Item1 and t1.Item2 == t2.Item2, and so on.  For ordering, it's a little more complex in that it compares the two tuples one at a time starting at Item1, and sees which one has a smaller Item1.  If one has a smaller Item1, it is the smaller tuple.  However if both Item1 are the same, it compares Item2 and so on. For example: 1: var t1 = Tuple.Create(1, 3.14, "Hi"); 2: var t2 = Tuple.Create(1, 3.14, "Hi"); 3: var t3 = Tuple.Create(2, 2.72, "Bye"); 4:  5: // true, t1 == t2 because all items are == 6: Console.WriteLine("t1 == t2 : " + t1.Equals(t2)); 7:  8: // false, t1 != t2 because at least one item different 9: Console.WriteLine("t2 == t2 : " + t2.Equals(t3)); The actual implementation of IComparable, IEquatable, IStructuralComparable, and IStructuralEquatable is explicit, so if you want to invoke the methods defined there you'll have to manually cast to the appropriate interface: 1: // true because t1.Item1 < t3.Item1, if had been same would check Item2 and so on 2: Console.WriteLine("t1 < t3 : " + (((IComparable)t1).CompareTo(t3) < 0)); So, as I mentioned, the fact that tuples are automatically equatable and comparable (provided the types you use define equality and comparability as needed) means that we can use tuples for compound keys in hashing and ordering containers like Dictionary and SortedList: 1: var tupleDict = new Dictionary<Tuple<int, double, string>, string>(); 2:  3: tupleDict.Add(t1, "First tuple"); 4: tupleDict.Add(t2, "Second tuple"); 5: tupleDict.Add(t3, "Third tuple"); Because IEquatable defines GetHashCode(), and Tuple's IStructuralEquatable implementation creates this hash code by combining the hash codes of the members, this makes using the tuple as a complex key quite easy!  For example, let's say you are creating account charts for a financial application, and you want to cache those charts in a Dictionary based on the account number and the number of days of chart data (for example, a 1 day chart, 1 week chart, etc): 1: // the account number (string) and number of days (int) are key to get cached chart 2: var chartCache = new Dictionary<Tuple<string, int>, IChart>(); Summary The System.Tuple, like any tool, is best used where it will achieve a greater benefit.  I wouldn't advise overusing them, on objects with a large scope or it can become difficult to maintain.  However, when used properly in a well defined scope they can make your code cleaner and easier to maintain by removing the need for extraneous POCOs and custom property hashing and ordering. They are especially useful in defining compound keys to IDictionary implementations and for returning multiple values from methods, or passing multiple values to a single object parameter. Tweet Technorati Tags: C#,.NET,Tuple,Little Wonders

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  • C#/.NET Little Wonders: The ConcurrentDictionary

    - by James Michael Hare
    Once again we consider some of the lesser known classes and keywords of C#.  In this series of posts, we will discuss how the concurrent collections have been developed to help alleviate these multi-threading concerns.  Last week’s post began with a general introduction and discussed the ConcurrentStack<T> and ConcurrentQueue<T>.  Today's post discusses the ConcurrentDictionary<T> (originally I had intended to discuss ConcurrentBag this week as well, but ConcurrentDictionary had enough information to create a very full post on its own!).  Finally next week, we shall close with a discussion of the ConcurrentBag<T> and BlockingCollection<T>. For more of the "Little Wonders" posts, see the index here. Recap As you'll recall from the previous post, the original collections were object-based containers that accomplished synchronization through a Synchronized member.  While these were convenient because you didn't have to worry about writing your own synchronization logic, they were a bit too finely grained and if you needed to perform multiple operations under one lock, the automatic synchronization didn't buy much. 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.  This cuts both ways in that you have a lot more control as a developer over when and how fine-grained you want to synchronize, but on the other hand if you just want simple synchronization it creates more work. With .NET 4.0, we get the best of both worlds in generic collections.  A new breed of collections was born called the concurrent collections in the System.Collections.Concurrent namespace.  These amazing collections are fine-tuned to have best overall performance for situations requiring concurrent access.  They are not meant to replace the generic collections, but to simply be an alternative to creating your own locking mechanisms. Among those concurrent collections were the ConcurrentStack<T> and ConcurrentQueue<T> which provide classic LIFO and FIFO collections with a concurrent twist.  As we saw, some of the traditional methods that required calls to be made in a certain order (like checking for not IsEmpty before calling Pop()) were replaced in favor of an umbrella operation that combined both under one lock (like TryPop()). Now, let's take a look at the next in our series of concurrent collections!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 wonderful whitepaper by the Microsoft Parallel Computing Platform team here. ConcurrentDictionary – the fully thread-safe dictionary The ConcurrentDictionary<TKey,TValue> is the thread-safe counterpart to the generic Dictionary<TKey, TValue> collection.  Obviously, both are designed for quick – O(1) – lookups of data based on a key.  If you think of algorithms where you need lightning fast lookups of data and don’t care whether the data is maintained in any particular ordering or not, the unsorted dictionaries are generally the best way to go. Note: as a side note, there are sorted implementations of IDictionary, namely SortedDictionary and SortedList which are stored as an ordered tree and a ordered list respectively.  While these are not as fast as the non-sorted dictionaries – they are O(log2 n) – they are a great combination of both speed and ordering -- and still greatly outperform a linear search. Now, once again keep in mind that if all you need to do is load a collection once and then allow multi-threaded reading you do not need any locking.  Examples of this tend to be situations where you load a lookup or translation table once at program start, then keep it in memory for read-only reference.  In such cases locking is completely non-productive. However, most of the time when we need a concurrent dictionary we are interleaving both reads and updates.  This is where the ConcurrentDictionary really shines!  It achieves its thread-safety with no common lock to improve efficiency.  It actually uses a series of locks to provide concurrent updates, and has lockless reads!  This means that the ConcurrentDictionary gets even more efficient the higher the ratio of reads-to-writes you have. ConcurrentDictionary and Dictionary differences For the most part, the ConcurrentDictionary<TKey,TValue> behaves like it’s Dictionary<TKey,TValue> counterpart with a few differences.  Some notable examples of which are: Add() does not exist in the concurrent dictionary. This means you must use TryAdd(), AddOrUpdate(), or GetOrAdd().  It also means that you can’t use a collection initializer with the concurrent dictionary. TryAdd() replaced Add() to attempt atomic, safe adds. Because Add() only succeeds if the item doesn’t already exist, we need an atomic operation to check if the item exists, and if not add it while still under an atomic lock. TryUpdate() was added to attempt atomic, safe updates. If we want to update an item, we must make sure it exists first and that the original value is what we expected it to be.  If all these are true, we can update the item under one atomic step. TryRemove() was added to attempt atomic, safe removes. To safely attempt to remove a value we need to see if the key exists first, this checks for existence and removes under an atomic lock. AddOrUpdate() was added to attempt an thread-safe “upsert”. There are many times where you want to insert into a dictionary if the key doesn’t exist, or update the value if it does.  This allows you to make a thread-safe add-or-update. GetOrAdd() was added to attempt an thread-safe query/insert. Sometimes, you want to query for whether an item exists in the cache, and if it doesn’t insert a starting value for it.  This allows you to get the value if it exists and insert if not. Count, Keys, Values properties take a snapshot of the dictionary. Accessing these properties may interfere with add and update performance and should be used with caution. ToArray() returns a static snapshot of the dictionary. That is, the dictionary is locked, and then copied to an array as a O(n) operation.  GetEnumerator() is thread-safe and efficient, but allows dirty reads. Because reads require no locking, you can safely iterate over the contents of the dictionary.  The only downside is that, depending on timing, you may get dirty reads. Dirty reads during iteration The last point on GetEnumerator() bears some explanation.  Picture a scenario in which you call GetEnumerator() (or iterate using a foreach, etc.) and then, during that iteration the dictionary gets updated.  This may not sound like a big deal, but it can lead to inconsistent results if used incorrectly.  The problem is that items you already iterated over that are updated a split second after don’t show the update, but items that you iterate over that were updated a split second before do show the update.  Thus you may get a combination of items that are “stale” because you iterated before the update, and “fresh” because they were updated after GetEnumerator() but before the iteration reached them. Let’s illustrate with an example, let’s say you load up a concurrent dictionary like this: 1: // load up a dictionary. 2: var dictionary = new ConcurrentDictionary<string, int>(); 3:  4: dictionary["A"] = 1; 5: dictionary["B"] = 2; 6: dictionary["C"] = 3; 7: dictionary["D"] = 4; 8: dictionary["E"] = 5; 9: dictionary["F"] = 6; Then you have one task (using the wonderful TPL!) to iterate using dirty reads: 1: // attempt iteration in a separate thread 2: var iterationTask = new Task(() => 3: { 4: // iterates using a dirty read 5: foreach (var pair in dictionary) 6: { 7: Console.WriteLine(pair.Key + ":" + pair.Value); 8: } 9: }); And one task to attempt updates in a separate thread (probably): 1: // attempt updates in a separate thread 2: var updateTask = new Task(() => 3: { 4: // iterates, and updates the value by one 5: foreach (var pair in dictionary) 6: { 7: dictionary[pair.Key] = pair.Value + 1; 8: } 9: }); Now that we’ve done this, we can fire up both tasks and wait for them to complete: 1: // start both tasks 2: updateTask.Start(); 3: iterationTask.Start(); 4:  5: // wait for both to complete. 6: Task.WaitAll(updateTask, iterationTask); Now, if I you didn’t know about the dirty reads, you may have expected to see the iteration before the updates (such as A:1, B:2, C:3, D:4, E:5, F:6).  However, because the reads are dirty, we will quite possibly get a combination of some updated, some original.  My own run netted this result: 1: F:6 2: E:6 3: D:5 4: C:4 5: B:3 6: A:2 Note that, of course, iteration is not in order because ConcurrentDictionary, like Dictionary, is unordered.  Also note that both E and F show the value 6.  This is because the output task reached F before the update, but the updates for the rest of the items occurred before their output (probably because console output is very slow, comparatively). If we want to always guarantee that we will get a consistent snapshot to iterate over (that is, at the point we ask for it we see precisely what is in the dictionary and no subsequent updates during iteration), we should iterate over a call to ToArray() instead: 1: // attempt iteration in a separate thread 2: var iterationTask = new Task(() => 3: { 4: // iterates using a dirty read 5: foreach (var pair in dictionary.ToArray()) 6: { 7: Console.WriteLine(pair.Key + ":" + pair.Value); 8: } 9: }); The atomic Try…() methods As you can imagine TryAdd() and TryRemove() have few surprises.  Both first check the existence of the item to determine if it can be added or removed based on whether or not the key currently exists in the dictionary: 1: // try add attempts an add and returns false if it already exists 2: if (dictionary.TryAdd("G", 7)) 3: Console.WriteLine("G did not exist, now inserted with 7"); 4: else 5: Console.WriteLine("G already existed, insert failed."); TryRemove() also has the virtue of returning the value portion of the removed entry matching the given key: 1: // attempt to remove the value, if it exists it is removed and the original is returned 2: int removedValue; 3: if (dictionary.TryRemove("C", out removedValue)) 4: Console.WriteLine("Removed C and its value was " + removedValue); 5: else 6: Console.WriteLine("C did not exist, remove failed."); Now TryUpdate() is an interesting creature.  You might think from it’s name that TryUpdate() first checks for an item’s existence, and then updates if the item exists, otherwise it returns false.  Well, note quite... It turns out when you call TryUpdate() on a concurrent dictionary, you pass it not only the new value you want it to have, but also the value you expected it to have before the update.  If the item exists in the dictionary, and it has the value you expected, it will update it to the new value atomically and return true.  If the item is not in the dictionary or does not have the value you expected, it is not modified and false is returned. 1: // attempt to update the value, if it exists and if it has the expected original value 2: if (dictionary.TryUpdate("G", 42, 7)) 3: Console.WriteLine("G existed and was 7, now it's 42."); 4: else 5: Console.WriteLine("G either didn't exist, or wasn't 7."); The composite Add methods The ConcurrentDictionary also has composite add methods that can be used to perform updates and gets, with an add if the item is not existing at the time of the update or get. The first of these, AddOrUpdate(), allows you to add a new item to the dictionary if it doesn’t exist, or update the existing item if it does.  For example, let’s say you are creating a dictionary of counts of stock ticker symbols you’ve subscribed to from a market data feed: 1: public sealed class SubscriptionManager 2: { 3: private readonly ConcurrentDictionary<string, int> _subscriptions = new ConcurrentDictionary<string, int>(); 4:  5: // adds a new subscription, or increments the count of the existing one. 6: public void AddSubscription(string tickerKey) 7: { 8: // add a new subscription with count of 1, or update existing count by 1 if exists 9: var resultCount = _subscriptions.AddOrUpdate(tickerKey, 1, (symbol, count) => count + 1); 10:  11: // now check the result to see if we just incremented the count, or inserted first count 12: if (resultCount == 1) 13: { 14: // subscribe to symbol... 15: } 16: } 17: } Notice the update value factory Func delegate.  If the key does not exist in the dictionary, the add value is used (in this case 1 representing the first subscription for this symbol), but if the key already exists, it passes the key and current value to the update delegate which computes the new value to be stored in the dictionary.  The return result of this operation is the value used (in our case: 1 if added, existing value + 1 if updated). Likewise, the GetOrAdd() allows you to attempt to retrieve a value from the dictionary, and if the value does not currently exist in the dictionary it will insert a value.  This can be handy in cases where perhaps you wish to cache data, and thus you would query the cache to see if the item exists, and if it doesn’t you would put the item into the cache for the first time: 1: public sealed class PriceCache 2: { 3: private readonly ConcurrentDictionary<string, double> _cache = new ConcurrentDictionary<string, double>(); 4:  5: // adds a new subscription, or increments the count of the existing one. 6: public double QueryPrice(string tickerKey) 7: { 8: // check for the price in the cache, if it doesn't exist it will call the delegate to create value. 9: return _cache.GetOrAdd(tickerKey, symbol => GetCurrentPrice(symbol)); 10: } 11:  12: private double GetCurrentPrice(string tickerKey) 13: { 14: // do code to calculate actual true price. 15: } 16: } There are other variations of these two methods which vary whether a value is provided or a factory delegate, but otherwise they work much the same. Oddities with the composite Add methods The AddOrUpdate() and GetOrAdd() methods are totally thread-safe, on this you may rely, but they are not atomic.  It is important to note that the methods that use delegates execute those delegates outside of the lock.  This was done intentionally so that a user delegate (of which the ConcurrentDictionary has no control of course) does not take too long and lock out other threads. This is not necessarily an issue, per se, but it is something you must consider in your design.  The main thing to consider is that your delegate may get called to generate an item, but that item may not be the one returned!  Consider this scenario: A calls GetOrAdd and sees that the key does not currently exist, so it calls the delegate.  Now thread B also calls GetOrAdd and also sees that the key does not currently exist, and for whatever reason in this race condition it’s delegate completes first and it adds its new value to the dictionary.  Now A is done and goes to get the lock, and now sees that the item now exists.  In this case even though it called the delegate to create the item, it will pitch it because an item arrived between the time it attempted to create one and it attempted to add it. Let’s illustrate, assume this totally contrived example program which has a dictionary of char to int.  And in this dictionary we want to store a char and it’s ordinal (that is, A = 1, B = 2, etc).  So for our value generator, we will simply increment the previous value in a thread-safe way (perhaps using Interlocked): 1: public static class Program 2: { 3: private static int _nextNumber = 0; 4:  5: // the holder of the char to ordinal 6: private static ConcurrentDictionary<char, int> _dictionary 7: = new ConcurrentDictionary<char, int>(); 8:  9: // get the next id value 10: public static int NextId 11: { 12: get { return Interlocked.Increment(ref _nextNumber); } 13: } Then, we add a method that will perform our insert: 1: public static void Inserter() 2: { 3: for (int i = 0; i < 26; i++) 4: { 5: _dictionary.GetOrAdd((char)('A' + i), key => NextId); 6: } 7: } Finally, we run our test by starting two tasks to do this work and get the results… 1: public static void Main() 2: { 3: // 3 tasks attempting to get/insert 4: var tasks = new List<Task> 5: { 6: new Task(Inserter), 7: new Task(Inserter) 8: }; 9:  10: tasks.ForEach(t => t.Start()); 11: Task.WaitAll(tasks.ToArray()); 12:  13: foreach (var pair in _dictionary.OrderBy(p => p.Key)) 14: { 15: Console.WriteLine(pair.Key + ":" + pair.Value); 16: } 17: } If you run this with only one task, you get the expected A:1, B:2, ..., Z:26.  But running this in parallel you will get something a bit more complex.  My run netted these results: 1: A:1 2: B:3 3: C:4 4: D:5 5: E:6 6: F:7 7: G:8 8: H:9 9: I:10 10: J:11 11: K:12 12: L:13 13: M:14 14: N:15 15: O:16 16: P:17 17: Q:18 18: R:19 19: S:20 20: T:21 21: U:22 22: V:23 23: W:24 24: X:25 25: Y:26 26: Z:27 Notice that B is 3?  This is most likely because both threads attempted to call GetOrAdd() at roughly the same time and both saw that B did not exist, thus they both called the generator and one thread got back 2 and the other got back 3.  However, only one of those threads can get the lock at a time for the actual insert, and thus the one that generated the 3 won and the 3 was inserted and the 2 got discarded.  This is why on these methods your factory delegates should be careful not to have any logic that would be unsafe if the value they generate will be pitched in favor of another item generated at roughly the same time.  As such, it is probably a good idea to keep those generators as stateless as possible. Summary The ConcurrentDictionary is a very efficient and thread-safe version of the Dictionary generic collection.  It has all the benefits of type-safety that it’s generic collection counterpart does, and in addition is extremely efficient especially when there are more reads than writes concurrently. Tweet Technorati Tags: C#, .NET, Concurrent Collections, Collections, Little Wonders, Black Rabbit Coder,James Michael Hare

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