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  • Auto-Suggest via ‘Trie’ (Pre-fix Tree)

    - by Strenium
    Auto-Suggest (Auto-Complete) “thing” has been around for a few years. Here’s my little snippet on the subject. For one of my projects, I had to deal with a non-trivial set of items to be pulled via auto-suggest used by multiple concurrent users. Simple, dumb iteration through a list in local cache or back-end access didn’t quite cut it. Enter a nifty little structure, perfectly suited for storing and matching verbal data: “Trie” (http://tinyurl.com/db56g) also known as a Pre-fix Tree: “Unlike a binary search tree, no node in the tree stores the key associated with that node; instead, its position in the tree defines the key with which it is associated. All the descendants of a node have a common prefix of the string associated with that node, and the root is associated with the empty string. Values are normally not associated with every node, only with leaves and some inner nodes that correspond to keys of interest.” This is a very scalable, performing structure. Though, as usual, something ‘fast’ comes at a cost of ‘size’; fortunately RAM is more plentiful today so I can live with that. I won’t bore you with the detailed algorithmic performance here - Google can do a better job of such. So, here’s C# implementation of all this. Let’s start with individual node: Trie Node /// <summary> /// Contains datum of a single trie node. /// </summary> public class AutoSuggestTrieNode {     public char Value { get; set; }       /// <summary>     /// Gets a value indicating whether this instance is leaf node.     /// </summary>     /// <value>     ///     <c>true</c> if this instance is leaf node; otherwise, a prefix node <c>false</c>.     /// </value>     public bool IsLeafNode { get; private set; }       public List<AutoSuggestTrieNode> DescendantNodes { get; private set; }         /// <summary>     /// Initializes a new instance of the <see cref="AutoSuggestTrieNode"/> class.     /// </summary>     /// <param name="value">The phonetic value.</param>     /// <param name="isLeafNode">if set to <c>true</c> [is leaf node].</param>     public AutoSuggestTrieNode(char value = ' ', bool isLeafNode = false)     {         Value = value;         IsLeafNode = isLeafNode;           DescendantNodes = new List<AutoSuggestTrieNode>();     }       /// <summary>     /// Gets the descendants of the pre-fix node, if any.     /// </summary>     /// <param name="descendantValue">The descendant value.</param>     /// <returns></returns>     public AutoSuggestTrieNode GetDescendant(char descendantValue)     {         return DescendantNodes.FirstOrDefault(descendant => descendant.Value == descendantValue);     } }   Quite self-explanatory, imho. A node is either a “Pre-fix” or a “Leaf” node. “Leaf” contains the full “word”, while the “Pre-fix” nodes act as indices used for matching the results.   Ok, now the Trie: Trie Structure /// <summary> /// Contains structure and functionality of an AutoSuggest Trie (Pre-fix Tree) /// </summary> public class AutoSuggestTrie {     private readonly AutoSuggestTrieNode _root = new AutoSuggestTrieNode();       /// <summary>     /// Adds the word to the trie by breaking it up to pre-fix nodes + leaf node.     /// </summary>     /// <param name="word">Phonetic value.</param>     public void AddWord(string word)     {         var currentNode = _root;         word = word.Trim().ToLower();           for (int i = 0; i < word.Length; i++)         {             var child = currentNode.GetDescendant(word[i]);               if (child == null) /* this character hasn't yet been indexed in the trie */             {                 var newNode = new AutoSuggestTrieNode(word[i], word.Count() - 1 == i);                   currentNode.DescendantNodes.Add(newNode);                 currentNode = newNode;             }             else                 currentNode = child; /* this character is already indexed, move down the trie */         }     }         /// <summary>     /// Gets the suggested matches.     /// </summary>     /// <param name="word">The phonetic search value.</param>     /// <returns></returns>     public List<string> GetSuggestedMatches(string word)     {         var currentNode = _root;         word = word.Trim().ToLower();           var indexedNodesValues = new StringBuilder();         var resultBag = new ConcurrentBag<string>();           for (int i = 0; i < word.Trim().Length; i++)  /* traverse the trie collecting closest indexed parent (parent can't be leaf, obviously) */         {             var child = currentNode.GetDescendant(word[i]);               if (child == null || word.Count() - 1 == i)                 break; /* done looking, the rest of the characters aren't indexed in the trie */               indexedNodesValues.Append(word[i]);             currentNode = child;         }           Action<AutoSuggestTrieNode, string> collectAllMatches = null;         collectAllMatches = (node, aggregatedValue) => /* traverse the trie collecting matching leafNodes (i.e. "full words") */             {                 if (node.IsLeafNode) /* full word */                     resultBag.Add(aggregatedValue); /* thread-safe write */                   Parallel.ForEach(node.DescendantNodes, descendandNode => /* asynchronous recursive traversal */                 {                     collectAllMatches(descendandNode, String.Format("{0}{1}", aggregatedValue, descendandNode.Value));                 });             };           collectAllMatches(currentNode, indexedNodesValues.ToString());           return resultBag.OrderBy(o => o).ToList();     }         /// <summary>     /// Gets the total words (leafs) in the trie. Recursive traversal.     /// </summary>     public int TotalWords     {         get         {             int runningCount = 0;               Action<AutoSuggestTrieNode> traverseAllDecendants = null;             traverseAllDecendants = n => { runningCount += n.DescendantNodes.Count(o => o.IsLeafNode); n.DescendantNodes.ForEach(traverseAllDecendants); };             traverseAllDecendants(this._root);               return runningCount;         }     } }   Matching operations and Inserts involve traversing the nodes before the right “spot” is found. Inserts need be synchronous since ordering of data matters here. However, matching can be done in parallel traversal using recursion (line 64). Here’s sample usage:   [TestMethod] public void AutoSuggestTest() {     var autoSuggestCache = new AutoSuggestTrie();       var testInput = @"Lorem ipsum dolor sit amet, consectetur adipiscing elit. Integer nec odio. Praesent libero.                 Sed cursus ante dapibus diam. Sed nisi. Nulla quis sem at nibh elementum imperdiet. Duis sagittis ipsum. Praesent mauris.                 Fusce nec tellus sed augue semper porta. Mauris massa. Vestibulum lacinia arcu eget nulla. Class aptent taciti sociosqu ad                 litora torquent per conubia nostra, per inceptos himenaeos. Curabitur sodales ligula in libero. Sed dignissim lacinia nunc.                 Curabitur tortor. Pellentesque nibh. Aenean quam. In scelerisque sem at dolor. Maecenas mattis. Sed convallis tristique sem.                 Proin ut ligula vel nunc egestas porttitor. Morbi lectus risus, iaculis vel, suscipit quis, luctus non, massa. Fusce ac                 turpis quis ligula lacinia aliquet. Mauris ipsum. Nulla metus metus, ullamcorper vel, tincidunt sed, euismod in, nibh. Quisque                 volutpat condimentum velit. Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos. Nam                 nec ante. Sed lacinia, urna non tincidunt mattis, tortor neque adipiscing diam, a cursus ipsum ante quis turpis. Nulla                 facilisi. Ut fringilla. Suspendisse potenti. Nunc feugiat mi a tellus consequat imperdiet. Vestibulum sapien. Proin quam. Etiam                 ultrices. Suspendisse in justo eu magna luctus suscipit. Sed lectus. Integer euismod lacus luctus magna. Quisque cursus, metus                 vitae pharetra auctor, sem massa mattis sem, at interdum magna augue eget diam. Vestibulum ante ipsum primis in faucibus orci                 luctus et ultrices posuere cubilia Curae; Morbi lacinia molestie dui. Praesent blandit dolor. Sed non quam. In vel mi sit amet                 augue congue elementum. Morbi in ipsum sit amet pede facilisis laoreet. Donec lacus nunc, viverra nec.";       testInput.Split(' ').ToList().ForEach(word => autoSuggestCache.AddWord(word));       var testMatches = autoSuggestCache.GetSuggestedMatches("le"); }   ..and the result: That’s it!

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  • What’s ‘default’ for?

    - by Strenium
    Sometimes there's a need to communicate explicitly that value variable is yet to be "initialized" or in other words - we’ve never changed it from its' default value. Perhaps "initialized" is not the right word since a value type will always have some sort of value (even a nullable one) but it's just that - how do we tell? Of course an 'int' would be 0, an 'enum' would the first defined value of a given enum and so on – we sure can make this kind of check "by hand" but eventually it would get a bit messy. There's a more elegant way with a use of little-known functionality of: 'default'Let’s just say we have a simple Enum: Simple Enum namespace xxx.Common.Domain{    public enum SimpleEnum    {        White = 1,         Black = 2,         Red = 3    }}   In case below we set the value of the enum to ‘White’ which happens to be a first and therefore default value for the enum. So the snippet below will set value of the ‘isDefault’ Boolean to ‘true’. 'True' Case SimpleEnum simpleEnum = SimpleEnum.White;bool isDefault; /* btw this one is 'false' by default */ isDefault = simpleEnum == default(SimpleEnum) ? true : false; /* default value 'white' */   Here we set the value to ‘Red’ and ‘default’ will tell us whether or not this the default value for this enum type. In this case: ‘false’. 'False' Case simpleEnum = SimpleEnum.Red; /* change from default */isDefault = simpleEnum == default(SimpleEnum) ? true : false; /* value is not default any longer */ Same 'default' functionality can also be applied to DateTimes, value types and other custom types as well. Sweet ‘n Short. Happy Coding!

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  • Using ConcurrentQueue for thread-safe Performance Bookkeeping.

    - by Strenium
    Just a small tidbit that's sprung up today. I had to book-keep and emit diagnostics for the average thread performance in a highly-threaded code over a period of last X number of calls and no more. Need of the day: a thread-safe, self-managing stats container. Since .NET 4.0 introduced new thread-safe 'Collections.Concurrent' objects and I've been using them frequently - the one in particular seemed like a good fit for storing each threads' performance data - ConcurrentQueue. But I wanted to store only the most recent X# of calls and since the ConcurrentQueue currently does not support size constraint I had to come up with my own generic version which attempts to restrict usage to numeric types only: unfortunately there is no IArithmetic-like interface which constrains to only numeric types – so the constraints here here aren't as elegant as they could be. (Note the use of the Average() method, of course you can use others as well as make your own).   FIFO FixedSizedConcurrentQueue using System;using System.Collections.Concurrent;using System.Linq; namespace xxxxx.Data.Infrastructure{    [Serializable]    public class FixedSizedConcurrentQueue<T> where T : struct, IConvertible, IComparable<T>    {        private FixedSizedConcurrentQueue() { }         public FixedSizedConcurrentQueue(ConcurrentQueue<T> queue)        {            _queue = queue;        }         ConcurrentQueue<T> _queue = new ConcurrentQueue<T>();         public int Size { get { return _queue.Count; } }        public double Average { get { return _queue.Average(arg => Convert.ToInt32(arg)); } }         public int Limit { get; set; }        public void Enqueue(T obj)        {            _queue.Enqueue(obj);            lock (this)            {                T @out;                while (_queue.Count > Limit) _queue.TryDequeue(out @out);            }        }    } }   The usage case is straight-forward, in this case I’m using a FIFO queue of maximum size of 200 to store doubles to which I simply Enqueue() the calculated rates: Usage var RateQueue = new FixedSizedConcurrentQueue<double>(new ConcurrentQueue<double>()) { Limit = 200 }; /* greater size == longer history */   That’s about it. Happy coding!

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