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  • Create Pivot collections much faster than DeepZoomTools CollectionCreator class

    - by John Conwell
    I've been playing with Microsoft Live Labs Pivot to create a hierarchy of collections all linked together to allow someone to explore a hierarchy of data visually. The problem has been the generation time of the entire hierarchy. I end up creating 500 - 600 collections total and it takes hours and hours using the CollectionCreator class that comes with the DeepZoomTools.  So digging around I found a way to make the actual DeepZoom collection creation wicked fast. Dont use the CollectionCreator!  Turns out Pivot doesnt actually use the image pyramid generated by the CollectionCreator. Or if it does, its only when you open a new collection it shows all the images zooming in. But once the zoom in is complete, Pivot uses the individual DeepZoom images. What Pivot does need is the xml generated by the CollectionCreator, which is in a very simple format.  So what i did was manually generate the xml for the collection image pyramid, and then create the folder structure required (one folder per level of the pyramid), and put a single pixel png file in each folder.  Now, I can create the required files and folders for 500 collections in about 10 seconds. Sweet! Now you still have to use the ImageCreator to create a DeepZoom image for each image in the collection and that still takes some time, but at least the total processing time is way better.

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  • What's the best way of accessing a DRb object (e.g. Ruby Queue) from Scala (and Java)?

    - by Tom Morris
    I have built a variety of little scripts using Ruby's very simple Queue class, and share the Queue between Ruby and JRuby processes using DRb. It would be nice to be able to access these from Scala (and maybe Java) using JRuby. I've put together something Scala and the JSR-223 interface to access jruby-complete.jar. import javax.script._ class DRbQueue(host: String, port: Int) { private var engine = DRbQueue.factory.getEngineByName("jruby") private var invoker = engine.asInstanceOf[Invocable] engine.eval("require \"drb\" ") private var queue = engine.eval("DRbObject.new(nil, \"druby://" + host + ":" + port.toString + "\")") def isEmpty(): Boolean = invoker.invokeMethod(this.queue, "empty?").asInstanceOf[Boolean] def size(): Long = invoker.invokeMethod(this.queue, "length").asInstanceOf[Long] def threadsWaiting: Long = invoker.invokeMethod(this.queue, "num_waiting").asInstanceOf[Long] def offer(obj: Any) = invoker.invokeMethod(this.queue, "push", obj.asInstanceOf[java.lang.Object]) def poll(): Any = invoker.invokeMethod(this.queue, "pop") def clear(): Unit = { invoker.invokeMethod(this.queue, "clear") } } object DRbQueue { var factory = new ScriptEngineManager() } (It conforms roughly to java.util.Queue interface, but I haven't declared the interface because it doesn't implement the element and peek methods because the Ruby class doesn't offer them.) The problem with this is the type conversion. JRuby is fine with Scala's Strings - because they are Java strings. But if I give it a Scala Int or Long, or one of the other Scala types (List, Set, RichString, Array, Symbol) or some other custom type. This seems unnecessarily hacky: surely there has got to be a better way of doing RMI/DRb interop without having to use JSR-223 API. I could either make it so that the offer method serializes the object to, say, a JSON string and takes a structural type of only objects that have a toJson method. I could then write a Ruby wrapper class (or just monkeypatch Queue) to would parse the JSON. Is there any point in carrying on with trying to access DRb from Java/Scala? Might it just be easier to install a real message queue? (If so, any suggestions for a lightweight JVM-based MQ?)

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  • C#: System.Collections.Concurrent.ConcurrentQueue vs. Queue

    - by James Michael Hare
    I love new toys, so of course when .NET 4.0 came out I felt like the proverbial kid in the candy store!  Now, some people get all excited about the IDE and it’s new features or about changes to WPF and Silver Light and yes, those are all very fine and grand.  But me, I get all excited about things that tend to affect my life on the backside of development.  That’s why when I heard there were going to be concurrent container implementations in the latest version of .NET I was salivating like Pavlov’s dog at the dinner bell. They seem so simple, really, that one could easily overlook them.  Essentially they are implementations of containers (many that mirror the generic collections, others are new) that have either been optimized with very efficient, limited, or no locking but are still completely thread safe -- and I just had to see what kind of an improvement that would translate into. Since part of my job as a solutions architect here where I work is to help design, develop, and maintain the systems that process tons of requests each second, the thought of extremely efficient thread-safe containers was extremely appealing.  Of course, they also rolled out a whole parallel development framework which I won’t get into in this post but will cover bits and pieces of as time goes by. This time, I was mainly curious as to how well these new concurrent containers would perform compared to areas in our code where we manually synchronize them using lock or some other mechanism.  So I set about to run a processing test with a series of producers and consumers that would be either processing a traditional System.Collections.Generic.Queue or a System.Collection.Concurrent.ConcurrentQueue. Now, I wanted to keep the code as common as possible to make sure that the only variance was the container, so I created a test Producer and a test Consumer.  The test Producer takes an Action<string> delegate which is responsible for taking a string and placing it on whichever queue we’re testing in a thread-safe manner: 1: internal class Producer 2: { 3: public int Iterations { get; set; } 4: public Action<string> ProduceDelegate { get; set; } 5: 6: public void Produce() 7: { 8: for (int i = 0; i < Iterations; i++) 9: { 10: ProduceDelegate(“Hello”); 11: } 12: } 13: } Then likewise, I created a consumer that took a Func<string> that would read from whichever queue we’re testing and return either the string if data exists or null if not.  Then, if the item doesn’t exist, it will do a 10 ms wait before testing again.  Once all the producers are done and join the main thread, a flag will be set in each of the consumers to tell them once the queue is empty they can shut down since no other data is coming: 1: internal class Consumer 2: { 3: public Func<string> ConsumeDelegate { get; set; } 4: public bool HaltWhenEmpty { get; set; } 5: 6: public void Consume() 7: { 8: bool processing = true; 9: 10: while (processing) 11: { 12: string result = ConsumeDelegate(); 13: 14: if(result == null) 15: { 16: if (HaltWhenEmpty) 17: { 18: processing = false; 19: } 20: else 21: { 22: Thread.Sleep(TimeSpan.FromMilliseconds(10)); 23: } 24: } 25: else 26: { 27: DoWork(); // do something non-trivial so consumers lag behind a bit 28: } 29: } 30: } 31: } Okay, now that we’ve done that, we can launch threads of varying numbers using lambdas for each different method of production/consumption.  First let's look at the lambdas for a typical System.Collections.Generics.Queue with locking: 1: // lambda for putting to typical Queue with locking... 2: var productionDelegate = s => 3: { 4: lock (_mutex) 5: { 6: _mutexQueue.Enqueue(s); 7: } 8: }; 9:  10: // and lambda for typical getting from Queue with locking... 11: var consumptionDelegate = () => 12: { 13: lock (_mutex) 14: { 15: if (_mutexQueue.Count > 0) 16: { 17: return _mutexQueue.Dequeue(); 18: } 19: } 20: return null; 21: }; Nothing new or interesting here.  Just typical locks on an internal object instance.  Now let's look at using a ConcurrentQueue from the System.Collections.Concurrent library: 1: // lambda for putting to a ConcurrentQueue, notice it needs no locking! 2: var productionDelegate = s => 3: { 4: _concurrentQueue.Enqueue(s); 5: }; 6:  7: // lambda for getting from a ConcurrentQueue, once again, no locking required. 8: var consumptionDelegate = () => 9: { 10: string s; 11: return _concurrentQueue.TryDequeue(out s) ? s : null; 12: }; So I pass each of these lambdas and the number of producer and consumers threads to launch and take a look at the timing results.  Basically I’m timing from the time all threads start and begin producing/consuming to the time that all threads rejoin.  I won't bore you with the test code, basically it just launches code that creates the producers and consumers and launches them in their own threads, then waits for them all to rejoin.  The following are the timings from the start of all threads to the Join() on all threads completing.  The producers create 10,000,000 items evenly between themselves and then when all producers are done they trigger the consumers to stop once the queue is empty. These are the results in milliseconds from the ordinary Queue with locking: 1: Consumers Producers 1 2 3 Time (ms) 2: ---------- ---------- ------ ------ ------ --------- 3: 1 1 4284 5153 4226 4554.33 4: 10 10 4044 3831 5010 4295.00 5: 100 100 5497 5378 5612 5495.67 6: 1000 1000 24234 25409 27160 25601.00 And the following are the results in milliseconds from the ConcurrentQueue with no locking necessary: 1: Consumers Producers 1 2 3 Time (ms) 2: ---------- ---------- ------ ------ ------ --------- 3: 1 1 3647 3643 3718 3669.33 4: 10 10 2311 2136 2142 2196.33 5: 100 100 2480 2416 2190 2362.00 6: 1000 1000 7289 6897 7061 7082.33 Note that even though obviously 2000 threads is quite extreme, the concurrent queue actually scales really well, whereas the traditional queue with simple locking scales much more poorly. I love the new concurrent collections, they look so much simpler without littering your code with the locking logic, and they perform much better.  All in all, a great new toy to add to your arsenal of multi-threaded processing!

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  • rewrite not a member of LiftRules

    - by José Leal
    Hi guys, I was following http://www.assembla.com/wiki/show/liftweb/URL_Rewriting tutorial for url rewritting in liftweb.. but I get this error: error: value rewrite is not a member of object net.liftweb.http.LiftRules .. it is really odd.. and the documentation says that it exists. I'm using idea IDE, and I've done everything from scratch, using the lift maven blank archifact. Some more info: [INFO] ------------------------------------------------------------------------ [INFO] Building Joseph3 [INFO] task-segment: [tomcat:run] [INFO] ------------------------------------------------------------------------ [INFO] Preparing tomcat:run [INFO] [resources:resources {execution: default-resources}] [WARNING] Using platform encoding (UTF-8 actually) to copy filtered resources, i.e. build is platform dependent! [INFO] Copying 0 resource [INFO] [yuicompressor:compress {execution: default}] [INFO] nb warnings: 0, nb errors: 0 [INFO] artifact org.mortbay.jetty:jetty: checking for updates from scala-tools.org [INFO] artifact org.mortbay.jetty:jetty: checking for updates from central [INFO] [compiler:compile {execution: default-compile}] [INFO] Nothing to compile - all classes are up to date [INFO] [scala:compile {execution: default}] [INFO] Checking for multiple versions of scala [INFO] /home/dpz/Scala/Doit/Joseph3/src/main/scala:-1: info: compiling [INFO] Compiling 2 source files to /home/dpz/Scala/Doit/Joseph3/target/classes at 1274922123910 [ERROR] /home/dpz/Scala/Doit/Joseph3/src/main/scala/bootstrap/liftweb/Boot.scala:16: error: value rewrite is not a member of object net.liftweb.http.LiftRules [INFO] LiftRules.rewrite.prepend(NamedPF("ProductExampleRewrite") { [INFO] ^ [ERROR] one error found [INFO] ------------------------------------------------------------------------ [ERROR] BUILD ERROR [INFO] ------------------------------------------------------------------------ [INFO] wrap: org.apache.commons.exec.ExecuteException: Process exited with an error: 1(Exit value: 1) [INFO] ------------------------------------------------------------------------ [INFO] For more information, run Maven with the -e switch [INFO] ------------------------------------------------------------------------ [INFO] Total time: 19 seconds [INFO] Finished at: Thu May 27 03:02:07 CEST 2010 [INFO] Final Memory: 20M/175M [INFO] ------------------------------------------------------------------------ Process finished with exit code 1 enter code here

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  • How to specialize a type parameterized argument to multiple different types for in Scala?

    - by jmount
    I need a back-check (please). In an article ( http://www.win-vector.com/blog/2010/06/automatic-differentiation-with-scala/ ) I just wrote I stated that it is my belief in Scala that you can not specify a function that takes an argument that is itself a function with an unbound type parameter. What I mean is you can write: def g(f:Array[Double]=>Double,Array[Double]):Double but you can not write something like: def g(f[Y]:Array[Y]=>Double,Array[Double]):Double because Y is not known. The intended use is that inside g() I will specialize fY to multiple different types at different times. You can write: def g[Y](f:Array[Y]=>Double,Array[Double]):Double but then f() is of a single type per call to g() (which is exactly what we do not want). However, you can get all of the equivalent functionality by using a trait extension instead insisting on passing around a function. What I advocated in my article was: 1) Creating a trait that imitates the structure of Scala's Function1 trait. Something like: abstract trait VectorFN { def apply[Y](x:Array[Y]):Y } 2) declaring def g(f:VectorFN,Double):Double (using the trait is the type). This works (people here on StackOverflow helped me find it, and I am happy with it)- but am I mis-representing Scala by missing an even better solution?

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  • C#/.NET Fundamentals: Choosing the Right Collection Class

    - by James Michael Hare
    The .NET Base Class Library (BCL) has a wide array of collection classes at your disposal which make it easy to manage collections of objects. While it's great to have so many classes available, it can be daunting to choose the right collection to use for any given situation. As hard as it may be, choosing the right collection can be absolutely key to the performance and maintainability of your application! This post will look at breaking down any confusion between each collection and the situations in which they excel. We will be spending most of our time looking at the System.Collections.Generic namespace, which is the recommended set of collections. The Generic Collections: System.Collections.Generic namespace The generic collections were introduced in .NET 2.0 in the System.Collections.Generic namespace. This is the main body of collections you should tend to focus on first, as they will tend to suit 99% of your needs right up front. It is important to note that the generic collections are unsynchronized. This decision was made for performance reasons because depending on how you are using the collections its completely possible that synchronization may not be required or may be needed on a higher level than simple method-level synchronization. Furthermore, concurrent read access (all writes done at beginning and never again) is always safe, but for concurrent mixed access you should either synchronize the collection or use one of the concurrent collections. So let's look at each of the collections in turn and its various pros and cons, at the end we'll summarize with a table to help make it easier to compare and contrast the different collections. The Associative Collection Classes Associative collections store a value in the collection by providing a key that is used to add/remove/lookup the item. Hence, the container associates the value with the key. These collections are most useful when you need to lookup/manipulate a collection using a key value. For example, if you wanted to look up an order in a collection of orders by an order id, you might have an associative collection where they key is the order id and the value is the order. The Dictionary<TKey,TVale> is probably the most used associative container class. The Dictionary<TKey,TValue> is the fastest class for associative lookups/inserts/deletes because it uses a hash table under the covers. Because the keys are hashed, the key type should correctly implement GetHashCode() and Equals() appropriately or you should provide an external IEqualityComparer to the dictionary on construction. The insert/delete/lookup time of items in the dictionary is amortized constant time - O(1) - which means no matter how big the dictionary gets, the time it takes to find something remains relatively constant. This is highly desirable for high-speed lookups. The only downside is that the dictionary, by nature of using a hash table, is unordered, so you cannot easily traverse the items in a Dictionary in order. The SortedDictionary<TKey,TValue> is similar to the Dictionary<TKey,TValue> in usage but very different in implementation. The SortedDictionary<TKey,TValye> uses a binary tree under the covers to maintain the items in order by the key. As a consequence of sorting, the type used for the key must correctly implement IComparable<TKey> so that the keys can be correctly sorted. The sorted dictionary trades a little bit of lookup time for the ability to maintain the items in order, thus insert/delete/lookup times in a sorted dictionary are logarithmic - O(log n). Generally speaking, with logarithmic time, you can double the size of the collection and it only has to perform one extra comparison to find the item. Use the SortedDictionary<TKey,TValue> when you want fast lookups but also want to be able to maintain the collection in order by the key. The SortedList<TKey,TValue> is the other ordered associative container class in the generic containers. Once again SortedList<TKey,TValue>, like SortedDictionary<TKey,TValue>, uses a key to sort key-value pairs. Unlike SortedDictionary, however, items in a SortedList are stored as an ordered array of items. This means that insertions and deletions are linear - O(n) - because deleting or adding an item may involve shifting all items up or down in the list. Lookup time, however is O(log n) because the SortedList can use a binary search to find any item in the list by its key. So why would you ever want to do this? Well, the answer is that if you are going to load the SortedList up-front, the insertions will be slower, but because array indexing is faster than following object links, lookups are marginally faster than a SortedDictionary. Once again I'd use this in situations where you want fast lookups and want to maintain the collection in order by the key, and where insertions and deletions are rare. The Non-Associative Containers The other container classes are non-associative. They don't use keys to manipulate the collection but rely on the object itself being stored or some other means (such as index) to manipulate the collection. The List<T> is a basic contiguous storage container. Some people may call this a vector or dynamic array. Essentially it is an array of items that grow once its current capacity is exceeded. Because the items are stored contiguously as an array, you can access items in the List<T> by index very quickly. However inserting and removing in the beginning or middle of the List<T> are very costly because you must shift all the items up or down as you delete or insert respectively. However, adding and removing at the end of a List<T> is an amortized constant operation - O(1). Typically List<T> is the standard go-to collection when you don't have any other constraints, and typically we favor a List<T> even over arrays unless we are sure the size will remain absolutely fixed. The LinkedList<T> is a basic implementation of a doubly-linked list. This means that you can add or remove items in the middle of a linked list very quickly (because there's no items to move up or down in contiguous memory), but you also lose the ability to index items by position quickly. Most of the time we tend to favor List<T> over LinkedList<T> unless you are doing a lot of adding and removing from the collection, in which case a LinkedList<T> may make more sense. The HashSet<T> is an unordered collection of unique items. This means that the collection cannot have duplicates and no order is maintained. Logically, this is very similar to having a Dictionary<TKey,TValue> where the TKey and TValue both refer to the same object. This collection is very useful for maintaining a collection of items you wish to check membership against. For example, if you receive an order for a given vendor code, you may want to check to make sure the vendor code belongs to the set of vendor codes you handle. In these cases a HashSet<T> is useful for super-quick lookups where order is not important. Once again, like in Dictionary, the type T should have a valid implementation of GetHashCode() and Equals(), or you should provide an appropriate IEqualityComparer<T> to the HashSet<T> on construction. The SortedSet<T> is to HashSet<T> what the SortedDictionary<TKey,TValue> is to Dictionary<TKey,TValue>. That is, the SortedSet<T> is a binary tree where the key and value are the same object. This once again means that adding/removing/lookups are logarithmic - O(log n) - but you gain the ability to iterate over the items in order. For this collection to be effective, type T must implement IComparable<T> or you need to supply an external IComparer<T>. Finally, the Stack<T> and Queue<T> are two very specific collections that allow you to handle a sequential collection of objects in very specific ways. The Stack<T> is a last-in-first-out (LIFO) container where items are added and removed from the top of the stack. Typically this is useful in situations where you want to stack actions and then be able to undo those actions in reverse order as needed. The Queue<T> on the other hand is a first-in-first-out container which adds items at the end of the queue and removes items from the front. This is useful for situations where you need to process items in the order in which they came, such as a print spooler or waiting lines. So that's the basic collections. Let's summarize what we've learned in a quick reference table.  Collection Ordered? Contiguous Storage? Direct Access? Lookup Efficiency Manipulate Efficiency Notes Dictionary No Yes Via Key Key: O(1) O(1) Best for high performance lookups. SortedDictionary Yes No Via Key Key: O(log n) O(log n) Compromise of Dictionary speed and ordering, uses binary search tree. SortedList Yes Yes Via Key Key: O(log n) O(n) Very similar to SortedDictionary, except tree is implemented in an array, so has faster lookup on preloaded data, but slower loads. List No Yes Via Index Index: O(1) Value: O(n) O(n) Best for smaller lists where direct access required and no ordering. LinkedList No No No Value: O(n) O(1) Best for lists where inserting/deleting in middle is common and no direct access required. HashSet No Yes Via Key Key: O(1) O(1) Unique unordered collection, like a Dictionary except key and value are same object. SortedSet Yes No Via Key Key: O(log n) O(log n) Unique ordered collection, like SortedDictionary except key and value are same object. Stack No Yes Only Top Top: O(1) O(1)* Essentially same as List<T> except only process as LIFO Queue No Yes Only Front Front: O(1) O(1) Essentially same as List<T> except only process as FIFO   The Original Collections: System.Collections namespace The original collection classes are largely considered deprecated by developers and by Microsoft itself. In fact they indicate that for the most part you should always favor the generic or concurrent collections, and only use the original collections when you are dealing with legacy .NET code. Because these collections are out of vogue, let's just briefly mention the original collection and their generic equivalents: ArrayList A dynamic, contiguous collection of objects. Favor the generic collection List<T> instead. Hashtable Associative, unordered collection of key-value pairs of objects. Favor the generic collection Dictionary<TKey,TValue> instead. Queue First-in-first-out (FIFO) collection of objects. Favor the generic collection Queue<T> instead. SortedList Associative, ordered collection of key-value pairs of objects. Favor the generic collection SortedList<T> instead. Stack Last-in-first-out (LIFO) collection of objects. Favor the generic collection Stack<T> instead. In general, the older collections are non-type-safe and in some cases less performant than their generic counterparts. Once again, the only reason you should fall back on these older collections is for backward compatibility with legacy code and libraries only. The Concurrent Collections: System.Collections.Concurrent namespace The concurrent collections are new as of .NET 4.0 and are included in the System.Collections.Concurrent namespace. These collections are optimized for use in situations where multi-threaded read and write access of a collection is desired. The concurrent queue, stack, and dictionary work much as you'd expect. The bag and blocking collection are more unique. Below is the summary of each with a link to a blog post I did on each of them. ConcurrentQueue Thread-safe version of a queue (FIFO). For more information see: C#/.NET Little Wonders: The ConcurrentStack and ConcurrentQueue ConcurrentStack Thread-safe version of a stack (LIFO). For more information see: C#/.NET Little Wonders: The ConcurrentStack and ConcurrentQueue ConcurrentBag Thread-safe unordered collection of objects. Optimized for situations where a thread may be bother reader and writer. For more information see: C#/.NET Little Wonders: The ConcurrentBag and BlockingCollection ConcurrentDictionary Thread-safe version of a dictionary. Optimized for multiple readers (allows multiple readers under same lock). For more information see C#/.NET Little Wonders: The ConcurrentDictionary BlockingCollection Wrapper collection that implement producers & consumers paradigm. Readers can block until items are available to read. Writers can block until space is available to write (if bounded). For more information see C#/.NET Little Wonders: The ConcurrentBag and BlockingCollection Summary The .NET BCL has lots of collections built in to help you store and manipulate collections of data. Understanding how these collections work and knowing in which situations each container is best is one of the key skills necessary to build more performant code. Choosing the wrong collection for the job can make your code much slower or even harder to maintain if you choose one that doesn’t perform as well or otherwise doesn’t exactly fit the situation. Remember to avoid the original collections and stick with the generic collections.  If you need concurrent access, you can use the generic collections if the data is read-only, or consider the concurrent collections for mixed-access if you are running on .NET 4.0 or higher.   Tweet Technorati Tags: C#,.NET,Collecitons,Generic,Concurrent,Dictionary,List,Stack,Queue,SortedList,SortedDictionary,HashSet,SortedSet

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  • Fastest Functional Language

    - by Farouk
    I've recently been delving into functional programming especially Haskell and F#, the prior more so. After some googling around I could not find a benchmark comparison of the more prominent functional languages (Scala,F# etc). I know it's not necessarily fair to some of the languages (Scala comes to mind) given that they are hybrids, but I just wanna know which outperforms which on what operations and overall.

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  • Some non-generic collections

    - by Simon Cooper
    Although the collections classes introduced in .NET 2, 3.5 and 4 cover most scenarios, there are still some .NET 1 collections that don't have generic counterparts. In this post, I'll be examining what they do, why you might use them, and some things you'll need to bear in mind when doing so. BitArray System.Collections.BitArray is conceptually the same as a List<bool>, but whereas List<bool> stores each boolean in a single byte (as that's what the backing bool[] does), BitArray uses a single bit to store each value, and uses various bitmasks to access each bit individually. This means that BitArray is eight times smaller than a List<bool>. Furthermore, BitArray has some useful functions for bitmasks, like And, Xor and Not, and it's not limited to 32 or 64 bits; a BitArray can hold as many bits as you need. However, it's not all roses and kittens. There are some fundamental limitations you have to bear in mind when using BitArray: It's a non-generic collection. The enumerator returns object (a boxed boolean), rather than an unboxed bool. This means that if you do this: foreach (bool b in bitArray) { ... } Every single boolean value will be boxed, then unboxed. And if you do this: foreach (var b in bitArray) { ... } you'll have to manually unbox b on every iteration, as it'll come out of the enumerator an object. Instead, you should manually iterate over the collection using a for loop: for (int i=0; i<bitArray.Length; i++) { bool b = bitArray[i]; ... } Following on from that, if you want to use BitArray in the context of an IEnumerable<bool>, ICollection<bool> or IList<bool>, you'll need to write a wrapper class, or use the Enumerable.Cast<bool> extension method (although Cast would box and unbox every value you get out of it). There is no Add or Remove method. You specify the number of bits you need in the constructor, and that's what you get. You can change the length yourself using the Length property setter though. It doesn't implement IList. Although not really important if you're writing a generic wrapper around it, it is something to bear in mind if you're using it with pre-generic code. However, if you use BitArray carefully, it can provide significant gains over a List<bool> for functionality and efficiency of space. OrderedDictionary System.Collections.Specialized.OrderedDictionary does exactly what you would expect - it's an IDictionary that maintains items in the order they are added. It does this by storing key/value pairs in a Hashtable (to get O(1) key lookup) and an ArrayList (to maintain the order). You can access values by key or index, and insert or remove items at a particular index. The enumerator returns items in index order. However, the Keys and Values properties return ICollection, not IList, as you might expect; CopyTo doesn't maintain the same ordering, as it copies from the backing Hashtable, not ArrayList; and any operations that insert or remove items from the middle of the collection are O(n), just like a normal list. In short; don't use this class. If you need some sort of ordered dictionary, it would be better to write your own generic dictionary combining a Dictionary<TKey, TValue> and List<KeyValuePair<TKey, TValue>> or List<TKey> for your specific situation. ListDictionary and HybridDictionary To look at why you might want to use ListDictionary or HybridDictionary, we need to examine the performance of these dictionaries compared to Hashtable and Dictionary<object, object>. For this test, I added n items to each collection, then randomly accessed n/2 items: So, what's going on here? Well, ListDictionary is implemented as a linked list of key/value pairs; all operations on the dictionary require an O(n) search through the list. However, for small n, the constant factor that big-o notation doesn't measure is much lower than the hashing overhead of Hashtable or Dictionary. HybridDictionary combines a Hashtable and ListDictionary; for small n, it uses a backing ListDictionary, but switches to a Hashtable when it gets to 9 items (you can see the point it switches from a ListDictionary to Hashtable in the graph). Apart from that, it's got very similar performance to Hashtable. So why would you want to use either of these? In short, you wouldn't. Any gain in performance by using ListDictionary over Dictionary<TKey, TValue> would be offset by the generic dictionary not having to cast or box the items you store, something the graphs above don't measure. Only if the performance of the dictionary is vital, the dictionary will hold less than 30 items, and you don't need type safety, would you use ListDictionary over the generic Dictionary. And even then, there's probably more useful performance gains you can make elsewhere.

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  • Seeking questions about creating Microsoft Live Labs Pivot collections

    - by John Conwell
    I've spent the past 3 weeks working a lot with Pivot from Microsoft Live Labs (http://getpivot.com/).  Pivot is a tool that allows you to visually explore data. Its an interesting take on visual data mining. Anyway, I've been writing a lot of code that creates a hierarchy of Pivot collections, where one item in the collection drills down into an entirly new collection. The dev community around Pivot is still very young, so there isnt much tribal knowledge built up yet.  I've spent a lot of time trying to get things to work through trial and error, as well as digging around in Reflector.  But I've finally got a framework built for programatically creating DeepZoom images, Pivot collections, Sparse Images, etc.   If anyone has any questions, or suggestions on a post topic, leave a comment and I'll try and answer your question.

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  • Grafting Scala 2.8 into a Netbeans NBAndroid Project...What steps am I missing?

    - by Michael Kohout
    Hi All; Due to Apple's recent T+C hijinks, I've become interested in developing for Android. Anyways, I'm trying to get a mixed-language Android 2.1 project going in Netbeans 6.8 (with the NBAndroid 0.10 plugin). The two languages being Java and Scala(2.8 head build). To give you a basic idea of what the app does right now, it's just a simple "Hello World" app. To get this to build, I've modified the projects's build.xml file: -- -injars ${scala-library}(!META-INF/MANIFEST.MF,!library.properties) -outjars "${build.classes.dir}/classes.min.jar" -libraryjars "${file.reference.android.jar}" -dontwarn -dontoptimize -dontobfuscate -keep public class * extends android.app.Activity -keep public class scala.xml.include.sax.Main** I've gotten the project so that it'll build, but it errors on startup in my Android Emulator(inside the emulator Android tells me my application has stopped unexpectedly). So my questions are: Does anyone see what I may be doing wrong? And is there any way to get access to the logs that the emulator must create? thanks Mike Kohout

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  • How do Scala parser combinators compare to Haskell's Parsec?

    - by artif
    I have read that Haskell parser combinators (in Parsec) can parse context sensitive grammars. Is this also true for Scala parser combinators? If so, is this what the "into" (aka "") function is for? What are some strengths/weaknesses of Scala's implementation of parser combinators, vs Haskell's? Do they accept the same class of grammars? Is it easier to generate error messages or do other miscellaneous useful things with one or the other? How does packrat parsing (introduced in Scala 2.8) fit into this picture? Is there a webpage or some other resource that shows how different operators/functions/DSL-sugar from one language's implementation maps onto the other's?

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  • How to customize Json serialization using Scala and Play Framework?

    - by Jonas
    I would like to serialize some Scala case classes to Json. E.g my case class looks like: case class Item ( id: Int, name: String, price: BigDecimal, created: java.util.Date) and I would like to serialize it to Json like this: {"id":3, "name": "apple", "price": 8.00, "created": 123424434} so I need a custom serilization for BigDecimal and for Date. Where I want the data in milliseconds since 1 jan 1970. When using Scala and Play Framework, I can return Json using Json(myObject), but how do I customize the serialization? Or is there any recommended Scala library?

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  • How to check whether a String fully matches a Regex in Scala?

    - by mkneissl
    Assume I have a Regex pattern I want to match many Strings to. val Digit = """\d""".r I just want to check whether a given String fully matches the Regex. What is a good and idiomatic way to do this in Scala? I know that I can pattern match on Regexes, but this is syntactically not very pleasing in this case, because I have no groups to extract: scala> "5" match { case Digit() => true case _ => false } res4: Boolean = true Or I could fall back to the underlying Java pattern: scala> Digit.pattern.matcher("5").matches res6: Boolean = true which is not elegant, either. Is there a better solution?

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  • How do I return a String from a for comprehension in Scala?

    - by Vonn
    Scala Newbie alert: basically I'm trying to do something like this: where I pattern match and return a String. scala> def processList(list: List[String], m: String): String={list foreach (x=> m match{ | case "test" => "we got test" | case "test1"=> "we got test1"})} :10: error: type mismatch; found : Unit required: String def processList(list: List[String], m: String): String={list foreach (x= m match{ I know I can set a var and return it after the for comp... but that doesn't seem to be the Scala way.

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  • How does java.util.Collections.contains() perform faster than a linear search?

    - by The111
    I've been fooling around with a bunch of different ways of searching collections, collections of collections, etc. Doing lots of stupid little tests to verify my understanding. Here is one which boggles me (source code further below). In short, I am generating N random integers and adding them to a list. The list is NOT sorted. I then use Collections.contains() to look for a value in the list. I intentionally look for a value that I know won't be there, because I want to ensure that the entire list space is probed. I time this search. I then do another linear search manually, iterating through each element of the list and checking if it matches my target. I also time this search. On average, the second search takes 33% longer than the first one. By my logic, the first search must also be linear, because the list is unsorted. The only possibility I could think of (which I immediately discard) is that Java is making a sorted copy of my list just for the search, but (1) I did not authorize that usage of memory space and (2) I would think that would result in MUCH more significant time savings with such a large N. So if both searches are linear, they should both take the same amount of time. Somehow the Collections class has optimized this search, but I can't figure out how. So... what am I missing? import java.util.*; public class ListSearch { public static void main(String[] args) { int N = 10000000; // number of ints to add to the list int high = 100; // upper limit for random int generation List<Integer> ints; int target = -1; // target will not be found, forces search of entire list space long start; long end; ints = new ArrayList<Integer>(); start = System.currentTimeMillis(); System.out.print("Generating new list... "); for (int i = 0; i < N; i++) { ints.add(((int) (Math.random() * high)) + 1); } end = System.currentTimeMillis(); System.out.println("took " + (end-start) + "ms."); start = System.currentTimeMillis(); System.out.print("Searching list for target (method 1)... "); if (ints.contains(target)) { // nothing } end = System.currentTimeMillis(); System.out.println(" Took " + (end-start) + "ms."); System.out.println(); ints = new ArrayList<Integer>(); start = System.currentTimeMillis(); System.out.print("Generating new list... "); for (int i = 0; i < N; i++) { ints.add(((int) (Math.random() * high)) + 1); } end = System.currentTimeMillis(); System.out.println("took " + (end-start) + "ms."); start = System.currentTimeMillis(); System.out.print("Searching list for target (method 2)... "); for (Integer i : ints) { // nothing } end = System.currentTimeMillis(); System.out.println(" Took " + (end-start) + "ms."); } }

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  • Strange Play Framework 2.2 exceptions after trying to add MySQL / slick

    - by Mike Cialowicz
    I'm working on a Play 2.2 application, and things have gone a bit south on me since I've tried adding my DB layer. Below are my build.sbt dependencies. As you can see I use mysql-connector-java and play-slick: libraryDependencies ++= Seq( jdbc, anorm, cache, "joda-time" % "joda-time" % "2.3", "mysql" % "mysql-connector-java" % "5.1.26", "com.typesafe.play" %% "play-slick" % "0.5.0.8", "com.aetrion.flickr" % "flickrapi" % "1.1" ) My application.conf has some similarly simple DB stuff in it: db.default.url="jdbc:mysql://localhost/myDb" db.default.driver="com.mysql.jdbc.Driver" db.default.user="root" db.default.pass="" This is what it looks like when my Play server starts: [info] play - Listening for HTTP on /0:0:0:0:0:0:0:0:9000 (Server started, use Ctrl+D to stop and go back to the console...) [info] Compiling 1 Scala source to C:\bbq\cats\in\space [info] play - database [default] connected at jdbc:mysql://localhost/myDb [info] play - Application started (Dev) So, it appears that Play can connect to the MySQL DB just fine (I think). However, I get this exception when I make any request to my server: [error] p.nettyException - Exception caught in Netty java.lang.NoSuchMethodError: akka.actor.ActorSystem.dispatcher()Lscala/concurren t/ExecutionContext; at play.core.Invoker$.<init>(Invoker.scala:24) ~[play_2.10.jar:2.2.0] at play.core.Invoker$.<clinit>(Invoker.scala) ~[play_2.10.jar:2.2.0] at play.api.libs.concurrent.Execution$Implicits$.defaultContext$lzycompu te(Execution.scala:7) ~[play_2.10.jar:2.2.0] at play.api.libs.concurrent.Execution$Implicits$.defaultContext(Executio n.scala:6) ~[play_2.10.jar:2.2.0] at play.api.libs.concurrent.Execution$.<init>(Execution.scala:10) ~[play _2.10.jar:2.2.0] at play.api.libs.concurrent.Execution$.<clinit>(Execution.scala) ~[play_ 2.10.jar:2.2.0] The odd thing is that the 2nd request (to the exact same URL, same controller, no changes) comes back with a different error: [error] p.nettyException - Exception caught in Netty java.lang.NoClassDefFoundError: Could not initialize class play.api.libs.concurr ent.Execution$ at play.core.server.netty.PlayDefaultUpstreamHandler.handleAction$1(Play DefaultUpstreamHandler.scala:194) ~[play_2.10.jar:2.2.0] at play.core.server.netty.PlayDefaultUpstreamHandler.messageReceived(Pla yDefaultUpstreamHandler.scala:169) ~[play_2.10.jar:2.2.0] at com.typesafe.netty.http.pipelining.HttpPipeliningHandler.messageRecei ved(HttpPipeliningHandler.java:62) ~[netty-http-pipelining.jar:na] at org.jboss.netty.handler.codec.http.HttpContentDecoder.messageReceived (HttpContentDecoder.java:108) ~[netty-3.6.5.Final.jar:na] at org.jboss.netty.channel.Channels.fireMessageReceived(Channels.java:29 6) ~[netty-3.6.5.Final.jar:na] at org.jboss.netty.handler.codec.frame.FrameDecoder.unfoldAndFireMessage Received(FrameDecoder.java:459) ~[netty-3.6.5.Final.jar:na] The URL / controller that I'm requesting just renders a static web page and doesn't do anything of any significance. It was working just fine before I started adding my DB layer. I'm rather stuck. Any help would be greatly appreciated, thanks. I'm using Scala 2.10.2, Play 2.2.0, and MySQL Server 5.6.14.0 (community edition).

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  • scalacheck/scalatest not found: how to add it in sbt/scala?

    - by Pavel Reich
    I've installed typesafe-stack from http://typesafe.com/stack/download on my ubuntu12, than I created a play project (g8 typesafehub/play-scala) and now I want to add scalatest or scalacheck to my project. So my_app/project/plugins.sbt has the following lines: // The Typesafe repository resolvers += "Typesafe repository" at "http://repo.typesafe.com/typesafe/releases/" // Use the Play sbt plugin for Play projects addSbtPlugin("play" % "sbt-plugin" % "2.0.1") Then I added scalatest using addSbtPlugin: addSbtPlugin("org.scalatest" %% "scalatest" % "2.0.M1" % "test") and now it fails with the following message when I run 'sbt test' [info] Resolving org.scalatest#scalatest;2.0.M1 ... [warn] module not found: org.scalatest#scalatest;2.0.M1 [warn] ==== typesafe-ivy-releases: tried [warn] http://repo.typesafe.com/typesafe/ivy-releases/org.scalatest/scalatest/scala_2.9.1/sbt_0.11.3/2.0.M1/ivys/ivy.xml [warn] ==== local: tried [warn] ~/.ivy2/local/org.scalatest/scalatest/scala_2.9.1/sbt_0.11.3/2.0.M1/ivys/ivy.xml [warn] ==== Typesafe repository: tried [warn] http://repo.typesafe.com/typesafe/releases/org/scalatest/scalatest_2.9.1_0.11.3/2.0.M1/scalatest-2.0.M1.pom [warn] ==== typesafe-ivy-releases: tried [warn] http://repo.typesafe.com/typesafe/ivy- releases/org.scalatest/scalatest/scala_2.9.1/sbt_0.11.3/2.0.M1/ivys/ivy.xml [warn] ==== public: tried [warn] http://repo1.maven.org/maven2/org/scalatest/scalatest_2.9.1_0.11.3/2.0.M1/scalatest-2.0.M1.pom What I don't understand: why does it use this http://repo.typesafe.com/typesafe/releases/org/scalatest/scalatest_2.9.1_0.11.3/2.0.M1/scalatest-2.0.M1.pom URL instead of the real one http://repo.typesafe.com/typesafe/releases/org/scalatest/scalatest_2.9.1/2.0.M1/scalatest_2.9.1-2.0.M1.pom? Quite the same problem I have with scalacheck: it also tries to download using sbt-version specific artifactId whereas the repository has only scala-version specific. What am I doing wrong? I understand there must be a switch in sbt somewhere, not to use sbt-version as part of the artifact URL? I also tried using this in my plugins.sbt libraryDependencies += "org.scalatest" %% "scalatest" % "2.0.M1" % "test" but looks like it is completely ignored by sbt and scalatest.jar hasn't appeared in the classpath: my_app/test/AppTest.scala:1: object scalatest is not a member of package org [error] import org.scalatest.FunSuite because the output of sbt clean && sbt test has lots of Resolving org.easytesting#fest-util;1.1.6 or just another library, but nothing about scalatest. I use scala 2.9.1 and sbt 0.11.3, trying to use scalatest 2.0.M1 and 1.8; scalacheck: resolvers ++= Seq( "snapshots" at "http://oss.sonatype.org/content/repositories/snapshots", "releases" at "http://oss.sonatype.org/content/repositories/releases" ) libraryDependencies ++= Seq( "org.scalacheck" %% "scalacheck" % "1.9" % "test" ) With the same outcome, i.e. it uses the sbtVersion specific POM URL, which doesn't exist. What am I doing wrong? Thanks.

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  • Are there any tools for performing static analysis of Scala code?

    - by Roman Kagan
    Are there any tools for performing static analysis of Scala code, similar to FindBugs and PMD for Java or Splint for C/C++? I know that FindBugs works on the bytecode produced by compiling Java, so I'm curious as to how it would work on Scala. Google searches (as of 27 October 2009) reveal very little. Google searches (as of 01 February 2010) reveal this question.

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  • Has anyone got the vim taglist plugin working with Scala?

    - by Eric Hauser
    I'm having trouble getting the taglist plugin working properly with Scala. I've installed the plugin and ctags and verified that it works properly with Java and C++. I then followed the instructions on this page (minus the Lift specific instructuions), but was nothing shows up in the taglist window when I open it while editing a Scala file. Has anyone got this working and what are the proper steps? Thanks.

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  • How to store date into Mysql database with play framework in scala?

    - by Rahul Kulhari
    I am working with play framework with scala and what am i doing : login page to login into web app sign up page to register into web app after login i want to store all databases values to user what i want to do: when user register for web app then i want to store user values into database with current time and date but my form is giving error. error: List(FormError(dates,error.required,List())),None) controllers/Application.scala object Application extends Controller { val ta:Form[Keyword] = Form( mapping( "id" -> ignored(NotAssigned:Pk[Long]), "word" -> nonEmptyText, "blog" -> nonEmptyText, "cat" -> nonEmptyText, "score"-> of[Long], "summaryId"-> nonEmptyText, "dates" -> date("yyyy-MM-dd HH:mm:ss") )(Keyword.apply)(Keyword.unapply) ) def index = Action { Ok(html.index(ta)); } def newTask= Action { implicit request => ta.bindFromRequest.fold( errors => {println(errors) BadRequest(html.index(errors))}, keywo => { Keyword.create(keywo) Ok(views.html.data(Keyword.all())) } ) } models/keyword.scala case class Keyword(id: Pk[Long],word: String,blog: String,cat: String,score: Long, summaryId: String,dates: Date ) object Keyword { val keyw = { get[Pk[Long]]("keyword.id") ~ get[String]("keyword.word")~ get[String]("keyword.blog")~ get[String]("keyword.cat")~ get[Long]("keyword.score") ~ get[String]("keyword.summaryId")~ get[Date]("keyword.dates") map { case id~blog~cat~word~score~summaryId~dates => Keyword(id,word,blog,cat,score, summaryId,dates) } } def all(): List[Keyword] = DB.withConnection { implicit c => SQL("select * from keyword").as(Keyword.keyw *) } def create(key: Keyword){DB.withConnection{implicit c=> SQL("insert into keyword values({word},{blog}, {cat}, {score},{summaryId},{dates})").on('word-> key.word,'blog->key.blog, 'cat -> key.cat, 'score-> key.score, 'summaryId -> key.summaryId, 'dates->new Date()).executeUpdate } } views/index.scala.html @(taskForm: Form[Keyword]) @import helper._ @main("Todo list") { @form(routes.Application.newTask) { @inputText(taskForm("word")) @inputText(taskForm("blog")) @inputText(taskForm("cat")) @inputText(taskForm("score")) @inputText(taskForm("summaryId")) <input type="submit"> <a href="">Go Back</a> } } please give me some idea to store date into mysql databse and date is not a field of form

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  • How do I provide basic configuration for a Scala application?

    - by Dave
    I am working on a small GUI application written in Scala. There are a few settings that the user will set in the GUI and I want them to persist between program executions. Basically I want a scala.collections.mutable.Map that automatically persists to a file when modified. This seems like it must be a common problem, but I have been unable to find a lightweight solution. How is this problem typically solved?

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