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  • Find messages from certain key till certain key while being able to remove stale keys.

    - by Alfred
    My problem Let's say I add messages to some sort of datastructure: 1. "dude" 2. "where" 3. "is" 4. "my" 5. "car" Asking for messages from index[4,5] should return: "my","car". Next let's assume that after a while I would like to purge old messages because they aren't useful anymore and I want to save memory. Let's say at time x messages[1-3] became stale. I assume that it would be most efficient to just do the deletion once every x seconds. Next my datastructure should contain: 4. "my" 5. "car" My solution? I was thinking of using a concurrentskiplistset or concurrentskiplist map. Also I was thinking of deleting the old messages from inside a newSingleThreadScheduledExecutor. I would like to know how you would implement(efficiently/thread-safe) this or maybe use a library?

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  • SharePoint 2010 – Central Admin tooling to create host header site collections

    - by eJugnoo
    Just like SharePoint 2007, you can create host-header based site collections in SharePoint 2010 as well. It means, that you do not necessarily need to create a site-collection under a managed path like /sites/, you can create multiple root-level site collections on same web-application/port by using host-header site collections. All you need to do is point your domain or sub-domain to your web-application and create a matching site-collection that you want. But, just like in 2007, it is something that you do by using STSADM, and is not available on Central Admin UI in 2010 as well. Yeah, though you can now also use PowerShell to create one: C:\PS>$w = Get-SPWebApplication http://sitename   C:\PS>New-SPSite http://www.contoso.com -OwnerAlias "DOMAIN\jdoe" -HostHeaderWebApplication $w -Title "Contoso" -Template "STS#0"   This example creates a host header site collection. Because the template is provided, the root Web of this site collection will be created. .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } I’ve been playing with WCM in SharePoint 2010 more and more, and for that I preferred creating hosts file entries for desired domains and create site-collections by those headers – in my dev environment. I used PowerShell initially, but then got interested to build my own UI on Central Admin instead. Developed with Visual Studio 2010 So I used new Visual Studio 2010 tooling to create an empty SharePoint 2010 project. Added an application page (there is no option to add _Admin page item in VS 2010 RC), that got created in Layouts “mapped” folder. Created a new Admin mapped folder for 14-“hive”, and moved my new page there instead. Yes, I didn’t change the base class for page, its just that it runs under _admin, but it is indeed a LayoutsPageBase inherited page. To introduce a action-link in Central Admin console, I created following element: 1: <Elements xmlns="http://schemas.microsoft.com/sharepoint/"> 2: <CustomAction 3: Id="CreateSiteByHeader" 4: Location="Microsoft.SharePoint.Administration.Applications" 5: Title="Create site collections by host header" 6: GroupId="SiteCollections" 7: Sequence="15" 8: RequiredAdmin="Delegated" 9: Description="Create a new top-level web site, by host header" > 10: <UrlAction Url="/_admin/OfficeToolbox/CreateSiteByHeader.aspx" /> 11: </CustomAction> 12: </Elements> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Used Reflector to understand any special code behind createpage.aspx, and created a new for our purpose – CreateSiteByHeader.aspx. From there I quickly created a similar code behind, without all the fancy of Farm Config Wizard handling and dealt with alternate implementations of sealed classes! Goal was to create a professional looking and OOB-type experience. I also added Regex validation to ensure user types a valid domain name as header value. Below is the result…   Release @ Codeplex I’ve released to WSP on OfficeToolbox @ Codeplex, and you can download from here. Hope you find it useful… -- Sharad

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  • Visualising data a different way with Pivot collections

    - by Rob Farley
    Roger’s been doing a great job extending PivotViewer recently, and you can find the list of LobsterPot pivots at http://pivot.lobsterpot.com.au Many months back, the TED Talk that Gary Flake did about Pivot caught my imagination, and I did some research into it. At the time, most of what we did with Pivot was geared towards what we could do for clients, including making Pivot collections based on students at a school, and using it to browse PDF invoices by their various properties. We had actual commercial work based on Pivot collections back then, and it was all kinds of fun. Later, we made some collections for events that were happening, and even got featured in the TechEd Australia keynote. But I’m getting ahead of myself... let me explain the concept. A Pivot collection is an XML file (with .cxml extension) which lists Items, each linking to an image that’s stored in a Deep Zoom format (this means that it contains tiles like Bing Maps, so that the browser can request only the ones of interest according to the zoom level). This collection can be shown in a Silverlight application that uses the PivotViewer control, or in the Pivot Browser that’s available from getpivot.com. Filtering and sorting the items according to their facets (attributes, such as size, age, category, etc), the PivotViewer rearranges the way that these are shown in a very dynamic way. To quote Gary Flake, this lets us “see patterns which are otherwise hidden”. This browsing mechanism is very suited to a number of different methods, because it’s just that – browsing. It’s not searching, it’s more akin to window-shopping than doing an internet search. When we decided to put something together for the conferences such as TechEd Australia 2010 and the PASS Summit 2010, we did some screen-scraping to provide a different view of data that was already available online. Nick Hodge and Michael Kordahi from Microsoft liked the idea a lot, and after a bit of tweaking, we produced one that Michael used in the TechEd Australia keynote to show the variety of talks on offer. It’s interesting to see a pattern in this data: The Office track has the most sessions, but if the Interactive Sessions and Instructor-Led Labs are removed, it drops down to only the sixth most popular track, with Cloud Computing taking over. This is something which just isn’t obvious when you look an ordinary search tool. You get a much better feel for the data when moving around it like this. The more observant amongst you will have noticed some difference in the collection that Michael is demonstrating in the picture above with the screenshots I’ve shown. That’s because it’s been extended some more. At the SQLBits conference in the UK this year, I had some interesting discussions with the guys from Xpert360, particularly Phil Carter, who I’d met in 2009 at an earlier SQLBits conference. They had got around to producing a Pivot collection based on the SQLBits data, which we had been planning to do but ran out of time. We discussed some of ways that Pivot could be used, including the ways that my old friend Howard Dierking had extended it for the MSDN Magazine. I’m not suggesting I influenced Xpert360 at all, but they certainly inspired us with some of their posts on the matter So with LobsterPot guys David Gardiner and Roger Noble both having dabbled in Pivot collections (and Dave doing some for clients), I set Roger to work on extending it some more. He’s used various events and so on to be able to make an environment that allows us to do quick deployment of new collections, as well as showing the data in a grid view which behaves as if it were simply a third view of the data (the other two being the array of images and the ‘histogram’ view). I see PivotViewer as being a significant step in data visualisation – so much so that I feature it when I deliver talks on Spatial Data Visualisation methods. Any time when there is information that can be conveyed through an image, you have to ask yourself how best to show that image, and whether that image is the focal point. For Spatial data, the image is most often a map, and the map becomes the central mode for navigation. I show Pivot with postcode areas, since I can browse the postcodes based on their data, and many of the images are recognisable (to locals of South Australia). Naturally, the images could link through to the map itself, and so on, but generally people think of Spatial data in terms of navigating a map, which doesn’t always gel with the information you’re trying to extract. Roger’s even looking into ways to hook PivotViewer into the Bing Maps API, in a similar way to the Deep Earth project, displaying different levels of map detail according to how ‘zoomed in’ the images are. Some of the work that Dave did with one of the schools was generating the Deep Zoom tiles “on the fly”, based on images stored in a database, and Roger has produced a collection which uses images from flickr, that lets you move from one search term to another. Pulling the images down from flickr.com isn’t particularly ideal from a performance aspect, and flickr doesn’t store images in a small-enough format to really lend itself to this use, but you might agree that it’s an interesting concept which compares nicely to using Maps. I’m looking forward to future versions of the PivotViewer control, and hope they provide many more events that can be used, and even more hooks into it. Naturally, LobsterPot could help provide your business with a PivotViewer experience, but you can probably do a lot of it yourself too. There’s a thorough guide at getpivot.com, which is how we got into it. For some examples of what we’ve done, have a look at http://pivot.lobsterpot.com.au. I’d like to see PivotViewer really catch on a data visualisation tool.

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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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  • Webcast Replay Available: Performance Tuning E-Business Suite Concurrent Manager (Performance Series Part 2 of 3)

    - by BillSawyer
    I am pleased to release the replay and presentation for the latest ATG Live Webcast: Performance Tuning E-Business Suite Concurrent Manager (Performance Series Part 2 of 3) (Presentation)Andy Tremayne, Senior Architect, Applications Performance, and co-author of Oracle Applications Performance Tuning Handbook from Oracle Press, and Uday Moogala, Senior Principal Engineer, Applications Performance discussed two major components of E-Business Suite performance tuning:  concurrent management and tracing. They dispel some myths surrounding these topics, and shared with you the recommended best practices that you can use on your own E-Business Suite instance.Finding other recorded ATG webcastsThe catalog of ATG Live Webcast replays, presentations, and all ATG training materials is available in this blog's Webcasts and Training section.

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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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  • 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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  • 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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  • Caching strategies for entities and collections

    - by Rob West
    We currently have an application framework in which we automatically cache both entities and collections of entities at the business layer (using .NET cache). So the method GetWidget(int id) checks the cache using a key GetWidget_Id_{0} before hitting the database, and the method GetWidgetsByStatusId(int statusId) checks the cache using GetWidgets_Collections_ByStatusId_{0}. If the objects are not in the cache they are retrieved from the database and added to the cache. This approach is obviously quick for read scenarios, and as a blanket approach is quick for us to implement, but requires large numbers of cache keys to be purged when CRUD operations are carried out on entities. Obviously as additional methods are added this impacts performance and the benefits of caching diminish. I'm interested in alternative approaches to handling caching of collections. I know that NHibernate caches a list of the identifiers in the collection rather than the actual entities. Is this an approach other people have tried - what are the pros and cons? In particular I am looking for options that optimise performance and can be implemented automatically through boilerplate generated code (we have our own code generation tool). I know some people will say that caching needs to be done by hand each time to meet the needs of the specific situation but I am looking for something that will get us most of the way automatically.

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  • Convert collections of enums to collection of strings and vice versa

    - by Michael Freidgeim
    Recently I needed to convert collections of  strings, that represent enum names, to collection of enums, and opposite,  to convert collections of   enums  to collection of  strings. I didn’t find standard LINQ extensions.However, in our big collection of helper extensions I found what I needed - just with different names: /// <summary> /// Safe conversion, ignore any unexpected strings/// Consider to name as Convert extension /// </summary> /// <typeparam name="EnumType"></typeparam> /// <param name="stringsList"></param> /// <returns></returns> public static List<EnumType> StringsListAsEnumList<EnumType>(this List<string> stringsList) where EnumType : struct, IComparable, IConvertible, IFormattable     { List<EnumType> enumsList = new List<EnumType>(); foreach (string sProvider in stringsList)     {     EnumType provider;     if (EnumHelper.TryParse<EnumType>(sProvider, out provider))     {     enumsList.Add(provider);     }     }     return enumsList;     }/// <summary> /// Convert each element of collection to string /// </summary> /// <typeparam name="T"></typeparam> /// <param name="objects"></param> /// <returns></returns> public static IEnumerable<string> ToStrings<T>(this IEnumerable<T> objects) {//from http://www.c-sharpcorner.com/Blogs/997/using-linq-to-convert-an-array-from-one-type-to-another.aspx return objects.Select(en => en.ToString()); }

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  • Concurrent modification during backup: rsync vs dump vs tar vs ?

    - by pehrs
    I have a Linux log server where multiple applications write data. Data is written in bursts, and in a lot of different files. I need to make a backup of this mess, preferably preserving as much coherence between the file versions as possible and avoiding getting truncated files. Total amount of data on the server is about 100Gb. What I really would want (but can't) is to shut-down, backup the system cold and then start it up again. What kind of guarantees against concurrent modification does the various backup tools give? When do they "freeze" the file versions? I am looking at rsync, dump and tar at the moment, but I am open for other (open source) alternatives. Changing the application or blocking writing for backups is sadly not an option. System is not running LVM (yet), but I have considered that for rebuilding the system and then snapshots.

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  • NUMA-aware constructs for java.util.concurrent

    - by Dave
    The constructs in the java.util.concurrent JSR-166 "JUC" concurrency library are currently NUMA-oblivious. That's because we currently don't have the topology discovery infrastructure and underpinnings in place that would allow and enable NUMA-awareness. But some quick throw-away prototypes show that it's possible to write NUMA-aware library code. I happened to use JUC Exchanger as a research vehicle. Another interesting idea is to adapt fork-join work-stealing to favor stealing from queues associated with 'nearby' threads.

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  • proper concurrent users estimation case studies

    - by golemwashere
    I've been asked to size a web architecture for an excessive number of concurrent users ( hundreds of thousands ). I'm having a hard time convincing these people that unless you are in the top 5 of your country websites it's quite hard to hit those numbers. Can anyone provide some real world case studies providing stats for total / concurrent users explaining what is the usual ratio between total vs concurrent?

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  • Concurrent Affairs

    - by Tony Davis
    I once wrote an editorial, multi-core mania, on the conundrum of ever-increasing numbers of processor cores, but without the concurrent programming techniques to get anywhere near exploiting their performance potential. I came to the.controversial.conclusion that, while the problem loomed for all procedural languages, it was not a big issue for the vast majority of programmers. Two years later, I still think most programmers don't concern themselves overly with this issue, but I do think that's a bigger problem than I originally implied. Firstly, is the performance boost from writing code that can fully exploit all available cores worth the cost of the additional programming complexity? Right now, with quad-core processors that, at best, can make our programs four times faster, the answer is still no for many applications. But what happens in a few years, as the number of cores grows to 100 or even 1000? At this point, it becomes very hard to ignore the potential gains from exploiting concurrency. Possibly, I was optimistic to assume that, by the time we have 100-core processors, and most applications really needed to exploit them, some technology would be around to allow us to do so with relative ease. The ideal solution would be one that allows programmers to forget about the problem, in much the same way that garbage collection removed the need to worry too much about memory allocation. From all I can find on the topic, though, there is only a remote likelihood that we'll ever have a compiler that takes a program written in a single-threaded style and "auto-magically" converts it into an efficient, correct, multi-threaded program. At the same time, it seems clear that what is currently the most common solution, multi-threaded programming with shared memory, is unsustainable. As soon as a piece of state can be changed by a different thread of execution, the potential number of execution paths through your program grows exponentially with the number of threads. If you have two threads, each executing n instructions, then there are 2^n possible "interleavings" of those instructions. Of course, many of those interleavings will have identical behavior, but several won't. Not only does this make understanding how a program works an order of magnitude harder, but it will also result in irreproducible, non-deterministic, bugs. And of course, the problem will be many times worse when you have a hundred or a thousand threads. So what is the answer? All of the possible alternatives require a change in the way we write programs and, currently, seem to be plagued by performance issues. Software transactional memory (STM) applies the ideas of database transactions, and optimistic concurrency control, to memory. However, working out how to break down your program into sufficiently small transactions, so as to avoid contention issues, isn't easy. Another approach is concurrency with actors, where instead of having threads share memory, each thread runs in complete isolation, and communicates with others by passing messages. It simplifies concurrent programs but still has performance issues, if the threads need to operate on the same large piece of data. There are doubtless other possible solutions that I haven't mentioned, and I would love to know to what extent you, as a developer, are considering the problem of multi-core concurrency, what solution you currently favor, and why. Cheers, Tony.

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  • "Microsoft ne défend pas assez les Droits de l'Homme", Google n'apprécie pas que son concurrent rest

    "Microsoft ne défend pas assez les Droits de l'Homme", Google n'apprécie pas que son concurrent reste en Chine La morale businesso-américaine commence à s'intéresser au cas de la Chine. Suite à l'altercation musclée entre Google et le régime en place à Pékin, d'autres entreprises se mettent à considérer l'idée de quitter le pays du riz. La politique chinoise est montrée du doigt dans les discussions mondaines entre les dirigeants des plus grands groupes américains. Fort de son nouveau statut de justicier, Sergey Brin (l'un des co-fondateurs de Google), s'en est pris à Microsoft, accusant la firme de ne pas assez défendre les droits de l'Homme et la liberté d'expression. « J'es...

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  • How do Tortoise svn handle concurrent file updation

    - by sabithpocker
    I don't know much about Tortoise SVN, but have been using it for a while :) I understand that it is capable of managing concurrent users on same file, but how does it do that? I am working on a file that another user is using concurrently and he committed couple of times before me, Now my files doesnt have the changes he made. Every time i end up in such a situation I gets a conflict and I am stuck. So is there something else I should do instead of just committing and causing conflict. Is it safe to do a update first and then commit ? Will I lose my local changes in this case? Please dont beat me up if this is somthing basic, A link to some tutorial will be useful in that case :)

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  • NoSQL : JSON, indexation distribuée et géoréplication débarquent dans Couchbase, le concurrent de MongoDB

    Base de données NoSQL : documents JSON, indexation distribuée et géoréplication débarquent dans Couchbase Le concurrent de MongoDB Couchbase Server, le système de gestion de bases de données NoSQL, vient de subir une mise à jour assez importante. La version 2.0 de Couchbase introduit un modèle de stockage de documents et un magasin clé-valeur (key-value), permettant à l'outil de faire un grand pas dans le support du Big Data (gros volumes de données). Pour rappel, CouchBase est un projet initialement basé sur le système noSQL Apache CouchDB, à la différence que le code Erlang de CouchDB a été entièrement réécrit en C++, avec des ajustements et ajouts en tirant profit du système de ...

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  • Les Google Apps veulent se positionner en concurrent de Sharepoint, Gmail passe les 425 millions d'utilisateurs

    Les Google Apps veulent se positionner en concurrent de Sharepoint Gmail passe les 425 millions d'utilisateurs Parmi les nombreux chiffres donnés sur ses différents produits, Google en a mis deux particulièrement en avant : ceux de ses Web Apps et de sa messagerie. Lancée en 2004, la messagerie Gmail possède aujourd'hui 425 millions d'utilisateurs. Un bon résultat. Surtout si on lui ajoute 5 millions de client "business" qui utilisent les Google Apps (en résumé Gmail + Google Docs) comme par exemple la compagnie aérienne européenne KLM. Mais cette annonce a surtout été l'occasion pour Sundar Pichai, vice-président de Google, de s'attaquer à son conc...

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  • Programmatically use a server as the Build Server for multiple Project Collections

    Important: With this post you create an unsupported scenario by Microsoft. It will break your support for this server with Microsoft. So handle with care. I am the administrator an a TFS environment with a lot of Project Collections. In the supported configuration of Microsoft 2010 you need one Build Controller per Project Collection, and it is not supported to have multiple Build Controllers installed. Jim Lamb created a post how you can modify your system to change this behaviour. But since I have so many Project Collections, I automated this with the API of TFS. When you install a new build server via the UI, you do the following steps Register the build service (with this you hook the windows server into the build server environment) Add a new build controller Add a new build agent So in pseudo code, the code would look like foreach (projectCollection in GetAllProjectCollections) {       CreateNewWindowsService();       RegisterService();       AddNewController();       AddNewAgent(); } The following code fragements show you the most important parts of the method implementations. Attached is the full project. CreateNewWindowsService We create a new windows service with the SC command via the Diagnostics.Process class:             var pi = new ProcessStartInfo("sc.exe")                         {                             Arguments =                                 string.Format(                                     "create \"{0}\" start= auto binpath= \"C:\\Program Files\\Microsoft Team Foundation Server 2010\\Tools\\TfsBuildServiceHost.exe              /NamedInstance:{0}\" DisplayName= \"Visual Studio Team Foundation Build Service Host ({1})\"",                                     serviceHostName, tpcName)                         };            Process.Start(pi);             pi.Arguments = string.Format("failure {0} reset= 86400 actions= restart/60000", serviceHostName);            Process.Start(pi); RegisterService The trick in this method is that we set the NamedInstance static property. This property is Internal, so we need to set it through reflection. To get information on these you need nice Microsoft friends and the .Net reflector .             // Indicate which build service host instance we are using            typeof(BuildServiceHostUtilities).Assembly.GetType("Microsoft.TeamFoundation.Build.Config.BuildServiceHostProcess").InvokeMember("NamedInstance",              System.Reflection.BindingFlags.NonPublic | System.Reflection.BindingFlags.SetProperty | System.Reflection.BindingFlags.Static, null, null, new object[] { serviceName });             // Create the build service host            serviceHost = buildServer.CreateBuildServiceHost(serviceName, endPoint);            serviceHost.Save();             // Register the build service host            BuildServiceHostUtilities.Register(serviceHost, user, password); AddNewController and AddNewAgent Once you have the BuildServerHost, the rest is pretty straightforward. There are methods on the BuildServerHost to modify the controllers and the agents                 controller = serviceHost.CreateBuildController(controllerName);                 agent = controller.ServiceHost.CreateBuildAgent(agentName, buildDirectory, controller);                controller.AddBuildAgent(agent); You have now seen the highlights of the application. If you need it and want to have sample information when you work in this area, download the app TFS2010_RegisterBuildServerToTPCs

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  • Massive Google Street View Update: 250,000 Miles of Roadways, New Special Collections, and More

    - by Jason Fitzpatrick
    If you like tooling around in Google Street View to check out attractions near and far, you just got a whole lot more to look at. Street View’s new update adds in 250,000 miles of roads, increased coverage in over a dozen countries, and a whole pile of new special collections. From Russia to Taiwan to Canada, there’s thousands of new places and tens of thousands of new roads to explore. Hit up the link below to read the full announcement at the Google Maps blog. Making Google Maps More Comprehensive with Ciggest Street View Update Ever [Google Maps] HTG Explains: What is the Windows Page File and Should You Disable It? How To Get a Better Wireless Signal and Reduce Wireless Network Interference How To Troubleshoot Internet Connection Problems

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  • PowerShell One-Liners: Collections, Hashtables, Arrays and Strings

    The way to learn PowerShell is to browse and nibble, rather than to sit down to a formal five-course meal. In his continuing series on PowerShell one-liners, Michael Sorens provides Fast Food for busy professionals who want results quickly and aren't too faddy. Part 3 has as its tasty confections - Collections, Hashtables, arrays and strings. "A real time saver" Andy Doyle, Head of IT ServicesAndy and his team saved time by automating backup and restores with SQL Backup Pro. Find out how much time you could save. Download a free trial now.

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