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• Uniquing with Existing Core Data Entities

  - by warrenm

  I'm using Core Data to store a lot (1000s) of items. A pair of properties on each item are used to determine uniqueness, so when a new item comes in, I compare it against the existing items before inserting it. Since the incoming data is in the form of an RSS feed, there are often many duplicates, and the cost of the uniquing step is O(N^2), which has become significant. Right now, I create a set of existing items before iterating over the list of (possible) new items. My theory is that on the first iteration, all the items will be faulted in, and assuming we aren't pressed for memory, most of those items will remain resident over the course of the iteration. I see my options thusly: Use string comparison for uniquing, iterating over all "new" items and comparing to all existing items (Current approach) Use a predicate to filter the set of existing items against the properties of the "new" items. Use a predicate with Core Data to determine uniqueness of each "new" item (without retrieving the set of existing items). Is option 3 likely to be faster than my current approach? Do you know of a better way?

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• WCF data services - Limiting related objects returned based on critera

  - by Mike Morley

  I have an object graph consisting of a base employee object, and a set of related message objects. I am able to return the employee objects based on search criteria on the employee properties (eg team) etc. However, if I expand on the messages, I get the full collection of messages back. I would like to be able to either take the top n messages (i.e. restrict to 10 most recent) or ideally use a date range on the message objects to limit how many are brought back. So far I have not been able to figure out a way of doing this: I get an error if I attempt to filter on properties on the message (&$filter=employee/message/StartDate gives an error "No property 'StartDate' exists in type 'System.Data.Objects.DataClasses.EntityCollection`1). Attempting to use Top on the message related object doesn't work either. I have also tried using a WebGet extension that takes a string list of employee IDs. That works until the list gets too long, and then fails due to the URL getting too long (it might be possible to setup a paging mechanism on this approach)... Unfortunately the UI control I am using requires the data to be in a fairly specific hierarchical shape, so I can't easily come at this from starting on the message side and working backwards. Outside of making multiple calls does anyone know of a method to accomplish this with wcf data services? Thanks! M.

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• Multidimensional data structure?

  - by Austin Truong

  I need a multidimensional data structure with a row and a column. Must be able to insert elements any location in the data structure. Example: {A , B} I want to insert C in between A and B. {A, C, B}. Dynamic: I do not know the size of the data structure. Another example: I know the [row][col] of where I want to insert the element. EX. insert("A", 1, 5), where A is the element to be inserted, 1 is the row, 5 is the column. EDIT I want to be able to insert like this. static void Main(string[] args) { Program p = new Program(); List<string> list = new List<string>(); list.Insert(1, "HELLO"); list.Insert(5, "RAWR"); for (int i = 0; i < list.Count; i++) { Console.WriteLine(list[i]); } Console.ReadKey(); } And of course this crashes with an out of bounds error. So in a sense I will have a user who will choose which ROW and COL to insert the element to.

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• Compact data structure for storing a large set of integral values

  - by Odrade

  I'm working on an application that needs to pass around large sets of Int32 values. The sets are expected to contain ~1,000,000-50,000,000 items, where each item is a database key in the range 0-50,000,000. I expect distribution of ids in any given set to be effectively random over this range. The operations I need on the set are dirt simple: Add a new value Iterate over all of the values. There is a serious concern about the memory usage of these sets, so I'm looking for a data structure that can store the ids more efficiently than a simple List<int>or HashSet<int>. I've looked at BitArray, but that can be wasteful depending on how sparse the ids are. I've also considered a bitwise trie, but I'm unsure how to calculate the space efficiency of that solution for the expected data. A Bloom Filter would be great, if only I could tolerate the false negatives. I would appreciate any suggestions of data structures suitable for this purpose. I'm interested in both out-of-the-box and custom solutions. EDIT: To answer your questions: No, the items don't need to be sorted By "pass around" I mean both pass between methods and serialize and send over the wire. I clearly should have mentioned this. There could be a decent number of these sets in memory at once (~100).

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• Display data FROM Sheet1 on Sheet2 based on conditional value

  - by Shawn

  Imagine a worksheet with 30 pieces of information, such as: A1= Start Date A2 = End Date A3 = Resource Name A4 = Cost .... A30 = Whatever B1 = 1/1/2010 B2 = 2/15/2010 B3 = Joe Smith B4 = $10,000.00 ... B30 = Blah Blah Now imagine a third column, C. The purpose of the third column is to determine WHICH report that row of data needs to appear in. C1 = Report 1 C2 = Report 1 and Report 2 C3 = Report 4 and Report 7 C4 = Report 1 and Report 5 ... C30 = Report 2 Each report is on Sheets 2, 3, 4, 5 and so on (depending on how many I decide to create). As you can see form my example above, some data may need to appear in multiple reports. For example, the data in Row 3 (Resource Name: Joe Smith) needs to appear in Report 4 and Report 7. That is to say, it needs to DYNAMICALLY appear on two additional worksheets. If I change the values in column C, then the reports need to update automatically. How can I create the worksheets which will serve as the reports such that they only diaplay the rows which have been "flagged" to be displayed in that report? Thanks!

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• Python, web log data mining for frequent patterns

  - by descent

  Hello! I need to develop a tool for web log data mining. Having many sequences of urls, requested in a particular user session (retrieved from web-application logs), I need to figure out the patterns of usage and groups (clusters) of users of the website. I am new to Data Mining, and now examining Google a lot. Found some useful info, i.e. querying Frequent Pattern Mining in Web Log Data seems to point to almost exactly similar studies. So my questions are: Are there any python-based tools that do what I need or at least smth similar? Can Orange toolkit be of any help? Can reading the book Programming Collective Intelligence be of any help? What to Google for, what to read, which relatively simple algorithms to use best? I am very limited in time (to around a week), so any help would be extremely precious. What I need is to point me into the right direction and the advice of how to accomplish the task in the shortest time. Thanks in advance!

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• Data Integration Solution?

  - by Shlomo

  At my company we have a number of data feeds and processing that run on any given day. The number of feeds and processing steps is starting to out-number the ability to manage it ad-hoc as it is managed currently. Is there a good solution that helps with logging and managing/scheduling dependencies? For example: A: When file x is FTP dropped into directory D1, kick off processing step B B: Load flat file into DB1 C: When file y is FTP dropped into directory D2, kick off processing Step D D: Load flat file into DB11 E: When B and D are done, churn through the data, and load new data into DB111. F: When Step E is done, launch application process P G: etc... I want those steps to run at the appropriate times, not to mention if B fails, there's no reason to run steps E & F, but I could still run C & D. When I re-run B successfully, it should trigger just E & F to re-run, not C & D. We're a .NET/C#/Sql Server shop, and I'm already familiar with SSIS. Is that really the best there is? That manages steps well, but not external dependencies, or logging. Open source (.NET) preferred, but not required.

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• Save many-to-one relationship from JSON into Core Data

  - by Snow Crash

  I'm wanting to save a Many-to-one relationship parsed from JSON into Core Data. The code that parses the JSON and does the insert into Core Data looks like this: for (NSDictionary *thisRecipe in recipes) { Recipe *recipe = [NSEntityDescription insertNewObjectForEntityForName:@"Recipe" inManagedObjectContext:insertionContext]; recipe.title = [thisRecipe objectForKey:@"Title"]; NSDictionary *ingredientsForRecipe = [thisRecipe objectForKey:@"Ingredients"]; NSArray *ingredientsArray = [ingredientsForRecipe objectForKey:@"Results"]; for (NSDictionary *thisIngredient in ingredientsArray) { Ingredient *ingredient = [NSEntityDescription insertNewObjectForEntityForName:@"Ingredient" inManagedObjectContext:insertionContext]; ingredient.name = [thisIngredient objectForKey:@"Name"]; } } NSSet *ingredientsSet = [NSSet ingredientsArray]; [recipe setIngredients:ingredientsSet]; Notes: "setIngredients" is a Core Data generated accessor method. There is a many-to-one relationship between Ingredients and Recipe However, when I run this I get the following error: NSCFDictionary managedObjectContext]: unrecognized selector sent to instance If I remove the last line (i.e. [recipe setIngredients:ingredientsSet];) then, taking a peek at the SQLite database, I see the Recipe and Ingredients have been stored but no relationship has been created between Recipe and Ingredients Any suggestions as to how to ensure the relationship is stored correctly?

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• Creating a dynamic, extensible C# Expando Object

  - by Rick Strahl

  I love dynamic functionality in a strongly typed language because it offers us the best of both worlds. In C# (or any of the main .NET languages) we now have the dynamic type that provides a host of dynamic features for the static C# language. One place where I've found dynamic to be incredibly useful is in building extensible types or types that expose traditionally non-object data (like dictionaries) in easier to use and more readable syntax. I wrote about a couple of these for accessing old school ADO.NET DataRows and DataReaders more easily for example. These classes are dynamic wrappers that provide easier syntax and auto-type conversions which greatly simplifies code clutter and increases clarity in existing code. ExpandoObject in .NET 4.0 Another great use case for dynamic objects is the ability to create extensible objects - objects that start out with a set of static members and then can add additional properties and even methods dynamically. The .NET 4.0 framework actually includes an ExpandoObject class which provides a very dynamic object that allows you to add properties and methods on the fly and then access them again. For example with ExpandoObject you can do stuff like this:dynamic expand = new ExpandoObject(); expand.Name = "Rick"; expand.HelloWorld = (Func<string, string>) ((string name) => { return "Hello " + name; }); Console.WriteLine(expand.Name); Console.WriteLine(expand.HelloWorld("Dufus")); Internally ExpandoObject uses a Dictionary like structure and interface to store properties and methods and then allows you to add and access properties and methods easily. As cool as ExpandoObject is it has a few shortcomings too: It's a sealed type so you can't use it as a base class It only works off 'properties' in the internal Dictionary - you can't expose existing type data It doesn't serialize to XML or with DataContractSerializer/DataContractJsonSerializer Expando - A truly extensible Object ExpandoObject is nice if you just need a dynamic container for a dictionary like structure. However, if you want to build an extensible object that starts out with a set of strongly typed properties and then allows you to extend it, ExpandoObject does not work because it's a sealed class that can't be inherited. I started thinking about this very scenario for one of my applications I'm building for a customer. In this system we are connecting to various different user stores. Each user store has the same basic requirements for username, password, name etc. But then each store also has a number of extended properties that is available to each application. In the real world scenario the data is loaded from the database in a data reader and the known properties are assigned from the known fields in the database. All unknown fields are then 'added' to the expando object dynamically. In the past I've done this very thing with a separate property - Properties - just like I do for this class. But the property and dictionary syntax is not ideal and tedious to work with. I started thinking about how to represent these extra property structures. One way certainly would be to add a Dictionary, or an ExpandoObject to hold all those extra properties. But wouldn't it be nice if the application could actually extend an existing object that looks something like this as you can with the Expando object:public class User : Westwind.Utilities.Dynamic.Expando { public string Email { get; set; } public string Password { get; set; } public string Name { get; set; } public bool Active { get; set; } public DateTime? ExpiresOn { get; set; } } and then simply start extending the properties of this object dynamically? Using the Expando object I describe later you can now do the following:[TestMethod] public void UserExampleTest() { var user = new User(); // Set strongly typed properties user.Email = "[email protected]"; user.Password = "nonya123"; user.Name = "Rickochet"; user.Active = true; // Now add dynamic properties dynamic duser = user; duser.Entered = DateTime.Now; duser.Accesses = 1; // you can also add dynamic props via indexer user["NickName"] = "AntiSocialX"; duser["WebSite"] = "http://www.west-wind.com/weblog"; // Access strong type through dynamic ref Assert.AreEqual(user.Name,duser.Name); // Access strong type through indexer Assert.AreEqual(user.Password,user["Password"]); // access dyanmically added value through indexer Assert.AreEqual(duser.Entered,user["Entered"]); // access index added value through dynamic Assert.AreEqual(user["NickName"],duser.NickName); // loop through all properties dynamic AND strong type properties (true) foreach (var prop in user.GetProperties(true)) { object val = prop.Value; if (val == null) val = "null"; Console.WriteLine(prop.Key + ": " + val.ToString()); } } As you can see this code somewhat blurs the line between a static and dynamic type. You start with a strongly typed object that has a fixed set of properties. You can then cast the object to dynamic (as I discussed in my last post) and add additional properties to the object. You can also use an indexer to add dynamic properties to the object. To access the strongly typed properties you can use either the strongly typed instance, the indexer or the dynamic cast of the object. Personally I think it's kinda cool to have an easy way to access strongly typed properties by string which can make some data scenarios much easier. To access the 'dynamically added' properties you can use either the indexer on the strongly typed object, or property syntax on the dynamic cast. Using the dynamic type allows all three modes to work on both strongly typed and dynamic properties. Finally you can iterate over all properties, both dynamic and strongly typed if you chose. Lots of flexibility. Note also that by default the Expando object works against the (this) instance meaning it extends the current object. You can also pass in a separate instance to the constructor in which case that object will be used to iterate over to find properties rather than this. Using this approach provides some really interesting functionality when use the dynamic type. To use this we have to add an explicit constructor to the Expando subclass:public class User : Westwind.Utilities.Dynamic.Expando { public string Email { get; set; } public string Password { get; set; } public string Name { get; set; } public bool Active { get; set; } public DateTime? ExpiresOn { get; set; } public User() : base() { } // only required if you want to mix in seperate instance public User(object instance) : base(instance) { } } to allow the instance to be passed. When you do you can now do:[TestMethod] public void ExpandoMixinTest() { // have Expando work on Addresses var user = new User( new Address() ); // cast to dynamicAccessToPropertyTest dynamic duser = user; // Set strongly typed properties duser.Email = "[email protected]"; user.Password = "nonya123"; // Set properties on address object duser.Address = "32 Kaiea"; //duser.Phone = "808-123-2131"; // set dynamic properties duser.NonExistantProperty = "This works too"; // shows default value Address.Phone value Console.WriteLine(duser.Phone); } Using the dynamic cast in this case allows you to access *three* different 'objects': The strong type properties, the dynamically added properties in the dictionary and the properties of the instance passed in! Effectively this gives you a way to simulate multiple inheritance (which is scary - so be very careful with this, but you can do it). How Expando works Behind the scenes Expando is a DynamicObject subclass as I discussed in my last post. By implementing a few of DynamicObject's methods you can basically create a type that can trap 'property missing' and 'method missing' operations. When you access a non-existant property a known method is fired that our code can intercept and provide a value for. Internally Expando uses a custom dictionary implementation to hold the dynamic properties you might add to your expandable object. Let's look at code first. The code for the Expando type is straight forward and given what it provides relatively short. Here it is.using System; using System.Collections.Generic; using System.Linq; using System.Dynamic; using System.Reflection; namespace Westwind.Utilities.Dynamic { /// <summary> /// Class that provides extensible properties and methods. This /// dynamic object stores 'extra' properties in a dictionary or /// checks the actual properties of the instance. /// /// This means you can subclass this expando and retrieve either /// native properties or properties from values in the dictionary. /// /// This type allows you three ways to access its properties: /// /// Directly: any explicitly declared properties are accessible /// Dynamic: dynamic cast allows access to dictionary and native properties/methods /// Dictionary: Any of the extended properties are accessible via IDictionary interface /// </summary> [Serializable] public class Expando : DynamicObject, IDynamicMetaObjectProvider { /// <summary> /// Instance of object passed in /// </summary> object Instance; /// <summary> /// Cached type of the instance /// </summary> Type InstanceType; PropertyInfo[] InstancePropertyInfo { get { if (_InstancePropertyInfo == null && Instance != null) _InstancePropertyInfo = Instance.GetType().GetProperties(BindingFlags.Instance | BindingFlags.Public | BindingFlags.DeclaredOnly); return _InstancePropertyInfo; } } PropertyInfo[] _InstancePropertyInfo; /// <summary> /// String Dictionary that contains the extra dynamic values /// stored on this object/instance /// </summary> /// <remarks>Using PropertyBag to support XML Serialization of the dictionary</remarks> public PropertyBag Properties = new PropertyBag(); //public Dictionary<string,object> Properties = new Dictionary<string, object>(); /// <summary> /// This constructor just works off the internal dictionary and any /// public properties of this object. /// /// Note you can subclass Expando. /// </summary> public Expando() { Initialize(this); } /// <summary> /// Allows passing in an existing instance variable to 'extend'. /// </summary> /// <remarks> /// You can pass in null here if you don't want to /// check native properties and only check the Dictionary! /// </remarks> /// <param name="instance"></param> public Expando(object instance) { Initialize(instance); } protected virtual void Initialize(object instance) { Instance = instance; if (instance != null) InstanceType = instance.GetType(); } /// <summary> /// Try to retrieve a member by name first from instance properties /// followed by the collection entries. /// </summary> /// <param name="binder"></param> /// <param name="result"></param> /// <returns></returns> public override bool TryGetMember(GetMemberBinder binder, out object result) { result = null; // first check the Properties collection for member if (Properties.Keys.Contains(binder.Name)) { result = Properties[binder.Name]; return true; } // Next check for Public properties via Reflection if (Instance != null) { try { return GetProperty(Instance, binder.Name, out result); } catch { } } // failed to retrieve a property result = null; return false; } /// <summary> /// Property setter implementation tries to retrieve value from instance /// first then into this object /// </summary> /// <param name="binder"></param> /// <param name="value"></param> /// <returns></returns> public override bool TrySetMember(SetMemberBinder binder, object value) { // first check to see if there's a native property to set if (Instance != null) { try { bool result = SetProperty(Instance, binder.Name, value); if (result) return true; } catch { } } // no match - set or add to dictionary Properties[binder.Name] = value; return true; } /// <summary> /// Dynamic invocation method. Currently allows only for Reflection based /// operation (no ability to add methods dynamically). /// </summary> /// <param name="binder"></param> /// <param name="args"></param> /// <param name="result"></param> /// <returns></returns> public override bool TryInvokeMember(InvokeMemberBinder binder, object[] args, out object result) { if (Instance != null) { try { // check instance passed in for methods to invoke if (InvokeMethod(Instance, binder.Name, args, out result)) return true; } catch { } } result = null; return false; } /// <summary> /// Reflection Helper method to retrieve a property /// </summary> /// <param name="instance"></param> /// <param name="name"></param> /// <param name="result"></param> /// <returns></returns> protected bool GetProperty(object instance, string name, out object result) { if (instance == null) instance = this; var miArray = InstanceType.GetMember(name, BindingFlags.Public | BindingFlags.GetProperty | BindingFlags.Instance); if (miArray != null && miArray.Length > 0) { var mi = miArray[0]; if (mi.MemberType == MemberTypes.Property) { result = ((PropertyInfo)mi).GetValue(instance,null); return true; } } result = null; return false; } /// <summary> /// Reflection helper method to set a property value /// </summary> /// <param name="instance"></param> /// <param name="name"></param> /// <param name="value"></param> /// <returns></returns> protected bool SetProperty(object instance, string name, object value) { if (instance == null) instance = this; var miArray = InstanceType.GetMember(name, BindingFlags.Public | BindingFlags.SetProperty | BindingFlags.Instance); if (miArray != null && miArray.Length > 0) { var mi = miArray[0]; if (mi.MemberType == MemberTypes.Property) { ((PropertyInfo)mi).SetValue(Instance, value, null); return true; } } return false; } /// <summary> /// Reflection helper method to invoke a method /// </summary> /// <param name="instance"></param> /// <param name="name"></param> /// <param name="args"></param> /// <param name="result"></param> /// <returns></returns> protected bool InvokeMethod(object instance, string name, object[] args, out object result) { if (instance == null) instance = this; // Look at the instanceType var miArray = InstanceType.GetMember(name, BindingFlags.InvokeMethod | BindingFlags.Public | BindingFlags.Instance); if (miArray != null && miArray.Length > 0) { var mi = miArray[0] as MethodInfo; result = mi.Invoke(Instance, args); return true; } result = null; return false; } /// <summary> /// Convenience method that provides a string Indexer /// to the Properties collection AND the strongly typed /// properties of the object by name. /// /// // dynamic /// exp["Address"] = "112 nowhere lane"; /// // strong /// var name = exp["StronglyTypedProperty"] as string; /// </summary> /// <remarks> /// The getter checks the Properties dictionary first /// then looks in PropertyInfo for properties. /// The setter checks the instance properties before /// checking the Properties dictionary. /// </remarks> /// <param name="key"></param> /// /// <returns></returns> public object this[string key] { get { try { // try to get from properties collection first return Properties[key]; } catch (KeyNotFoundException ex) { // try reflection on instanceType object result = null; if (GetProperty(Instance, key, out result)) return result; // nope doesn't exist throw; } } set { if (Properties.ContainsKey(key)) { Properties[key] = value; return; } // check instance for existance of type first var miArray = InstanceType.GetMember(key, BindingFlags.Public | BindingFlags.GetProperty); if (miArray != null && miArray.Length > 0) SetProperty(Instance, key, value); else Properties[key] = value; } } /// <summary> /// Returns and the properties of /// </summary> /// <param name="includeProperties"></param> /// <returns></returns> public IEnumerable<KeyValuePair<string,object>> GetProperties(bool includeInstanceProperties = false) { if (includeInstanceProperties && Instance != null) { foreach (var prop in this.InstancePropertyInfo) yield return new KeyValuePair<string, object>(prop.Name, prop.GetValue(Instance, null)); } foreach (var key in this.Properties.Keys) yield return new KeyValuePair<string, object>(key, this.Properties[key]); } /// <summary> /// Checks whether a property exists in the Property collection /// or as a property on the instance /// </summary> /// <param name="item"></param> /// <returns></returns> public bool Contains(KeyValuePair<string, object> item, bool includeInstanceProperties = false) { bool res = Properties.ContainsKey(item.Key); if (res) return true; if (includeInstanceProperties && Instance != null) { foreach (var prop in this.InstancePropertyInfo) { if (prop.Name == item.Key) return true; } } return false; } } } Although the Expando class supports an indexer, it doesn't actually implement IDictionary or even IEnumerable. It only provides the indexer and Contains() and GetProperties() methods, that work against the Properties dictionary AND the internal instance. The reason for not implementing IDictionary is that a) it doesn't add much value since you can access the Properties dictionary directly and that b) I wanted to keep the interface to class very lean so that it can serve as an entity type if desired. Implementing these IDictionary (or even IEnumerable) causes LINQ extension methods to pop up on the type which obscures the property interface and would only confuse the purpose of the type. IDictionary and IEnumerable are also problematic for XML and JSON Serialization - the XML Serializer doesn't serialize IDictionary<string,object>, nor does the DataContractSerializer. The JavaScriptSerializer does serialize, but it treats the entire object like a dictionary and doesn't serialize the strongly typed properties of the type, only the dictionary values which is also not desirable. Hence the decision to stick with only implementing the indexer to support the user["CustomProperty"] functionality and leaving iteration functions to the publicly exposed Properties dictionary. Note that the Dictionary used here is a custom PropertyBag class I created to allow for serialization to work. One important aspect for my apps is that whatever custom properties get added they have to be accessible to AJAX clients since the particular app I'm working on is a SIngle Page Web app where most of the Web access is through JSON AJAX calls. PropertyBag can serialize to XML and one way serialize to JSON using the JavaScript serializer (not the DCS serializers though). The key components that make Expando work in this code are the Properties Dictionary and the TryGetMember() and TrySetMember() methods. The Properties collection is public so if you choose you can explicitly access the collection to get better performance or to manipulate the members in internal code (like loading up dynamic values form a database). Notice that TryGetMember() and TrySetMember() both work against the dictionary AND the internal instance to retrieve and set properties. This means that user["Name"] works against native properties of the object as does user["Name"] = "RogaDugDog". What's your Use Case? This is still an early prototype but I've plugged it into one of my customer's applications and so far it's working very well. The key features for me were the ability to easily extend the type with values coming from a database and exposing those values in a nice and easy to use manner. I'm also finding that using this type of object for ViewModels works very well to add custom properties to view models. I suspect there will be lots of uses for this - I've been using the extra dictionary approach to extensibility for years - using a dynamic type to make the syntax cleaner is just a bonus here. What can you think of to use this for? Resources Source Code and Tests (GitHub) Also integrated in Westwind.Utilities of the West Wind Web Toolkit West Wind Utilities NuGet© Rick Strahl, West Wind Technologies, 2005-2012Posted in CSharp  .NET  Dynamic Types   Tweet !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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• Parallelism in .NET – Part 2, Simple Imperative Data Parallelism

  - by Reed

  In my discussion of Decomposition of the problem space, I mentioned that Data Decomposition is often the simplest abstraction to use when trying to parallelize a routine.  If a problem can be decomposed based off the data, we will often want to use what MSDN refers to as Data Parallelism as our strategy for implementing our routine.  The Task Parallel Library in .NET 4 makes implementing Data Parallelism, for most cases, very simple. Data Parallelism is the main technique we use to parallelize a routine which can be decomposed based off data.  Data Parallelism refers to taking a single collection of data, and having a single operation be performed concurrently on elements in the collection.  One side note here: Data Parallelism is also sometimes referred to as the Loop Parallelism Pattern or Loop-level Parallelism.  In general, for this series, I will try to use the terminology used in the MSDN Documentation for the Task Parallel Library.  This should make it easier to investigate these topics in more detail. Once we’ve determined we have a problem that, potentially, can be decomposed based on data, implementation using Data Parallelism in the TPL is quite simple.  Let’s take our example from the Data Decomposition discussion – a simple contrast stretching filter.  Here, we have a collection of data (pixels), and we need to run a simple operation on each element of the pixel.  Once we know the minimum and maximum values, we most likely would have some simple code like the following: for (int row=0; row < pixelData.GetUpperBound(0); ++row) { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } } .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; } This simple routine loops through a two dimensional array of pixelData, and calls the AdjustContrast routine on each pixel. As I mentioned, when you’re decomposing a problem space, most iteration statements are potentially candidates for data decomposition.  Here, we’re using two for loops – one looping through rows in the image, and a second nested loop iterating through the columns.  We then perform one, independent operation on each element based on those loop positions. This is a prime candidate – we have no shared data, no dependencies on anything but the pixel which we want to change.  Since we’re using a for loop, we can easily parallelize this using the Parallel.For method in the TPL: Parallel.For(0, pixelData.GetUpperBound(0), row => { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } }); Here, by simply changing our first for loop to a call to Parallel.For, we can parallelize this portion of our routine.  Parallel.For works, as do many methods in the TPL, by creating a delegate and using it as an argument to a method.  In this case, our for loop iteration block becomes a delegate creating via a lambda expression.  This lets you write code that, superficially, looks similar to the familiar for loop, but functions quite differently at runtime. We could easily do this to our second for loop as well, but that may not be a good idea.  There is a balance to be struck when writing parallel code.  We want to have enough work items to keep all of our processors busy, but the more we partition our data, the more overhead we introduce.  In this case, we have an image of data – most likely hundreds of pixels in both dimensions.  By just parallelizing our first loop, each row of pixels can be run as a single task.  With hundreds of rows of data, we are providing fine enough granularity to keep all of our processors busy. If we parallelize both loops, we’re potentially creating millions of independent tasks.  This introduces extra overhead with no extra gain, and will actually reduce our overall performance.  This leads to my first guideline when writing parallel code: Partition your problem into enough tasks to keep each processor busy throughout the operation, but not more than necessary to keep each processor busy. Also note that I parallelized the outer loop.  I could have just as easily partitioned the inner loop.  However, partitioning the inner loop would have led to many more discrete work items, each with a smaller amount of work (operate on one pixel instead of one row of pixels).  My second guideline when writing parallel code reflects this: Partition your problem in a way to place the most work possible into each task. This typically means, in practice, that you will want to parallelize the routine at the “highest” point possible in the routine, typically the outermost loop.  If you’re looking at parallelizing methods which call other methods, you’ll want to try to partition your work high up in the stack – as you get into lower level methods, the performance impact of parallelizing your routines may not overcome the overhead introduced. Parallel.For works great for situations where we know the number of elements we’re going to process in advance.  If we’re iterating through an IList<T> or an array, this is a typical approach.  However, there are other iteration statements common in C#.  In many situations, we’ll use foreach instead of a for loop.  This can be more understandable and easier to read, but also has the advantage of working with collections which only implement IEnumerable<T>, where we do not know the number of elements involved in advance. As an example, lets take the following situation.  Say we have a collection of Customers, and we want to iterate through each customer, check some information about the customer, and if a certain case is met, send an email to the customer and update our instance to reflect this change.  Normally, this might look something like: foreach(var customer in customers) { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { theStore.EmailCustomer(customer); customer.LastEmailContact = DateTime.Now; } } Here, we’re doing a fair amount of work for each customer in our collection, but we don’t know how many customers exist.  If we assume that theStore.GetLastContact(customer) and theStore.EmailCustomer(customer) are both side-effect free, thread safe operations, we could parallelize this using Parallel.ForEach: Parallel.ForEach(customers, customer => { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { theStore.EmailCustomer(customer); customer.LastEmailContact = DateTime.Now; } }); Just like Parallel.For, we rework our loop into a method call accepting a delegate created via a lambda expression.  This keeps our new code very similar to our original iteration statement, however, this will now execute in parallel.  The same guidelines apply with Parallel.ForEach as with Parallel.For. The other iteration statements, do and while, do not have direct equivalents in the Task Parallel Library.  These, however, are very easy to implement using Parallel.ForEach and the yield keyword. Most applications can benefit from implementing some form of Data Parallelism.  Iterating through collections and performing “work” is a very common pattern in nearly every application.  When the problem can be decomposed by data, we often can parallelize the workload by merely changing foreach statements to Parallel.ForEach method calls, and for loops to Parallel.For method calls.  Any time your program operates on a collection, and does a set of work on each item in the collection where that work is not dependent on other information, you very likely have an opportunity to parallelize your routine.

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• ERROR: Attempted to read or write protected memory. This is often an indication that other memory is corrupt

  - by SPSamL

  I get this error after having edited a few pages in SharePoint 2010. I have to do an IISReset on both front ends to get this to resolve. I don't know how to fix it or even what else to supply here, but please let me know as the resets now happen several times per day. Log Name: Application Source: ASP.NET 2.0.50727.0 Date: 1/26/2011 11:12:48 AM Event ID: 1309 Task Category: Web Event Level: Warning Keywords: Classic User: N/A Computer: PINTSPSFE02.samcstl.org Description: Event code: 3005 Event message: An unhandled exception has occurred. Event time: 1/26/2011 11:12:48 AM Event time (UTC): 1/26/2011 5:12:48 PM Event ID: c52fb336b7f147a3913fff3617a99d57 Event sequence: 4965 Event occurrence: 2178 Event detail code: 0 Application information: Application domain: /LM/W3SVC/1449762715/ROOT-2-129405348166941887 Trust level: WSS_Minimal Application Virtual Path: / Application Path: C:\inetpub\wwwroot\wss\VirtualDirectories\80\ Machine name: PINTSPSFE02 Process information: Process ID: 5928 Process name: w3wp.exe Account name: SAMC\MossAppPool Exception information: Exception type: AccessViolationException Exception message: Attempted to read or write protected memory. This is often an indication that other memory is corrupt. Request information: Request URL: http://mosscluster/Pages/Home.aspx Request path: /Pages/Home.aspx User host address: 10.3.60.26 User: SAMC\BARNMD Is authenticated: True Authentication Type: NTLM Thread account name: SAMC\MossAppPool Thread information: Thread ID: 110 Thread account name: SAMC\MossAppPool Is impersonating: False Stack trace: at Microsoft.Office.Server.ObjectCache.SPCache.MossObjectCache_Tracked.Delete(String key, Boolean recursive, DeletionReason reason) at Microsoft.Office.Server.ObjectCache.SPCache.MossObjectCache_Tracked.Get(String key) at Microsoft.Office.Server.ObjectCache.SPCache.Get(String objectTypeName, String id) at Microsoft.Office.Server.Administration.UserProfileServiceProxy.GetPartitionPropertiesCache(Guid applicationID) at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.get_PartitionPropertiesCache() at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.DataCache.get_PartitionProperties() at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.GetMySitePortalUrl(SPUrlZone zone, Guid partitionID) at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.GetMySitePortalUrl(SPUrlZone zone, SPServiceContext serviceContext) at Microsoft.Office.Server.WebControls.MyLinksRibbon.EnsureMySiteUrls() at Microsoft.Office.Server.WebControls.MyLinksRibbon.get_PortalMySiteUrlAvailable() at Microsoft.Office.Server.WebControls.MyLinksRibbon.OnLoad(EventArgs e) at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Page.ProcessRequestMain(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) Custom event details: Event Xml: <Event xmlns="http://schemas.microsoft.com/win/2004/08/events/event"> <System> <Provider Name="ASP.NET 2.0.50727.0" /> <EventID Qualifiers="32768">1309</EventID> <Level>3</Level> <Task>3</Task> <Keywords>0x80000000000000</Keywords> <TimeCreated SystemTime="2011-01-26T17:12:48.000000000Z" /> <EventRecordID>35834</EventRecordID> <Channel>Application</Channel> <Computer>PINTSPSFE02.samcstl.org</Computer> <Security /> </System> <EventData> <Data>3005</Data> <Data>An unhandled exception has occurred.</Data> <Data>1/26/2011 11:12:48 AM</Data> <Data>1/26/2011 5:12:48 PM</Data> <Data>c52fb336b7f147a3913fff3617a99d57</Data> <Data>4965</Data> <Data>2178</Data> <Data>0</Data> <Data>/LM/W3SVC/1449762715/ROOT-2-129405348166941887</Data> <Data>WSS_Minimal</Data> <Data>/</Data> <Data>C:\inetpub\wwwroot\wss\VirtualDirectories\80\</Data> <Data>PINTSPSFE02</Data> <Data> </Data> <Data>5928</Data> <Data>w3wp.exe</Data> <Data>SAMC\MossAppPool</Data> <Data>AccessViolationException</Data> <Data></Data> <Data>http://mosscluster/Pages/Home.aspx</Data> <Data>/Pages/Home.aspx</Data> <Data>10.3.60.26</Data> <Data>SAMC\BARNMD</Data> <Data>True</Data> <Data>NTLM</Data> <Data>SAMC\MossAppPool</Data> <Data>110</Data> <Data>SAMC\MossAppPool</Data> <Data>False</Data> <Data> at Microsoft.Office.Server.ObjectCache.SPCache.MossObjectCache_Tracked.Delete(String key, Boolean recursive, DeletionReason reason) at Microsoft.Office.Server.ObjectCache.SPCache.MossObjectCache_Tracked.Get(String key) at Microsoft.Office.Server.ObjectCache.SPCache.Get(String objectTypeName, String id) at Microsoft.Office.Server.Administration.UserProfileServiceProxy.GetPartitionPropertiesCache(Guid applicationID) at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.get_PartitionPropertiesCache() at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.DataCache.get_PartitionProperties() at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.GetMySitePortalUrl(SPUrlZone zone, Guid partitionID) at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.GetMySitePortalUrl(SPUrlZone zone, SPServiceContext serviceContext) at Microsoft.Office.Server.WebControls.MyLinksRibbon.EnsureMySiteUrls() at Microsoft.Office.Server.WebControls.MyLinksRibbon.get_PortalMySiteUrlAvailable() at Microsoft.Office.Server.WebControls.MyLinksRibbon.OnLoad(EventArgs e) at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Page.ProcessRequestMain(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) </Data> </EventData> </Event>

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• Data Profiling without SSIS

  Strangely enough for a predominantly SSIS blog, this post is all about how to perform data profiling without using SSIS. Whilst the Data Profiling Task is a worthy addition, there are a couple of limitations I’ve encountered of late. The first is that it requires SQL Server 2008, and not everyone is there yet. The second is that it can only target SQL Server 2005 and above. What about older systems, which are the ones that we probably need to investigate the most, or other vendor databases such as Oracle? With these limitations in mind I did some searching to find a quick and easy alternative to help me perform some data profiling for a project I was working on recently. I only had SQL Server 2005 available, and anyway most of my target source systems were Oracle, and of course I had short timescales. I looked at several options. Some never got beyond the download stage, they failed to install or just did not run, and others provided less than I could have produced myself by spending 2 minutes writing some basic SQL queries. In the end I settled on an open source product called DataCleaner. To quote from their website: DataCleaner is an Open Source application for profiling, validating and comparing data. These activities help you administer and monitor your data quality in order to ensure that your data is useful and applicable to your business situation. DataCleaner is the free alternative to software for master data management (MDM) methodologies, data warehousing (DW) projects, statistical research, preparation for extract-transform-load (ETL) activities and more. DataCleaner is developed in Java and licensed under LGPL. As quoted above it claims to support profiling, validating and comparing data, but I didn’t really get past the profiling functions, so won’t comment on the other two. The profiling whilst not prefect certainly saved some time compared to the limited alternatives. The ability to profile heterogeneous data sources is a big advantage over the SSIS option, and I found it overall quite easy to use and performance was good. I could see it struggling at times, but actually for what it does I was impressed. It had some data type niggles with Oracle, and some metrics seem a little strange, although thankfully they were easy to augment with some SQL queries to ensure a consistent picture. The report export options didn’t do it for me, but copy and paste with a bit of Excel magic was sufficient. One initial point for me personally is that I have had limited exposure to things of the Java persuasion and whilst I normally get by fine, sometimes the simplest things can throw me. For example installing a JDBC driver, why do I have to copy files to make it all work, has nobody ever heard of an MSI? In case there are other people out there like me who have become totally indoctrinated with the Microsoft software paradigm, I’ve written a quick start guide that details every step required. Steps 1- 5 are the key ones, the rest is really an excuse for some screenshots to show you the tool. Quick Start Guide Step 1  - Download Data Cleaner. The Microsoft Windows zipped exe option, and I chose the latest stable build, currently DataCleaner 1.5.3 (final). Extract the files to a suitable location. Step 2 - Download Java. If you try and run datacleaner.exe without Java it will warn you, and then open your default browser and take you to the Java download site. Follow the installation instructions from there, normally just click Download Java a couple of times and you’re done. Step 3 - Download Microsoft SQL Server JDBC Driver. You may have SQL Server installed, but you won’t have a JDBC driver. Version 3.0 is the latest as of April 2010. There is no real installer, we are in the Java world here, but run the exe you downloaded to extract the files. The default Unzip to folder is not much help, so try a fully qualified path such as C:\Program Files\Microsoft SQL Server JDBC Driver 3.0\ to ensure you can find the files afterwards. Step 4 - If you wish to use Windows Authentication to connect to your SQL Server then first we need to copy a file so that Data Cleaner can find it. Browse to the JDBC extract location from Step 3 and drill down to the file sqljdbc_auth.dll. You will have to choose the correct directory for your processor architecture. e.g. C:\Program Files\Microsoft SQL Server JDBC Driver 3.0\sqljdbc_3.0\enu\auth\x86\sqljdbc_auth.dll. Now copy this file to the Data Cleaner extract folder you chose in Step 1. An alternative method is to edit datacleaner.cmd in the data cleaner extract folder as detailed in this data cleaner wiki topic, but I find copying the file simpler. Step 5 – Now lets run Data Cleaner, just run datacleaner.exe from the extract folder you chose in Step 1. Step 6 – Complete or skip the registration screen, and ignore the task window for now. In the main window click settings. Step 7 – In the Settings dialog, select the Database drivers tab, then click Register database driver and select the Local JAR file option. Step 8 – Browse to the JDBC driver extract location from Step 3 and drill down to select sqljdbc4.jar. e.g. C:\Program Files\Microsoft SQL Server JDBC Driver 3.0\sqljdbc_3.0\enu\sqljdbc4.jar Step 9 – Select the Database driver class as com.microsoft.sqlserver.jdbc.SQLServerDriver, and then click the Test and Save database driver button. Step 10 - You should be back at the Settings dialog with a the list of drivers that includes SQL Server. Just click Save Settings to persist all your hard work. Step 11 – Now we can start to profile some data. In the main Data Cleaner window click New Task, and then Profile from the task window. Step 12 – In the Profile window click Open Database Step 13 – Now choose the SQL Server connection string option. Selecting a connection string gives us a template like jdbc:sqlserver://<hostname>:1433;databaseName=<database>, but obviously it requires some details to be entered for example  jdbc:sqlserver://localhost:1433;databaseName=SQLBits. This will connect to the database called SQLBits on my local machine. The port may also have to be changed if using such as when you have a multiple instances of SQL Server running. If using SQL Server Authentication enter a username and password as required and then click Connect to database. You can use Window Authentication, just add integratedSecurity=true to the end of your connection string. e.g jdbc:sqlserver://localhost:1433;databaseName=SQLBits;integratedSecurity=true.  If you didn’t complete Step 4 above you will need to do so now and restart Data Cleaner before it will work. Manually setting the connection string is fine, but creating a named connection makes more sense if you will be spending any length of time profiling a specific database. As highlighted in the left-hand screen-shot, at the bottom of the dialog it includes partial instructions on how to create named connections. In the folder shown C:\Users\<Username>\.datacleaner\1.5.3, open the datacleaner-config.xml file in your editor of choice add your own details. You’ll see a sample connection in the file already, just add yours following the same pattern. e.g. <!-- Darren's Named Connections --> <bean class="dk.eobjects.datacleaner.gui.model.NamedConnection"> <property name="name" value="SQLBits Local Connection" /> <property name="driverClass" value="com.microsoft.sqlserver.jdbc.SQLServerDriver" /> <property name="connectionString" value="jdbc:sqlserver://localhost:1433;databaseName=SQLBits;integratedSecurity=true" /> <property name="tableTypes"> <list> <value>TABLE</value> <value>VIEW</value> </list> </property> </bean> Step 14 – Once back at the Profile window, you should now see your schemas, tables and/or views listed down the left hand side. Browse this tree and double-click a table to select it for profiling. You can then click Add profile, and choose some profiling options, before finally clicking Run profiling. You can see below a sample output for three of the most common profiles, click the image for full size.   I hope this has given you a taster for DataCleaner, and should help you get up and running pretty quickly.

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• SQL SERVER – LCK_M_XXX – Wait Type – Day 15 of 28

  - by pinaldave

  Locking is a mechanism used by the SQL Server Database Engine to synchronize access by multiple users to the same piece of data, at the same time. In simpler words, it maintains the integrity of data by protecting (or preventing) access to the database object. From Book On-Line: LCK_M_BU Occurs when a task is waiting to acquire a Bulk Update (BU) lock. LCK_M_IS Occurs when a task is waiting to acquire an Intent Shared (IS) lock. LCK_M_IU Occurs when a task is waiting to acquire an Intent Update (IU) lock. LCK_M_IX Occurs when a task is waiting to acquire an Intent Exclusive (IX) lock. LCK_M_S Occurs when a task is waiting to acquire a Shared lock. LCK_M_SCH_M Occurs when a task is waiting to acquire a Schema Modify lock. LCK_M_SCH_S Occurs when a task is waiting to acquire a Schema Share lock. LCK_M_SIU Occurs when a task is waiting to acquire a Shared With Intent Update lock. LCK_M_SIX Occurs when a task is waiting to acquire a Shared With Intent Exclusive lock. LCK_M_U Occurs when a task is waiting to acquire an Update lock. LCK_M_UIX Occurs when a task is waiting to acquire an Update With Intent Exclusive lock. LCK_M_X Occurs when a task is waiting to acquire an Exclusive lock. LCK_M_XXX Explanation: I think the explanation of this wait type is the simplest. When any task is waiting to acquire lock on any resource, this particular wait type occurs. The common reason for the task to be waiting to put lock on the resource is that the resource is already locked and some other operations may be going on within it. This wait also indicates that resources are not available or are occupied at the moment due to some reasons. There is a good chance that the waiting queries start to time out if this wait type is very high. Client application may degrade the performance as well. You can use various methods to find blocking queries: EXEC sp_who2 SQL SERVER – Quickest Way to Identify Blocking Query and Resolution – Dirty Solution DMV – sys.dm_tran_locks DMV – sys.dm_os_waiting_tasks Reducing LCK_M_XXX wait: Check the Explicit Transactions. If transactions are very long, this wait type can start building up because of other waiting transactions. Keep the transactions small. Serialization Isolation can build up this wait type. If that is an acceptable isolation for your business, this wait type may be natural. The default isolation of SQL Server is ‘Read Committed’. One of my clients has changed their isolation to “Read Uncommitted”. I strongly discourage the use of this because this will probably lead to having lots of dirty data in the database. Identify blocking queries mentioned using various methods described above, and then optimize them. Partition can be one of the options to consider because this will allow transactions to execute concurrently on different partitions. If there are runaway queries, use timeout. (Please discuss this solution with your database architect first as timeout can work against you). Check if there is no memory and IO-related issue using the following counters: Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussion of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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• Oracle Data Integration Solutions and the Oracle EXADATA Database Machine

  - by João Vilanova

  Oracle's data integration solutions provide a complete, open and integrated solution for building, deploying, and managing real-time data-centric architectures in operational and analytical environments. Fully integrated with and optimized for the Oracle Exadata Database Machine, Oracle's data integration solutions take data integration to the next level and delivers extremeperformance and scalability for all the enterprise data movement and transformation needs. Easy-to-use, open and standards-based Oracle's data integration solutions dramatically improve productivity, provide unparalleled efficiency, and lower the cost of ownership.You can watch a video about this subject, after clicking on the link below.DIS for EXADATA Video

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• 11 Types of Developers

  - by Lee Brandt

  Jack Dawson Jack Dawson is the homeless drifter in Titanic. At one point in the movie he says, “I figure life’s a gift, and I don’t intend on wasting it.” He is happy to wander wherever life takes him. He works himself from place to place, making just enough money to make it to his next adventure. The “Jack Dawson” developer clings on to any new technology as the ‘next big thing’, and will find ways to shoe-horn it in to places where it is not a fit. He is very appealing to the other developers because they want to try the newest techniques and tools too, He will only stay until the new technology either bores him or becomes problematic. Jack will also be hard to find once the technology has been implemented, because he will be on to the next shiny thing. However, having a Jack Dawson on your team can be beneficial. Jack can be a great ally when attempting to convince a stodgy, corporate entity to upgrade. Jack usually has an encyclopedic recall of all the new features of the technology upgrade and is more than happy to interject them in any conversation. Tom Smykowski Tom is the neurotic employee in Office Space, and is deathly afraid of being fired. He will do only what is necessary to keep the status quo. He believes as long as nothing changes, his job is safe. He will scoff at anything new and be the naysayer during any change initiative. Tom can be useful in off-setting Jack Dawson. Jack will constantly be pushing for change and Tom will constantly be fighting it. When you see that Jack is getting kind of bored with a new technology and Tom has finally stopped wetting himself at the mere mention of it, then it is probably the sweet spot of beginning to implement that new technology (providing it is the right tool for the job). Ray Consella Ray is the guy who built the Field of Dreams. He took a risk. Sometimes he screwed it up, but he knew he didn’t want to end up regretting not attempting it. He constantly doubted himself, but he knew he had to keep going. Granted, he was doing what the voices in his head were telling him to do, but my point is he was driven to do something that most people considered crazy. Even when his friends, his wife and even he told himself he was crazy, somewhere inside himself, he knew it was the right thing to do. These are the innovators. These are the Bill Gates and Steve Jobs of the world. The take risks, they fail, they learn and the get better. Obviously, this kind of person thrives in start-ups and smaller companies, but that is due to their natural aversion to bureaucracy. They want to see their ideas put into motion quickly, and withdrawn quickly if it doesn’t work. Short feedback cycles are essential to Ray. He wants to know if his idea is working or not. He wants to modify or reverse his idea if it is not working or makes things worse. These are the agilistas. May I always be one.

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• Open Different Types of New Google Documents Directly with These 7 New Chrome Apps

  - by Asian Angel

  Every time you want to open a new document of one kind or another in Google Drive you have to go through the whole ‘menu’ and ‘type selection’ process to do so. Now you can open the desired type directly from the New Tab Page using these terrific new Chrome apps from Google! The best part about this new set of apps is the ability to choose only the ones you want and/or need, then be able to start working on those new documents quickly without all the ‘selection’ hassle. How Hackers Can Disguise Malicious Programs With Fake File Extensions Can Dust Actually Damage My Computer? What To Do If You Get a Virus on Your Computer

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• Converting Openfire IM datetime values in SQL Server to / from VARCHAR(15) and DATETIME data types

  - by Brian Biales

  A client is using Openfire IM for their users, and would like some custom queries to audit user conversations (which are stored by Openfire in tables in the SQL Server database). Because Openfire supports multiple database servers and multiple platforms, the designers chose to store all date/time stamps in the database as 15 character strings, which get converted to Java Date objects in their code (Openfire is written in Java).  I did some digging around, and, so I don't forget and in case someone else will find this useful, I will put the simple algorithms here for converting back and forth between SQL DATETIME and the Java string representation. The Java string representation is the number of milliseconds since 1/1/1970.  SQL Server's DATETIME is actually represented as a float, the value being the number of days since 1/1/1900, the portion after the decimal point representing the hours/minutes/seconds/milliseconds... as a fractional part of a day.  Try this and you will see this is true:     SELECT CAST(0 AS DATETIME) and you will see it returns the date 1/1/1900. The difference in days between SQL Server's 0 date of 1/1/1900 and the Java representation's 0 date of 1/1/1970 is found easily using the following SQL:   SELECT DATEDIFF(D, '1900-01-01', '1970-01-01') which returns 25567.  There are 25567 days between these dates. So to convert from the Java string to SQL Server's date time, we need to convert the number of milliseconds to a floating point representation of the number of days since 1/1/1970, then add the 25567 to change this to the number of days since 1/1/1900.  To convert to days, you need to divide the number by 1000 ms/s, then by  60 seconds/minute, then by 60 minutes/hour, then by 24 hours/day.  Or simply divide by 1000*60*60*24, or 86400000.   So, to summarize, we need to cast this string as a float, divide by 86400000 milliseconds/day, then add 25567 days, and cast the resulting value to a DateTime.  Here is an example:   DECLARE @tmp as VARCHAR(15)   SET @tmp = '1268231722123'   SELECT @tmp as JavaTime, CAST((CAST(@tmp AS FLOAT) / 86400000) + 25567 AS DATETIME) as SQLTime   To convert from SQL datetime back to the Java time format is not quite as simple, I found, because floats of that size do not convert nicely to strings, they end up in scientific notation using the CONVERT function or CAST function.  But I found a couple ways around that problem. You can convert a date to the number of  seconds since 1/1/1970 very easily using the DATEDIFF function, as this value fits in an Int.  If you don't need to worry about the milliseconds, simply cast this integer as a string, and then concatenate '000' at the end, essentially multiplying this number by 1000, and making it milliseconds since 1/1/1970.  If, however, you do care about the milliseconds, you will need to use DATEPART to get the milliseconds part of the date, cast this integer to a string, and then pad zeros on the left to make sure this is three digits, and concatenate these three digits to the number of seconds string above.  And finally, I discovered by casting to DECIMAL(15,0) then to VARCHAR(15), I avoid the scientific notation issue.  So here are all my examples, pick the one you like best... First, here is the simple approach if you don't care about the milliseconds:   DECLARE @tmp as VARCHAR(15)   DECLARE @dt as DATETIME   SET @dt = '2010-03-10 14:35:22.123'   SET @tmp = CAST(DATEDIFF(s, '1970-01-01 00:00:00' , @dt) AS VARCHAR(15)) + '000'   SELECT @tmp as JavaTime, @dt as SQLTime If you want to keep the milliseconds:   DECLARE @tmp as VARCHAR(15)   DECLARE @dt as DATETIME   DECLARE @ms as int   SET @dt = '2010-03-10 14:35:22.123'   SET @ms as DATEPART(ms, @dt)   SET @tmp = CAST(DATEDIFF(s, '1970-01-01 00:00:00' , @dt) AS VARCHAR(15))           + RIGHT('000' + CAST(@ms AS VARCHAR(3)), 3)   SELECT @tmp as JavaTime, @dt as SQLTime Or, in one fell swoop:   DECLARE @dt as DATETIME   SET @dt = '2010-03-10 14:35:22.123'   SELECT @dt as SQLTime     , CAST(DATEDIFF(s, '1970-01-01 00:00:00' , @dt) AS VARCHAR(15))           + RIGHT('000' + CAST( DATEPART(ms, @dt) AS VARCHAR(3)), 3) as JavaTime   And finally, a way to simply reverse the math used converting from Java date to SQL date. Note the parenthesis - watch out for operator precedence, you want to subtract, then multiply:   DECLARE @dt as DATETIME   SET @dt = '2010-03-10 14:35:22.123'   SELECT @dt as SQLTime     , CAST(CAST((CAST(@dt as Float) - 25567.0) * 86400000.0 as DECIMAL(15,0)) as VARCHAR(15)) as JavaTime Interestingly, I found that converting to SQL Date time can lose some accuracy, when I converted the time above to Java time then converted  that back to DateTime, the number of milliseconds is 120, not 123.  As I am not interested in the milliseconds, this is ok for me.  But you may want to look into using DateTime2 in SQL Server 2008 for more accuracy.

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• Enjoy Playing Dozens of Classic Atari, Adventure, and Other Types of Games Directly in Your Browser

  - by Akemi Iwaya

  Would you love to play classic Atari games, journey once again with Bilbo Baggins in The Hobbit v1.0, or even try out WordStar 2.26? Then we have the perfect way to indulge in hours of browser-based fun to share with you. The Internet Archive has worked hard to put together a JavaScript port of the MESS computer software emulator and create an awesome online Historical Software Collection of classic games and software from yesteryear! When you visit the homepage, you will be able to scroll down through it for a ‘guided tour’ of the games and software currently available in the initial collection. This is what the individual homepages for each game or bit of software looks like. Keep in mind that none of the ‘Download item’ links we checked were working for us even though they are ‘shown’… Browse on over to the Internet Archive’s Historical Software Collection homepage to start having fun with all the classic games and programs. Historical Software Collection Homepage If you would like to visit the homepage for The Hobbit v1.0 directly, then use the link below. Play The Hobbit v1.0 [via The Verge]     

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• BIWA Wednesday TechCast Series - Opposition to Data Warehouse Initiatives

  - by jenny.gelhausen

  BIWA Wednesday TechCast Series - 19th Event! Opposition to Data Warehouse Initiatives Please join us for this webcast on Wednesday, March 24, 12 noon Eastern or check your local area's time Webcast is open to clients, prospects and partners. No matter how good your technology and technical skills, organizational issues can derail a data warehousing or BI project. Therefore BIWA presents a vital topic that crosses product boundaries: organizational resistance to data warehouse initiatives - how to recognize it and what to do about it. Many a DW/BI professional has been surprised by organizational resistance to DW/BI initiatives. Yet real organizational imperatives may be behind this apparently irrational behavior. Based on in-depth interviews with IT professionals, industry consultants, and power users, our speaker Bruce Jenks will present his research findings about what drives organizational resistance to data warehouse initiatives. The talk will cover specific behaviors that can signal organizational resistance to a data warehouse program and what organizations have done to address such resistance. Presenter: Bruce Jenks of Dun and Bradstreet Bruce Jenks has over 20 years experience in data warehousing and business intelligence, much of it as a consultant to large organizations spanning the US. Bruce's data warehousing clients have included firms such as Sprint, Gallo Wines, Southern California Edison, The Gap, and Safeway. He started his data warehousing career at Metaphor Computers, a pioneering DW/BI firm from which a number of industry luminaries sprang including Ralph Kimball (author of The Data Warehouse Toolkit ). Bruce continued his data warehousing career at HP, Stanford University and other firms. Bruce is currently completing his doctorate in business administration at Golden Gate University, and today's material arises from his doctoral research. He is also a principal consultant for Dun and Bradstreet. Audio Dial-In: 866 682 4770 Audio Meeting ID: 1683901 Audio Meeting Passcode: 334451 Web Conference: Please register at https://www1.gotomeeting.com/register/807185273 After you register you will be provided with a link to the TechCast. Invitation to Speakers: All BIWA members and Oracle professionals (experts, end users, managers, DBAs, developers, data analysts, ISVs, partners, etc.) may submit abstracts for 45 minute technical webcasts to our Oracle BIWA (IOUG SIG) Community. Submit your BIWA TechCast abstract today! BIWA is a worldwide forum with over 2000 members who are business intelligence, warehousing and analytics professionals. BIWA presents information, experiences and best practices in successfully deploying Oracle Database-centric BI, Data Warehousing, and Analytics products, features and Options--the Oracle Database "BIWA" platform. Attendance Information & Replays at the BIWA website: oraclebiwa.org var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); try { var pageTracker = _gat._getTracker("UA-13185312-1"); pageTracker._trackPageview(); } catch(err) {}

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• SQL Monitor’s data repository

  - by Chris Lambrou

  As one of the developers of SQL Monitor, I often get requests passed on by our support people from customers who are looking to dip into SQL Monitor’s own data repository, in order to pull out bits of information that they’re interested in. Since there’s clearly interest out there in playing around directly with the data repository, I thought I’d write some blog posts to start to describe how it all works. The hardest part for me is knowing where to begin, since the schema of the data repository is pretty big. Hmmm… I guess it’s tricky for anyone to write anything but the most trivial of queries against the data repository without understanding the hierarchy of monitored objects, so perhaps my first post should start there. I always imagine that whenever a customer fires up SSMS and starts to explore their SQL Monitor data repository database, they become immediately bewildered by the schema – that was certainly my experience when I did so for the first time. The following query shows the number of different object types in the data repository schema: SELECT type_desc, COUNT(*) AS [count] FROM sys.objects GROUP BY type_desc ORDER BY type_desc;  type_desccount 1DEFAULT_CONSTRAINT63 2FOREIGN_KEY_CONSTRAINT181 3INTERNAL_TABLE3 4PRIMARY_KEY_CONSTRAINT190 5SERVICE_QUEUE3 6SQL_INLINE_TABLE_VALUED_FUNCTION381 7SQL_SCALAR_FUNCTION2 8SQL_STORED_PROCEDURE100 9SYSTEM_TABLE41 10UNIQUE_CONSTRAINT54 11USER_TABLE193 12VIEW124 With 193 tables, 124 views, 100 stored procedures and 381 table valued functions, that’s quite a hefty schema, and when you browse through it using SSMS, it can be a bit daunting at first. So, where to begin? Well, let’s narrow things down a bit and only look at the tables belonging to the data schema. That’s where all of the collected monitoring data is stored by SQL Monitor. The following query gives us the names of those tables: SELECT sch.name + '.' + obj.name AS [name] FROM sys.objects obj JOIN sys.schemas sch ON sch.schema_id = obj.schema_id WHERE obj.type_desc = 'USER_TABLE' AND sch.name = 'data' ORDER BY sch.name, obj.name; This query still returns 110 tables. I won’t show them all here, but let’s have a look at the first few of them:  name 1data.Cluster_Keys 2data.Cluster_Machine_ClockSkew_UnstableSamples 3data.Cluster_Machine_Cluster_StableSamples 4data.Cluster_Machine_Keys 5data.Cluster_Machine_LogicalDisk_Capacity_StableSamples 6data.Cluster_Machine_LogicalDisk_Keys 7data.Cluster_Machine_LogicalDisk_Sightings 8data.Cluster_Machine_LogicalDisk_UnstableSamples 9data.Cluster_Machine_LogicalDisk_Volume_StableSamples 10data.Cluster_Machine_Memory_Capacity_StableSamples 11data.Cluster_Machine_Memory_UnstableSamples 12data.Cluster_Machine_Network_Capacity_StableSamples 13data.Cluster_Machine_Network_Keys 14data.Cluster_Machine_Network_Sightings 15data.Cluster_Machine_Network_UnstableSamples 16data.Cluster_Machine_OperatingSystem_StableSamples 17data.Cluster_Machine_Ping_UnstableSamples 18data.Cluster_Machine_Process_Instances 19data.Cluster_Machine_Process_Keys 20data.Cluster_Machine_Process_Owner_Instances 21data.Cluster_Machine_Process_Sightings 22data.Cluster_Machine_Process_UnstableSamples 23… There are two things I want to draw your attention to: The table names describe a hierarchy of the different types of object that are monitored by SQL Monitor (e.g. clusters, machines and disks). For each object type in the hierarchy, there are multiple tables, ending in the suffixes _Keys, _Sightings, _StableSamples and _UnstableSamples. Not every object type has a table for every suffix, but the _Keys suffix is especially important and a _Keys table does indeed exist for every object type. In fact, if we limit the query to return only those tables ending in _Keys, we reveal the full object hierarchy: SELECT sch.name + '.' + obj.name AS [name] FROM sys.objects obj JOIN sys.schemas sch ON sch.schema_id = obj.schema_id WHERE obj.type_desc = 'USER_TABLE' AND sch.name = 'data' AND obj.name LIKE '%_Keys' ORDER BY sch.name, obj.name;  name 1data.Cluster_Keys 2data.Cluster_Machine_Keys 3data.Cluster_Machine_LogicalDisk_Keys 4data.Cluster_Machine_Network_Keys 5data.Cluster_Machine_Process_Keys 6data.Cluster_Machine_Services_Keys 7data.Cluster_ResourceGroup_Keys 8data.Cluster_ResourceGroup_Resource_Keys 9data.Cluster_SqlServer_Agent_Job_History_Keys 10data.Cluster_SqlServer_Agent_Job_Keys 11data.Cluster_SqlServer_Database_BackupType_Backup_Keys 12data.Cluster_SqlServer_Database_BackupType_Keys 13data.Cluster_SqlServer_Database_CustomMetric_Keys 14data.Cluster_SqlServer_Database_File_Keys 15data.Cluster_SqlServer_Database_Keys 16data.Cluster_SqlServer_Database_Table_Index_Keys 17data.Cluster_SqlServer_Database_Table_Keys 18data.Cluster_SqlServer_Error_Keys 19data.Cluster_SqlServer_Keys 20data.Cluster_SqlServer_Services_Keys 21data.Cluster_SqlServer_SqlProcess_Keys 22data.Cluster_SqlServer_TopQueries_Keys 23data.Cluster_SqlServer_Trace_Keys 24data.Group_Keys The full object type hierarchy looks like this: Cluster Machine LogicalDisk Network Process Services ResourceGroup Resource SqlServer Agent Job History Database BackupType Backup CustomMetric File Table Index Error Services SqlProcess TopQueries Trace Group Okay, but what about the individual objects themselves represented at each level in this hierarchy? Well that’s what the _Keys tables are for. This is probably best illustrated by way of a simple example – how can I query my own data repository to find the databases on my own PC for which monitoring data has been collected? Like this: SELECT clstr._Name AS cluster_name, srvr._Name AS instance_name, db._Name AS database_name FROM data.Cluster_SqlServer_Database_Keys db JOIN data.Cluster_SqlServer_Keys srvr ON db.ParentId = srvr.Id -- Note here how the parent of a Database is a Server JOIN data.Cluster_Keys clstr ON srvr.ParentId = clstr.Id -- Note here how the parent of a Server is a Cluster WHERE clstr._Name = 'dev-chrisl2' -- This is the hostname of my own PC ORDER BY clstr._Name, srvr._Name, db._Name;  cluster_nameinstance_namedatabase_name 1dev-chrisl2SqlMonitorData 2dev-chrisl2master 3dev-chrisl2model 4dev-chrisl2msdb 5dev-chrisl2mssqlsystemresource 6dev-chrisl2tempdb 7dev-chrisl2sql2005SqlMonitorData 8dev-chrisl2sql2005TestDatabase 9dev-chrisl2sql2005master 10dev-chrisl2sql2005model 11dev-chrisl2sql2005msdb 12dev-chrisl2sql2005mssqlsystemresource 13dev-chrisl2sql2005tempdb 14dev-chrisl2sql2008SqlMonitorData 15dev-chrisl2sql2008master 16dev-chrisl2sql2008model 17dev-chrisl2sql2008msdb 18dev-chrisl2sql2008mssqlsystemresource 19dev-chrisl2sql2008tempdb These results show that I have three SQL Server instances on my machine (a default instance, one named sql2005 and one named sql2008), and each instance has the usual set of system databases, along with a database named SqlMonitorData. Basically, this is where I test SQL Monitor on different versions of SQL Server, when I’m developing. There are a few important things we can learn from this query: Each _Keys table has a column named Id. This is the primary key. Each _Keys table has a column named ParentId. A foreign key relationship is defined between each _Keys table and its parent _Keys table in the hierarchy. There are two exceptions to this, Cluster_Keys and Group_Keys, because clusters and groups live at the root level of the object hierarchy. Each _Keys table has a column named _Name. This is used to uniquely identify objects in the table within the scope of the same shared parent object. Actually, that last item isn’t always true. In some cases, the _Name column is actually called something else. For example, the data.Cluster_Machine_Services_Keys table has a column named _ServiceName instead of _Name (sorry for the inconsistency). In other cases, a name isn’t sufficient to uniquely identify an object. For example, right now my PC has multiple processes running, all sharing the same name, Chrome (one for each tab open in my web-browser). In such cases, multiple columns are used to uniquely identify an object within the scope of the same shared parent object. Well, that’s it for now. I’ve given you enough information for you to explore the _Keys tables to see how objects are stored in your own data repositories. In a future post, I’ll try to explain how monitoring data is stored for each object, using the _StableSamples and _UnstableSamples tables. If you have any questions about this post, or suggestions for future posts, just submit them in the comments section below.

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• SQL – Migrate Database from SQL Server to NuoDB – A Quick Tutorial

  - by Pinal Dave

  Data is growing exponentially and every organization with growing data is thinking of next big innovation in the world of Big Data. Big data is a indeed a future for every organization at one point of the time. Just like every other next big thing, big data has its own challenges and issues. The biggest challenge associated with the big data is to find the ideal platform which supports the scalability and growth of the data. If you are a regular reader of this blog, you must be familiar with NuoDB. I have been working with NuoDB for a while and their recent release is the best thus far. NuoDB is an elastically scalable SQL database that can run on local host, datacenter and cloud-based resources. A key feature of the product is that it does not require sharding (read more here). Last week, I was able to install NuoDB in less than 90 seconds and have explored their Explorer and Admin sections. You can read about my experiences in these posts: SQL – Step by Step Guide to Download and Install NuoDB – Getting Started with NuoDB SQL – Quick Start with Admin Sections of NuoDB – Manage NuoDB Database SQL – Quick Start with Explorer Sections of NuoDB – Query NuoDB Database Many SQL Authority readers have been following me in my journey to evaluate NuoDB. One of the frequently asked questions I’ve received from you is if there is any way to migrate data from SQL Server to NuoDB. The fact is that there is indeed a way to do so and NuoDB provides a fantastic tool which can help users to do it. NuoDB Migrator is a command line utility that supports the migration of Microsoft SQL Server, MySQL, Oracle, and PostgreSQL schemas and data to NuoDB. The migration to NuoDB is a three-step process: NuoDB Migrator generates a schema for a target NuoDB database It loads data into the target NuoDB database It dumps data from the source database Let’s see how we can migrate our data from SQL Server to NuoDB using a simple three-step approach. But before we do that we will create a sample database in MSSQL and later we will migrate the same database to NuoDB: Setup Step 1: Build a sample data CREATE DATABASE [Test]; CREATE TABLE [Department]( [DepartmentID] [smallint] NOT NULL, [Name] VARCHAR(100) NOT NULL, [GroupName] VARCHAR(100) NOT NULL, [ModifiedDate] [datetime] NOT NULL, CONSTRAINT [PK_Department_DepartmentID] PRIMARY KEY CLUSTERED ( [DepartmentID] ASC ) ) ON [PRIMARY]; INSERT INTO Department SELECT * FROM AdventureWorks2012.HumanResources.Department; Note that I am using the SQL Server AdventureWorks database to build this sample table but you can build this sample table any way you prefer. Setup Step 2: Install Java 64 bit Before you can begin the migration process to NuoDB, make sure you have 64-bit Java installed on your computer. This is due to the fact that the NuoDB Migrator tool is built in Java. You can download 64-bit Java for Windows, Mac OSX, or Linux from the following link: http://java.com/en/download/manual.jsp. One more thing to remember is that you make sure that the path in your environment settings is set to your JAVA_HOME directory or else the tool will not work. Here is how you can do it: Go to My Computer >> Right Click >> Select Properties >> Click on Advanced System Settings >> Click on Environment Variables >> Click on New and enter the following values. Variable Name: JAVA_HOME Variable Value: C:\Program Files\Java\jre7 Make sure you enter your Java installation directory in the Variable Value field. Setup Step 3: Install JDBC driver for SQL Server. There are two JDBC drivers available for SQL Server.  Select the one you prefer to use by following one of the two links below: Microsoft JDBC Driver jTDS JDBC Driver In this example we will be using jTDS JDBC driver. Once you download the driver, move the driver to your NuoDB installation folder. In my case, I have moved the JAR file of the driver into the C:\Program Files\NuoDB\tools\migrator\jar folder as this is my NuoDB installation directory. Now we are all set to start the three-step migration process from SQL Server to NuoDB: Migration Step 1: NuoDB Schema Generation Here is the command I use to generate a schema of my SQL Server Database in NuoDB. First I go to the folder C:\Program Files\NuoDB\tools\migrator\bin and execute the nuodb-migrator.bat file. Note that my database name is ‘test’. Additionally my username and password is also ‘test’. You can see that my SQL Server database is running on my localhost on port 1433. Additionally, the schema of the table is ‘dbo’. nuodb-migrator schema –source.driver=net.sourceforge.jtds.jdbc.Driver –source.url=jdbc:jtds:sqlserver://localhost:1433/ –source.username=test –source.password=test –source.catalog=test –source.schema=dbo –output.path=/tmp/schema.sql The above script will generate a schema of all my SQL Server tables and will put it in the folder C:\tmp\schema.sql . You can open the schema.sql file and execute this file directly in your NuoDB instance. You can follow the link here to see how you can execute the SQL script in NuoDB. Please note that if you have not yet created the schema in the NuoDB database, you should create it before executing this step. Step 2: Generate the Dump File of the Data Once you have recreated your schema in NuoDB from SQL Server, the next step is very easy. Here we create a CSV format dump file, which will contain all the data from all the tables from the SQL Server database. The command to do so is very similar to the above command. Be aware that this step may take a bit of time based on your database size. nuodb-migrator dump –source.driver=net.sourceforge.jtds.jdbc.Driver –source.url=jdbc:jtds:sqlserver://localhost:1433/ –source.username=test –source.password=test –source.catalog=test –source.schema=dbo –output.type=csv –output.path=/tmp/dump.cat Once the above command is successfully executed you can find your CSV file in the C:\tmp\ folder. However, you do not have to do anything manually. The third and final step will take care of completing the migration process. Migration Step 3: Load the Data into NuoDB After building schema and taking a dump of the data, the very next step is essential and crucial. It will take the CSV file and load it into the NuoDB database. nuodb-migrator load –target.url=jdbc:com.nuodb://localhost:48004/mytest –target.schema=dbo –target.username=test –target.password=test –input.path=/tmp/dump.cat Please note that in the above script we are now targeting the NuoDB database, which we have already created with the name of “MyTest”. If the database does not exist, create it manually before executing the above script. I have kept the username and password as “test”, but please make sure that you create a more secure password for your database for security reasons. Voila!  You’re Done That’s it. You are done. It took 3 setup and 3 migration steps to migrate your SQL Server database to NuoDB.  You can now start exploring the database and build excellent, scale-out applications. In this blog post, I have done my best to come up with simple and easy process, which you can follow to migrate your app from SQL Server to NuoDB. Download NuoDB I strongly encourage you to download NuoDB and go through my 3-step migration tutorial from SQL Server to NuoDB. Additionally here are two very important blog post from NuoDB CTO Seth Proctor. He has written excellent blog posts on the concept of the Administrative Domains. NuoDB has this concept of an Administrative Domain, which is a collection of hosts that can run one or multiple databases.  Each database has its own TEs and SMs, but all are managed within the Admin Console for that particular domain. http://www.nuodb.com/techblog/2013/03/11/getting-started-provisioning-a-domain/ http://www.nuodb.com/techblog/2013/03/14/getting-started-running-a-database/ Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: NuoDB

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• Types of Open

  - by EmbeddedInsider

  Good post here from Bill Anderson http://scienceblogs.com/bookoftrogool/2010/03/battle_of_the_opens.php

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• Types of ER Diagrams

  - by syrion

  I'm currently taking a class for database design, and we're using the ER diagram style designed by Peter Chen. I have a couple of problems with this style: Keys in relationships don't seem realistic. In practice, synthetic keys like "orderid" seem to be used in almost all tables, including association tables, but the Chen style diagrams heavily favor (table1key, table2key) compound keys. There is no notation for datatype. The diamond shape for associations is horrible, and produces a cluttered diagram. In general, it just seems hard to capture some relationships with the Chen system. What ERD style, if any, do you use? What has been the most popular in your workplaces? What tools have you used, or do you use, to create these diagrams?

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• Ameristar Wins with Oracle GoldenGate’s Heterogeneous Real-Time Data Integration

  - by Irem Radzik

  Today we announced a press release about another successful project with Oracle GoldenGate. This time at Ameristar. Ameristar is a casino gaming company and needed a single data integration solution to connect multiple heterogeneous systems to its Teradata data warehouse. The project involves integration of Ameristar’s promotional and gaming data from 14 data sources across its 7 casino hotel properties in real time into a central Teradata data warehouse. The source systems include the Aristocrat gaming and MGT promotional management platforms running on Microsoft SQL Server 2000 databases. As you can notice, there was no Oracle Database involved in this project, but Ameristar’s IT leadership knew that  GoldenGate’s strong heterogeneous and real-time data integration capabilities is the right technology for their data warehousing project. With GoldenGate Ameristar was able to reduce data latency to the enterprise data warehouse, and use this real-time customer information for marketing teams in improving overall customer experience. Ameristar customers receive more targeted and timely campaign offers, and the company has more up-to-date visibility into financial metrics of the company. One other key benefit the company experienced with GoldenGate is in operational costs. The previous data capture solution Ameristar used was trigger based and required a lot of effort to manage. They needed dedicated IT staff to maintain it. With GoldenGate, the solution runs seamlessly without needing a fully-dedicated staff, giving the IT team at Ameristar more resources for their other IT projects. If you want to learn more about GoldenGate and the latest features for Oracle Database and non-Oracle databases, please watch our on demand webcast about Oracle GoldenGate 11g Release 2.

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• Declaring Anonymous Types in VB

  Using an anonymous type in VB, which is essential for technologies like LINQ, means that the compiler will generate a class for you based on context and named initializers saving you time and effort. To learn more read on.

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