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  • how to convert server datetime to client machine datetime for the website.

    - by Shailendra
    I have datetime fieldI have datetime field into the database which stores the universal time i.e. UTC time. I want to show the datetime at the client machine in clients time zone and format. Example: Someone from US updated the database field for a site and it is stored into the UTC format. Someone from India goes and sees the site . What i want is that the person from India sees the time in IST or from Australia sees in his local machines time format not the server time format and zone. Whats the best way to do this ?? Please paste code snippet if you have. Thanx in advance!

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  • rspec mocking object property assignment

    - by charlielee
    I have a rspec mocked object, a value is assign to is property. I am struggleing to have that expectation met in my rspec test. Just wondering what the sytax is? The code: def create @new_campaign = AdCampaign.new(params[:new_campaign]) @new_campaign.creationDate = "#{Time.now.year}/#{Time.now.mon}/#{Time.now.day}" if @new_campaign.save flash[:status] = "Success" else flash[:status] = "Failed" end end The test it "should able to create new campaign when form is submitted" do campaign_model = mock_model(AdCampaign) AdCampaign.should_receive(:new).with(params[:new_campaign]).and_return(campaign_model) campaign_model.should_receive(:creationDate).with("#{Time.now.year}/#{Time.now.mon}/#{Time.now.day}")campaign_model.should_receive(:save).and_return(true) post :create flash[:status].should == 'Success' response.should render_template('create') end The problem is I am getting this error: Spec::Mocks::MockExpectationError in 'CampaignController new campaigns should able to create new campaign when form is submitted' Mock "AdCampaign_1002" received unexpected message :creationDate= with ("2010/5/7") So how do i set a expectation for object property assignment? Thanks

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  • Inconsistent Session data from IE - cached sessions???

    - by pedalpete
    I'm trying to prevent some basic click-fraud on my site, and am building links based on session time data. Everything works in FF, but in IE the information I'm storing in the session is somehow being changed. When I load up the main page, I set my session variables like this session_start(); $_SESSION['time']=$time(); I'm out putting the session value into the page, so I get something like 1275512393. When the user clicks on a link, I send an ajax request, and that page is returning the session which I am putting into an alert. session_start(); echo $_SESSION['time']; die(); The alert is returning 1275512422. Only in IE is the $_SESSION['time'] being returned different from the original $_SESSION['time'] It doesn't appear that this is a caching issue, as the times are always VERY near each other, and the second one is always after the first, but I'm not positive.

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  • Information stored in a cookie file

    - by jklmuk
    Thanks for you help in advance. I am trying to figure out the structure of the cookie file, more specifically i want to be able to determine the expiry time. From the cookies i have created they all appear to be in a standard format. Name, Value, website,followed by 5 numbers and a star. See example below. name value www.website.co.uk/ 1536 3041141504 30135951 1632526096 30135949 * Obviously the expiry time is one of the numbers, the question is which one. From experiments I have determined that the first and fifth number don't seem to change. In a case where i generated three cookies at the same time with a 1000 second time difference i noticed that the fourth number appeared to increase by 2000 suggesting that this has a connection with the expiry time. Can anyone confirm if i am heading in the right direction? And does any one know how i convert this to a human time and date(preferably in php but any language would give me a starting point) thanks Jason

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  • Accurate clock in Erlang

    - by buddhabrot
    I was thinking about how to implement a process that gives the number of discrete intervals in time that occurred since it started. Am I losing accuracy here? How do I implement this without loss of accuracy after a while and after heavy client abuse. I am kind of stumped how to do this in Erlang. -module(clock). -compile([export_all]). start(Time) -> register(clock, spawn(fun() -> tick(Time, 0) end)). stop() -> clock ! stop. tick(Time, Count) -> receive nticks -> io:format("~p ticks have passed since start~n", [Count]) after 0 -> true end, receive stop -> void after Time -> tick(Time, Count + 1) end.

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  • Date range advanced count calculation in TSQL

    - by cihata87
    I am working on call center project and I have to calculate the call arrivals at the same time between specific time ranges. I have to write a procedure which has parameters StartTime, EndTime and Interval For Example: Start Time: 11:00 End Time: 12:00 Interval: 20 minutes so program should divide the 1-hour time range into 3 parts and each part should count the arrivals which started and finished in this range OR arrivals which started and haven't finished yet Should be like this: 11:00 - 11:20 15 calls at the same time(TimePeaks) 11:20 - 11:40 21 calls ... 11:40 - 12:00 8 calls ... Any suggestions how to calculate them?

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  • Array as struct database?

    - by user2985179
    I have a struct that reads data from the user: typedef struct { int seconds; } Time; typedef struct { Time time; double distance; } Training; Training input; scanf("%d %lf", input.time.seconds, input.distance); This scanf will be looped and the user can input different data every time, I want to store this data in an array for later use. I THINK I want something like arr[0].seconds and arr[0].distance. I tried to store the entered data in an array but it didn't really work at all... Training data[10]; data[10].seconds = input.time.seconds; data[10].distance = input.distance; The data will wipe when the program closes and that's how I like it to be. So I want it to be stored in an array, no files or databases!

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  • What are good design practices when working with Entity Framework

    - by AD
    This will apply mostly for an asp.net application where the data is not accessed via soa. Meaning that you get access to the objects loaded from the framework, not Transfer Objects, although some recommendation still apply. This is a community post, so please add to it as you see fit. Applies to: Entity Framework 1.0 shipped with Visual Studio 2008 sp1. Why pick EF in the first place? Considering it is a young technology with plenty of problems (see below), it may be a hard sell to get on the EF bandwagon for your project. However, it is the technology Microsoft is pushing (at the expense of Linq2Sql, which is a subset of EF). In addition, you may not be satisfied with NHibernate or other solutions out there. Whatever the reasons, there are people out there (including me) working with EF and life is not bad.make you think. EF and inheritance The first big subject is inheritance. EF does support mapping for inherited classes that are persisted in 2 ways: table per class and table the hierarchy. The modeling is easy and there are no programming issues with that part. (The following applies to table per class model as I don't have experience with table per hierarchy, which is, anyway, limited.) The real problem comes when you are trying to run queries that include one or many objects that are part of an inheritance tree: the generated sql is incredibly awful, takes a long time to get parsed by the EF and takes a long time to execute as well. This is a real show stopper. Enough that EF should probably not be used with inheritance or as little as possible. Here is an example of how bad it was. My EF model had ~30 classes, ~10 of which were part of an inheritance tree. On running a query to get one item from the Base class, something as simple as Base.Get(id), the generated SQL was over 50,000 characters. Then when you are trying to return some Associations, it degenerates even more, going as far as throwing SQL exceptions about not being able to query more than 256 tables at once. Ok, this is bad, EF concept is to allow you to create your object structure without (or with as little as possible) consideration on the actual database implementation of your table. It completely fails at this. So, recommendations? Avoid inheritance if you can, the performance will be so much better. Use it sparingly where you have to. In my opinion, this makes EF a glorified sql-generation tool for querying, but there are still advantages to using it. And ways to implement mechanism that are similar to inheritance. Bypassing inheritance with Interfaces First thing to know with trying to get some kind of inheritance going with EF is that you cannot assign a non-EF-modeled class a base class. Don't even try it, it will get overwritten by the modeler. So what to do? You can use interfaces to enforce that classes implement some functionality. For example here is a IEntity interface that allow you to define Associations between EF entities where you don't know at design time what the type of the entity would be. public enum EntityTypes{ Unknown = -1, Dog = 0, Cat } public interface IEntity { int EntityID { get; } string Name { get; } Type EntityType { get; } } public partial class Dog : IEntity { // implement EntityID and Name which could actually be fields // from your EF model Type EntityType{ get{ return EntityTypes.Dog; } } } Using this IEntity, you can then work with undefined associations in other classes // lets take a class that you defined in your model. // that class has a mapping to the columns: PetID, PetType public partial class Person { public IEntity GetPet() { return IEntityController.Get(PetID,PetType); } } which makes use of some extension functions: public class IEntityController { static public IEntity Get(int id, EntityTypes type) { switch (type) { case EntityTypes.Dog: return Dog.Get(id); case EntityTypes.Cat: return Cat.Get(id); default: throw new Exception("Invalid EntityType"); } } } Not as neat as having plain inheritance, particularly considering you have to store the PetType in an extra database field, but considering the performance gains, I would not look back. It also cannot model one-to-many, many-to-many relationship, but with creative uses of 'Union' it could be made to work. Finally, it creates the side effet of loading data in a property/function of the object, which you need to be careful about. Using a clear naming convention like GetXYZ() helps in that regards. Compiled Queries Entity Framework performance is not as good as direct database access with ADO (obviously) or Linq2SQL. There are ways to improve it however, one of which is compiling your queries. The performance of a compiled query is similar to Linq2Sql. What is a compiled query? It is simply a query for which you tell the framework to keep the parsed tree in memory so it doesn't need to be regenerated the next time you run it. So the next run, you will save the time it takes to parse the tree. Do not discount that as it is a very costly operation that gets even worse with more complex queries. There are 2 ways to compile a query: creating an ObjectQuery with EntitySQL and using CompiledQuery.Compile() function. (Note that by using an EntityDataSource in your page, you will in fact be using ObjectQuery with EntitySQL, so that gets compiled and cached). An aside here in case you don't know what EntitySQL is. It is a string-based way of writing queries against the EF. Here is an example: "select value dog from Entities.DogSet as dog where dog.ID = @ID". The syntax is pretty similar to SQL syntax. You can also do pretty complex object manipulation, which is well explained [here][1]. Ok, so here is how to do it using ObjectQuery< string query = "select value dog " + "from Entities.DogSet as dog " + "where dog.ID = @ID"; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>(query, EntityContext.Instance)); oQuery.Parameters.Add(new ObjectParameter("ID", id)); oQuery.EnablePlanCaching = true; return oQuery.FirstOrDefault(); The first time you run this query, the framework will generate the expression tree and keep it in memory. So the next time it gets executed, you will save on that costly step. In that example EnablePlanCaching = true, which is unnecessary since that is the default option. The other way to compile a query for later use is the CompiledQuery.Compile method. This uses a delegate: static readonly Func<Entities, int, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, Dog>((ctx, id) => ctx.DogSet.FirstOrDefault(it => it.ID == id)); or using linq static readonly Func<Entities, int, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, Dog>((ctx, id) => (from dog in ctx.DogSet where dog.ID == id select dog).FirstOrDefault()); to call the query: query_GetDog.Invoke( YourContext, id ); The advantage of CompiledQuery is that the syntax of your query is checked at compile time, where as EntitySQL is not. However, there are other consideration... Includes Lets say you want to have the data for the dog owner to be returned by the query to avoid making 2 calls to the database. Easy to do, right? EntitySQL string query = "select value dog " + "from Entities.DogSet as dog " + "where dog.ID = @ID"; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>(query, EntityContext.Instance)).Include("Owner"); oQuery.Parameters.Add(new ObjectParameter("ID", id)); oQuery.EnablePlanCaching = true; return oQuery.FirstOrDefault(); CompiledQuery static readonly Func<Entities, int, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, Dog>((ctx, id) => (from dog in ctx.DogSet.Include("Owner") where dog.ID == id select dog).FirstOrDefault()); Now, what if you want to have the Include parametrized? What I mean is that you want to have a single Get() function that is called from different pages that care about different relationships for the dog. One cares about the Owner, another about his FavoriteFood, another about his FavotireToy and so on. Basicly, you want to tell the query which associations to load. It is easy to do with EntitySQL public Dog Get(int id, string include) { string query = "select value dog " + "from Entities.DogSet as dog " + "where dog.ID = @ID"; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>(query, EntityContext.Instance)) .IncludeMany(include); oQuery.Parameters.Add(new ObjectParameter("ID", id)); oQuery.EnablePlanCaching = true; return oQuery.FirstOrDefault(); } The include simply uses the passed string. Easy enough. Note that it is possible to improve on the Include(string) function (that accepts only a single path) with an IncludeMany(string) that will let you pass a string of comma-separated associations to load. Look further in the extension section for this function. If we try to do it with CompiledQuery however, we run into numerous problems: The obvious static readonly Func<Entities, int, string, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, string, Dog>((ctx, id, include) => (from dog in ctx.DogSet.Include(include) where dog.ID == id select dog).FirstOrDefault()); will choke when called with: query_GetDog.Invoke( YourContext, id, "Owner,FavoriteFood" ); Because, as mentionned above, Include() only wants to see a single path in the string and here we are giving it 2: "Owner" and "FavoriteFood" (which is not to be confused with "Owner.FavoriteFood"!). Then, let's use IncludeMany(), which is an extension function static readonly Func<Entities, int, string, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, string, Dog>((ctx, id, include) => (from dog in ctx.DogSet.IncludeMany(include) where dog.ID == id select dog).FirstOrDefault()); Wrong again, this time it is because the EF cannot parse IncludeMany because it is not part of the functions that is recognizes: it is an extension. Ok, so you want to pass an arbitrary number of paths to your function and Includes() only takes a single one. What to do? You could decide that you will never ever need more than, say 20 Includes, and pass each separated strings in a struct to CompiledQuery. But now the query looks like this: from dog in ctx.DogSet.Include(include1).Include(include2).Include(include3) .Include(include4).Include(include5).Include(include6) .[...].Include(include19).Include(include20) where dog.ID == id select dog which is awful as well. Ok, then, but wait a minute. Can't we return an ObjectQuery< with CompiledQuery? Then set the includes on that? Well, that what I would have thought so as well: static readonly Func<Entities, int, ObjectQuery<Dog>> query_GetDog = CompiledQuery.Compile<Entities, int, string, ObjectQuery<Dog>>((ctx, id) => (ObjectQuery<Dog>)(from dog in ctx.DogSet where dog.ID == id select dog)); public Dog GetDog( int id, string include ) { ObjectQuery<Dog> oQuery = query_GetDog(id); oQuery = oQuery.IncludeMany(include); return oQuery.FirstOrDefault; } That should have worked, except that when you call IncludeMany (or Include, Where, OrderBy...) you invalidate the cached compiled query because it is an entirely new one now! So, the expression tree needs to be reparsed and you get that performance hit again. So what is the solution? You simply cannot use CompiledQueries with parametrized Includes. Use EntitySQL instead. This doesn't mean that there aren't uses for CompiledQueries. It is great for localized queries that will always be called in the same context. Ideally CompiledQuery should always be used because the syntax is checked at compile time, but due to limitation, that's not possible. An example of use would be: you may want to have a page that queries which two dogs have the same favorite food, which is a bit narrow for a BusinessLayer function, so you put it in your page and know exactly what type of includes are required. Passing more than 3 parameters to a CompiledQuery Func is limited to 5 parameters, of which the last one is the return type and the first one is your Entities object from the model. So that leaves you with 3 parameters. A pitance, but it can be improved on very easily. public struct MyParams { public string param1; public int param2; public DateTime param3; } static readonly Func<Entities, MyParams, IEnumerable<Dog>> query_GetDog = CompiledQuery.Compile<Entities, MyParams, IEnumerable<Dog>>((ctx, myParams) => from dog in ctx.DogSet where dog.Age == myParams.param2 && dog.Name == myParams.param1 and dog.BirthDate > myParams.param3 select dog); public List<Dog> GetSomeDogs( int age, string Name, DateTime birthDate ) { MyParams myParams = new MyParams(); myParams.param1 = name; myParams.param2 = age; myParams.param3 = birthDate; return query_GetDog(YourContext,myParams).ToList(); } Return Types (this does not apply to EntitySQL queries as they aren't compiled at the same time during execution as the CompiledQuery method) Working with Linq, you usually don't force the execution of the query until the very last moment, in case some other functions downstream wants to change the query in some way: static readonly Func<Entities, int, string, IEnumerable<Dog>> query_GetDog = CompiledQuery.Compile<Entities, int, string, IEnumerable<Dog>>((ctx, age, name) => from dog in ctx.DogSet where dog.Age == age && dog.Name == name select dog); public IEnumerable<Dog> GetSomeDogs( int age, string name ) { return query_GetDog(YourContext,age,name); } public void DataBindStuff() { IEnumerable<Dog> dogs = GetSomeDogs(4,"Bud"); // but I want the dogs ordered by BirthDate gridView.DataSource = dogs.OrderBy( it => it.BirthDate ); } What is going to happen here? By still playing with the original ObjectQuery (that is the actual return type of the Linq statement, which implements IEnumerable), it will invalidate the compiled query and be force to re-parse. So, the rule of thumb is to return a List< of objects instead. static readonly Func<Entities, int, string, IEnumerable<Dog>> query_GetDog = CompiledQuery.Compile<Entities, int, string, IEnumerable<Dog>>((ctx, age, name) => from dog in ctx.DogSet where dog.Age == age && dog.Name == name select dog); public List<Dog> GetSomeDogs( int age, string name ) { return query_GetDog(YourContext,age,name).ToList(); //<== change here } public void DataBindStuff() { List<Dog> dogs = GetSomeDogs(4,"Bud"); // but I want the dogs ordered by BirthDate gridView.DataSource = dogs.OrderBy( it => it.BirthDate ); } When you call ToList(), the query gets executed as per the compiled query and then, later, the OrderBy is executed against the objects in memory. It may be a little bit slower, but I'm not even sure. One sure thing is that you have no worries about mis-handling the ObjectQuery and invalidating the compiled query plan. Once again, that is not a blanket statement. ToList() is a defensive programming trick, but if you have a valid reason not to use ToList(), go ahead. There are many cases in which you would want to refine the query before executing it. Performance What is the performance impact of compiling a query? It can actually be fairly large. A rule of thumb is that compiling and caching the query for reuse takes at least double the time of simply executing it without caching. For complex queries (read inherirante), I have seen upwards to 10 seconds. So, the first time a pre-compiled query gets called, you get a performance hit. After that first hit, performance is noticeably better than the same non-pre-compiled query. Practically the same as Linq2Sql When you load a page with pre-compiled queries the first time you will get a hit. It will load in maybe 5-15 seconds (obviously more than one pre-compiled queries will end up being called), while subsequent loads will take less than 300ms. Dramatic difference, and it is up to you to decide if it is ok for your first user to take a hit or you want a script to call your pages to force a compilation of the queries. Can this query be cached? { Dog dog = from dog in YourContext.DogSet where dog.ID == id select dog; } No, ad-hoc Linq queries are not cached and you will incur the cost of generating the tree every single time you call it. Parametrized Queries Most search capabilities involve heavily parametrized queries. There are even libraries available that will let you build a parametrized query out of lamba expressions. The problem is that you cannot use pre-compiled queries with those. One way around that is to map out all the possible criteria in the query and flag which one you want to use: public struct MyParams { public string name; public bool checkName; public int age; public bool checkAge; } static readonly Func<Entities, MyParams, IEnumerable<Dog>> query_GetDog = CompiledQuery.Compile<Entities, MyParams, IEnumerable<Dog>>((ctx, myParams) => from dog in ctx.DogSet where (myParams.checkAge == true && dog.Age == myParams.age) && (myParams.checkName == true && dog.Name == myParams.name ) select dog); protected List<Dog> GetSomeDogs() { MyParams myParams = new MyParams(); myParams.name = "Bud"; myParams.checkName = true; myParams.age = 0; myParams.checkAge = false; return query_GetDog(YourContext,myParams).ToList(); } The advantage here is that you get all the benifits of a pre-compiled quert. The disadvantages are that you most likely will end up with a where clause that is pretty difficult to maintain, that you will incur a bigger penalty for pre-compiling the query and that each query you run is not as efficient as it could be (particularly with joins thrown in). Another way is to build an EntitySQL query piece by piece, like we all did with SQL. protected List<Dod> GetSomeDogs( string name, int age) { string query = "select value dog from Entities.DogSet where 1 = 1 "; if( !String.IsNullOrEmpty(name) ) query = query + " and dog.Name == @Name "; if( age > 0 ) query = query + " and dog.Age == @Age "; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>( query, YourContext ); if( !String.IsNullOrEmpty(name) ) oQuery.Parameters.Add( new ObjectParameter( "Name", name ) ); if( age > 0 ) oQuery.Parameters.Add( new ObjectParameter( "Age", age ) ); return oQuery.ToList(); } Here the problems are: - there is no syntax checking during compilation - each different combination of parameters generate a different query which will need to be pre-compiled when it is first run. In this case, there are only 4 different possible queries (no params, age-only, name-only and both params), but you can see that there can be way more with a normal world search. - Noone likes to concatenate strings! Another option is to query a large subset of the data and then narrow it down in memory. This is particularly useful if you are working with a definite subset of the data, like all the dogs in a city. You know there are a lot but you also know there aren't that many... so your CityDog search page can load all the dogs for the city in memory, which is a single pre-compiled query and then refine the results protected List<Dod> GetSomeDogs( string name, int age, string city) { string query = "select value dog from Entities.DogSet where dog.Owner.Address.City == @City "; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>( query, YourContext ); oQuery.Parameters.Add( new ObjectParameter( "City", city ) ); List<Dog> dogs = oQuery.ToList(); if( !String.IsNullOrEmpty(name) ) dogs = dogs.Where( it => it.Name == name ); if( age > 0 ) dogs = dogs.Where( it => it.Age == age ); return dogs; } It is particularly useful when you start displaying all the data then allow for filtering. Problems: - Could lead to serious data transfer if you are not careful about your subset. - You can only filter on the data that you returned. It means that if you don't return the Dog.Owner association, you will not be able to filter on the Dog.Owner.Name So what is the best solution? There isn't any. You need to pick the solution that works best for you and your problem: - Use lambda-based query building when you don't care about pre-compiling your queries. - Use fully-defined pre-compiled Linq query when your object structure is not too complex. - Use EntitySQL/string concatenation when the structure could be complex and when the possible number of different resulting queries are small (which means fewer pre-compilation hits). - Use in-memory filtering when you are working with a smallish subset of the data or when you had to fetch all of the data on the data at first anyway (if the performance is fine with all the data, then filtering in memory will not cause any time to be spent in the db). Singleton access The best way to deal with your context and entities accross all your pages is to use the singleton pattern: public sealed class YourContext { private const string instanceKey = "On3GoModelKey"; YourContext(){} public static YourEntities Instance { get { HttpContext context = HttpContext.Current; if( context == null ) return Nested.instance; if (context.Items[instanceKey] == null) { On3GoEntities entity = new On3GoEntities(); context.Items[instanceKey] = entity; } return (YourEntities)context.Items[instanceKey]; } } class Nested { // Explicit static constructor to tell C# compiler // not to mark type as beforefieldinit static Nested() { } internal static readonly YourEntities instance = new YourEntities(); } } NoTracking, is it worth it? When executing a query, you can tell the framework to track the objects it will return or not. What does it mean? With tracking enabled (the default option), the framework will track what is going on with the object (has it been modified? Created? Deleted?) and will also link objects together, when further queries are made from the database, which is what is of interest here. For example, lets assume that Dog with ID == 2 has an owner which ID == 10. Dog dog = (from dog in YourContext.DogSet where dog.ID == 2 select dog).FirstOrDefault(); //dog.OwnerReference.IsLoaded == false; Person owner = (from o in YourContext.PersonSet where o.ID == 10 select dog).FirstOrDefault(); //dog.OwnerReference.IsLoaded == true; If we were to do the same with no tracking, the result would be different. ObjectQuery<Dog> oDogQuery = (ObjectQuery<Dog>) (from dog in YourContext.DogSet where dog.ID == 2 select dog); oDogQuery.MergeOption = MergeOption.NoTracking; Dog dog = oDogQuery.FirstOrDefault(); //dog.OwnerReference.IsLoaded == false; ObjectQuery<Person> oPersonQuery = (ObjectQuery<Person>) (from o in YourContext.PersonSet where o.ID == 10 select o); oPersonQuery.MergeOption = MergeOption.NoTracking; Owner owner = oPersonQuery.FirstOrDefault(); //dog.OwnerReference.IsLoaded == false; Tracking is very useful and in a perfect world without performance issue, it would always be on. But in this world, there is a price for it, in terms of performance. So, should you use NoTracking to speed things up? It depends on what you are planning to use the data for. Is there any chance that the data your query with NoTracking can be used to make update/insert/delete in the database? If so, don't use NoTracking because associations are not tracked and will causes exceptions to be thrown. In a page where there are absolutly no updates to the database, you can use NoTracking. Mixing tracking and NoTracking is possible, but it requires you to be extra careful with updates/inserts/deletes. The problem is that if you mix then you risk having the framework trying to Attach() a NoTracking object to the context where another copy of the same object exist with tracking on. Basicly, what I am saying is that Dog dog1 = (from dog in YourContext.DogSet where dog.ID == 2).FirstOrDefault(); ObjectQuery<Dog> oDogQuery = (ObjectQuery<Dog>) (from dog in YourContext.DogSet where dog.ID == 2 select dog); oDogQuery.MergeOption = MergeOption.NoTracking; Dog dog2 = oDogQuery.FirstOrDefault(); dog1 and dog2 are 2 different objects, one tracked and one not. Using the detached object in an update/insert will force an Attach() that will say "Wait a minute, I do already have an object here with the same database key. Fail". And when you Attach() one object, all of its hierarchy gets attached as well, causing problems everywhere. Be extra careful. How much faster is it with NoTracking It depends on the queries. Some are much more succeptible to tracking than other. I don't have a fast an easy rule for it, but it helps. So I should use NoTracking everywhere then? Not exactly. There are some advantages to tracking object. The first one is that the object is cached, so subsequent call for that object will not hit the database. That cache is only valid for the lifetime of the YourEntities object, which, if you use the singleton code above, is the same as the page lifetime. One page request == one YourEntity object. So for multiple calls for the same object, it will load only once per page request. (Other caching mechanism could extend that). What happens when you are using NoTracking and try to load the same object multiple times? The database will be queried each time, so there is an impact there. How often do/should you call for the same object during a single page request? As little as possible of course, but it does happens. Also remember the piece above about having the associations connected automatically for your? You don't have that with NoTracking, so if you load your data in multiple batches, you will not have a link to between them: ObjectQuery<Dog> oDogQuery = (ObjectQuery<Dog>)(from dog in YourContext.DogSet select dog); oDogQuery.MergeOption = MergeOption.NoTracking; List<Dog> dogs = oDogQuery.ToList(); ObjectQuery<Person> oPersonQuery = (ObjectQuery<Person>)(from o in YourContext.PersonSet select o); oPersonQuery.MergeOption = MergeOption.NoTracking; List<Person> owners = oPersonQuery.ToList(); In this case, no dog will have its .Owner property set. Some things to keep in mind when you are trying to optimize the performance. No lazy loading, what am I to do? This can be seen as a blessing in disguise. Of course it is annoying to load everything manually. However, it decreases the number of calls to the db and forces you to think about when you should load data. The more you can load in one database call the better. That was always true, but it is enforced now with this 'feature' of EF. Of course, you can call if( !ObjectReference.IsLoaded ) ObjectReference.Load(); if you want to, but a better practice is to force the framework to load the objects you know you will need in one shot. This is where the discussion about parametrized Includes begins to make sense. Lets say you have you Dog object public class Dog { public Dog Get(int id) { return YourContext.DogSet.FirstOrDefault(it => it.ID == id ); } } This is the type of function you work with all the time. It gets called from all over the place and once you have that Dog object, you will do very different things to it in different functions. First, it should be pre-compiled, because you will call that very often. Second, each different pages will want to have access to a different subset of the Dog data. Some will want the Owner, some the FavoriteToy, etc. Of course, you could call Load() for each reference you need anytime you need one. But that will generate a call to the database each time. Bad idea. So instead, each page will ask for the data it wants to see when it first request for the Dog object: static public Dog Get(int id) { return GetDog(entity,"");} static public Dog Get(int id, string includePath) { string query = "select value o " + " from YourEntities.DogSet as o " +

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  • Converting linear colors to SRGB shows banding in FFmpeg

    - by user1863947
    When I convert an EXR file sequence with x264 using FFmpeg and convert the colorspace from linear to SRGB (with gamma 0.45454545) I get some heavy banding issues (most visible on a dark gradient). Here is the ffmpeg command I use: C:/ffmpeg.exe -y -i C:/seq_v001.%04d.exr -vf lutrgb=r=gammaval(0.45454545):g=gammaval(0.45454545):b=gammaval(0.45454545) -vcodec libx264 -pix_fmt yuv420p -preset slow -crf 18 -r 25 C:/out.mov Here is the output: ffmpeg version N-47062-g26c531c Copyright (c) 2000-2012 the FFmpeg developers built on Nov 25 2012 12:25:21 with gcc 4.7.2 (GCC) configuration: --enable-gpl --enable-version3 --disable-pthreads --enable-runtime-cpudetect --enable-avisynth --enable-bzlib --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libfreetype --enable-libgsm --enable-libmp3lame --enable-libnut --enable-libopenjpeg --enable-libopus --enable-librtmp --enable-libschroedinger --enable-libspeex --enable-libtheora --enable-libutvideo --enable-libvo-aacenc --enable-libvo-amrwbenc --enable-libvorbis --enable-libvpx --enable-libx264 --enable-libxavs --enable-libxvid --enable-zlib libavutil 52. 9.100 / 52. 9.100 libavcodec 54. 77.100 / 54. 77.100 libavformat 54. 37.100 / 54. 37.100 libavdevice 54. 3.100 / 54. 3.100 libavfilter 3. 23.102 / 3. 23.102 libswscale 2. 1.102 / 2. 1.102 libswresample 0. 17.101 / 0. 17.101 libpostproc 52. 2.100 / 52. 2.100 Input #0, image2, from 'C:/seq_v001.%04d.exr': Duration: 00:00:09.60, start: 0.000000, bitrate: N/A Stream #0:0: Video: exr, rgb48le, 960x540 [SAR 1:1 DAR 16:9], 25 fps, 25 tbr, 25 tbn, 25 tbc [libx264 @ 0000000004d11540] using SAR=1/1 [libx264 @ 0000000004d11540] using cpu capabilities: MMX2 SSE2Fast SSSE3 FastShuffle SSE4.2 [libx264 @ 0000000004d11540] profile High, level 3.1 [libx264 @ 0000000004d11540] 264 - core 128 r2216 198a7ea - H.264/MPEG-4 AVC codec - Copyleft 2003-2012 - http://www.videolan.org/x264.html - options: cabac=1 ref=5 deblock=1:0:0 analyse=0x3:0x113 me=umh subme=8 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=18 lookahead_threads=3 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=2 b_bias=0 direct=3 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=50 rc=crf mbtree=1 crf=18.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00 Output #0, mov, to 'C:/out.mov': Metadata: encoder : Lavf54.37.100 Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p, 960x540 [SAR 1:1 DAR 16:9], q=-1--1, 12800 tbn, 25 tbc Stream mapping: Stream #0:0 -> #0:0 (exr -> libx264) Press [q] to stop, [?] for help [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute frame= 16 fps=0.0 q=0.0 size= 0kB time=00:00:00.00 bitrate= 0.0kbits/s Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute frame= 34 fps= 33 q=0.0 size= 0kB time=00:00:00.00 bitrate= 0.0kbits/s Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute frame= 52 fps= 34 q=0.0 size= 0kB time=00:00:00.00 bitrate= 0.0kbits/s Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute frame= 68 fps= 34 q=0.0 size= 0kB time=00:00:00.00 bitrate= 0.0kbits/s Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute frame= 85 fps= 33 q=23.0 size= 47kB time=00:00:00.44 bitrate= 867.5kbits/s Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute frame= 104 fps= 34 q=23.0 size= 94kB time=00:00:01.20 bitrate= 640.3kbits/s Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute frame= 121 fps= 34 q=23.0 size= 133kB time=00:00:01.88 bitrate= 577.8kbits/s Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute frame= 139 fps= 34 q=23.0 size= 172kB time=00:00:02.60 bitrate= 543.4kbits/s Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute frame= 157 fps= 34 q=23.0 size= 213kB time=00:00:03.32 bitrate= 525.6kbits/s Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute frame= 175 fps= 34 q=23.0 size= 254kB time=00:00:04.04 bitrate= 516.0kbits/s Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute frame= 193 fps= 35 q=23.0 size= 287kB time=00:00:04.76 bitrate= 494.6kbits/s Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute frame= 211 fps= 35 q=23.0 size= 332kB time=00:00:05.48 bitrate= 496.4kbits/s Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute [exr @ 000000000dffa660] Found more than one compression attribute [exr @ 000000000dffaaa0] Found more than one compression attribute [exr @ 000000000dffaf00] Found more than one compression attribute [exr @ 000000000dffb340] Found more than one compression attribute [exr @ 000000000dffb7a0] Found more than one compression attribute [exr @ 000000000dffbbe0] Found more than one compression attribute [exr @ 000000000dffc040] Found more than one compression attribute [exr @ 000000000dff8c40] Found more than one compression attribute [exr @ 000000000dff90c0] Found more than one compression attribute [exr @ 000000000dff9520] Found more than one compression attribute [exr @ 000000000dff9960] Found more than one compression attribute [exr @ 000000000dff9dc0] Found more than one compression attribute [exr @ 000000000dffa200] Found more than one compression attribute frame= 228 fps= 34 q=23.0 size= 421kB time=00:00:06.16 bitrate= 559.8kbits/s frame= 240 fps= 32 q=-1.0 Lsize= 708kB time=00:00:09.52 bitrate= 609.3kbits/s video:705kB audio:0kB subtitle:0 global headers:0kB muxing overhead 0.505636% [libx264 @ 0000000004d11540] frame I:2 Avg QP:15.07 size: 18186 [libx264 @ 0000000004d11540] frame P:73 Avg QP:16.51 size: 3719 [libx264 @ 0000000004d11540] frame B:165 Avg QP:18.38 size: 2502 [libx264 @ 0000000004d11540] consecutive B-frames: 2.5% 3.3% 42.5% 51.7% [libx264 @ 0000000004d11540] mb I I16..4: 46.2% 33.3% 20.4% [libx264 @ 0000000004d11540] mb P I16..4: 6.8% 2.0% 0.6% P16..4: 29.4% 10.5% 4.6% 0.0% 0.0% skip:46.1% [libx264 @ 0000000004d11540] mb B I16..4: 1.8% 0.7% 0.2% B16..8: 40.9% 6.5% 0.3% direct: 1.2% skip:48.5% L0:52.0% L1:47.5% BI: 0.5% [libx264 @ 0000000004d11540] 8x8 transform intra:24.7% inter:81.3% [libx264 @ 0000000004d11540] direct mvs spatial:93.3% temporal:6.7% [libx264 @ 0000000004d11540] coded y,uvDC,uvAC intra: 10.7% 31.4% 24.9% inter: 2.3% 9.0% 2.9% [libx264 @ 0000000004d11540] i16 v,h,dc,p: 83% 11% 6% 1% [libx264 @ 0000000004d11540] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 9% 9% 52% 6% 4% 4% 5% 5% 5% [libx264 @ 0000000004d11540] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 22% 11% 44% 5% 4% 3% 3% 4% 3% [libx264 @ 0000000004d11540] i8c dc,h,v,p: 69% 15% 15% 2% [libx264 @ 0000000004d11540] Weighted P-Frames: Y:0.0% UV:0.0% [libx264 @ 0000000004d11540] ref P L0: 48.9% 0.1% 16.8% 17.0% 11.3% 5.8% [libx264 @ 0000000004d11540] ref B L0: 57.7% 21.9% 13.9% 6.4% [libx264 @ 0000000004d11540] ref B L1: 82.4% 17.6% [libx264 @ 0000000004d11540] kb/s:600.61 For me it looks like it converts the video first and afterwards applies the gamma correction on 8-bit clipped video. Does someone have an idea?

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  • Troubleshooting unwanted NTP Traffic

    - by Jaxaeon
    A domain controller running Windows Server 2012 is sending NTP and NETBIOS traffic to an address that has never been configured as a time provider. The server logs give no indication that any NTP traffic is failing. The only place I see any evidence of this traffic is in pfSense system logs: (Blocked) Jun 9 08:48:50 DOMAIN 10.0.1.100:123 192.128.127.254:123 UDP (Blocked) Jun 9 08:48:53 DOMAIN 10.0.1.100:137 192.128.127.254:137 UDP As far as I can tell the NTP service is working normally otherwise: DC2.domain.com[10.0.1.101:123]: ICMP: 0ms delay NTP: -0.0131705s offset from DC1.domain.com RefID: DC1.domain.com [10.0.1.100] Stratum: 3 DC1.domain.com *** PDC ***[10.0.1.100:123]: ICMP: 0ms delay NTP: +0.0000000s offset from DC1.domain.com RefID: clock1.albyny.inoc.net [64.246.132.14] Stratum: 2 The time provider NtpClient is currently receiving valid time data from 1.pool.ntp.org,0×1 (ntp.m|0x0|0.0.0.0:123->204.2.134.163:123). The time provider NtpClient is currently receiving valid time data from 0.pool.ntp.org,0×1 (ntp.m|0x0|0.0.0.0:123->64.246.132.14:123). The time service is now synchronizing the system time with the time source 0.pool.ntp.org,0×1 (ntp.m|0x0|0.0.0.0:123->64.246.132.14:123). I've been inside and out of the NTP configuration and cannot find any reason for this traffic. Reverse DNS points the destination address to nothing.attdns.com. pinging nothing.attdns.com from the domain controller in question leads to a response from loopback (127.0.0.2) which makes my head hurt. Any ideas? EDIT1: It should probably be noted that after a dns flush, nslookup 192.128.127.254 returns nothing.attdns.com. 192.128.127.254 is not present in domain.com DNS records. The attdns.com domain is not present in cached lookups. 127.in-addr.arpa is clean of any funkyness. EDIT2: The loopback ping response from nothing.attdns.com is possibly unrelated. Machines on other networks are also displaying this behavior. EDIT3: As mentioned in the comments, I tracked the problem network adapter back to my pfSense VM hosted in esxi 5.5 (I know shame on me for virtualizing a firewall). pfSense was configured to use DC1.domain.com as its primary time provider, but upon changing it back to pool.ntp.org the problem persists. pfSense logs give no indication of NTP misconfiguration. Everywhere I can think to look this VM is identified as 10.0.1.253, so I still have no idea why it’s sending NTP requests as 192.128… Since this firewall was a temporary solution to a problem that no longer exists so I am going to decommission it. EDIT4: The queries were coming from another machine sharing the same virtual adapter as the firewall. The machine has two local adapters: one for LAN, and the other for attached hardware that uses an Ethernet connection. That hardware sits in the the mystery subnet, and the machine is broadcasting NTP requests over both adapters.

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  • September 2011 Release of the Ajax Control Toolkit

    - by Stephen Walther
    I’m happy to announce the release of the September 2011 Ajax Control Toolkit. This release has several important new features including: Date ranges – When using the Calendar extender, you can specify a start and end date and a user can pick only those dates which fall within the specified range. This was the fourth top-voted feature request for the Ajax Control Toolkit at CodePlex. Twitter Control – You can use the new Twitter control to display recent tweets associated with a particular Twitter user or tweets which match a search query. Gravatar Control – You can use the new Gravatar control to display a unique image for each user of your website. Users can upload custom images to the Gravatar.com website or the Gravatar control can display a unique, auto-generated, image for a user. You can download this release this very minute by visiting CodePlex: http://AjaxControlToolkit.CodePlex.com Alternatively, you can execute the following command from the Visual Studio NuGet console: Improvements to the Ajax Control Toolkit Calendar Control The Ajax Control Toolkit Calendar extender control is one of the most heavily used controls from the Ajax Control Toolkit. The developers on the Superexpert team spent the last sprint focusing on improving this control. There are three important changes that we made to the Calendar control: we added support for date ranges, we added support for highlighting today’s date, and we made fixes to several bugs related to time zones and daylight savings. Using Calendar Date Ranges One of the top-voted feature requests for the Ajax Control Toolkit was a request to add support for date ranges to the Calendar control (this was the fourth most voted feature request at CodePlex). With the latest release of the Ajax Control Toolkit, the Calendar extender now supports date ranges. For example, the following page illustrates how you can create a popup calendar which allows a user only to pick dates between March 2, 2009 and May 16, 2009. <%@ Page Language="C#" AutoEventWireup="true" CodeBehind="CalendarDateRange.aspx.cs" Inherits="WebApplication1.CalendarDateRange" %> <%@ Register TagPrefix="asp" Namespace="AjaxControlToolkit" Assembly="AjaxControlToolkit" %> <html> <head runat="server"> <title>Calendar Date Range</title> </head> <body> <form id="form1" runat="server"> <asp:ToolkitScriptManager ID="tsm" runat="server" /> <asp:TextBox ID="txtHotelReservationDate" runat="server" /> <asp:CalendarExtender ID="Calendar1" TargetControlID="txtHotelReservationDate" StartDate="3/2/2009" EndDate="5/16/2009" SelectedDate="3/2/2009" runat="server" /> </form> </body> </html> This page contains three controls: an Ajax Control Toolkit ToolkitScriptManager control, a standard ASP.NET TextBox control, and an Ajax Control Toolkit CalendarExtender control. Notice that the Calendar control includes StartDate and EndDate properties which restrict the range of valid dates. The Calendar control shows days, months, and years outside of the valid range as struck out. You cannot select days, months, or years which fall outside of the range. The following video illustrates interacting with the new date range feature: If you want to experiment with a live version of the Ajax Control Toolkit Calendar extender control then you can visit the Calendar Sample Page at the Ajax Control Toolkit Sample Site. Highlighted Today’s Date Another highly requested feature for the Calendar control was support for highlighting today’s date. The Calendar control now highlights the user’s current date regardless of the user’s time zone. Fixes to Time Zone and Daylight Savings Time Bugs We fixed several significant Calendar extender bugs related to time zones and daylight savings time. For example, previously, when you set the Calendar control’s SelectedDate property to the value 1/1/2007 then the selected data would appear as 12/31/2006 or 1/1/2007 or 1/2/2007 depending on the server time zone. For example, if your server time zone was set to Samoa (UTC-11:00), then setting SelectedDate=”1/1/2007” would result in “12/31/2006” being selected in the Calendar. Users of the Calendar extender control found this behavior confusing. After careful consideration, we decided to change the Calendar extender so that it interprets all dates as UTC dates. In other words, if you set StartDate=”1/1/2007” then the Calendar extender parses the date as 1/1/2007 UTC instead of parsing the date according to the server time zone. By interpreting all dates as UTC dates, we avoid all of the reported issues with the SelectedDate property showing the wrong date. Furthermore, when you set the StartDate and EndDate properties, you know that the same StartDate and EndDate will be selected regardless of the time zone associated with the server or associated with the browser. The date 1/1/2007 will always be the date 1/1/2007. The New Twitter Control This release of the Ajax Control Toolkit introduces a new twitter control. You can use the Twitter control to display recent tweets associated with a particular twitter user. You also can use this control to show the results of a twitter search. The following page illustrates how you can use the Twitter control to display recent tweets made by Scott Hanselman: <%@ Page Language="C#" AutoEventWireup="true" CodeBehind="TwitterProfile.aspx.cs" Inherits="WebApplication1.TwitterProfile" %> <%@ Register TagPrefix="asp" Namespace="AjaxControlToolkit" Assembly="AjaxControlToolkit" %> <html > <head runat="server"> <title>Twitter Profile</title> </head> <body> <form id="form1" runat="server"> <asp:ToolkitScriptManager ID="tsm" runat="server" /> <asp:Twitter ID="Twitter1" ScreenName="shanselman" runat="server" /> </form> </body> </html> This page includes two Ajax Control Toolkit controls: the ToolkitScriptManager control and the Twitter control. The Twitter control is set to display tweets from Scott Hanselman (shanselman): You also can use the Twitter control to display the results of a search query. For example, the following page displays all recent tweets related to the Ajax Control Toolkit: Twitter limits the number of times that you can interact with their API in an hour. Twitter recommends that you cache results on the server (https://dev.twitter.com/docs/rate-limiting). By default, the Twitter control caches results on the server for a duration of 5 minutes. You can modify the cache duration by assigning a value (in seconds) to the Twitter control's CacheDuration property. The Twitter control wraps a standard ASP.NET ListView control. You can customize the appearance of the Twitter control by modifying its LayoutTemplate, StatusTemplate, AlternatingStatusTemplate, and EmptyDataTemplate. To learn more about the new Twitter control, visit the live Twitter Sample Page. The New Gravatar Control The September 2011 release of the Ajax Control Toolkit also includes a new Gravatar control. This control makes it easy to display a unique image for each user of your website. A Gravatar is associated with an email address. You can visit Gravatar.com and upload an image and associate the image with your email address. That way, every website which uses Gravatars (such as the www.ASP.NET website) will display your image next to your name. For example, I visited the Gravatar.com website and associated an image of a Koala Bear with the email address [email protected]. The following page illustrates how you can use the Gravatar control to display the Gravatar image associated with the [email protected] email address: <%@ Page Language="C#" AutoEventWireup="true" CodeBehind="GravatarDemo.aspx.cs" Inherits="WebApplication1.GravatarDemo" %> <%@ Register TagPrefix="asp" Namespace="AjaxControlToolkit" Assembly="AjaxControlToolkit" %> <html xmlns="http://www.w3.org/1999/xhtml"> <head id="Head1" runat="server"> <title>Gravatar Demo</title> </head> <body> <form id="form1" runat="server"> <asp:ToolkitScriptManager ID="tsm" runat="server" /> <asp:Gravatar ID="Gravatar1" Email="[email protected]" runat="server" /> </form> </body> </html> The page above simply displays the Gravatar image associated with the [email protected] email address: If a user has not uploaded an image to Gravatar.com then you can auto-generate a unique image for the user from the user email address. The Gravatar control supports four types of auto-generated images: Identicon -- A different geometric pattern is generated for each unrecognized email. MonsterId -- A different image of a monster is generated for each unrecognized email. Wavatar -- A different image of a face is generated for each unrecognized email. Retro -- A different 8-bit arcade-style face is generated for each unrecognized email. For example, there is no Gravatar image associated with the email address [email protected]. The following page displays an auto-generated MonsterId for this email address: <%@ Page Language="C#" AutoEventWireup="true" CodeBehind="GravatarMonster.aspx.cs" Inherits="WebApplication1.GravatarMonster" %> <%@ Register TagPrefix="asp" Namespace="AjaxControlToolkit" Assembly="AjaxControlToolkit" %> <html xmlns="http://www.w3.org/1999/xhtml"> <head id="Head1" runat="server"> <title>Gravatar Monster</title> </head> <body> <form id="form1" runat="server"> <asp:ToolkitScriptManager ID="tsm" runat="server" /> <asp:Gravatar ID="Gravatar1" Email="[email protected]" DefaultImageBehavior="MonsterId" runat="server" /> </form> </body> </html> The page above generates the following image automatically from the supplied email address: To learn more about the properties of the new Gravatar control, visit the live Gravatar Sample Page. ASP.NET Connections Talk on the Ajax Control Toolkit If you are interested in learning more about the changes that we are making to the Ajax Control Toolkit then please come to my talk on the Ajax Control Toolkit at the upcoming ASP.NET Connections conference. In the talk, I will present a summary of the changes that we have made to the Ajax Control Toolkit over the last several months and discuss our future plans. Do you have ideas for new Ajax Control Toolkit controls? Ideas for improving the toolkit? Come to my talk – I would love to hear from you. You can register for the ASP.NET Connections conference by visiting the following website: Register for ASP.NET Connections   Summary The previous release of the Ajax Control Toolkit – the July 2011 Release – has had over 100,000 downloads. That is a huge number of developers who are working with the Ajax Control Toolkit. We are really excited about the new features which we added to the Ajax Control Toolkit in the latest September sprint. We hope that you find the updated Calender control, the new Twitter control, and the new Gravatar control valuable when building your ASP.NET Web Forms applications.

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  • Adding A Custom Dropdown in RCDC for Forefront Identity Manager 2010

    - by Daniel Lackey
    My latest exploration has been FIM 2010 for Identity Management. The following is a post of how to add a custom dropdown for the FIM Portal. I have decided to document this as I cannot find documentation on how to do this anywhere else. I hope that it finds useful to others.   For starters, this was to me not an easy task to figure out. I really would like to know why it is so cumbersome to do something that seems like a lot of people would need to do, but that’s for another day J   The dropdown I wanted to add was for ‘Account Status’ which would display if the account is ‘Enabled’ or ‘Disabled’ in the data source Active Directory. This option would also allow helpdesk users or admins to administer the userAccountControl attribute in AD from the FIM Portal interface.   The first thing I had to do was create the attribute itself. This is done by going to Administration à Schema Management from the FIM 2010 portal. Once here, you click on All Attributes. What is listed here are all attributes and their associated Resource Types in FIM. To create the ‘AccountStatus’ attribute, click on New. As shown below, enter ‘AccountStatus’ with no spaces for the System Name and ‘Account Status’ for the Display Name. The Data Type is going to be ‘Indexed String’. Click Next.           Leave everything on the Localization tab default and click Next.   On the Validation tab as shown below, we will enter the regex expression ^(Enabled|Disabled)?$ with our two desired string values ‘Enabled’ and ‘Disabled’. Click on Finish and then and Submit to complete adding the attribute.       The next step involves associating the attribute with a resource type. This is called ‘Binding’ the attribute. From the Schema Management page, click on All Bindings. From the page that comes up, click on New. As shown below, enter ‘User’ for the Resource Type and ‘Account Status’ for the Attribute Type. This is essentially binding the Account Status attribute to the ‘User’ Resource Type. Click Next.    On the ‘Attribute Override’ tab, type in ‘Account Status’ for the Display Name field. Click Next.   On the ‘Localization’ tab, click Next.   On the ‘Validation’ tab, enter the regex expression ^(Enabled|Disabled)?$ we entered previously for the attribute. Click Finish and then Submit to complete.   Now that the Attribute and the Binding are complete, you have to give users permission to see the attribute on the User Edit page. Go to Administration à Management Policy Rules. Look for the rule named Administration: Administrators can read and update Users and click on it. Once it opens, click on the ‘Target Resources’ tab and look at the section named Resource Attributes. Type in at the end the ‘Account Status’ attribute and check it with the validator. Once done click on OK to save the changes.         Lastly, we need to add the actual dropdown control to the RCDC (Resource Control Display Configuration) for User Editing. Go to Administration à Resource Control Display Configuration. From here navigate until you find the RCDC named Configuration for User Editing RCDC and click on it. The following is what you will see:       First step is to export the Configuration Data file. Click on the Export configuration link and save the file to your desktop of other folder.   Find the file you just exported and open the file in your XML editor of choice. I use notepad but anything will work. Since we are adding a dropdown control, first find another control in the existing file that is already a dropdown in FIM. I used EmployeeType as my example. Copy the control from the beginning tag named <my:Control… to the ending tag </my:Control>. Now take what you copied and paste it in whatever location you desire within the form between two other controls. I chose to place the ‘Account Status’ field after the ‘Account Name’ field. After you paste the control you will need to modify so it looks like this:       Notice where you specify what attribute you are dealing with where it has AccountStatus in the XML. Once you are complete with modifying this, save the file and make sure it is a .xml file.   Now go back to the Configuration for User Editing screen and look at the section named ‘Configuration Data’. Click the ‘Browse’ button and find the XML file you just modified and choose it. Click OK on the bottom of the window and you are done!   Now when you click on a user’s name in the FIM Portal, you should see the newly added dropdown box as below:       Later I will post more about this drop down, specifically on how to automate actually ‘Disabling’ the account in the data source through the FIM Workflows and MAs.   <my:Control my:Name="AccountStatus" my:TypeName="UocDropDownList" my:Caption="{Binding Source=schema, Path=AccountStatus.DisplayName}" my:Description="{Binding Source=schema, Path=AccountStatus.Description}" my:RightsLevel="{Binding Source=rights, Path=AccountStatus}"> <my:Properties> <my:Property my:Name="ValuePath" my:Value="Value"/> <my:Property my:Name="CaptionPath" my:Value="Caption"/> <my:Property my:Name="HintPath" my:Value="Hint"/> <my:Property my:Name="ItemSource" my:Value="{Binding Source=schema, Path=AccountStatus.LocalizedAllowedValues}"/> <my:Property my:Name="SelectedValue" my:Value="{Binding Source=object, Path=AccountStatus, Mode=TwoWay}"/> </my:Properties> </my:Control>

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  • Moving from Winforms to WPF

    - by Elmex
    I am a long time experienced Windows Forms developer, but now it's time to move to WPF because a new WPF project is comming soon to me and I have only a short lead time to prepare myself to learn WPF. What is the best way for a experienced Winforms devleoper? Can you give me some hints and recommendations to learn WPF in a very short time! Are there simple sample WPF solutions and short (video) tutorials? Which books do you recommend? Is www.windowsclient.net a good starting point? Are there alternatives to the official Microsoft site? Thanks in advance for your help!

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  • Issue 15: Oracle PartnerNetwork Exchange @ Oracle OpenWorld

    - by rituchhibber
         ORACLE FOCUS Oracle PartnerNetwork Exchange@ ORACLE OpenWorld Sylvie MichouSenior DirectorPartner Marketing & Communications and Strategic Programs RESOURCES -- Oracle OpenWorld 2012 Oracle PartnerNetwork Exchange @ OpenWorld Oracle PartnerNetwork Exchange @ OpenWorld Registration Oracle PartnerNetwork Exchange SpecializationTest Fest Oracle OpenWorld Schedule Builder Oracle OpenWorld Promotional Toolkit for Partners Oracle Partner Events Oracle Partner Webcasts Oracle EMEA Partner News SUBSCRIBE FEEDBACK PREVIOUS ISSUES If you are attending our forthcoming Oracle OpenWorld 2012 conference in San Francisco from 30 September to 4 October, you will discover a new dedicated programme of keynotes and sessions tailored especially for you, our valued partners. Oracle PartnerNetwork Exchange @ OpenWorld has been created to enhance the opportunities for you to learn from and network with Oracle executives and experts. The programme also provides more informal opportunities than ever throughout the week to meet up with the people who are most important to your business: customers, prospects, colleagues and the Oracle EMEA Alliances & Channels management team. Oracle remains fully focused on building the industry's most admired partner ecosystem—which today spans over 25,000 partners. This new OPN Exchange programme offers an exciting change of pace for partners throughout the conference. Now it will be possible to enjoy a fully-integrated, partner-dedicated session schedule throughout the week, as well as key social events such as the Sunday night Welcome Reception, networking lunches from Monday to Thursday at the Howard Street Tent, and a fantastic closing event on the last Thursday afternoon. In addition to the regular Oracle OpenWorld conference schedule, if you have registered for the Oracle PartnerNetwork Exchange @ OpenWorld programme, you will be invited to attend a much anticipated global partner keynote presentation, plus more than 40 conference sessions aimed squarely at what's most important to you, as partners. Prominent topics for discussion will include: Oracle technologies and roadmaps and how they fit with partners' business plans; business development; regional distinctions in business practices; and much more. Each session will provide plenty of food for thought ahead of the numerous networking opportunities throughout the week, encouraging the knowledge exchange with Oracle executives, customers, prospects, and colleagues that will make this conference of even greater value for you. At Oracle we always work closely with our partners to deliver solution offerings that improve business value, simplify the IT experience and drive innovation and efficiencies for joint customers. The most important element of our new OPN Exchange is content that helps you get more from technology investments, more from your peer-to-peer connections, and more from your interactions with customers. To this end we've created some partner-specific tools which can be used by OPN members ahead of the conference itself. Crucially, a comprehensive Content Catalog already lists and organises details of every OPN Exchange session, speaker, exhibitor, demonstration and related materials. This Content Catalog can be used by all our partners to identify interesting content that you can add to your own personalised Oracle OpenWorld Schedule Builder, allowing more effective planning and pre-enrolment for vital sessions. There are numerous highlights that you will definitely want to include in those personal schedules. On Sunday morning, 30 September we will start the week with partner dedicated OPN Exchange sessions, following our Global Partner Keynote at 13:00 with Judson Althoff, SVP, Worldwide Alliances & Channels and Embedded Sales and senior executives, giving insight into Oracle's partner vision, strategy, and resources—all designed to help build and strengthen market opportunities for you. This will be followed by a number of OPN Exchange general sessions, the Oracle OpenWorld Opening Keynote with Larry Ellison, CEO, Oracle and concluded with the OPN Exchange AfterDark Welcome Reception, starting at 19:30 at the Metreon. From Monday 1 to Thursday 4 October, you can attend the OPN Exchange sessions that are most relevant to your business today and over the coming year. Oracle's top product and sales leaders will be on hand to discuss Oracle's strategic direction in 40+ targeted and in-depth sessions focussing on critical success factors to develop your business. Oracle's dedication to innovation, specialization, enablement and engineering provides Oracle partners with a huge opportunity to create new services and solutions, differentiate themselves and deliver extreme value to joint customers across the globe. Oracle will even be helping over 1000 partners to earn OPN Specialization certification during the Oracle OpenWorld OPN Exchange Test Fest, which will be providing all the study materials and exams required to drive Specialization for free at the conference. You simply need to check the list of current certification tracks available, and make sure you pre-register to reserve a seat in one of the ten sessions being offered free to OPN Exchange registered attendees. And finally, let's not forget those all-important networking opportunities, which can so often provide partners with valuable long-term alliances as well as exciting new business leads. The Oracle PartnerNetwork Lounge, located at Moscone South, exhibition hall, room 100 is the place where partners can meet formally or informally with colleagues, customers, prospects, and other industry professionals. OPN Specialized partners with OPN Exchange passes can also visit the OPN Video Blogging room to record and share ideas, and at the OPN Information Station you will find consultants available to answer your questions. "For the first time ever we will have a full partner conference within OpenWorld. OPN Exchange @ OpenWorld will kick-off on the first Sunday and run the entire week. We'll have over 40 sessions throughout that time and partners will hear from our top development executives, with special sessions dedicated to partnering throughout. It's going to be a phenomenal event, and we look forward to seeing our partners there." Judson Althoff, SVP, Oracle Worldwide Alliances & Channels and Embedded Sales So if you haven't done so already, please register for Oracle PartnerNetwork Exchange @ OpenWorld today or add OPN Exchange to your existing registration for just $100 through My Account. And if you have any further questions regarding partner activities at Oracle OpenWorld, please don't hesitate to contact the Oracle PartnerNetwork team at [email protected] will be on hand to share the very latest information about: Oracle's SPARC Superclusters: the latest Engineered Systems from Oracle, delivering radically improved performance, faster deployment and greatly reduced operational costs for mixed database and enterprise application consolidation Oracle's SPARC T4 servers: with the newly developed T4 processor and Oracle Solaris providing up to five times the single threaded performance and better overall system throughput for expanded application versatility Oracle Database Appliance: a new way to take advantage of the world's most popular database, Oracle Database 11g, in a single, easy-to-deploy and manage system. It's a complete package engineered to deliver simple, reliable and affordable database services to small and medium size businesses and departmental systems. All hardware and software components are supported together and offer customers unique pay-as-you-grow software licensing to quickly scale from two to 24 processor cores without incurring the costs and downtime usually associated with hardware upgrades Oracle Exalogic: the world's only integrated cloud machine, featuring server hardware and middleware software engineered together for maximum performance with minimum set-up and operational cost Oracle Exadata Database Machine: the only database machine that provides extreme performance for both data warehousing and online transaction processing (OLTP) applications, making it the ideal platform for consolidating onto grids or private clouds. It is a complete package of servers, storage, networking and software that is massively scalable, secure and redundant Oracle Sun ZFS Storage Appliances: providing enterprise-class NAS performance, price-performance, manageability and TCO by combining third-generation software with high-performance controllers, flash-based caches and disks Oracle Pillar Axiom Quality-of-Service: confidently consolidate storage for multiple applications into a single datacentre storage solution Oracle Solaris 11: delivering secure enterprise cloud deployments with the ability to run hundreds of virtual application with no overhead and co-engineered with other Oracle software products to provide the highest levels of security, manageability and performance Oracle Enterprise Manager 12c: Oracle's integrated enterprise IT management product, providing the industry's only complete, integrated and business-driven enterprise cloud management solution Oracle VM 3.0: the latest release of Oracle's server virtualisation and management solution, helping to move datacentres beyond server consolidation to improve application deployment and management. Register today and ensure your place at the Extreme Performance Tour! Extreme Performance Tour events are free to attend, but places are limited. To make sure that you don't miss out, please visit Oracle's Extreme Performance Tour website, select the city that you'd be interest in attending an event in, and then click on the 'Register Now' button for that city to secure your interest. Each individual city page also contains more in-depth information about your local event, including logistics, agenda and maybe even a preview of VIP guest speakers. -- Oracle OpenWorld 2010 Whether you attended Oracle OpenWorld 2009 or not, don't forget to save the date now for Oracle OpenWorld 2010. The event will be held a little earlier next year, from 19th-23rd September, so please don't miss out. With thousands of sessions and hundreds of exhibits and demos already lined up, there's no better place to learn how to optimise your existing systems, get an inside line on upcoming technology breakthroughs, and meet with your partner peers, Oracle strategists and even the developers responsible for the products and services that help you get better results for your end customers. Register Now for Oracle OpenWorld 2010! Perhaps you are interested in learning more about Oracle OpenWorld 2010, but don't wish to register at this time? Great! Please just enter your contact information here and we will contact you at a later date. How to Exhibit at Oracle OpenWorld 2010 Sponsorship Opportunities at Oracle OpenWorld 2010 Advertising Opportunities at Oracle OpenWorld 2010 -- Back to the welcome page

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  • Improving Partitioned Table Join Performance

    - by Paul White
    The query optimizer does not always choose an optimal strategy when joining partitioned tables. This post looks at an example, showing how a manual rewrite of the query can almost double performance, while reducing the memory grant to almost nothing. Test Data The two tables in this example use a common partitioning partition scheme. The partition function uses 41 equal-size partitions: CREATE PARTITION FUNCTION PFT (integer) AS RANGE RIGHT FOR VALUES ( 125000, 250000, 375000, 500000, 625000, 750000, 875000, 1000000, 1125000, 1250000, 1375000, 1500000, 1625000, 1750000, 1875000, 2000000, 2125000, 2250000, 2375000, 2500000, 2625000, 2750000, 2875000, 3000000, 3125000, 3250000, 3375000, 3500000, 3625000, 3750000, 3875000, 4000000, 4125000, 4250000, 4375000, 4500000, 4625000, 4750000, 4875000, 5000000 ); GO CREATE PARTITION SCHEME PST AS PARTITION PFT ALL TO ([PRIMARY]); There two tables are: CREATE TABLE dbo.T1 ( TID integer NOT NULL IDENTITY(0,1), Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T1 PRIMARY KEY CLUSTERED (TID) ON PST (TID) );   CREATE TABLE dbo.T2 ( TID integer NOT NULL, Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T2 PRIMARY KEY CLUSTERED (TID, Column1) ON PST (TID) ); The next script loads 5 million rows into T1 with a pseudo-random value between 1 and 5 for Column1. The table is partitioned on the IDENTITY column TID: INSERT dbo.T1 WITH (TABLOCKX) (Column1) SELECT (ABS(CHECKSUM(NEWID())) % 5) + 1 FROM dbo.Numbers AS N WHERE n BETWEEN 1 AND 5000000; In case you don’t already have an auxiliary table of numbers lying around, here’s a script to create one with 10 million rows: CREATE TABLE dbo.Numbers (n bigint PRIMARY KEY);   WITH L0 AS(SELECT 1 AS c UNION ALL SELECT 1), L1 AS(SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B), L2 AS(SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B), L3 AS(SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B), L4 AS(SELECT 1 AS c FROM L3 AS A CROSS JOIN L3 AS B), L5 AS(SELECT 1 AS c FROM L4 AS A CROSS JOIN L4 AS B), Nums AS(SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS n FROM L5) INSERT dbo.Numbers WITH (TABLOCKX) SELECT TOP (10000000) n FROM Nums ORDER BY n OPTION (MAXDOP 1); Table T1 contains data like this: Next we load data into table T2. The relationship between the two tables is that table 2 contains ‘n’ rows for each row in table 1, where ‘n’ is determined by the value in Column1 of table T1. There is nothing particularly special about the data or distribution, by the way. INSERT dbo.T2 WITH (TABLOCKX) (TID, Column1) SELECT T.TID, N.n FROM dbo.T1 AS T JOIN dbo.Numbers AS N ON N.n >= 1 AND N.n <= T.Column1; Table T2 ends up containing about 15 million rows: The primary key for table T2 is a combination of TID and Column1. The data is partitioned according to the value in column TID alone. Partition Distribution The following query shows the number of rows in each partition of table T1: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T1 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are 40 partitions containing 125,000 rows (40 * 125k = 5m rows). The rightmost partition remains empty. The next query shows the distribution for table 2: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T2 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are roughly 375,000 rows in each partition (the rightmost partition is also empty): Ok, that’s the test data done. Test Query and Execution Plan The task is to count the rows resulting from joining tables 1 and 2 on the TID column: SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; The optimizer chooses a plan using parallel hash join, and partial aggregation: The Plan Explorer plan tree view shows accurate cardinality estimates and an even distribution of rows across threads (click to enlarge the image): With a warm data cache, the STATISTICS IO output shows that no physical I/O was needed, and all 41 partitions were touched: Running the query without actual execution plan or STATISTICS IO information for maximum performance, the query returns in around 2600ms. Execution Plan Analysis The first step toward improving on the execution plan produced by the query optimizer is to understand how it works, at least in outline. The two parallel Clustered Index Scans use multiple threads to read rows from tables T1 and T2. Parallel scan uses a demand-based scheme where threads are given page(s) to scan from the table as needed. This arrangement has certain important advantages, but does result in an unpredictable distribution of rows amongst threads. The point is that multiple threads cooperate to scan the whole table, but it is impossible to predict which rows end up on which threads. For correct results from the parallel hash join, the execution plan has to ensure that rows from T1 and T2 that might join are processed on the same thread. For example, if a row from T1 with join key value ‘1234’ is placed in thread 5’s hash table, the execution plan must guarantee that any rows from T2 that also have join key value ‘1234’ probe thread 5’s hash table for matches. The way this guarantee is enforced in this parallel hash join plan is by repartitioning rows to threads after each parallel scan. The two repartitioning exchanges route rows to threads using a hash function over the hash join keys. The two repartitioning exchanges use the same hash function so rows from T1 and T2 with the same join key must end up on the same hash join thread. Expensive Exchanges This business of repartitioning rows between threads can be very expensive, especially if a large number of rows is involved. The execution plan selected by the optimizer moves 5 million rows through one repartitioning exchange and around 15 million across the other. As a first step toward removing these exchanges, consider the execution plan selected by the optimizer if we join just one partition from each table, disallowing parallelism: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = 1 AND $PARTITION.PFT(T2.TID) = 1 OPTION (MAXDOP 1); The optimizer has chosen a (one-to-many) merge join instead of a hash join. The single-partition query completes in around 100ms. If everything scaled linearly, we would expect that extending this strategy to all 40 populated partitions would result in an execution time around 4000ms. Using parallelism could reduce that further, perhaps to be competitive with the parallel hash join chosen by the optimizer. This raises a question. If the most efficient way to join one partition from each of the tables is to use a merge join, why does the optimizer not choose a merge join for the full query? Forcing a Merge Join Let’s force the optimizer to use a merge join on the test query using a hint: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN); This is the execution plan selected by the optimizer: This plan results in the same number of logical reads reported previously, but instead of 2600ms the query takes 5000ms. The natural explanation for this drop in performance is that the merge join plan is only using a single thread, whereas the parallel hash join plan could use multiple threads. Parallel Merge Join We can get a parallel merge join plan using the same query hint as before, and adding trace flag 8649: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN, QUERYTRACEON 8649); The execution plan is: This looks promising. It uses a similar strategy to distribute work across threads as seen for the parallel hash join. In practice though, performance is disappointing. On a typical run, the parallel merge plan runs for around 8400ms; slower than the single-threaded merge join plan (5000ms) and much worse than the 2600ms for the parallel hash join. We seem to be going backwards! The logical reads for the parallel merge are still exactly the same as before, with no physical IOs. The cardinality estimates and thread distribution are also still very good (click to enlarge): A big clue to the reason for the poor performance is shown in the wait statistics (captured by Plan Explorer Pro): CXPACKET waits require careful interpretation, and are most often benign, but in this case excessive waiting occurs at the repartitioning exchanges. Unlike the parallel hash join, the repartitioning exchanges in this plan are order-preserving ‘merging’ exchanges (because merge join requires ordered inputs): Parallelism works best when threads can just grab any available unit of work and get on with processing it. Preserving order introduces inter-thread dependencies that can easily lead to significant waits occurring. In extreme cases, these dependencies can result in an intra-query deadlock, though the details of that will have to wait for another time to explore in detail. The potential for waits and deadlocks leads the query optimizer to cost parallel merge join relatively highly, especially as the degree of parallelism (DOP) increases. This high costing resulted in the optimizer choosing a serial merge join rather than parallel in this case. The test results certainly confirm its reasoning. Collocated Joins In SQL Server 2008 and later, the optimizer has another available strategy when joining tables that share a common partition scheme. This strategy is a collocated join, also known as as a per-partition join. It can be applied in both serial and parallel execution plans, though it is limited to 2-way joins in the current optimizer. Whether the optimizer chooses a collocated join or not depends on cost estimation. The primary benefits of a collocated join are that it eliminates an exchange and requires less memory, as we will see next. Costing and Plan Selection The query optimizer did consider a collocated join for our original query, but it was rejected on cost grounds. The parallel hash join with repartitioning exchanges appeared to be a cheaper option. There is no query hint to force a collocated join, so we have to mess with the costing framework to produce one for our test query. Pretending that IOs cost 50 times more than usual is enough to convince the optimizer to use collocated join with our test query: -- Pretend IOs are 50x cost temporarily DBCC SETIOWEIGHT(50);   -- Co-located hash join SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (RECOMPILE);   -- Reset IO costing DBCC SETIOWEIGHT(1); Collocated Join Plan The estimated execution plan for the collocated join is: The Constant Scan contains one row for each partition of the shared partitioning scheme, from 1 to 41. The hash repartitioning exchanges seen previously are replaced by a single Distribute Streams exchange using Demand partitioning. Demand partitioning means that the next partition id is given to the next parallel thread that asks for one. My test machine has eight logical processors, and all are available for SQL Server to use. As a result, there are eight threads in the single parallel branch in this plan, each processing one partition from each table at a time. Once a thread finishes processing a partition, it grabs a new partition number from the Distribute Streams exchange…and so on until all partitions have been processed. It is important to understand that the parallel scans in this plan are different from the parallel hash join plan. Although the scans have the same parallelism icon, tables T1 and T2 are not being co-operatively scanned by multiple threads in the same way. Each thread reads a single partition of T1 and performs a hash match join with the same partition from table T2. The properties of the two Clustered Index Scans show a Seek Predicate (unusual for a scan!) limiting the rows to a single partition: The crucial point is that the join between T1 and T2 is on TID, and TID is the partitioning column for both tables. A thread that processes partition ‘n’ is guaranteed to see all rows that can possibly join on TID for that partition. In addition, no other thread will see rows from that partition, so this removes the need for repartitioning exchanges. CPU and Memory Efficiency Improvements The collocated join has removed two expensive repartitioning exchanges and added a single exchange processing 41 rows (one for each partition id). Remember, the parallel hash join plan exchanges had to process 5 million and 15 million rows. The amount of processor time spent on exchanges will be much lower in the collocated join plan. In addition, the collocated join plan has a maximum of 8 threads processing single partitions at any one time. The 41 partitions will all be processed eventually, but a new partition is not started until a thread asks for it. Threads can reuse hash table memory for the new partition. The parallel hash join plan also had 8 hash tables, but with all 5,000,000 build rows loaded at the same time. The collocated plan needs memory for only 8 * 125,000 = 1,000,000 rows at any one time. Collocated Hash Join Performance The collated join plan has disappointing performance in this case. The query runs for around 25,300ms despite the same IO statistics as usual. This is much the worst result so far, so what went wrong? It turns out that cardinality estimation for the single partition scans of table T1 is slightly low. The properties of the Clustered Index Scan of T1 (graphic immediately above) show the estimation was for 121,951 rows. This is a small shortfall compared with the 125,000 rows actually encountered, but it was enough to cause the hash join to spill to physical tempdb: A level 1 spill doesn’t sound too bad, until you realize that the spill to tempdb probably occurs for each of the 41 partitions. As a side note, the cardinality estimation error is a little surprising because the system tables accurately show there are 125,000 rows in every partition of T1. Unfortunately, the optimizer uses regular column and index statistics to derive cardinality estimates here rather than system table information (e.g. sys.partitions). Collocated Merge Join We will never know how well the collocated parallel hash join plan might have worked without the cardinality estimation error (and the resulting 41 spills to tempdb) but we do know: Merge join does not require a memory grant; and Merge join was the optimizer’s preferred join option for a single partition join Putting this all together, what we would really like to see is the same collocated join strategy, but using merge join instead of hash join. Unfortunately, the current query optimizer cannot produce a collocated merge join; it only knows how to do collocated hash join. So where does this leave us? CROSS APPLY sys.partitions We can try to write our own collocated join query. We can use sys.partitions to find the partition numbers, and CROSS APPLY to get a count per partition, with a final step to sum the partial counts. The following query implements this idea: SELECT row_count = SUM(Subtotals.cnt) FROM ( -- Partition numbers SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1 ) AS P CROSS APPLY ( -- Count per collocated join SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals; The estimated plan is: The cardinality estimates aren’t all that good here, especially the estimate for the scan of the system table underlying the sys.partitions view. Nevertheless, the plan shape is heading toward where we would like to be. Each partition number from the system table results in a per-partition scan of T1 and T2, a one-to-many Merge Join, and a Stream Aggregate to compute the partial counts. The final Stream Aggregate just sums the partial counts. Execution time for this query is around 3,500ms, with the same IO statistics as always. This compares favourably with 5,000ms for the serial plan produced by the optimizer with the OPTION (MERGE JOIN) hint. This is another case of the sum of the parts being less than the whole – summing 41 partial counts from 41 single-partition merge joins is faster than a single merge join and count over all partitions. Even so, this single-threaded collocated merge join is not as quick as the original parallel hash join plan, which executed in 2,600ms. On the positive side, our collocated merge join uses only one logical processor and requires no memory grant. The parallel hash join plan used 16 threads and reserved 569 MB of memory:   Using a Temporary Table Our collocated merge join plan should benefit from parallelism. The reason parallelism is not being used is that the query references a system table. We can work around that by writing the partition numbers to a temporary table (or table variable): SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   CREATE TABLE #P ( partition_number integer PRIMARY KEY);   INSERT #P (partition_number) SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1;   SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals;   DROP TABLE #P;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; Using the temporary table adds a few logical reads, but the overall execution time is still around 3500ms, indistinguishable from the same query without the temporary table. The problem is that the query optimizer still doesn’t choose a parallel plan for this query, though the removal of the system table reference means that it could if it chose to: In fact the optimizer did enter the parallel plan phase of query optimization (running search 1 for a second time): Unfortunately, the parallel plan found seemed to be more expensive than the serial plan. This is a crazy result, caused by the optimizer’s cost model not reducing operator CPU costs on the inner side of a nested loops join. Don’t get me started on that, we’ll be here all night. In this plan, everything expensive happens on the inner side of a nested loops join. Without a CPU cost reduction to compensate for the added cost of exchange operators, candidate parallel plans always look more expensive to the optimizer than the equivalent serial plan. Parallel Collocated Merge Join We can produce the desired parallel plan using trace flag 8649 again: SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: One difference between this plan and the collocated hash join plan is that a Repartition Streams exchange operator is used instead of Distribute Streams. The effect is similar, though not quite identical. The Repartition uses round-robin partitioning, meaning the next partition id is pushed to the next thread in sequence. The Distribute Streams exchange seen earlier used Demand partitioning, meaning the next partition id is pulled across the exchange by the next thread that is ready for more work. There are subtle performance implications for each partitioning option, but going into that would again take us too far off the main point of this post. Performance The important thing is the performance of this parallel collocated merge join – just 1350ms on a typical run. The list below shows all the alternatives from this post (all timings include creation, population, and deletion of the temporary table where appropriate) from quickest to slowest: Collocated parallel merge join: 1350ms Parallel hash join: 2600ms Collocated serial merge join: 3500ms Serial merge join: 5000ms Parallel merge join: 8400ms Collated parallel hash join: 25,300ms (hash spill per partition) The parallel collocated merge join requires no memory grant (aside from a paltry 1.2MB used for exchange buffers). This plan uses 16 threads at DOP 8; but 8 of those are (rather pointlessly) allocated to the parallel scan of the temporary table. These are minor concerns, but it turns out there is a way to address them if it bothers you. Parallel Collocated Merge Join with Demand Partitioning This final tweak replaces the temporary table with a hard-coded list of partition ids (dynamic SQL could be used to generate this query from sys.partitions): SELECT row_count = SUM(Subtotals.cnt) FROM ( VALUES (1),(2),(3),(4),(5),(6),(7),(8),(9),(10), (11),(12),(13),(14),(15),(16),(17),(18),(19),(20), (21),(22),(23),(24),(25),(26),(27),(28),(29),(30), (31),(32),(33),(34),(35),(36),(37),(38),(39),(40),(41) ) AS P (partition_number) CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: The parallel collocated hash join plan is reproduced below for comparison: The manual rewrite has another advantage that has not been mentioned so far: the partial counts (per partition) can be computed earlier than the partial counts (per thread) in the optimizer’s collocated join plan. The earlier aggregation is performed by the extra Stream Aggregate under the nested loops join. The performance of the parallel collocated merge join is unchanged at around 1350ms. Final Words It is a shame that the current query optimizer does not consider a collocated merge join (Connect item closed as Won’t Fix). The example used in this post showed an improvement in execution time from 2600ms to 1350ms using a modestly-sized data set and limited parallelism. In addition, the memory requirement for the query was almost completely eliminated  – down from 569MB to 1.2MB. The problem with the parallel hash join selected by the optimizer is that it attempts to process the full data set all at once (albeit using eight threads). It requires a large memory grant to hold all 5 million rows from table T1 across the eight hash tables, and does not take advantage of the divide-and-conquer opportunity offered by the common partitioning. The great thing about the collocated join strategies is that each parallel thread works on a single partition from both tables, reading rows, performing the join, and computing a per-partition subtotal, before moving on to a new partition. From a thread’s point of view… If you have trouble visualizing what is happening from just looking at the parallel collocated merge join execution plan, let’s look at it again, but from the point of view of just one thread operating between the two Parallelism (exchange) operators. Our thread picks up a single partition id from the Distribute Streams exchange, and starts a merge join using ordered rows from partition 1 of table T1 and partition 1 of table T2. By definition, this is all happening on a single thread. As rows join, they are added to a (per-partition) count in the Stream Aggregate immediately above the Merge Join. Eventually, either T1 (partition 1) or T2 (partition 1) runs out of rows and the merge join stops. The per-partition count from the aggregate passes on through the Nested Loops join to another Stream Aggregate, which is maintaining a per-thread subtotal. Our same thread now picks up a new partition id from the exchange (say it gets id 9 this time). The count in the per-partition aggregate is reset to zero, and the processing of partition 9 of both tables proceeds just as it did for partition 1, and on the same thread. Each thread picks up a single partition id and processes all the data for that partition, completely independently from other threads working on other partitions. One thread might eventually process partitions (1, 9, 17, 25, 33, 41) while another is concurrently processing partitions (2, 10, 18, 26, 34) and so on for the other six threads at DOP 8. The point is that all 8 threads can execute independently and concurrently, continuing to process new partitions until the wider job (of which the thread has no knowledge!) is done. This divide-and-conquer technique can be much more efficient than simply splitting the entire workload across eight threads all at once. Related Reading Understanding and Using Parallelism in SQL Server Parallel Execution Plans Suck © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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  • Toorcon14

    - by danx
    Toorcon 2012 Information Security Conference San Diego, CA, http://www.toorcon.org/ Dan Anderson, October 2012 It's almost Halloween, and we all know what that means—yes, of course, it's time for another Toorcon Conference! Toorcon is an annual conference for people interested in computer security. This includes the whole range of hackers, computer hobbyists, professionals, security consultants, press, law enforcement, prosecutors, FBI, etc. We're at Toorcon 14—see earlier blogs for some of the previous Toorcon's I've attended (back to 2003). This year's "con" was held at the Westin on Broadway in downtown San Diego, California. The following are not necessarily my views—I'm just the messenger—although I could have misquoted or misparaphrased the speakers. Also, I only reviewed some of the talks, below, which I attended and interested me. MalAndroid—the Crux of Android Infections, Aditya K. Sood Programming Weird Machines with ELF Metadata, Rebecca "bx" Shapiro Privacy at the Handset: New FCC Rules?, Valkyrie Hacking Measured Boot and UEFI, Dan Griffin You Can't Buy Security: Building the Open Source InfoSec Program, Boris Sverdlik What Journalists Want: The Investigative Reporters' Perspective on Hacking, Dave Maas & Jason Leopold Accessibility and Security, Anna Shubina Stop Patching, for Stronger PCI Compliance, Adam Brand McAfee Secure & Trustmarks — a Hacker's Best Friend, Jay James & Shane MacDougall MalAndroid—the Crux of Android Infections Aditya K. Sood, IOActive, Michigan State PhD candidate Aditya talked about Android smartphone malware. There's a lot of old Android software out there—over 50% Gingerbread (2.3.x)—and most have unpatched vulnerabilities. Of 9 Android vulnerabilities, 8 have known exploits (such as the old Gingerbread Global Object Table exploit). Android protection includes sandboxing, security scanner, app permissions, and screened Android app market. The Android permission checker has fine-grain resource control, policy enforcement. Android static analysis also includes a static analysis app checker (bouncer), and a vulnerablity checker. What security problems does Android have? User-centric security, which depends on the user to grant permission and make smart decisions. But users don't care or think about malware (the're not aware, not paranoid). All they want is functionality, extensibility, mobility Android had no "proper" encryption before Android 3.0 No built-in protection against social engineering and web tricks Alternative Android app markets are unsafe. Simply visiting some markets can infect Android Aditya classified Android Malware types as: Type A—Apps. These interact with the Android app framework. For example, a fake Netflix app. Or Android Gold Dream (game), which uploads user files stealthy manner to a remote location. Type K—Kernel. Exploits underlying Linux libraries or kernel Type H—Hybrid. These use multiple layers (app framework, libraries, kernel). These are most commonly used by Android botnets, which are popular with Chinese botnet authors What are the threats from Android malware? These incude leak info (contacts), banking fraud, corporate network attacks, malware advertising, malware "Hackivism" (the promotion of social causes. For example, promiting specific leaders of the Tunisian or Iranian revolutions. Android malware is frequently "masquerated". That is, repackaged inside a legit app with malware. To avoid detection, the hidden malware is not unwrapped until runtime. The malware payload can be hidden in, for example, PNG files. Less common are Android bootkits—there's not many around. What they do is hijack the Android init framework—alteering system programs and daemons, then deletes itself. For example, the DKF Bootkit (China). Android App Problems: no code signing! all self-signed native code execution permission sandbox — all or none alternate market places no robust Android malware detection at network level delayed patch process Programming Weird Machines with ELF Metadata Rebecca "bx" Shapiro, Dartmouth College, NH https://github.com/bx/elf-bf-tools @bxsays on twitter Definitions. "ELF" is an executable file format used in linking and loading executables (on UNIX/Linux-class machines). "Weird machine" uses undocumented computation sources (I think of them as unintended virtual machines). Some examples of "weird machines" are those that: return to weird location, does SQL injection, corrupts the heap. Bx then talked about using ELF metadata as (an uintended) "weird machine". Some ELF background: A compiler takes source code and generates a ELF object file (hello.o). A static linker makes an ELF executable from the object file. A runtime linker and loader takes ELF executable and loads and relocates it in memory. The ELF file has symbols to relocate functions and variables. ELF has two relocation tables—one at link time and another one at loading time: .rela.dyn (link time) and .dynsym (dynamic table). GOT: Global Offset Table of addresses for dynamically-linked functions. PLT: Procedure Linkage Tables—works with GOT. The memory layout of a process (not the ELF file) is, in order: program (+ heap), dynamic libraries, libc, ld.so, stack (which includes the dynamic table loaded into memory) For ELF, the "weird machine" is found and exploited in the loader. ELF can be crafted for executing viruses, by tricking runtime into executing interpreted "code" in the ELF symbol table. One can inject parasitic "code" without modifying the actual ELF code portions. Think of the ELF symbol table as an "assembly language" interpreter. It has these elements: instructions: Add, move, jump if not 0 (jnz) Think of symbol table entries as "registers" symbol table value is "contents" immediate values are constants direct values are addresses (e.g., 0xdeadbeef) move instruction: is a relocation table entry add instruction: relocation table "addend" entry jnz instruction: takes multiple relocation table entries The ELF weird machine exploits the loader by relocating relocation table entries. The loader will go on forever until told to stop. It stores state on stack at "end" and uses IFUNC table entries (containing function pointer address). The ELF weird machine, called "Brainfu*k" (BF) has: 8 instructions: pointer inc, dec, inc indirect, dec indirect, jump forward, jump backward, print. Three registers - 3 registers Bx showed example BF source code that implemented a Turing machine printing "hello, world". More interesting was the next demo, where bx modified ping. Ping runs suid as root, but quickly drops privilege. BF modified the loader to disable the library function call dropping privilege, so it remained as root. Then BF modified the ping -t argument to execute the -t filename as root. It's best to show what this modified ping does with an example: $ whoami bx $ ping localhost -t backdoor.sh # executes backdoor $ whoami root $ The modified code increased from 285948 bytes to 290209 bytes. A BF tool compiles "executable" by modifying the symbol table in an existing ELF executable. The tool modifies .dynsym and .rela.dyn table, but not code or data. Privacy at the Handset: New FCC Rules? "Valkyrie" (Christie Dudley, Santa Clara Law JD candidate) Valkyrie talked about mobile handset privacy. Some background: Senator Franken (also a comedian) became alarmed about CarrierIQ, where the carriers track their customers. Franken asked the FCC to find out what obligations carriers think they have to protect privacy. The carriers' response was that they are doing just fine with self-regulation—no worries! Carriers need to collect data, such as missed calls, to maintain network quality. But carriers also sell data for marketing. Verizon sells customer data and enables this with a narrow privacy policy (only 1 month to opt out, with difficulties). The data sold is not individually identifiable and is aggregated. But Verizon recommends, as an aggregation workaround to "recollate" data to other databases to identify customers indirectly. The FCC has regulated telephone privacy since 1934 and mobile network privacy since 2007. Also, the carriers say mobile phone privacy is a FTC responsibility (not FCC). FTC is trying to improve mobile app privacy, but FTC has no authority over carrier / customer relationships. As a side note, Apple iPhones are unique as carriers have extra control over iPhones they don't have with other smartphones. As a result iPhones may be more regulated. Who are the consumer advocates? Everyone knows EFF, but EPIC (Electrnic Privacy Info Center), although more obsecure, is more relevant. What to do? Carriers must be accountable. Opt-in and opt-out at any time. Carriers need incentive to grant users control for those who want it, by holding them liable and responsible for breeches on their clock. Location information should be added current CPNI privacy protection, and require "Pen/trap" judicial order to obtain (and would still be a lower standard than 4th Amendment). Politics are on a pro-privacy swing now, with many senators and the Whitehouse. There will probably be new regulation soon, and enforcement will be a problem, but consumers will still have some benefit. Hacking Measured Boot and UEFI Dan Griffin, JWSecure, Inc., Seattle, @JWSdan Dan talked about hacking measured UEFI boot. First some terms: UEFI is a boot technology that is replacing BIOS (has whitelisting and blacklisting). UEFI protects devices against rootkits. TPM - hardware security device to store hashs and hardware-protected keys "secure boot" can control at firmware level what boot images can boot "measured boot" OS feature that tracks hashes (from BIOS, boot loader, krnel, early drivers). "remote attestation" allows remote validation and control based on policy on a remote attestation server. Microsoft pushing TPM (Windows 8 required), but Google is not. Intel TianoCore is the only open source for UEFI. Dan has Measured Boot Tool at http://mbt.codeplex.com/ with a demo where you can also view TPM data. TPM support already on enterprise-class machines. UEFI Weaknesses. UEFI toolkits are evolving rapidly, but UEFI has weaknesses: assume user is an ally trust TPM implicitly, and attached to computer hibernate file is unprotected (disk encryption protects against this) protection migrating from hardware to firmware delays in patching and whitelist updates will UEFI really be adopted by the mainstream (smartphone hardware support, bank support, apathetic consumer support) You Can't Buy Security: Building the Open Source InfoSec Program Boris Sverdlik, ISDPodcast.com co-host Boris talked about problems typical with current security audits. "IT Security" is an oxymoron—IT exists to enable buiness, uptime, utilization, reporting, but don't care about security—IT has conflict of interest. There's no Magic Bullet ("blinky box"), no one-size-fits-all solution (e.g., Intrusion Detection Systems (IDSs)). Regulations don't make you secure. The cloud is not secure (because of shared data and admin access). Defense and pen testing is not sexy. Auditors are not solution (security not a checklist)—what's needed is experience and adaptability—need soft skills. Step 1: First thing is to Google and learn the company end-to-end before you start. Get to know the management team (not IT team), meet as many people as you can. Don't use arbitrary values such as CISSP scores. Quantitive risk assessment is a myth (e.g. AV*EF-SLE). Learn different Business Units, legal/regulatory obligations, learn the business and where the money is made, verify company is protected from script kiddies (easy), learn sensitive information (IP, internal use only), and start with low-hanging fruit (customer service reps and social engineering). Step 2: Policies. Keep policies short and relevant. Generic SANS "security" boilerplate policies don't make sense and are not followed. Focus on acceptable use, data usage, communications, physical security. Step 3: Implementation: keep it simple stupid. Open source, although useful, is not free (implementation cost). Access controls with authentication & authorization for local and remote access. MS Windows has it, otherwise use OpenLDAP, OpenIAM, etc. Application security Everyone tries to reinvent the wheel—use existing static analysis tools. Review high-risk apps and major revisions. Don't run different risk level apps on same system. Assume host/client compromised and use app-level security control. Network security VLAN != segregated because there's too many workarounds. Use explicit firwall rules, active and passive network monitoring (snort is free), disallow end user access to production environment, have a proxy instead of direct Internet access. Also, SSL certificates are not good two-factor auth and SSL does not mean "safe." Operational Controls Have change, patch, asset, & vulnerability management (OSSI is free). For change management, always review code before pushing to production For logging, have centralized security logging for business-critical systems, separate security logging from administrative/IT logging, and lock down log (as it has everything). Monitor with OSSIM (open source). Use intrusion detection, but not just to fulfill a checkbox: build rules from a whitelist perspective (snort). OSSEC has 95% of what you need. Vulnerability management is a QA function when done right: OpenVas and Seccubus are free. Security awareness The reality is users will always click everything. Build real awareness, not compliance driven checkbox, and have it integrated into the culture. Pen test by crowd sourcing—test with logging COSSP http://www.cossp.org/ - Comprehensive Open Source Security Project What Journalists Want: The Investigative Reporters' Perspective on Hacking Dave Maas, San Diego CityBeat Jason Leopold, Truthout.org The difference between hackers and investigative journalists: For hackers, the motivation varies, but method is same, technological specialties. For investigative journalists, it's about one thing—The Story, and they need broad info-gathering skills. J-School in 60 Seconds: Generic formula: Person or issue of pubic interest, new info, or angle. Generic criteria: proximity, prominence, timeliness, human interest, oddity, or consequence. Media awareness of hackers and trends: journalists becoming extremely aware of hackers with congressional debates (privacy, data breaches), demand for data-mining Journalists, use of coding and web development for Journalists, and Journalists busted for hacking (Murdock). Info gathering by investigative journalists include Public records laws. Federal Freedom of Information Act (FOIA) is good, but slow. California Public Records Act is a lot stronger. FOIA takes forever because of foot-dragging—it helps to be specific. Often need to sue (especially FBI). CPRA is faster, and requests can be vague. Dumps and leaks (a la Wikileaks) Journalists want: leads, protecting ourselves, our sources, and adapting tools for news gathering (Google hacking). Anonomity is important to whistleblowers. They want no digital footprint left behind (e.g., email, web log). They don't trust encryption, want to feel safe and secure. Whistleblower laws are very weak—there's no upside for whistleblowers—they have to be very passionate to do it. Accessibility and Security or: How I Learned to Stop Worrying and Love the Halting Problem Anna Shubina, Dartmouth College Anna talked about how accessibility and security are related. Accessibility of digital content (not real world accessibility). mostly refers to blind users and screenreaders, for our purpose. Accessibility is about parsing documents, as are many security issues. "Rich" executable content causes accessibility to fail, and often causes security to fail. For example MS Word has executable format—it's not a document exchange format—more dangerous than PDF or HTML. Accessibility is often the first and maybe only sanity check with parsing. They have no choice because someone may want to read what you write. Google, for example, is very particular about web browser you use and are bad at supporting other browsers. Uses JavaScript instead of links, often requiring mouseover to display content. PDF is a security nightmare. Executible format, embedded flash, JavaScript, etc. 15 million lines of code. Google Chrome doesn't handle PDF correctly, causing several security bugs. PDF has an accessibility checker and PDF tagging, to help with accessibility. But no PDF checker checks for incorrect tags, untagged content, or validates lists or tables. None check executable content at all. The "Halting Problem" is: can one decide whether a program will ever stop? The answer, in general, is no (Rice's theorem). The same holds true for accessibility checkers. Language-theoretic Security says complicated data formats are hard to parse and cannot be solved due to the Halting Problem. W3C Web Accessibility Guidelines: "Perceivable, Operable, Understandable, Robust" Not much help though, except for "Robust", but here's some gems: * all information should be parsable (paraphrasing) * if not parsable, cannot be converted to alternate formats * maximize compatibility in new document formats Executible webpages are bad for security and accessibility. They say it's for a better web experience. But is it necessary to stuff web pages with JavaScript for a better experience? A good example is The Drudge Report—it has hand-written HTML with no JavaScript, yet drives a lot of web traffic due to good content. A bad example is Google News—hidden scrollbars, guessing user input. Solutions: Accessibility and security problems come from same source Expose "better user experience" myth Keep your corner of Internet parsable Remember "Halting Problem"—recognize false solutions (checking and verifying tools) Stop Patching, for Stronger PCI Compliance Adam Brand, protiviti @adamrbrand, http://www.picfun.com/ Adam talked about PCI compliance for retail sales. Take an example: for PCI compliance, 50% of Brian's time (a IT guy), 960 hours/year was spent patching POSs in 850 restaurants. Often applying some patches make no sense (like fixing a browser vulnerability on a server). "Scanner worship" is overuse of vulnerability scanners—it gives a warm and fuzzy and it's simple (red or green results—fix reds). Scanners give a false sense of security. In reality, breeches from missing patches are uncommon—more common problems are: default passwords, cleartext authentication, misconfiguration (firewall ports open). Patching Myths: Myth 1: install within 30 days of patch release (but PCI §6.1 allows a "risk-based approach" instead). Myth 2: vendor decides what's critical (also PCI §6.1). But §6.2 requires user ranking of vulnerabilities instead. Myth 3: scan and rescan until it passes. But PCI §11.2.1b says this applies only to high-risk vulnerabilities. Adam says good recommendations come from NIST 800-40. Instead use sane patching and focus on what's really important. From NIST 800-40: Proactive: Use a proactive vulnerability management process: use change control, configuration management, monitor file integrity. Monitor: start with NVD and other vulnerability alerts, not scanner results. Evaluate: public-facing system? workstation? internal server? (risk rank) Decide:on action and timeline Test: pre-test patches (stability, functionality, rollback) for change control Install: notify, change control, tickets McAfee Secure & Trustmarks — a Hacker's Best Friend Jay James, Shane MacDougall, Tactical Intelligence Inc., Canada "McAfee Secure Trustmark" is a website seal marketed by McAfee. A website gets this badge if they pass their remote scanning. The problem is a removal of trustmarks act as flags that you're vulnerable. Easy to view status change by viewing McAfee list on website or on Google. "Secure TrustGuard" is similar to McAfee. Jay and Shane wrote Perl scripts to gather sites from McAfee and search engines. If their certification image changes to a 1x1 pixel image, then they are longer certified. Their scripts take deltas of scans to see what changed daily. The bottom line is change in TrustGuard status is a flag for hackers to attack your site. Entire idea of seals is silly—you're raising a flag saying if you're vulnerable.

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  • External Monitors shut off when Laptop Lid closes

    - by John Lanz
    I have researched the solution... gconftool-2 --type string --set /apps/gnome-power-manager/buttons/lid_ac "nothing" does not fix it. I have two external monitors and when I close my lid the settings are reset and the laptop's monitor is set to the default. Thanks! gsettings list-recursively org.gnome.settings-daemon.plugins.power org.gnome.settings-daemon.plugins.power active true org.gnome.settings-daemon.plugins.power button-hibernate 'nothing' org.gnome.settings-daemon.plugins.power button-power 'nothing' org.gnome.settings-daemon.plugins.power button-sleep 'nothing' org.gnome.settings-daemon.plugins.power button-suspend 'nothing' org.gnome.settings-daemon.plugins.power critical-battery-action 'suspend' org.gnome.settings-daemon.plugins.power idle-brightness 30 org.gnome.settings-daemon.plugins.power idle-dim-ac false org.gnome.settings-daemon.plugins.power idle-dim-battery true org.gnome.settings-daemon.plugins.power idle-dim-time 10 org.gnome.settings-daemon.plugins.power lid-close-ac-action 'nothing' org.gnome.settings-daemon.plugins.power lid-close-battery-action 'nothing' org.gnome.settings-daemon.plugins.power notify-perhaps-recall true org.gnome.settings-daemon.plugins.power percentage-action 2 org.gnome.settings-daemon.plugins.power percentage-critical 3 org.gnome.settings-daemon.plugins.power percentage-low 10 org.gnome.settings-daemon.plugins.power priority 1 org.gnome.settings-daemon.plugins.power sleep-display-ac 600 org.gnome.settings-daemon.plugins.power sleep-display-battery 600 org.gnome.settings-daemon.plugins.power sleep-inactive-ac false org.gnome.settings-daemon.plugins.power sleep-inactive-ac-timeout 0 org.gnome.settings-daemon.plugins.power sleep-inactive-ac-type 'suspend' org.gnome.settings-daemon.plugins.power sleep-inactive-battery true org.gnome.settings-daemon.plugins.power sleep-inactive-battery-timeout 0 org.gnome.settings-daemon.plugins.power sleep-inactive-battery-type 'suspend' org.gnome.settings-daemon.plugins.power time-action 120 org.gnome.settings-daemon.plugins.power time-critical 300 org.gnome.settings-daemon.plugins.power time-low 1200 org.gnome.settings-daemon.plugins.power use-time-for-policy true

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  • Azure Grid Computing - Worker Roles as HPC Compute Nodes

    - by JoshReuben
    Overview ·        With HPC 2008 R2 SP1 You can add Azure worker roles as compute nodes in a local Windows HPC Server cluster. ·        The subscription for Windows Azure like any other Azure Service - charged for the time that the role instances are available, as well as for the compute and storage services that are used on the nodes. ·        Win-Win ? - Azure charges the computer hour cost (according to vm size) amortized over a month – so you save on purchasing compute node hardware. Microsoft wins because you need to purchase HPC to have a local head node for managing this compute cluster grid distributed in the cloud. ·        Blob storage is used to hold input & output files of each job. I can see how Parametric Sweep HPC jobs can be supported (where the same job is run multiple times on each node against different input units), but not MPI.NET (where different HPC Job instances function as coordinated agents and conduct master-slave inter-process communication), unless Azure is somehow tunneling MPI communication through inter-WorkerRole Azure Queues. ·        this is not the end of the story for Azure Grid Computing. If MS requires you to purchase a local HPC license (and administrate it), what's to stop a 3rd party from doing this and encapsulating exposing HPC WCF Broker Service to you for managing compute nodes? If MS doesn’t  provide head node as a service, someone else will! Process ·        requires creation of a worker node template that specifies a connection to an existing subscription for Windows Azure + an availability policy for the worker nodes. ·        After worker nodes are added to the cluster, you can start them, which provisions the Windows Azure role instances, and then bring them online to run HPC cluster jobs. ·        A Windows Azure worker role instance runs a HPC compatible Azure guest operating system which runs on the VMs that host your service. The guest operating system is updated monthly. You can choose to upgrade the guest OS for your service automatically each time an update is released - All role instances defined by your service will run on the guest operating system version that you specify. see Windows Azure Guest OS Releases and SDK Compatibility Matrix (http://go.microsoft.com/fwlink/?LinkId=190549). ·        use the hpcpack command to upload file packages and install files to run on the worker nodes. see hpcpack (http://go.microsoft.com/fwlink/?LinkID=205514). Requirements ·        assuming you have an azure subscription account and the HPC head node installed and configured. ·        Install HPC Pack 2008 R2 SP 1 -  see Microsoft HPC Pack 2008 R2 Service Pack 1 Release Notes (http://go.microsoft.com/fwlink/?LinkID=202812). ·        Configure the head node to connect to the Internet - connectivity is provided by the connection of the head node to the enterprise network. You may need to configure a proxy client on the head node. Any cluster network topology (1-5) is supported). ·        Configure the firewall - allow outbound TCP traffic on the following ports: 80,       443, 5901, 5902, 7998, 7999 ·        Note: HPC Server  uses Admin Mode (Elevated Privileges) in Windows Azure to give the service administrator of the subscription the necessary privileges to initialize HPC cluster services on the worker nodes. ·        Obtain a Windows Azure subscription certificate - the Windows Azure subscription must be configured with a public subscription (API) certificate -a valid X.509 certificate with a key size of at least 2048 bits. Generate a self-sign certificate & upload a .cer file to the Windows Azure Portal Account page > Manage my API Certificates link. see Using the Windows Azure Service Management API (http://go.microsoft.com/fwlink/?LinkId=205526). ·        import the certificate with an associated private key on the HPC cluster head node - into the trusted root store of the local computer account. Obtain Windows Azure Connection Information for HPC Server ·        required for each worker node template ·        copy from azure portal - Get from: navigation pane > Hosted Services > Storage Accounts & CDN ·        Subscription ID - a 32-char hex string in the form xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx. In Properties pane. ·        Subscription certificate thumbprint - a 40-char hex string (you need to remove spaces). In Management Certificates > Properties pane. ·        Service name - the value of <ServiceName> configured in the public URL of the service (http://<ServiceName>.cloudapp.net). In Hosted Services > Properties pane. ·        Blob Storage account name - the value of <StorageAccountName> configured in the public URL of the account (http://<StorageAccountName>.blob.core.windows.net). In Storage Accounts > Properties pane. Import the Azure Subscription Certificate on the HPC Head Node ·        enable the services for Windows HPC Server  to authenticate properly with the Windows Azure subscription. ·        use the Certificates MMC snap-in to import the certificate to the Trusted Root Certification Authorities store of the local computer account. The certificate must be in PFX format (.pfx or .p12 file) with a private key that is protected by a password. ·        see Certificates (http://go.microsoft.com/fwlink/?LinkId=163918). ·        To open the certificates snapin: Run > mmc. File > Add/Remove Snap-in > certificates > Computer account > Local Computer ·        To import the certificate via wizard - Certificates > Trusted Root Certification Authorities > Certificates > All Tasks > Import ·        After the certificate is imported, it appears in the details pane in the Certificates snap-in. You can open the certificate to check its status. Configure a Proxy Client on the HPC Head Node ·        the following Windows HPC Server services must be able to communicate over the Internet (through the firewall) with the services for Windows Azure: HPCManagement, HPCScheduler, HPCBrokerWorker. ·        Create a Windows Azure Worker Node Template ·        Edit HPC node templates in HPC Node Template Editor. ·        Specify: 1) Windows Azure subscription connection info (unique service name) for adding a set of worker nodes to the cluster + 2)worker node availability policy – rules for deploying / removing worker role instances in Windows Azure o   HPC Cluster Manager > Configuration > Navigation Pane > Node Templates > Actions pane > New à Create Node Template Wizard or Edit à Node Template Editor o   Choose Node Template Type page - Windows Azure worker node template o   Specify Template Name page – template name & description o   Provide Connection Information page – Azure Subscription ID (text) & Subscription certificate (browse) o   Provide Service Information page - Azure service name + blob storage account name (optionally click Retrieve Connection Information to get list of available from azure – possible LRT). o   Configure Azure Availability Policy page - how Windows Azure worker nodes start / stop (online / offline the worker role instance -  add / remove) – manual / automatic o   for automatic - In the Configure Windows Azure Worker Availability Policy dialog -select days and hours for worker nodes to start / stop. ·        To validate the Windows Azure connection information, on the template's Connection Information tab > Validate connection information. ·        You can upload a file package to the storage account that is specified in the template - eg upload application or service files that will run on the worker nodes. see hpcpack (http://go.microsoft.com/fwlink/?LinkID=205514). Add Azure Worker Nodes to the HPC Cluster ·        Use the Add Node Wizard – specify: 1) the worker node template, 2) The number of worker nodes   (within the quota of role instances in the azure subscription), and 3)           The VM size of the worker nodes : ExtraSmall, Small, Medium, Large, or ExtraLarge.  ·        to add worker nodes of different sizes, must run the Add Node Wizard separately for each size. ·        All worker nodes that are added to the cluster by using a specific worker node template define a set of worker nodes that will be deployed and managed together in Windows Azure when you start the nodes. This includes worker nodes that you add later by using the worker node template and, if you choose, worker nodes of different sizes. You cannot start, stop, or delete individual worker nodes. ·        To add Windows Azure worker nodes o   In HPC Cluster Manager: Node Management > Actions pane > Add Node à Add Node Wizard o   Select Deployment Method page - Add Azure Worker nodes o   Specify New Nodes page - select a worker node template, specify the number and size of the worker nodes ·        After you add worker nodes to the cluster, they are in the Not-Deployed state, and they have a health state of Unapproved. Before you can use the worker nodes to run jobs, you must start them and then bring them online. ·        Worker nodes are numbered consecutively in a naming series that begins with the root name AzureCN – this is non-configurable. Deploying Windows Azure Worker Nodes ·        To deploy the role instances in Windows Azure - start the worker nodes added to the HPC cluster and bring the nodes online so that they are available to run cluster jobs. This can be configured in the HPC Azure Worker Node Template – Azure Availability Policy -  to be automatic or manual. ·        The Start, Stop, and Delete actions take place on the set of worker nodes that are configured by a specific worker node template. You cannot perform one of these actions on a single worker node in a set. You also cannot perform a single action on two sets of worker nodes (specified by two different worker node templates). ·        ·          Starting a set of worker nodes deploys a set of worker role instances in Windows Azure, which can take some time to complete, depending on the number of worker nodes and the performance of Windows Azure. ·        To start worker nodes manually and bring them online o   In HPC Node Management > Navigation Pane > Nodes > List / Heat Map view - select one or more worker nodes. o   Actions pane > Start – in the Start Azure Worker Nodes dialog, select a node template. o   the state of the worker nodes changes from Not Deployed to track the provisioning progress – worker node Details Pane > Provisioning Log tab. o   If there were errors during the provisioning of one or more worker nodes, the state of those nodes is set to Unknown and the node health is set to Unapproved. To determine the reason for the failure, review the provisioning logs for the nodes. o   After a worker node starts successfully, the node state changes to Offline. To bring the nodes online, select the nodes that are in the Offline state > Bring Online. ·        Troubleshooting o   check node template. o   use telnet to test connectivity: telnet <ServiceName>.cloudapp.net 7999 o   check node status - Deployment status information appears in the service account information in the Windows Azure Portal - HPC queries this -  see  node status information for any failed nodes in HPC Node Management. ·        When role instances are deployed, file packages that were previously uploaded to the storage account using the hpcpack command are automatically installed. You can also upload file packages to storage after the worker nodes are started, and then manually install them on the worker nodes. see hpcpack (http://go.microsoft.com/fwlink/?LinkID=205514). ·        to remove a set of role instances in Windows Azure - stop the nodes by using HPC Cluster Manager (apply the Stop action). This deletes the role instances from the service and changes the state of the worker nodes in the HPC cluster to Not Deployed. ·        Each time that you start a set of worker nodes, two proxy role instances (size Small) are configured in Windows Azure to facilitate communication between HPC Cluster Manager and the worker nodes. The proxy role instances are not listed in HPC Cluster Manager after the worker nodes are added. However, the instances appear in the Windows Azure Portal. The proxy role instances incur charges in Windows Azure along with the worker node instances, and they count toward the quota of role instances in the subscription.

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  • Create a Persistent Bootable Ubuntu USB Flash Drive

    - by Trevor Bekolay
    Don’t feel like reinstalling an antivirus program every time you boot up your Ubuntu flash drive? We’ll show you how to create a bootable Ubuntu flash drive that will remember your settings, installed programs, and more! Previously, we showed you how to create a bootable Ubuntu flash drive that would reset to its initial state every time you booted it up. This is great if you’re worried about messing something up, and want to start fresh every time you start tinkering with Ubuntu. However, if you’re using the Ubuntu flash drive to diagnose and solve problems with your PC, you might find that a lot of problems require guess-and-test cycles. It would be great if the settings you change in Ubuntu and the programs you install stay installed the next time you boot it up. Fortunately, Universal USB Installer, a great little program from Pen Drive Linux, can do just that! Note: You will need a USB drive at least 2 GB large. Make sure you back up any files on the flash drive because this process will format the drive, removing any files currently on it. Once Ubuntu has been installed on the flash drive, you can move those files back if there is enough space. Put Ubuntu on your flash drive Universal-USB-Installer.exe does not need to be installed, so just double click on it to run it wherever you downloaded it. Click Yes if you get a UAC prompt, and you will be greeted with this window. Click I Agree. In the drop-down box on the next screen, select Ubuntu 9.10 Desktop i386. Don’t worry if you normally use 64-bit operating systems – the 32-bit version of Ubuntu 9.10 will still work fine. Some useful tools do not have 64-bit versions, so unless you’re planning on switching to Ubuntu permanently, the 32-bit version will work best. If you don’t have a copy of the Ubuntu 9.10 CD downloaded, then click on the checkbox to Download the ISO. You’ll be prompted to launch a web browser; click Yes. The download should start immediately. When it’s finished, return the the Universal USB Installer and click on Browse to navigate to the ISO file you just downloaded. Click OK and the text field will be populated with the path to the ISO file. Select the drive letter that corresponds to the flash drive that you would like to use from the dropdown box. If you’ve backed up the files on this drive, we recommend checking the box to format the drive. Finally, you have to choose how much space you would like to set aside for the settings and programs that will be stored on the flash drive. Considering that Ubuntu itself only takes up around 700 MB, 1 GB should be plenty, but we’re choosing 2 GB in this example because we have lots of space on this USB drive. Click on the Create button and then make yourself a sandwich – it will take some time to install no matter how fast your PC is. Eventually it will finish. Click Close. Now you have a flash drive that will boot into a fully capable Ubuntu installation, and any changes you make will persist the next time you boot it up! Boot into Ubuntu If you’re not sure how to set your computer to boot using the USB drive, then check out the How to Boot Into Ubuntu section of our previous article on creating bootable USB drives, or refer to your motherboard’s manual. Once your computer is set to boot using the USB drive, you’ll be greeted with splash screen with some options. Press Enter to boot into Ubuntu. The first time you do this, it may take some time to boot up. Fortunately, we’ve found that the process speeds up on subsequent boots. You’ll be greeted with the Ubuntu desktop. Now, if you change settings like the desktop resolution, or install a program, those changes will be permanently stored on the USB drive! We installed avast! Antivirus, and on the next boot, found that it was still in the Accessories menu where we left it. Conclusion We think that a bootable Ubuntu USB flash drive is a great tool to have around in case your PC has problems booting otherwise. By having the changes you make persist, you can customize your Ubuntu installation to be the ultimate computer repair toolkit! Download Universal USB Installer from Pen Drive Linux Similar Articles Productive Geek Tips Create a Bootable Ubuntu USB Flash Drive the Easy WayCreate a Bootable Ubuntu 9.10 USB Flash DriveReset Your Ubuntu Password Easily from the Live CDHow-To Geek on Lifehacker: Control Your Computer with Shortcuts & Speed Up Vista SetupHow To Setup a USB Flash Drive to Install Windows 7 TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 Test Drive Windows 7 Online Download Wallpapers From National Geographic Site Spyware Blaster v4.3 Yes, it’s Patch Tuesday Generate Stunning Tag Clouds With Tagxedo Install, Remove and HIDE Fonts in Windows 7

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  • Oracle President Mark Hurd Highlights How Data-driven HR Decisions Help Maximize Business Performance

    - by Scott Ewart
    HR Intelligence Can Help Companies Win the Race for Talent Today during a keynote at Taleo World 2012, Oracle President Mark Hurd outlined the ways that executives can use HR intelligence to help them make better business decisions, shape the future of their organizations and improve the bottom line. He highlighted that talent management is one of the top three focus areas for CEOs, and explained how HR intelligence can help drive decisions to meet business objectives. Hurd urged HR leaders to use data to make fact-based decisions about hiring, talent management and succession to drive strategic growth. To win the race for talent, Hurd explained that organizations need powerful technology that provides fact-based valuable insight that is needed to proactively manage talent, drive strategic initiatives that promote innovation, and enhance business performance. To view the full story and press release, click here.

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  • Moving from Winforms to WPF

    - by Elmex
    I am a long time experienced Windows Forms developer, but now it's time to move to WPF because a new WPF project is comming soon to me and I have only a short lead time to prepare myself to learn WPF. What is the best way for a experienced Winforms devleoper? Can you give me some hints and recommendations to learn WPF in a very short time! Are there simple sample WPF solutions and short (video) tutorials? Which books do you recommend? Is www.windowsclient.net a good starting point? Are there alternatives to the official Microsoft site? Thanks in advance for your help!

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