Simple .NET/ASP.NET PDF document editor web control SDK

You have a lot of choices for putting a data access layer together. Some are useful in more situations than others. Data source controls are useful in some circumstances, while the Data Access Application Block is a likely boon to just about any application of decent size. Cache dependencies are a very powerful facility that can be leveraged to super-charge performance of applications in many situations that have historically been very difficult to address. SQL Server 2005 introduces a new era in relational database technology by providing an integrated asynchronous messaging system, hosting the CLR in the same process as the database engine, and treating XML as a first class data type. Taken individually, these are powerful new features. Taken together, however, these features elevate SQL Server 2005 from a database to an application platform in its own right. Personally, we re excited to see how innovative developers will combine these features to elegantly address problems that have traditionally been daunting.

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A basic control construct in F# programming is if/then/elif/else. Here s an example: let round x = if x >= 100 then 100 elif x < 0 then 0 else x Conditionals are really shorthand for pattern matching; for example, the previous code could have been written like this: let round x = match x with | _ when x >= 100 -> 100 | _ when x < 0 -> 0 | _ -> x Conditionals are always guarded by a Boolean-valued expression. You can build them using && and || (the and and or operators) as well as any library functions that return Boolean values: let round2 (x,y) = if x >= 100 || y >= 100 then 100,100 elif x < 0 || y < 0 then 0,0 else x,y

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irtually all business applications require some level of transaction support You can largely maintain data integrity in a static view using the rules of schema that a relational database provides In dynamic processes, however, a transaction can guarantee that all or none of the changes applied during the process are persisted when the process is complete ACID properties (atomicity, consistency, isolation, and durability) are the cornerstone of any transaction infrastructure In 7, you saw the attribute-based transactional behavior of Enterprise Services provided by COM+ These transactions are specific to a database, and it s common to think of work done with a database whenever you re considering transactions Transactional behavior can be supplied for any resource, however, be it an in-memory hash table, a file on the disk, or an XML document One of the design goals of the transactional engine built into version 20 of the .

The operators && and || have the usual shortcut behavior in that the second argument of && is evaluated only if the first evaluates to true, and likewise, the second argument of || is evaluated only if the first evaluates to false.

From Table 11-1, we can conclude the following: In my tests, there was no noticeable performance benefit in using the numeric extension getIntArray(). The best performance was obtained when using getOracleArray(). The method getResultSet() was the slowest; this could be attributed to the overhead of creating and destroying the ResultSet object. An important fact to keep in mind is that our code compared retrieving 10,000 elements from a single collection in a tight loop. This is perhaps not a typical scenario in real-life applications. Given that the difference in performance in absolute terms between all four methods is not very high, considering that we are retrieving 10,000 elements. Thus, my advice is to, in general, choose a method based on nonperformance criteria such as usability, maintainability, portability, etc., unless you can prove to yourself that performance improvement of one method over the others is substantial in your particular scenario.

type WebReferences.TerraService with member ws.GetPlaceFactsAsyncr(place) = Async.BuildPrimitive(place, ws.BeginGetPlaceFacts, ws.EndGetPlaceFacts) These have the following types: member ws.GetWeatherByPlaceNameAsyncr : placeName:string -> Async<WeatherForecast> member ws.GetPlaceFactsAsyncr: place:string -> Async<PlaceFacts> We can now define various asynchronous tasks using these primitives. For example, we can define a function getWeather that collects both the weather and position data for a given location but executes the two calls simultaneously. let getWeather(city,state,country) = async { let ws = new WeatherForecast() let ts = new TerraService() let place = new Place(City=city, State=state, Country=country) let! weather,facts = Async.Parallel2 (ws.GetWeatherByPlaceNameAsyncr(city), ts.GetPlaceFactsAsyncr(place)) let today = weather.Details.[0] return (today.MinTemperatureF,today.MaxTemperatureC, facts.Center.Lat,facts.Center.Lon) } The type of this function is as follows: