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

Data structures are generally divided between mutable and immutable, a distinction touched upon in 2 and covered in more detail in 4. Immutable data structures are sometimes called persistent or simply functional. Here are some of the immutable data structures commonly used with F#: Tuple values and option values: These are immutable and are basic workhorses of F# programming. Immutable linked lists of type 'a list: These are cheap to access from the left end. They are inefficient for random access lookup because the list must be traversed from the left for each lookup, that is, random access lookup is O(n) where n is the number of elements in the collection. The full name of this type is Microsoft.FSharp.Collections.List<'a>. Immutable sets based on balanced trees: We show some example uses of immutable sets in 2, and an implementation is provided via the type Set<'a> in the F# library namespace Microsoft. FSharp.Collections. These are cheap to add, access, and union, with O(log(n)) access times, where n is the number of elements in the collection. Because the type is immutable, internal nodes can be shared between different sets. Immutable maps based on balanced trees: These are similar to immutable sets but associate keys with values (that is, they are immutable dictionaries). One implementation of these is provided via the F# library type Map<'key,'value> in Microsoft.FSharp.Collections. As with sets, these have O(log(n)) access times. We cover imperative programming and mutable data structures in 4.

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Effectively, Oracle takes a detour around the modified data; it reads around it, reconstructing it from the undo (also known as a rollback) segment (discussed in detail in 9 Redo and Undo ) A consistent and correct answer comes back without waiting for the transaction to commit Now, a database that allowed a dirty read would simply return the value it saw in account 987 at the time it read it, in this case $50000 The query would count the transferred $400 twice Therefore, not only does it return the wrong answer, but also it returns a total that never existed in the table at any committed point in time In a multiuser database, a dirty read can be a dangerous feature and, personally, I have never seen the usefulness of it Say that, rather than transferring, the transaction was actually just depositing $40000 in account 987.

The dirty read would count the $40000 and get the right answer, wouldn t it Well, suppose the uncommitted transaction was rolled back We have just counted $40000 that was never actually in the database The point here is that dirty read is not a feature; rather, it is a liability In Oracle, it is just not needed You get all of the advantages of a dirty read (no blocking) without any of the incorrect results..

member this.Page_Load(sender: obj, e: EventArgs) = if not this.Page.IsPostBack then this.Time.Text <- DateTime.Now.ToString() member this.Reload_Click(sender: obj, e: EventArgs) = this.Time.Text <- "(R) " + DateTime.Now.ToString()

The READ COMMITTED isolation level states that a transaction may only read data that has been committed in the database There are no dirty reads There may be non-repeatable reads (ie, rereads of the same row may return a different answer in the same transaction) and phantom reads (ie, newly inserted and committed rows become visible to a query that were not visible earlier in the transaction) READ COMMITTED is perhaps the most commonly used isolation level in database applications everywhere, and it is the default mode for Oracle databases It is rare to see a different isolation level used However, achieving READ COMMITTED isolation is not as cut-and-dried as it sounds If you look at Table 7-1, it looks straightforward.

The minimalist application shown in Listing 14-2 and Figure 14-1 does nothing but use the server to compute the time, something easily done on the local machine. Listing 14-6 shows the .aspx code for a web application shown in Figure 14-2 that computes a list of prime numbers for a selected range. The web.config file for this application remains the same. Listing 14-6. Computing and Displaying a Range of Prime Numbers Using the Web Server <%@ Page Language="F#" %> <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <script language="F#" runat="server"> member page.GenerateData_Click(sender: obj, e: EventArgs) = let isPrime(i: bigint) = let lim = Math.BigInt.FromInt64(int64(sqrt(float(i)))) let rec check j = j > lim or (i % j <> 0I && check (j+1I)) check 2I let lowerLimit = Math.BigInt.Parse(page.LowerLimit.Text) let upperLimit = Math.BigInt.Parse(page.UpperLimit.Text) let data = [ let previousTime = ref System.DateTime.Now for i in lowerLimit..upperLimit do if isPrime(i) then let time = System.DateTime.Now yield (i, time-previousTime.Value) do previousTime := time ] page.Repeater.DataSource <- data page.Repeater.DataBind() </script> <html xmlns="http://www.w3.org/1999/xhtml"> <head id="Head1" runat="server"> <title>Current time</title> <style type="text/css"> body { font-family:calibri,verdana,sans-serif; } </style>