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Here is an example of using pattern matching with lists: let printFirst primes = match primes with | h :: t -> printfn "The first prime in the list is %d" h | [] -> printfn "No primes found in the list" > printFirst oddPrimes;; The first prime in the list is 3 val it : unit = () The first line after the match is a pattern-matching rule that matches the input primes against the pattern h :: t If primes is a nonempty list, then the match is successful, and the first printfn is executed with h bound to the head of the list and t to its tail The second line considers the case where primes is an empty list Note that the :: and [] symbols can be used both to build up lists in expressions and to decompose them in pattern matching.

I first call prepare_for_resend() to clear the buffer, then make as many calls to the overloaded store() method setting the value for each field (in order) Finally, I call the write() method to write the buffer to the network If anything goes wrong, I exit the function with a value of true (which means errors were generated) The last statement that ends the result set and finalizes communication to the client is the send_eof() function, which sends an end-offile signal to the client You can use these same classes, methods, and functions to send results from your commands If you want to compile the server, you can, but you ll encounter errors concerning the DISK_USAGE_SYM symbol If you have other errors during this compile, please fix them before moving on Now let s get back to the lexical hash and parser code.

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The final topics we cover in this chapter are the various primitive mechanisms used for threads, shared-memory concurrency, and signaling. In many ways, these are the assembly language of concurrency. In this chapter we ve concentrated mostly on techniques that work well with immutable data structures. That is not to say you should always use immutable data structures. It is, for example, perfectly valid to use mutable data structures as long as they are accessed from only one particular thread. Furthermore, private mutable data structures can often be safely passed through an asynchronous workflow, because at each point the mutable data structure will be accessed by only one thread, even if different parts of the asynchronous workflow are executed by different threads. This does not apply to workflows that use operators such as Async.Parallel or Async.SpawnChild that start additional threads of computation. This means that we ve largely avoided covering shared-memory primitives so far, because F# provides powerful declarative constructs such as asynchronous workflows and message passing that often subsume the need to resort to shared-memory concurrency. However, a working knowledge of thread primitives and shared-memory concurrency is still very useful, especially if you want to implement your own basic constructs or highly efficient concurrent algorithms on shared-memory hardware.

The F# library also includes a module List that contains some useful functions related to programming with lists You see many of these functions in the next section and throughout this book Table 3-9 shows some of them F# lists aren t appropriate for all circumstances; for example, very large data structures should probably be represented using arrays or other data structures or even managed by an external tool such.

If you ve been studying the MySQL source code, you ve probably noticed that there are sql_yacccc and sql_yacch files These files are generated from the sql_yaccyy file by Bison Let s use Bison to generate these files Open a command window and navigate to the /sql directory off the root of your source code tree Run the following command: bison y d sql_yaccyy This generates two new files: ytabc and ytabh These files will replace the sql_yacccc and sql_yacch files, respectively Before you copy them, make a backup of the original files After you have made a backup of the files, copy ytabc to sql_yacccc (cpp on Windows) and ytabh to sql_yacch..

In this chapter we ve avoided showing how to work with threads directly, instead relying on abstractions such as BackgroundWorker and the .NET thread pool. If you do want to create threads directly, here is a short sample:

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