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At the top of the listing the benchmarking suite gives the metadata describing the tests run including the date the tests were run, the version of the operating system, the version of the server, and any special optimization or hardware installed (in this case, none). Take a look at what follows the metadata. You see the results of each of the tests run reporting the wallclock elapsed seconds. The times indicated in the parentheses are the times recorded during the execution of the benchmark suite itself and should be deducted from the actual wallclock seconds for accurate times. Don t be too concerned about this as this section is mostly used for a brief look at the tests in groups. The next section is the most interesting of all as it contains the actual data collected during each test. The results of the example benchmark tests are shown in Table 4-4. I have omitted some of the rows to save space.

bit of getting used to, since they give you a way to write computations that may behave and execute quite differently than normal programs.

/// A type of binary trees, generic in the type of values carried at nodes and tips type Tree<'T> = | Node of 'T * Tree<'T> * Tree<'T> | Tip /// Compute the number of values in the tree member t.Size = match t with | Node(_,l,r) -> 1 + l.Size + r.Size | Tip -> 0

Table 4-4. Specific Test Result Data of the Small Tests Run (Totals per Operation)

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Computation expressions are the F# equivalent of monadic syntax in the programming language Haskell Monads are a powerful and expressive design pattern and are characterized by a generic type M<'a> combined with at least two operations: bind : M<'a> -> ('a -> M<'b>) -> M<'b> return : 'a -> M<'a> These correspond to the primitives let! and return in the F# computation expression syntax Several other elements of the computation expression syntax can be implemented in terms of these primitives, though the F# de-sugaring process leaves this up to the implementer of the workflow, since sometimes derived operations can have more efficient implementations Well-behaved monads should satisfy three important rules called the monad laws You can find out more about these at http://wwwexpert-fsharpcom/Topics/ Workflows F# uses the terms computation expression and workflow for three reasons.

F# lets you define both members associated with types and objects via the dot-notation and static functions that can perform essentially the same operations. For example, the length of a string s can be computed by both the s.Length property and the String.length function. Given the choice, which should you use in your code Although there is no fixed answer to this, here are some general rules: Use members (methods and properties) where they already exist, unless you have other good reasons not to do so. It s better to use s.Length than String.length, simply because it s shorter, even if it occasionally requires using an additional type annotation. That is, embrace dot-notation, but use it tastefully. When designing a framework or library, define members for the intrinsic, essential properties and operations associated with a type. When designing a framework or library, define additional functionality in new modules or by using extension members. The section Extending Existing Types and Modules later in this chapter covers extension members. Sometimes there is duplication in functionality between dot-notation members and values in associated modules. This is intended and should be accepted as part of the mixed OO/functional nature of F#.

alter_table_add alter_table_drop connect connect+select_1_row connect+select_simple count count_distinct count_distinct_2 select_range select_range_key2 select_range_prefix select_simple select_simple_cache select_simple_join update_big update_of_key update_of_key_big update_of_primary_key_many_keys update_with_key update_with_key_prefix wisc_benchmark TOTALS

First, when the designers of F# talked with the designers of Haskell about this, they agreed that the word monad is a bit obscure and sounds a little daunting and that using other names might be wise Second, there are some technical differences: for example, some F# workflows can be combined with imperative programming, utilizing the fact that workflows can have side effects not tracked by the F# type system In Haskell, all side-effecting operations must be lifted into the corresponding monad The Haskell approach has some important advantages: you can know for sure what side effects a function can have by looking at its type However, it also makes it more difficult to use external libraries from within a computation expression Third, F# workflows can be reified using F# quotations, giving a way to execute the workflow by alternative means, for example, by translation to SQL.

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