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So far you have seen how you can perform LINQ-style queries using a set of aggregate operators that work on enumerable objects, and you will see these very same operators query and manipulate XML data in the coming section. Performing querying and manipulation on relational data is done almost the same way, except that these are implemented under the hood by calling LINQ. Assuming that you have mapped your employees database with SqlMetal and created the main database object as db, here is an example similar to those in earlier sections using F# LinqToSql syntax: open Microsoft.FSharp.Quotations.Typed open Microsoft.FSharp.Data.Linq open Microsoft.FSharp.Linq.SequenceOps let res = SQL <@ { for emp in ( db.Employees) when emp.BirthDate.Value.Year > 1960 && emp.LastName.StartsWith "S" -> (emp.FirstName, emp.LastName) } |> take 5 @> for (first, last) in res do printfn "%s %s" first last

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It is important to understand how redo log files might impact us as developers. We will look at how the different ways we can write our code affect redo log utilization. We ve already seen the mechanics of redo earlier in the chapter, and now we ll look at some specific issues. You might detect many of these scenarios, but they would be fixed by the DBA as they affect the database instance as a whole. We ll start with what happens during a COMMIT, and then get into commonly asked questions and issues surrounding the online redo logs.

As a developer, you should have a good understanding of exactly what goes on during a COMMIT. In this section, we ll investigate what happens during the processing of the COMMIT statement in Oracle. A COMMIT is generally a very fast operation, regardless of the transaction size. You might think that the bigger a transaction (in other words, the more data it affects), the longer a COMMIT would take. This is not true. The response time of a COMMIT is generally flat, regardless of the transaction size. This is because a COMMIT does not really have too much work to do, but what it does do is vital.

One notable difference between this and previous queries is the use of F# quotations inside <@ and @>. As shown in 9, quotations are reified syntax trees that can be read and manipulated by F# programs. Quoted expressions (provided by the Microsoft.FSharp.Quotations.Typed namespace) are of type Expr<'a>, where 'a is the type of the unquoted expression. You can read more on meta-programming via F# quotations in depth in 9. Note that in F# quotation literals, the splice symbol indicates that a value is being inserted into the quotation expression tree. This allows quotations to reference defined objects and values such as those representing the database. The type of the previous SQL function is as follows:

One of the reasons this is an important fact to understand and embrace is that it will lead to let your transactions be as big as they should be As we discussed in the previous chapter, many developers artificially constrain the size of their transactions, committing every so many rows, instead of committing when a logical unit of work has been performed They do this in the mistaken belief that they are preserving scarce system resources, when in fact they are increasing them If a COMMIT of one row takes X units of time, and the COMMIT of 1,000 rows takes the same X units of time, then performing work in a manner that does 1,000 one-row COMMITs will take an additional 1,000*X units of time to perform.

By committing only when you have to (when the logical unit of work is complete), you will not only increase performance, you ll also reduce contention for shared resources (log files, various internal latches, and the like) A simple example demonstrates that it necessarily takes longer We ll use a Java application, although you can expect similar results from most any client except, in this case, PL/SQL (we ll discuss why that is after the example) To start, here is the sample table we ll be inserting into: scott%ORA11GR2> create table test 2 ( id number, 3 code varchar2(20), 4 descr varchar2(20), 5 insert_user varchar2(30), 6 insert_date date 7 ) 8 / Table created Our Java program will accept two inputs: the number of rows to INSERT (iters) and how many rows between commits (commitCnt).

val SQL: Expr<'a> -> 'a This function works on F# quotations. These are converted to LINQ Expression objects and passed to the underlying LINQ mechanism to produce SQL that is then executed on demand.