.NET/ASP.NET/C#/VB.NET PDF Document SDK

Many developers have some bad habits when it comes to transactions. I see this frequently with developers who have worked with a database that supports but does not promote the use of transactions. For example, in Informix (by default), Sybase, and SQL Server, you must explicitly BEGIN a transaction; otherwise, each individual statement is a transaction all by itself. In a similar manner to the way in which Oracle wraps a SAVEPOINT around discrete statements, these databases wrap a BEGIN WORK/COMMIT or ROLLBACK around each statement. This is because, in these databases, locks are precious resources, and readers block writers and vice versa. In an attempt to increase concurrency, these databases want you to make the transaction as short as possible sometimes at the expense of data integrity. Oracle takes the opposite approach. Transactions are always implicit, and there is no way to have an autocommit unless an application implements it (see the Using Autocommit section later in this chapter for more details). In Oracle, every transaction should be committed when it must and never before. Transactions should be as large as they need to be. Issues such as locks, blocking, and so on should not really be considered the driving forces behind transaction size data integrity is the driving force behind the size of your transaction. Locks are not a scarce resource, and there are no contention issues between concurrent readers and writers of data. This allows you to have robust transactions in the database. These transactions do not have to be short in duration they should be exactly as long as they need to be (but no longer). Transactions are not for the convenience of the computer and its software; they are to protect your data.

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With ADO.NET, data is acquired through a connection to the database via a provider. This connection serves as a medium to execute a command against; this can be used to fetch, update, insert, or delete data from the data store. Statements and queries are articulated as SQL text (CREATE, SELECT, UPDATE, INSERT, and DELETE statements) and are passed to the command object s constructor. When you execute these statements, you obtain data (in the case of queries) or the number of affected rows (in the case of UPDATE, INSERT, or DELETE statements). The data returned can be processed via two main mechanisms: sequentially in a read-only fashion using a DataReader object or by loading it into an in-memory representation (a DataSet object) for further disconnected processing. DataSet objects store data in a set of table objects and along with them metadata that describes their relationships and constraints in a fully contained model. ADO.NET 2.0 comes with four data providers: SQLClient, OleDb, Oracle, and Odbc. Table 16-2 describes them and a couple of more commonly used providers. These providers act as the main gateway to the database.

Faced with the task of updating many rows, most programmers will try to figure out some procedural way to do it in a loop, so that they can commit every so many rows. I ve heard two (false!) reasons for doing it this way: It is faster and more efficient to frequently commit lots of small transactions than it is to process and commit one big transaction. We don t have enough undo space.

Both of these reasons are misguided. Furthermore, committing too frequently leaves you prone to the danger of leaving your database in an unknown state should your update fail halfway through. It requires complex logic to write a process that is smoothly restartable in the event of failure. By far the best option is to commit only as frequently as your business processes dictate and to size your undo segments accordingly. Let s take a look at these issues in more detail.

> let plusExpr = <@ 1 + 1 @>;; val plusExpr : Expr<int> > plusExpr;; val it : Expr<int> = <@ Microsoft.FSharp.Core.Operators.op_Addition (Int32 1) (Int32 1) @> You can see here that the act of quoting an expression gives you the expression back as data. Those familiar with Lisp or Scheme will know a version of this in the form of Lisp quotations, and those familiar with C# 3.0 will find it familiar, since C# uses similar mechanisms for its lambda expressions. F# quotations are distinctive partly because they are typed (like C# lambda expressions) and because the functional, expression-based nature of F# means that so much of the language can be quoted and manipulated relatively easily. We use quotations in only a few places in this book. In 15, we utilize an F# library that converts F# quotations to SQL via the .NET LINQ library. The essence of the way this converter works is summarized by the following type:

It is generally not faster to commit frequently it is almost always faster to do the work in a single SQL statement. By way of a small example, say we have a table, T, with lots of rows, and we want to update a column value for every row in that table. We ll use this to set up such a table (run these four setup steps before each of the three cases below): ops$tkyte%ORA11GR2> drop table t; Table dropped. ops$tkyte%ORA11GR2> create table t as select * from all_objects; Table created.