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In this chapter, we covered a lot of material that, at times, might not have been obvious. However, it is vital that you understand these issues. For example, if you were not aware of the statement-level restart, you might not be able to figure out how a certain set of circumstances could have taken place. That is, you would not be able to explain some of the daily empirical observations you make. In fact, if you were not aware of the restarts, you might wrongly suspect the actual fault to be due to the circumstances or end user error. It would be one of those unreproducible issues, as it takes many things happening in a specific order to observe. We took a look at the meaning of the isolation levels set out in the SQL standard and at how Oracle implements them; at times, we contrasted Oracle s implementation with that of other databases. We saw that in other implementations (i.e., ones that employ read locks to provide consistent data), there is a huge trade-off between concurrency and consistency. To get highly concurrent access to data, you would have to decrease your need for consistent answers. To get consistent, correct answers, you would need to live with decreased concurrency. In Oracle that is not the case, due to its multiversioning feature. Table 7-9 sums up what you might expect in a database that employs read locking versus Oracle s multi-versioning approach.

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If you put a timer on these web service calls, you would see that they take significant time to execute, even seconds depending on your network connection, and this can be a serious idle time for your application. To remedy this problem, you can either minimize the number of web service calls through some sort of caching (for instance, in a web application you can store web service data in the session or even the application state and reuse it instead of making new calls) or make these calls in parallel, asynchronously. For example, it makes sense to connect to two webs services simultaneously and wait for both responses to come back before proceeding with the rest of an operation. The easiest and most compositional way to access a web service asynchronously is to use the asynchronous workflows discussed in 13. The proxy code generated for the web service includes methods such as BeginGetWeatherByPlaceName and EndGetWeatherByPlaceName that follow the style for .NET library asynchronous invocations described in 13. We first map these pairs of operations into methods that construct asynchronous tasks. As in 13, we do this by defining extension members to the types in the generated code. type WebReferences.WeatherForecast with member ws.GetWeatherByPlaceNameAsyncr(placeName) = Async.BuildPrimitive(placeName, ws.BeginGetWeatherByPlaceName, ws.EndGetWeatherByPlaceName)

Table 7-9. A Comparison of Transaction Isolation Levels and Locking Behaviour in Oracle Versus Databases That Employ Read Locking Writes Block Reads No Reads Block Writes No DeadlockSensitive Reads No Incorrect Query Results Yes

Isolation Level READ UNCOMMITTED READ COMMITTED READ COMMITTED REPEATABLE READ SERIALIZABLE SERIALIZABLE

Like lists and tuples, option values are simple constructs frequently used as the workhorses in F# coding. An option is simply either a value Some(v) or the absence of a value None. For example,

Concurrency controls and how the database implements them are definitely things you want to understand. I ve been singing the praises of multi-versioning and read consistency, but like everything else in the world, they are double-edged swords. If you don t understand that multi-versioning is there and how it works, you will make errors in application design. Consider the resource scheduler example from 1. In a database without multi-versioning and its associated non-blocking reads, the original logic employed by the program may very well have worked. However, this logic would fall apart when implemented in Oracle. It would allow data integrity to be compromised. Unless you know how multi-versioning works, you will write programs that corrupt data. It is that simple.