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However, it is relatively hard to use for validating data. There s no easy way to find a value given a key, or a key given a value. To simplify these common tasks, the class includes Key and Value properties: public V Value(K key) { foreach (NameValuePair item in this) if (item.Key.Equals(key)) return item.Value; return default(V); } public K Key(V value) { foreach (NameValuePair item in this) if (item.Value.Equals(value)) return item.Key; return default(K); } The Value property accepts a key (name) and returns the value corresponding to that key. The Key property does the reverse, accepting a value and returning the first matching key value. In either case, if the value is not found, then the default value of the generic type is returned. If the generic type is a reference type, this will be null; otherwise, it is typically 0 or false. Similarly, there are ContainsKey() and ContainsValue() methods: public bool ContainsKey(K key) { foreach (NameValuePair item in this) if (item.Key.Equals(key)) return true; return false; } public bool ContainsValue(V value) { foreach (NameValuePair item in this) if (item.Value.Equals(value)) return true; return false; }

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In addition, varrays are even less flexible when it comes to updating them, since they don t allow selective updates; you have to replace the entire varray even if you want to change only one value in the varray Besides, you can t create indexes on individual varray object columns Thus, you can conclude that using nested tables or varrays as a mechanism to persist your data isn t really a good idea The question becomes, is there a middle ground In other words, can you have the flexibility of storing data in relational tables, and yet access them as objects when needed Object views, covered in the next section, may provide you with one such mechanism..

Note The data is generated programmatically and is meaningless; its only purpose is to provide a raw

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Collectively, these properties and methods make it easy for a UI or business developer to use the name/value list to validate values and to translate between keys and values.

Object views allow you to access and manipulate relational data as if the data were stored in tables containing object type or collection columns. Object views give you the flexibility to store data in relational tables. Thus you can selectively choose to use object features when it makes sense (e.g., to retrieve data directly as objects for your Java applications). For the most part, you can use relational SQL directly on the underlying relational schema, thus avoiding the code complexity and performance problems associated with storing data in tables containing objects. The process of creating object views on relational tables involves the following steps: 1. Define an object type. In this step, we define an object type where each attribute corresponds to a relational table column. This object type will be used in creating the object view.

Selecting the tool bar menu path Tools Development Tools Benchmark does not start the Data Creation Wizard, but instead displays the application menu designed specifically for the benchmark module, shown in Figure 21-6.

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As with the framework base classes from 3, the ICloneable interface is implemented. This is done using the Csla.ObjectCloner class: object ICloneable.Clone() { return GetClone(); } [EditorBrowsable(EditorBrowsableState.Advanced)] protected virtual object GetClone() { return Core.ObjectCloner.Clone(this); } public NameValueListBase<K, V> Clone() { return (NameValueListBase<K, V>)GetClone(); } The strongly typed Clone() method is public, while the loosely typed implementation can only be accessed through the ICloneable interface.

2. Define an object view. Next, we define an object view with a query that represents the object-oriented view we have in mind. 3. Define the instead of triggers. In this step, we write instead of triggers on the view to support required DML statements such as insert, update, and delete that work directly on the object view. This step is required only if we want to insert, delete, and update directly on the object view. The alternative is to do these operations directly on the underlying tables. As you ll see shortly, the instead of triggers can be quite complex, and the resulting DMLs on the object view can result in very poor performance. Hence I recommend that you avoid creating these triggers and instead use object views only to perform selects on them. We ll look at each of the preceding steps in the following sections. We will demonstrate the use of object views by creating an object view on top of the relational tables, components_rel and parts_rel, that we created in the earlier section Relational Tables Based Approach. We assume that our relational schema consisting of the tables components_rel and parts_rel has the following data to begin with: benchmark@ORA10G> select * from components_rel; COMPONENT_ID -----------1 2 COMPONENT_NAME -------------component1 component2

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