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The list gets bound upon the first request of the page. protected void Page_Load(object sender, EventArgs e) { if (!IsPostBack) { SqlConnection cn = new SqlConnection( ConfigurationManager.ConnectionStrings ["localPubs"].ToString()); string sql = "select state from authors group by state order by state"; SqlCommand cm = new SqlCommand(sql, cn); cn.Open(); ddlState.DataSource = cm.ExecuteReader(); ddlState.DataTextField = "state"; ddlState.DataBind(); cn.Close(); ddlState.Items.Insert(0, ""); } } All postbacks are then fired by a change made to the DropDownList. Here s where you ll use a cached DataView that already has an index prepared for the state column of the authors table. By applying a row filter to the view, you re leveraging the index on the column you sorted by when creating the view. By keeping it in the cache you are once again using only a single instance of the data instead of returning to the database each time the user selects a state. private DataView GetAuthors() { DataSet ds; DataView dv; dv = (DataView)Cache["AuthorData"]; if (dv == null) { ds = new DataSet(); SqlConnection cn = new SqlConnection( ConfigurationManager.ConnectionStrings ["localPubs"].ToString());

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Oracle decides how to store the varray based on the maximum possible size of the varray computed using the limit of the declared array. According to the official Oracle documentation, if the size exceeds approximately 4,000 bytes, Oracle stores the varray as a LOB; otherwise, Oracle stores it as a raw value. However, it turns out that a raw data type can store only a maximum of 2,000 bytes. Thus it is highly likely that Oracle actually stores the varray as a varchar2 (not as a raw) when the size is less than 4,000 bytes. Now that we have discussed varrays in tables and their associated disadvantages in terms of increased code complexity and potential performance issues, let s move on to look at how we can use nested tables to store data.

Figure 12-4 shows a diagrammatic representation of three hardware circuits: a half adder, a full adder, and a 2-bit carry ripple adder. The first of these has two input wires, x and y, and sets the sum wire high if exactly one of these is high. If both x and y are high, then the sum is low, and the carry wire is high instead. Thus, the circuit computes the 2-bit sum of the inputs. Likewise, a full adder computes the sum of three Boolean inputs, which, since it is at most three, can still be represented by 2 bits. A 2-bit carry ripple adder is formed by composing a half adder and a full adder together, wiring the carry from the first adder to one of the inputs of the second adder. The overall circuit has four inputs and three outputs.

In this section, I ll illustrate how to use nested tables to store data. You can use a nested table column in a table as an alternative to creating separate parent/child tables (I ll discuss the pros and cons of both approaches subsequently). To compare and contrast methods, we ll also create a relational schema for the same example.

Figure 12-4. Three simple hardware circuits The following code models these circuit components. This uses relational modeling, where each circuit is modeled not as a function but as a propositional logic predicate that relates its input wires to its output wires: let sumBit x y = (x ^^^ y) let carryBit x y = (x &&& y) let halfAdder x y sum carry = (sum === sumBit x y) &&& (carry === carryBit x y) let fullAdder x y z sum carry = let xy = (sumBit x y) (sum === sumBit xy z) &&& (carry === (carryBit x y ||| carryBit xy z))

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