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As promised, after showing you that a lot of rather innocent-looking problems are actually unimaginably hard, I m going to show you a way out: sloppiness I mentioned earlier the idea of the instability of hardness, that even small tweaks to the problem requirements can take you from utterly horrible to pretty nice There are many kinds of tweaks you can do I m only going to cover two In this section, I ll show you what happens if you allow a certain percentage of sloppiness in your search for optimality; in the next section, I ll have a look at the fingers crossed school of algorithm design Let me first clarify the idea of approximation Basically, we ll be allowing the algorithm to find a solution that may not be optimal, but whose value is at most a given percentage off.



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<bean class="org.springframework.web.portlet.handler. PortletModeParameterHandlerMapping"> <property name="portletModeParameterMap"> <map> <entry key="view"> <map> <entry key="flightDetail" value-ref="flightDetailController" /> </map> </entry> </map> </property> <property name="order" value="0" /> </bean>





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Notice that we close the objects in the opposite order from which they were created. The object created first is closed last, and vice versa. Notice how clean this looks you don t have to put a try...catch block inside the finally block and you don t have to worry about the close(Statement) method throwing an exception that prevents close(Connection) from executing. The last method of Statement object that we re going to look at is the executeQuery() method. Unlike the executeUpate() or executeBatch() methods, executeQuery() does not return a simple int value. The method is used to execute a SQL SELECT command, and the SELECT command returns zero or more rows of data from one or more tables. These rows are returned in an object known as ResultSet, which is the subject of the next section.

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More commonly, this percentage is given as a factor, or approximation ratio For example, for a ratio of 2, a minimization algorithm would guarantee us a solution at most twice the optimum, while a maximization problem would give us one at least half the optimum14 Let s see how this works, by returning to a promise I made back in 7 What I said was that the unbounded integer knapsack problem can be approximated to within a factor of two using greed As for exact greedy algorithms, designing the solution here is trivial (just use the same greedy approach as for fractional knapsack); the problem is showing that it s correct.

When you perform a query of a table in a database, the results of the query are returned in a ResultSet object. The ResultSet object allows you to scroll through each row of the results, and read the data from each column in the row.

In portlet applications, you sometimes have to deal with forms. In order for a controller to handle forms, it has to render the form view to a user and also handle the form submission. You will get involved in too many form-handling details if you build your form controller from scratch.

The ResultSet interface defines a number of methods that can be used for moving through the results returned. However, not all methods are available for every resultset. Here again are the three methods that create Statement objects: public Statement createStatement() public Statement createStatement(int, int) public Statement createStatement(int, int, int)

How can it be that, if we keep adding the item type with the highest unit value (that is, value-to-weight ratio), we re guaranteed to achieve at least half the optimum value How on Earth can we know this when we have no idea what the optimum value is This is the crucial point of approximation algorithms We don t know the exact ratio of the approximation to the optimum we only give a guarantee for how bad it can get This means that if we get an estimate on how good the optimum can get, we can work with that instead of the actual optimum, and our answer will still be valid Let s consider the maximization case.

When you use the first method to create a Statement object, the ResultSet object that is returned by executeQuery() is a nonscrollable ResultSet, or one that is of type forward-only. This means that you can only move from the first row to the last row, and cannot scroll backwards through the results. The only method for moving through the ResultSet object that can be used is:

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