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10 BEGIN 11 LOOP 12 FETCH inputdata INTO inputrec; 13 EXIT WHEN inputdata%NOTFOUND; 14 IF INPUTREC.SALES_2001 IS NOT NULL THEN 15 outputrow_2001.store_name := inputrec.store_name; 16 outputrow_2001.sales_year := 2001; 17 outputrow_2001.total_sales:= inputrec.sales_2001; 18 pipe row (outputrow_2001); 19 END IF; 20 IF INPUTREC.SALES_2002 IS NOT NULL THEN 21 outputrow_2002.store_name := inputrec.store_name; 22 outputrow_2002.sales_year := 2002; 23 outputrow_2002.total_sales:= inputrec.sales_2002; 24 pipe row (outputrow_2002); 25 END IF; 26 END LOOP; 27 RETURN; 28 END; 29* END; SQL> / Package body created. SQL> Let s look at each part of the package carefully: In order to return sets of rows from the source table as inputs to the table function, you need to create a REF CURSOR based on the source table rows. The REF CURSOR in the example is named sales_cursor. The function modify_sales_data is the table function. It has one input parameter, the REF CURSOR sales_cursor. The function returns data in the format of the source table, yearly_store_sales. The keyword PIPELINED at the end means that data flows through the data transformation process. As the input data is processed, the transformed results are continuously fed into the target table. The package body shows the details of the function modify_sales_data. The function will transform the original structure of data in the source table into the desired format and insert it into the target table. In the following INSERT statement, the function modify_sales_data is used. Note how the function is applied to the row data from the original table sales_data. The data is transformed before it is inserted into the yearly_store_sales table. SQL> INSERT INTO yearly_store_sales t 2 SELECT * 3 FROM TABLE(sales_package.modify_sales_data( 4 CURSOR(select store_name,sales_2001,sales_2002 5 FROM sales_data))); 6 rows created. SQL> COMMIT; Commit complete. SQL>

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In a very similar way, the shutdown logic can be implemented: ~XYZHandle() { try {} finally { if (hxyz) { ::XYZDisconnect(hxyz); hxyz = 0; } } GC::KeepAlive(this); } One may criticize that this code misuses a well-known language construct, but using try...finally in this scenario is part of an officially recommended pattern for reliable resource cleanup. The following explanations complete the discussion of this pattern by discussing the other asynchronous exceptions mentioned previously.

Web services are self-contained, modular applications that can be published and invoked on the Web. Web services can perform complex business processes or serve as information providers. For example, you will find weather information services and stock market ticker services. Table functions can help you mine web services data. Here's an outline of how you might use a table function to mine the stock market information that is published on the Web to provide a stock price alert system: 1. A private web service run by a stock market information services is accessed to collect the stock price information. 2. A table function, using a REF CURSOR of stock symbols as inputs, calls a Java stored procedure to gather the stock information from the web service. The table function converts the necessary stock price information into relational table data. The table function processes the information in the REF CURSOR one row at a time, and loads it into the table in a streamed fashion. You can have this information updated at regular intervals. 3. You can then use SQL and PL/SQL code to mine the stock data you collected in step 2. For example, the following is a typical SQL statement that uses the web services data you downloaded into your database table(s): SQL> SELECT AVG(price), MIN(price), MAX(price) FROM table(stock_service_pack.to_table (cursor(select stock_symbol from stocks )));

Listing 13-13 shows the data in the new table. Note how the original data in the sales_data table has been transformed into a different format by the table function. Listing 13-13. The Transformed Table SQL> SELECT * FROM yearly_store_sales; STORE_NAME SALES_YEAR TOTAL_SALES ------------------------- ---------- -------shoe city 2002 500000 trinkets galore 2001 1400000 trinkets galore 2002 1500000 modern tools 2001 1000000 modern tools 2002 1200000 toys and toys 2002 800000 6 rows selected. SQL> The final SELECT statement from the yearly_store_sales table shows a different layout of data from that of the original table, sales_data. Now each store has a new column and year, and the yearly sales data is in separate rows. This makes it easier to compare the yearly sales figures of the various stores. This example is rather trivial, but it clearly illustrates how you can use table functions to easily transform data during the process of loading it into another table.

A math library available in ksh lets us perform more-sophisticated mathematical calculations. These are the functions it provides: abs(), acos(), asin(), atan(), atan2(), cos(), cosh(), exp(), floor(), fmod(), hypot(), int(), log(), pow(), sin(), sinh(), sqrt(), tan(), and tanh(). Table 11-1 gives a basic description of these functions, but their use is beyond the scope of this book. The following variable assignment demonstrates the use of one of these higher level mathematical functions: