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Listing 13-11. Partial Loading of Rows from the Source Table SQL> INSERT FIRST WHEN (quantity_sold > 10 AND product_id <1000) THEN INTO targetA VALUES (sysdate,product_id, customer_id, quantity_sold)) WHEN quantity_sold <= 10 and product_id >10000 THEN INTO targetB VALUES (sysdate,product_id, customer_id, quantity_sold) ELSE INTO targetC VALUES (time_id, cust_id, prod_id, sum_quantity_sold) SELECT s.time_id, s.cust_id, s.prod_id, p.prod_weight_class, SUM(amount_sold) AS sum_amount_sold, SUM(quantity_sold) AS sum_quantity_sold FROM sales s, products p WHERE s.prod_id = p.prod_id AND s.time_id = TRUNC(sysdate) GROUP BY s.time_id, s.cust_id, s.prod_id, p.prod_weight_class;

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Addition: answer=$(($c+$d)) Subtraction: answer=$(($c-$d)) Multiplication: answer=$(($c*$d)) Division: answer=$(($c/$d)) Remainder: answer=$(($c%$d)) Exponentiation: The first argument raised to the power of the second; answer=$(($c**$d)) Order of operations: The default order can be modified by using parentheses, as with the other methods of performing shell math; answer=$((($c+$d)*$c)). Without the use of parentheses to order the calculations as you desire, the common order is as follows:

You can use Oracle s table functions to perform efficient data transformations Table functions produce a collection of transformed rows that can be queried just like a regular table s data Oracle table functions are an excellent example of Oracle s sophisticated transform-while-loading paradigm Table functions can take a set of rows as input and return a transformed set of rows When you query a table function in a statement, the function returns a collection type instance representing the rows in a table The collection types can be either a VARRAY or a nested table Table functions allow you to use PL/SQL, C, or Java with SQL without any problems Table functions make the traditional use of staging tables redundant You don t need to create any intermediate tables to perform data transformations before loading data into the final data warehouse tables.

Three features make table functions a powerful means of performing fast transformation of data sets: Streaming: This refers to the direct transmission of results from one process to the other without any intermediate steps The way in which a table function orders or clusters rows that it fetches from cursor arguments is called data streaming Parallel execution: This refers to the concurrent execution of the functions on multiprocessor systems Pipelining: This technique lets you see the results of a query iteratively, instead of waiting for the entire result set to be batched and returned Pipelining can thus help table functions reduce the response time by sending results as soon as they are produced in batches You also have the option of having the table function immediately return rows from a collection by using pipelining.

The elimination of (sometimes multiple) staging tables and the lack of need for any manual coding of parallel processing makes the pipelined parallel processing provided by table functions very attractive during large-scale data loading and transformation Here s a brief summary of the tasks that table functions can help you perform: Return a set of rows Return a result set incrementally, so you can process the results gradually Accept a cursor as an input.

Return results continuously while the transformation is taking place Be parallelized It s easy to understand what a table function is when you think about a regular Oracle function An Oracle function such as SUBSTR or TRANSLATE transforms data For example, you can use the SUBSTR function to cut out a portion of a string, as shown in the following example: SQL> SELECT sysdate FROM dual; SYSDATE ======== 20-MAY-05 SQL> SELECT SUBSTR(sysdate,4,3) FROM dual; SUBSTRING(SYSDATE) =================== MAY SQL> Table functions work the same way as regular Oracle functions that transform data The only difference is that the table functions can be much more complex, and they can take cursors as inputs and return multiple rows after transforming them.

A typical asynchronous exception is System::Threading::ThreadAbortException, which is thrown to abort a thread. The most obvious way a thread can be aborted is the Thread.Abort API. Version 2.0 of the CLR guarantees that a ThreadAbortException is not thrown inside a catch or a finally block. This feature prevents error handling and cleanup code from being rudely interrupted. If you want to ensure that a ThreadAbortException cannot be thrown between the native call that allocates a native resource and the storage of the native handle in the wrapper class, you can modify your code so that both operations are executed inside a finally block. The following code solves the problem: XYZConnection() { try {} finally { xyzHandle.Handle = ::XYZConnect(); } }

1. Globbing is the term used for the shell s completion of paths and filenames that contain metacharacters.