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In addition to the four defined SQL isolation levels, Oracle provides another level, namely READ ONLY. A READ ONLY transaction is equivalent to a REPEATABLE READ or SERIALIZABLE transaction that can t perform any modifications in SQL. A transaction using a READ ONLY isolation level only sees those changes that were committed at the time the transaction began, but inserts, updates, and deletes are not permitted in this mode (other sessions may update data, but not the READ ONLY transaction). Using this mode, you can achieve REPEATABLE READ and SERIALIZABLE levels of isolation. Let s now move on to discuss exactly how multi-versioning and read consistency fit into the isolation scheme and how databases that do not support multi-versioning achieve the same results. This information is instructive for anyone who has used another database and believes she understands how the isolation levels must work. It is also interesting to see how a standard that was supposed to remove the differences between the databases, ANSI/ISO SQL, actually allows for them. The standard, while very detailed, can be implemented in very different ways.

WHEN 40 THEN 'Operations' ELSE 'Unknown' END) department FROM employees;

This allows you to have robust transactions in the database. These transactions do not have to be short in duration they should be exactly as long as they need to be (but no longer). Transactions are not for the convenience of the computer and its software; they are to protect your data.

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Oracle s SQL analytical functions are powerful tools for business intelligence applications. Oracle claims a potential improvement of 200 to 500 percent in query performance with the use of the SQL analytical functions. The purpose behind using analytical functions is to perform complex summary computations without using a lot of code. Here are the main SQL analytical functions of the Oracle database: Ranking functions: These enable you to rank items in a data set according to some criteria. Oracle has several types of ranking functions, including RANK, DENSE_RANK, CUME_DIST, PERCENT_ RANK, and NTILE. Listing A-1 shows a simple example of how a ranking function can help you rank some sales data. Listing A-1. An Example of a Ranking Function SQL> SELECT sales_type, TO_CHAR(SUM(amount_sold), '9,999,999,999') SALES, RANK() OVER (ORDER BY SUM(amount_sold) ) AS original_rank, RANK() OVER (ORDER BY SUM(amount_sold) DESC NULLS LAST) AS derived_rank FROM sales, products, customers, time_frame, sales_types WHERE sales.prod_id=products.prod_id AND sales.cust_id=customers.cust_id AND sales.time_id=time_frame.time_id AND sales.sales_type_id=sales_types.sales_type_id AND timeframe.calendar_month_desc IN ('2008-07', '2008-08') AND country_id='INDIA' GROUP BY sales_type; SALES_TYPE ------------Direct Sales Internet Catalog Partners Tele Sales SQL> SALES --------5,744,263 3,625,993 1,858,386 1,500,213 604,656 ORIGINAL_RANK -------------5 4 3 2 1 DERIVED_RANK -----------1 2 3 4 5

The READ UNCOMMITTED isolation level allows dirty reads. Oracle does not make use of dirty reads, nor does it even allow for them. The basic goal of a READ UNCOMMITTED isolation level is to provide a standardsbased definition that caters for non-blocking reads. As we have seen, Oracle provides for non-blocking reads by default. You would be hard-pressed to make a SELECT query block in the database (as noted earlier, there is the special case of a distributed transaction). Every single query, be it a SELECT, INSERT, UPDATE, MERGE, or DELETE, executes in a read-consistent fashion. It might seem funny to refer to an UPDATE statement as a query, but it is. UPDATE statements have two components: a read component as defined by the WHERE clause and a write component as defined by the SET clause. UPDATE statements read and write to the database; all DML statements have this ability. The case of a single row INSERT using the VALUES clause is the only exception, as such statements have no read component, just the write component. In 1 Developing Successful Oracle Applications , Oracle s method of obtaining read consistency was demonstrated by way of a simple single table query that retrieved rows that were deleted after the cursor was opened. We re now going to explore a real-world example to see what happens in Oracle using multi-versioning, as well as what happens in any number of other databases. Let s start with the same basic table and query: create table accounts ( account_number number primary key, account_balance number not null ); select sum(account_balance) from accounts; Before the query begins, assume we have the data shown in Table 7-2. Table 7-2. ACCOUNTS Table Before Modifications

Moving-window aggregates: These functions provide cumulative sums and moving averages. Period-over-period comparisons: These functions let you compare two periods (for example, How does the first quarter of 2008 compare with the first quarter of 2006 in terms of percentage growth ). Ratio-to-report comparisons: These make it possible to compare ratios (for example, What is August s enrollment as a percentage of the entire year s enrollment ). Statistical functions: These functions calculate correlations and regression functions so you can see cause-and-effect relationships among data. Inverse percentiles: These help you find the data corresponding to a percentile value (for example, Get me the names of the salespeople who correspond to the median sales value. ).

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