Oracle sql with 語句語法與例子

regonly1發表於2011-10-26
Oracle SQL中with語句是個有用的結構,下面是從eygle引用過來的一篇文章,講的很詳細,而且對於with的使用場合及機制也做了描述,很值得參考:
原始連結:


正文:

Starting in Oracle9i release 2 we see an incorporation of the SQL-99 "WITH clause", a tool for materializing subqueries to save Oracle from having to re-compute them multiple times.

The SQL "WITH clause" is very similar to the use of Global temporary tables (GTT), a technique that is often used to improve query speed for complex subqueries. Here are some important notes about the Oracle "WITH clause":

   ? The SQL "WITH clause" only works on Oracle 9i release 2 and beyond.
   ? Formally, the "WITH clause" is called subquery factoring
   ? The SQL "WITH clause" is used when a subquery is executed multiple times
   ? Also useful for recursive queries (SQL-99, but not Oracle SQL)

To keep it simple, the following example only references the aggregations once, where the SQL "WITH clause" is normally used when an aggregation is referenced multiple times in a query.

We can also use the SQL-99 "WITH clause" instead of temporary tables. The Oracle SQL "WITH clause" will compute the aggregation once, give it a name, and allow us to reference it (maybe multiple times), later in the query.

The SQL-99 "WITH clause" is very confusing at first because the SQL statement does not begin with the word SELECT. Instead, we use the "WITH clause" to start our SQL query, defining the aggregations, which can then be named in the main query as if they were "real" tables:

WITH
subquery_name
AS
(the aggregation SQL statement)
SELECT
(query naming subquery_name);


Retuning to our oversimplified example, let's replace the temporary tables with the SQL "WITH  clause" (Note:  You may find a faster execution plan by using Global Temporary tables, depending on your release of Oracle):

WITH sum_sales AS
  ( select /*+ materialize */  sum(quantity) all_sales from stores ),
number_stores AS 

( select /*+ materialize */  count(*) nbr_stores from stores ),
sales_by_store AS
  ( select /*+ materialize */   store_name, sum(quantity) store_sales from  store natural join sales )
SELECT   store_name
FROM   store,   sum_sales,   number_stores,   sales_by_store
where   store_sales > (all_sales / nbr_stores);


Note the use of the Oracle undocumented "materialize" hint in the "WITH clause". The Oracle materialize hint is used to ensure that the Oracle cost-based optimizer materializes the temporary tables that are created inside the "WITH" clause. This is not necessary in Oracle10g, but it helps ensure that the tables are only created one time.

It should be noted that the "WITH clause" does not yet fully-functional within Oracle SQL and it does not yet support the use of "WITH clause" replacement for "CONNECT BY" when performing recursive queries.

To see how the "WITH clause" is used in ANSI SQL-99 syntax, here is an excerpt from Jonathan Gennick's great work "Understanding the WITH Clause" showing the use of the SQL-99 "WITH clause" to traverse a recursive bill-of-materials hierarchy

The SQL-99 "WITH clause" is very confusing at first because the SQL statement does not begin with the word SELECT. Instead, we use the "WITH clause" to start our SQL query, defining the aggregations, which can then be named in the main query as if they were "real" tables:

WITH
subquery_name
AS
(the aggregation SQL statement)
SELECT
(query naming subquery_name);


Retuning to our oversimplified example, let's replace the temporary tables with the SQL "WITH" clause":

Link:


Improving Query Performance with the SQL WITH Clause
   

Oracle9i significantly enhances both the functionality and performance of SQL to address the requirements of business intelligence queries. The SELECT statement's WITH clause, introduced in Oracle9i, provides powerful new syntax for enhancing query performance. It optimizes query speed by eliminating redundant processing in complex queries.

Consider a lengthy query which has multiple references to a single subquery block. Processing subquery blocks can be costly, so recomputing a block every time it is referenced in the SELECT statement is highly inefficient. The WITH clause enables a SELECT statement to define the subquery block at the start of the query, process the block just once, label the results, and then refer to the results multiple times.

The WITH clause, formally known as the subquery factoring clause, is part of the SQL-99 standard. The clause precedes the SELECT statement of a query and starts with the keyword "WITH." The WITH is followed by the subquery definition and a label for the result set. The query below shows a basic example of the clause:

WITH channel_summary AS
  ( SELECT channels.channel_desc,
       SUM(amount_sold) AS channel_total
    FROM sales, channels
    WHERE sales.channel_id = channels.channel_id
    GROUP BY channels.channel_desc )
SELECT channel_desc, channel_total
FROM channel_summary
WHERE channel_total >
  ( SELECT SUM(channel_total) * 1/3
    FROM channel_summary );

This query uses the WITH clause to calculate the sum of sales for each sales channel and label the results as channel_summary. Then it checks each channel's sales total to see if any channel's sales are greater than one third of the total sales. By using the new clause, the channel_summary data is calculated just once, avoiding an extra scan through the large sales table.

Although the primary purpose of the WITH clause is performance improvement, it also makes queries easier to read, write and maintain. Rather than duplicating a large block repeatedly through a SELECT statement, the block is localized at the very start of the query. Note that the clause can define multiple subquery blocks at the start of a SELECT statement: when several blocks are defined at the start, the query text is greatly simplified and its speed vastly improved.

The SQL WITH clause in Oracle9i significantly improves performance for complex business intelligence queries. Together with the many other SQL enhancements in Oracle9i, the WITH clause extends Oracle's leadership in business intelligence.

More Info


: Chapter 17 - SELECT Statement

: Chapter 18 - SQL for Aggregation in Data Warehouses

Link:

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