《Pro Oracle SQL》CHAPTER2--2.10 Query Rewrite with Materialized Views

Query Rewrite with Materialized Views  用物化视图重写查询 (page 72)
    Query rewrite is a transformation that occurs when a query, or a portion of a query , has been saved as a materialized view and the transformer can rewrite the query to use the precomputed materialized view data instead of executing the current query. A materialized view is like a normal view except that the query has been executed and its result set has been stored in a table. What this does is to precompute the result of the query and make it available whenever the specific query is executed. That means that all the work to determine the plan, execute it, and gather up all the data has already been done. So, when the same query is executed again, there is no need to go through all that effort again. 
    查询重写是一种变换发生在，当一查询，或一部分查询，(执行后)作为物化视图保存且变换器可使用预先计算好的物化视图数据重写查询，而不是执行当前的查询。 除了查询已经执行且它的结果已经存入表中以外，物化视图像普通视图一样。(物化视图所作的是)预先计算查询的结果且在特定查询执行时使其(结果) 有效。这意味着所有确定计划，执行计划，收集全部数据的工作已经完成。这样的话，当相同的查询再次执行时，就不再需要重头到尾费力一番。
    The query transformer will match a query with available materialized views and then rewrite the query to simply select from the materialized result set. Listing 2-10 walks through creating a materialized view and how the transformer would rewrite the query to use the materialized view result set . 
    查询变化器将把一个查询和有效的物化视图相匹配，然后重写查询，直接的从物化的结果集中选取(数据)。 列表2-10通过创建一物化视图，展示变换器如何用物化视图的结果集重写查询。
Listing 2-10. Query Rewrite with Materialized Views
SQL > set autotrace traceonly explain
SQL >
SQL > SELECT p.prod_id, p.prod_name, t.time_id, t.week_ending_day,
   2                   s.channel_id, s.promo_id, s.cust_id, s.amount_sold
   3     FROM sales s, products p , times t
   4     WHERE  s.time_id = t.time_id   AND  s.prod_id = p.prod_id;

Execution Plan
--------------------------------------------------------------------------
Plan hash value : 1109402314
-----------------------------------------------------------------------------------------------------------------------------------
|  Id    |   Operation                                    |   Name         |   Rows    |   Bytes   |  Cost  (%CPU ) |  Pstart |  Pstop   |
-----------------------------------------------------------------------------------------------------------------------------------------
|    0  |   SELECT   STATEME N T            |                     |      918 K|        65 M |      485     (17) |           |             |
|*   1  |     HASH  JOIN                            |                     |      918 K|        65 M |      485     (17) |           |             |
|    2  |        TABLE  ACCESS  FULL         |   TIMES       |     1826   |   29216    |        15      (0) |            |             |
|*   3  |        HASH  JOIN                         |                     |      918 K|        51 M |      453     (14) |            |             |
|    4  |           TABLE  ACCESS   FULL    |   PRODUCTS |        72  |     2160     |         3      (0)  |            |             |
|    5  |           PARTITION  RANGE   ALL |                      |      918 K|        25 M |      434     (11) |         1 |       28   |
|    6  |             TABLE  ACCESS  FULL   |   SALES         |      918 K|        25 M |      434     (11) |         1 |       28   |
------------------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
-------------------------------------------------------------------------------
     1  -   access("S". "TIME_ID" = "T" . "TIME_ID")
     3  -   access("S". "PROD_ID" = "P"."PROD_ID")
SQL >
SQL >  set autotrace off

SQL>
SQL> CREATE MATERIALIZED VIEW sales_time_product_mv
  2  ENABLE QUERY REWRITE AS
  3  SELECT p.prod_id, p.prod_name, t.time_id, t.week_ending_day,
  4         s.channel_id, s.promo_id, s.cust_id, s.amount_sold
  5  FROM   sales s, products p, times t
  6  WHERE  s.time_id=t.time_id  AND s.prod_id = p.prod_id;
SQL>
SQL> set autotrace traceonly explain
SQL>
SQL> SELECT p.prod_id, p.prod_name, t.time_id, t.week_ending_day,
  2         s.channel_id, s.promo_id, s.cust_id, s.amount_sold
  3  FROM   sales s, products p, times t
  4  WHERE  s.time_id=t.time_id  AND s.prod_id = p.prod_id;
 Execution Plan
----------------------------------------------------------
Plan hash value: 1109402314
 
---------------------------------------------------------------------------------------
| Id  | Operation                                 | Name           | Rows   | Bytes | Cost (%CPU)| Pstart| Pstop |
---------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT               |                    |   918K |    65M |   485  (17)    |          |         |
|*  1 |   HASH JOIN                            |                    |   918K |    65M |   485  (17)     |         |         |
|   2 |      TABLE ACCESS FULL          | TIMES        |  1826   | 29216 |    15   (0)      |          |         |
|*  3 |      HASH JOIN                         |                    |   918K |    51M |   453  (14)     |         |         |
|   4 |         TABLE ACCESS FULL      | PRODUCTS |    72    |  2160  |     3   (0)        |         |         |
|   5 |         PARTITION RANGE ALL   |                    |   918K |    25M |   434  (11)      |     1  |    28 |
|   6 |           TABLE ACCESS FULL     | SALES        |   918K |    25M |   434  (11)     |     1   |    28 |
---------------------------------------------------------------------------------------
 
Predicate Information (identified by operation id):
---------------------------------------------------
 
   1 - access("S"."TIME_ID"="T"."TIME_ID")
   3 - access("S"."PROD_ID"="P"."PROD_ID")
 
Note
-----
   - dynamic sampling used for this statement
 
SQL>
SQL> SELECT /*+ rewrite(sales_time_product_mv) */
  2        p.prod_id, p.prod_name, t.time_id, t.week_ending_day,
  3         s.channel_id, s.promo_id, s.cust_id, s.amount_sold
  4  FROM   sales s, products p, times t
  5  WHERE  s.time_id=t.time_id  AND s.prod_id = p.prod_id;
Execution Plan
----------------------------------------------------------
Plan hash value: 663088863
 
-------------------------------------------------------------------------------------------
| Id  | Operation                                            | Name                                    | Rows  | Bytes | Cost (%CPU)|
-------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                         |                                               |   909K|    95M|  1935   (3)|
|   1 |  MAT_VIEW REWRITE ACCESS FULL| SALES_TIME_PRODUCT_MV |   909K|    95M|  1935   (3)|
-------------------------------------------------------------------------------------------
 
Note
-----
   - dynamic sampling used for this statement
    In order to keep the example simple, I used a  REWRITE  hint to turn on the query rewrite
transformation.  You can enable query rewrite to happen automatically as well.  But as you notice in the
example, when the rewrite does occur, the plan simply shows a full access on the materialized view
instead of the entire set of operations required to produce the result set originally.   As you can imagine,
the time savings can be substantial for complicated queries with large results sets, particularly if the
query contains aggregations.  For more information on query rewrite and materialized views, refer to
The Oracle Data Warehousing Guide where you’ll find an entire chapter on advanced query rewrite.
    为了让例子简单，我使用REWRITE提示打开查询重写变换。你也能让查询重写自动有效。但是如你在例子中所见，当查询重写发生时，计划直接展示在物化视图上的全扫描而不是最初产生结果集所需的整个操作集合。 你能想象，对于复杂的大结果集的查询能实质上的节约时间，特别是如果查询包含聚合操作。更多的信息关 于查询重写和物化视图，参考《Oracle数据仓库指南》，其中你能找到整章的查询重写的高级(论述)。