Oracle 12CR2查询转换之星型转换

星型转换是一种优化转换它用来避免对星型方案中的事实表进行全表扫描。一个星型方案将数据分成事实与维度表。事实是对一个事件比如销售的测量通常是数字。维度是标识事实的分类,比如日期,位置与产品。一个事实表有一个由方案中维度表主键所组成的复合键。维度表实际上充当查找或引用表能让你选择你查询所要请求的值。

星型转换的目的
在连接事实表与维度表时,星型转换可能避免对事实表执行完全扫描。星型转换通过只获取连接到约束维度行记录的相关事实行记录来提高性能。在有些情况下,查询已经在维度表的其它列上有限制性过滤了。过滤组合可以大大减少数据库从事实表中要处理的数据集大小。

星型转换的工作原理
星型转换增加了子查询谓词,叫作位图半连接谓词,关联到约束维度表。当在实际连接列上存在索引时优化器执行转换。通过驱动位图and和or来操作由子查询所提供的键值,数据库只需要从事实表中检索相关行记录。如果维度表上的谓词过滤掉了大量数据,那么星型转换比对事实表完全扫描更有效。

在数据库从事实表中检索相关行记录之后,数据库可能需要使用原始谓词连接这些行记录回维度表。当以下条件满足时数据库可以消除连接回维度表:
.维度表上的所有谓词是半连接子查询谓词的一部分
.从子查询中所选择的列具有唯一性
.维度列不在select列,group by子句中等等

控制星型转换
star_transformation_enabled参数控制着星型转换。这个参数有以下参数值:
.true
优化器通过自动识别事实与约束维度表来执行星型转换。只有转换后的执行计划成本比原始执行计划成本低时优化器才执行星型转换。当物化提高性能时优化器也会尝试临时表转换。

.false(缺省值)
优化器不执行星型转换

.temp_disable
这个值与true相同,只是优化器不会尝试临时表转换

星型转换:应用场景
下面的查询找出1999年Q1和Q2季度在California的所有城市中的总的网络销售额:

SELECT c.cust_city,
t.calendar_quarter_desc,
SUM(s.amount_sold) sales_amount
FROM sales s,
times t,
customers c,
channels ch
WHERE s.time_id = t.time_id
AND s.cust_id = c.cust_id
AND s.channel_id = ch.channel_id
AND c.cust_state_province = 'CA'
AND ch.channel_desc = 'Internet'
AND t.calendar_quarter_desc IN ('1999-01','1999-02')
GROUP BY c.cust_city, t.calendar_quarter_desc;

示例输出如下:

SQL> show parameter star_transformation_enabled

NAME                                 TYPE        VALUE
------------------------------------ ----------- ------------------------------
star_transformation_enabled          string      FALSE

SQL> SELECT c.cust_city,
  2  t.calendar_quarter_desc,
  3  SUM(s.amount_sold) sales_amount
  4  FROM sales s,
  5  times t,
  6  customers c,
  7  channels ch
  8  WHERE s.time_id = t.time_id
  9  AND s.cust_id = c.cust_id
 10  AND s.channel_id = ch.channel_id
 11  AND c.cust_state_province = 'CA'
 12  AND ch.channel_desc = 'Internet'
 13  AND t.calendar_quarter_desc IN ('1999-01','1999-02')
 14  GROUP BY c.cust_city, t.calendar_quarter_desc;

CUST_CITY                      CALENDA SALES_AMOUNT
------------------------------ ------- ------------
Montara                        1999-02      1618.01
Pala                           1999-01      3263.93
Cloverdale                     1999-01        52.64
Cloverdale                     1999-02       266.28
San Francisco                  1999-01      3058.27
San Mateo                      1999-01      8754.59
Los Angeles                    1999-01      1886.19
San Mateo                      1999-02     21399.42
Pala                           1999-02       936.62
El Sobrante                    1999-02      3744.03
El Sobrante                    1999-01      5392.34
Quartzhill                     1999-01        987.3
Legrand                        1999-01        26.32
Pescadero                      1999-01        26.32
Arbuckle                       1999-02        241.2
Quartzhill                     1999-02       412.83
Montara                        1999-01       289.07
Arbuckle                       1999-01       270.08
San Francisco                  1999-02        11257
Los Angeles                    1999-02      2128.59
Pescadero                      1999-02       298.44
Legrand                        1999-02        18.66

22 rows selected.

SQL> select * from table(dbms_xplan.display_cursor(null,null,'advanced allstats last runstats_last peeked_binds'));
SQL_ID  a069wzk60bbqd, child number 1
-------------------------------------
SELECT c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold)
sales_amount FROM sales s, times t, customers c, channels ch WHERE
s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id =
ch.channel_id AND c.cust_state_province = 'CA' AND ch.channel_desc =
'Internet' AND t.calendar_quarter_desc IN ('1999-01','1999-02') GROUP
BY c.cust_city, t.calendar_quarter_desc

Plan hash value: 1865285285

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
| Id  | Operation                      | Name      | Starts | E-Rows |E-Bytes| Cost (%CPU)| E-Time   | Pstart| Pstop | A-Rows |   A-Time   | Buffers |  OMem |  1Mem | Used-Mem |
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT               |           |      1 |        |       |   957 (100)|          |       |       |     22 |00:00:00.18 |    1812 |       |       |          |
|   1 |  HASH GROUP BY                 |           |      1 |     22 |  1672 |   957   (2)| 00:00:01 |       |       |     22 |00:00:00.18 |    1812 |  1022K|  1022K| 1382K (0)|
|*  2 |   HASH JOIN                    |           |      1 |    138 | 10488 |   956   (2)| 00:00:01 |       |       |    964 |00:00:00.14 |    1812 |  1538K|  1538K| 1588K (0)|
|   3 |    PART JOIN FILTER CREATE     | :BF0000   |      1 |    183 |  2928 |    18   (0)| 00:00:01 |       |       |    181 |00:00:00.01 |      65 |       |       |          |
|*  4 |     TABLE ACCESS FULL          | TIMES     |      1 |    183 |  2928 |    18   (0)| 00:00:01 |       |       |    181 |00:00:00.01 |      65 |       |       |          |
|*  5 |    HASH JOIN                   |           |      1 |    964 | 57840 |   938   (2)| 00:00:01 |       |       |    964 |00:00:00.11 |    1747 |  1448K|  1448K| 1521K (0)|
|   6 |     MERGE JOIN CARTESIAN       |           |      1 |   3341 |   127K|   426   (1)| 00:00:01 |       |       |   3341 |00:00:00.02 |    1531 |       |       |          |
|*  7 |      TABLE ACCESS FULL         | CHANNELS  |      1 |      1 |    13 |     3   (0)| 00:00:01 |       |       |      1 |00:00:00.01 |       9 |       |       |          |
|   8 |      BUFFER SORT               |           |      1 |   3341 | 86866 |   423   (1)| 00:00:01 |       |       |   3341 |00:00:00.02 |    1522 |   178K|   178K|  158K (0)|
|*  9 |       TABLE ACCESS FULL        | CUSTOMERS |      1 |   3341 | 86866 |   423   (1)| 00:00:01 |       |       |   3341 |00:00:00.01 |    1522 |       |       |          |
|  10 |     PARTITION RANGE JOIN-FILTER|           |      1 |    819K|    16M|   510   (2)| 00:00:01 |:BF0000|:BF0000|    118K|00:00:00.02 |     216 |       |       |          |
|  11 |      TABLE ACCESS FULL         | SALES     |      2 |    819K|    16M|   510   (2)| 00:00:01 |:BF0000|:BF0000|    118K|00:00:00.02 |     216 |       |       |          |
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

从上面的执行中可以看到,在没有使用星型转换时id=11,对表sales执行的是全表扫描。在这个例子中,sales表是事实表,并且其它的表是维度表。sales表对于每一个销售的产品都有一行记录,因此它可以包含上十亿行销售记录。然而,只有少量产品在指定的季度通过网络销售到了California的客户手中。

使用星形转换

SQL> alter session set star_transformation_enabled='true';

Session altered.

SQL> SELECT c.cust_city,
  2  t.calendar_quarter_desc,
  3  SUM(s.amount_sold) sales_amount
  4  FROM sales s,
  5  times t,
  6  customers c,
  7  channels ch
  8  WHERE s.time_id = t.time_id
  9  AND s.cust_id = c.cust_id
 10  AND s.channel_id = ch.channel_id
 11  AND c.cust_state_province = 'CA'
 12  AND ch.channel_desc = 'Internet'
 13  AND t.calendar_quarter_desc IN ('1999-01','1999-02')
 14  GROUP BY c.cust_city, t.calendar_quarter_desc;
Montara                        1999-02      1618.01
Pala                           1999-01      3263.93
Cloverdale                     1999-01        52.64
Cloverdale                     1999-02       266.28
San Francisco                  1999-01      3058.27
San Mateo                      1999-01      8754.59
Los Angeles                    1999-01      1886.19
San Mateo                      1999-02     21399.42
Pala                           1999-02       936.62
El Sobrante                    1999-02      3744.03
El Sobrante                    1999-01      5392.34
Quartzhill                     1999-01        987.3
Legrand                        1999-01        26.32
Pescadero                      1999-01        26.32
Arbuckle                       1999-02        241.2
Quartzhill                     1999-02       412.83
Montara                        1999-01       289.07
Arbuckle                       1999-01       270.08
San Francisco                  1999-02        11257
Los Angeles                    1999-02      2128.59
Pescadero                      1999-02       298.44
Legrand                        1999-02        18.66

22 rows selected.

从10053跟踪文件中找到的星型转换后的语句如下:

ST: Query after star xformation:******* UNPARSED QUERY IS *******
SELECT /*+ CACHE (T1) */
 T1.C1 CUST_CITY,
 T.CALENDAR_QUARTER_DESC CALENDAR_QUARTER_DESC,
 SUM(S.AMOUNT_SOLD) SALES_AMOUNT
  FROM SH.SALES                       S,
       SH.TIMES                       T,
       SYS.SYS_TEMP_0FD9D6684_63D6F82 T1
 WHERE S.CUST_ID = ANY (SELECT /*+ SEMIJOIN_DRIVER CACHE (T1) */
         T1.C0 C0
          FROM SYS.SYS_TEMP_0FD9D6684_63D6F82 T1)
   AND S.CHANNEL_ID = ANY (SELECT /*+ SEMIJOIN_DRIVER */
         CH.CHANNEL_ID ITEM_1
          FROM SH.CHANNELS CH
         WHERE CH.CHANNEL_DESC = 'Internet')
   AND S.TIME_ID = ANY
 (SELECT /*+ SEMIJOIN_DRIVER */
         T.TIME_ID ITEM_1
          FROM SH.TIMES T
         WHERE T.CALENDAR_QUARTER_DESC = '1999-01'
            OR T.CALENDAR_QUARTER_DESC = '1999-02')
   AND S.TIME_ID = T.TIME_ID
   AND S.CUST_ID = T1.C0
   AND (T.CALENDAR_QUARTER_DESC = '1999-01' OR
       T.CALENDAR_QUARTER_DESC = '1999-02')
 GROUP BY T1.C1, T.CALENDAR_QUARTER_DESC

其执行计划如下:

SQL> select * from table(dbms_xplan.display_cursor(null,null,'advanced allstats last runstats_last peeked_binds'));
SQL_ID  a069wzk60bbqd, child number 3
-------------------------------------
SELECT c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold)
sales_amount FROM sales s, times t, customers c, channels ch WHERE
s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id =
ch.channel_id AND c.cust_state_province = 'CA' AND ch.channel_desc =
'Internet' AND t.calendar_quarter_desc IN ('1999-01','1999-02') GROUP
BY c.cust_city, t.calendar_quarter_desc

Plan hash value: 2164696140

------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
| Id  | Operation                          | Name                       | Starts | E-Rows |E-Bytes| Cost (%CPU)| E-Time   | Pstart| Pstop | A-Rows |   A-Time   | Buffers | Reads  | Writes |  OMem |  1Mem | Used-Mem |
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                   |                            |      1 |        |       |   573 (100)|          |       |       |     22 |00:00:01.41 |    9083 |     96 |     10 |       |       |          |
|   1 |  TEMP TABLE TRANSFORMATION         |                            |      1 |        |       |            |          |       |       |     22 |00:00:01.41 |    9083 |     96 |     10 |       |       |          |
|   2 |   LOAD AS SELECT                   | SYS_TEMP_0FD9D667F_63D6F82 |      1 |        |       |            |          |       |       |      0 |00:00:01.07 |    1539 |      2 |     10 |  1042K|  1042K|          |
|*  3 |    TABLE ACCESS FULL               | CUSTOMERS                  |      1 |    383 |  9958 |   423   (1)| 00:00:01 |       |       |   3341 |00:00:00.01 |    1522 |      0 |      0 |       |       |          |
|   4 |   HASH GROUP BY                    |                            |      1 |    542 | 30894 |   150   (1)| 00:00:01 |       |       |     22 |00:00:00.33 |    7538 |     93 |      0 |  1022K|  1022K| 1346K (0)|
|*  5 |    HASH JOIN                       |                            |      1 |   1681 | 95817 |   149   (0)| 00:00:01 |       |       |    964 |00:00:00.31 |    7538 |     93 |      0 |  1572K|  1572K| 1677K (0)|
|   6 |     TABLE ACCESS FULL              | SYS_TEMP_0FD9D667F_63D6F82 |      1 |    383 |  5745 |     2   (0)| 00:00:01 |       |       |   3341 |00:00:00.01 |      18 |     10 |      0 |       |       |          |
|*  7 |     HASH JOIN                      |                            |      1 |   1681 | 70602 |   147   (0)| 00:00:01 |       |       |    964 |00:00:00.29 |    7520 |     83 |      0 |  1538K|  1538K| 1686K (0)|
|*  8 |      TABLE ACCESS FULL             | TIMES                      |      1 |    183 |  2928 |    18   (0)| 00:00:01 |       |       |    181 |00:00:00.01 |      65 |      0 |      0 |       |       |          |
|   9 |      VIEW                          | VW_ST_A3F94988             |      1 |   1685 | 43810 |   129   (0)| 00:00:01 |       |       |    964 |00:00:00.23 |    7455 |     83 |      0 |       |       |          |
|  10 |       NESTED LOOPS                 |                            |      1 |   1685 | 96045 |   106   (0)| 00:00:01 |       |       |    964 |00:00:00.23 |    7455 |     83 |      0 |       |       |          |
|  11 |        PARTITION RANGE SUBQUERY    |                            |      1 |   1684 | 47167 |    52   (0)| 00:00:01 |KEY(SQ)|KEY(SQ)|    964 |00:00:00.22 |    7271 |     83 |      0 |       |       |          |
|  12 |         BITMAP CONVERSION TO ROWIDS|                            |      2 |   1684 | 47167 |    52   (0)| 00:00:01 |       |       |    964 |00:00:00.21 |    7204 |     83 |      0 |       |       |          |
|  13 |          BITMAP AND                |                            |      2 |        |       |            |          |       |       |      2 |00:00:00.21 |    7204 |     83 |      0 |       |       |          |
|  14 |           BITMAP MERGE             |                            |      2 |        |       |            |          |       |       |      2 |00:00:00.05 |      15 |     10 |      0 |  1024K|   512K| 4096  (0)|
|  15 |            BITMAP KEY ITERATION    |                            |      2 |        |       |            |          |       |       |      2 |00:00:00.04 |      15 |     10 |      0 |       |       |          |
|  16 |             BUFFER SORT            |                            |      2 |        |       |            |          |       |       |      2 |00:00:00.01 |       9 |      0 |      0 | 73728 | 73728 |          |
|* 17 |              TABLE ACCESS FULL     | CHANNELS                   |      1 |      1 |    13 |     3   (0)| 00:00:01 |       |       |      1 |00:00:00.01 |       9 |      0 |      0 |       |       |          |
|* 18 |             BITMAP INDEX RANGE SCAN| SALES_CHANNEL_BIX          |      2 |        |       |            |          |KEY(SQ)|KEY(SQ)|      2 |00:00:00.04 |       6 |     10 |      0 |       |       |          |
|  19 |           BITMAP MERGE             |                            |      2 |        |       |            |          |       |       |      2 |00:00:00.03 |     445 |     10 |      0 |  1024K|   512K|39936  (0)|
|  20 |            BITMAP KEY ITERATION    |                            |      2 |        |       |            |          |       |       |    181 |00:00:00.02 |     445 |     10 |      0 |       |       |          |
|  21 |             BUFFER SORT            |                            |      2 |        |       |            |          |       |       |    362 |00:00:00.01 |      65 |      0 |      0 | 73728 | 73728 |          |
|* 22 |              TABLE ACCESS FULL     | TIMES                      |      1 |    183 |  2928 |    18   (0)| 00:00:01 |       |       |    181 |00:00:00.01 |      65 |      0 |      0 |       |       |          |
|* 23 |             BITMAP INDEX RANGE SCAN| SALES_TIME_BIX             |    362 |        |       |            |          |KEY(SQ)|KEY(SQ)|    181 |00:00:00.01 |     380 |     10 |      0 |       |       |          |
|  24 |           BITMAP MERGE             |                            |      2 |        |       |            |          |       |       |      2 |00:00:00.14 |    6744 |     63 |      0 |  1024K|   512K|45056  (0)|
|  25 |            BITMAP KEY ITERATION    |                            |      2 |        |       |            |          |       |       |    403 |00:00:00.14 |    6744 |     63 |      0 |       |       |          |
|  26 |             BUFFER SORT            |                            |      2 |        |       |            |          |       |       |   6682 |00:00:00.01 |      18 |      0 |      0 |  5512K|   964K|  174K (0)|
|  27 |              TABLE ACCESS FULL     | SYS_TEMP_0FD9D667F_63D6F82 |      1 |    383 |  1915 |     2   (0)| 00:00:01 |       |       |   3341 |00:00:00.01 |      18 |      0 |      0 |       |       |          |
|* 28 |             BITMAP INDEX RANGE SCAN| SALES_CUST_BIX             |   6682 |        |       |            |          |KEY(SQ)|KEY(SQ)|    403 |00:00:00.10 |    6726 |     63 |      0 |       |       |          |
|  29 |        TABLE ACCESS BY USER ROWID  | SALES                      |    964 |      1 |    29 |    77   (2)| 00:00:01 | ROWID | ROWID |    964 |00:00:00.01 |     184 |      0 |      0 |       |       |          |
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Query Block Name / Object Alias (identified by operation id):
-------------------------------------------------------------

   1 - SEL$D5EF7599
   2 - SEL$F6045C7B
   3 - SEL$F6045C7B / C@SEL$F6045C7B
   6 - SEL$D5EF7599 / T1@SEL$9C741BEB
   8 - SEL$D5EF7599 / T@SEL$1
   9 - SEL$5E9A798F / VW_ST_A3F94988@SEL$D5EF7599
  10 - SEL$5E9A798F
  12 - SEL$5E9A798F / S@SEL$1
  17 - SEL$6EE793B7 / CH@SEL$6EE793B7
  22 - SEL$ACF30367 / T@SEL$ACF30367
  27 - SEL$E1F9C76C / T1@SEL$E1F9C76C
  29 - SEL$5E9A798F / SYS_CP_S@SEL$5E9A798F

Outline Data
-------------

  /*+
      BEGIN_OUTLINE_DATA
      IGNORE_OPTIM_EMBEDDED_HINTS
      OPTIMIZER_FEATURES_ENABLE('12.2.0.1')
      DB_VERSION('12.2.0.1')
      OPT_PARAM('star_transformation_enabled' 'true')
      ALL_ROWS
      NO_PARALLEL
      OUTLINE_LEAF(@"SEL$F6045C7B")
      OUTLINE_LEAF(@"SEL$ACF30367")
      OUTLINE_LEAF(@"SEL$6EE793B7")
      OUTLINE_LEAF(@"SEL$E1F9C76C")
      OUTLINE_LEAF(@"SEL$5E9A798F")
      TABLE_LOOKUP_BY_NL(@"SEL$0E028FD0" "S"@"SEL$1")
      OUTLINE_LEAF(@"SEL$D5EF7599")
      OUTLINE(@"SEL$1")
      OUTLINE(@"SEL$0E028FD0")
      OUTLINE(@"SEL$C3AF6D21")
      ELIMINATE_JOIN(@"SEL$1" "CH"@"SEL$1")
      OUTLINE(@"SEL$5208623C")
      STAR_TRANSFORMATION(@"SEL$1" "S"@"SEL$1" SUBQUERIES(("T"@"SEL$1") ("CH"@"SEL$1") TEMP_TABLE("C"@"SEL$1")))
      FULL(@"SEL$D5EF7599" "T"@"SEL$1")
      NO_ACCESS(@"SEL$D5EF7599" "VW_ST_A3F94988"@"SEL$D5EF7599")
      FULL(@"SEL$D5EF7599" "T1"@"SEL$9C741BEB")
      LEADING(@"SEL$D5EF7599" "T"@"SEL$1" "VW_ST_A3F94988"@"SEL$D5EF7599" "T1"@"SEL$9C741BEB")
      USE_HASH(@"SEL$D5EF7599" "VW_ST_A3F94988"@"SEL$D5EF7599")
      USE_HASH(@"SEL$D5EF7599" "T1"@"SEL$9C741BEB")
      SWAP_JOIN_INPUTS(@"SEL$D5EF7599" "T1"@"SEL$9C741BEB")
      USE_HASH_AGGREGATION(@"SEL$D5EF7599")
      BITMAP_AND(@"SEL$5E9A798F" "S"@"SEL$1" ("SALES"."CHANNEL_ID") 1)
      BITMAP_AND(@"SEL$5E9A798F" "S"@"SEL$1" ("SALES"."TIME_ID") 2)
      BITMAP_AND(@"SEL$5E9A798F" "S"@"SEL$1" ("SALES"."CUST_ID") 3)
      ROWID(@"SEL$5E9A798F" "SYS_CP_S"@"SEL$5E9A798F")
      LEADING(@"SEL$5E9A798F" "S"@"SEL$1" "SYS_CP_S"@"SEL$5E9A798F")
      SUBQUERY_PRUNING(@"SEL$5E9A798F" "S"@"SEL$1" PARTITION)
      USE_NL(@"SEL$5E9A798F" "SYS_CP_S"@"SEL$5E9A798F")
      FULL(@"SEL$E1F9C76C" "T1"@"SEL$E1F9C76C")
      SEMIJOIN_DRIVER(@"SEL$E1F9C76C")
      FULL(@"SEL$6EE793B7" "CH"@"SEL$6EE793B7")
      SEMIJOIN_DRIVER(@"SEL$6EE793B7")
      FULL(@"SEL$ACF30367" "T"@"SEL$ACF30367")
      SEMIJOIN_DRIVER(@"SEL$ACF30367")
      FULL(@"SEL$F6045C7B" "C"@"SEL$F6045C7B")
      SEMIJOIN_DRIVER(@"SEL$F6045C7B")
      END_OUTLINE_DATA
  */

Predicate Information (identified by operation id):
---------------------------------------------------

   3 - filter("C"."CUST_STATE_PROVINCE"='CA')
   5 - access("ITEM_1"="C0")
   7 - access("ITEM_2"="T"."TIME_ID")
   8 - filter(("T"."CALENDAR_QUARTER_DESC"='1999-01' OR "T"."CALENDAR_QUARTER_DESC"='1999-02'))
  17 - filter("CH"."CHANNEL_DESC"='Internet')
  18 - access("S"."CHANNEL_ID"="CH"."CHANNEL_ID")
  22 - filter(("T"."CALENDAR_QUARTER_DESC"='1999-01' OR "T"."CALENDAR_QUARTER_DESC"='1999-02'))
  23 - access("S"."TIME_ID"="T"."TIME_ID")
  28 - access("S"."CUST_ID"="C0")

Column Projection Information (identified by operation id):
-----------------------------------------------------------

   1 - "C1"[VARCHAR2,30], "T"."CALENDAR_QUARTER_DESC"[CHARACTER,7], SUM("ITEM_3")[22]
   2 - SYSDEF[4], SYSDEF[0], SYSDEF[1], SYSDEF[120], SYSDEF[0]
   3 - "C"."CUST_ID"[NUMBER,22], "C"."CUST_CITY"[VARCHAR2,30], "C"."CUST_STATE_PROVINCE"[VARCHAR2,40]
   4 - "C1"[VARCHAR2,30], "T"."CALENDAR_QUARTER_DESC"[CHARACTER,7], SUM("ITEM_3")[22]
   5 - (#keys=1; rowset=256) "C0"[NUMBER,22], "ITEM_1"[NUMBER,22], "C1"[VARCHAR2,30], "T"."TIME_ID"[DATE,7], "ITEM_2"[DATE,7], "T"."CALENDAR_QUARTER_DESC"[CHARACTER,7], "ITEM_3"[NUMBER,22]
   6 - (rowset=256) "C0"[NUMBER,22], "C1"[VARCHAR2,30]
   7 - (#keys=1; rowset=256) "T"."TIME_ID"[DATE,7], "ITEM_2"[DATE,7], "T"."CALENDAR_QUARTER_DESC"[CHARACTER,7], "ITEM_1"[NUMBER,22], "ITEM_3"[NUMBER,22]
   8 - (rowset=256) "T"."TIME_ID"[DATE,7], "T"."CALENDAR_QUARTER_DESC"[CHARACTER,7]
   9 - "ITEM_1"[NUMBER,22], "ITEM_2"[DATE,7], "ITEM_3"[NUMBER,22]
  10 - ROWID[ROWID,10], ROWID[ROWID,10], "S"."CUST_ID"[NUMBER,22], "S"."TIME_ID"[DATE,7], "S"."AMOUNT_SOLD"[NUMBER,22]
  11 - ROWID[ROWID,10]
  12 - ROWID[ROWID,10]
  13 - STRDEF[BM VAR, 10], STRDEF[BM VAR, 10], STRDEF[BM VAR, 32496]
  14 - STRDEF[BM VAR, 10], STRDEF[BM VAR, 10], STRDEF[BM VAR, 32496]
  15 - STRDEF[10], STRDEF[10], STRDEF[7920], "S"."CHANNEL_ID"[NUMBER,22]
  16 - (#keys=2) "CH"."CHANNEL_ID"[NUMBER,22], "CH"."CHANNEL_DESC"[VARCHAR2,20]
  17 - (rowset=256) "CH"."CHANNEL_ID"[NUMBER,22], "CH"."CHANNEL_DESC"[VARCHAR2,20]
  18 - STRDEF[BM VAR, 10], STRDEF[BM VAR, 10], STRDEF[BM VAR, 7920], "S"."CHANNEL_ID"[NUMBER,22]
  19 - STRDEF[BM VAR, 10], STRDEF[BM VAR, 10], STRDEF[BM VAR, 32496]
  20 - STRDEF[10], STRDEF[10], STRDEF[7920], "S"."TIME_ID"[DATE,7]
  21 - (#keys=2) "T"."TIME_ID"[DATE,7], "T"."CALENDAR_QUARTER_DESC"[CHARACTER,7]
  22 - (rowset=256) "T"."TIME_ID"[DATE,7], "T"."CALENDAR_QUARTER_DESC"[CHARACTER,7]
  23 - STRDEF[BM VAR, 10], STRDEF[BM VAR, 10], STRDEF[BM VAR, 7920], "S"."TIME_ID"[DATE,7]
  24 - STRDEF[BM VAR, 10], STRDEF[BM VAR, 10], STRDEF[BM VAR, 32496]
  25 - STRDEF[10], STRDEF[10], STRDEF[7920], "S"."CUST_ID"[NUMBER,22]
  26 - (#keys=1) "C0"[NUMBER,22]
  27 - (rowset=256) "C0"[NUMBER,22]
  28 - STRDEF[BM VAR, 10], STRDEF[BM VAR, 10], STRDEF[BM VAR, 7920], "S"."CUST_ID"[NUMBER,22]
  29 - ROWID[ROWID,10], "S"."CUST_ID"[NUMBER,22], "S"."TIME_ID"[DATE,7], "S"."AMOUNT_SOLD"[NUMBER,22]

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of parallel threshold
   - cbqt star transformation used for this statement
   - this is an adaptive plan

从Note部分的cbqt star transformation used for this statement信息可知执行了星型转换,从执行计划中的ID=29这个步骤可知对表sales使用了索引扫描而不是全表扫描。对于子查询中的times(第22行),customers(第3行),channels(第17行)表中的每个键值,数据库使用事实表sales(第23,28,18行)上索引检索位图。

Leave a Reply

Your email address will not be published.

Proudly powered by WordPress | Indrajeet by Sus Hill.