如何通过数据库视图重用带有子查询因子的sql
使用子查询（with data as子句）转换以下sql语句以在数据库视图中使用它的最佳做法是什么。
AFAIK数据库视图中不支持with data as子句（编辑：Oracle支持公用表表达式），但在我的情况下，子查询因子提供了性能优势。如果我使用Common Table Expression创建数据库视图，那么这种优势就会丢失。
请看一下我的例子：
查询说明
a_table
选择声明中有数百万条目被选中。
anchor_table
对于a_table中的每个条目，都存在anchor_table中的相应条目。通过此表在运行时确定一行作为锚。见下面的例子。
horizon_table
对于每个选择，在运行时确定一个条目（a_table选择的所有条目具有相同的horizon_id）
请注意：这是一个非常简化的sql，到目前为止工作正常。
实际上，超过20个表连接在一起以获得data的结果。
where子句要复杂得多。
需要更多的horizon_table和anchor_table列来准备子查询中的where条件和结果列表，即将这些表移动到主查询是没有解决方案。
with data as (
select
a_table.id,
a_table.descr,
horizon_table.offset,
case
when anchor_table.a_date = trunc(sysdate) then
1
else
0
end as anchor,
row_number() over(
order by a_table.a_position_field) as position
from a_table
join anchor_table on (anchor_table.id = a_table.anchor_id)
join horizon_table on (horizon_table.id = a_table.horizon_id)
where a_table.a_value between 1 and 10000
)
select *
from data d
where d.position between (
select d1.position - d.offset
from data d1
where d1.anchor = 1)
and (
select d2.position + d.offset
from data d2
where d2.anchor = 1)
with data as选择的示例：
id descr offset anchor position
1 bla 3 0 1
2 blab 3 0 2
5 dfkdj 3 0 3
4 dld 3 0 4
6 oeroe 3 1 5
3 blab 3 0 6
9 dfkdj 3 0 7
14 dld 3 0 8
54 oeroe 3 0 9
...
select * from data
id descr offset anchor position
2 blab 3 0 2
5 dfkdj 3 0 3
4 dld 3 0 4
6 oeroe 3 1 5
3 blab 3 0 6
9 dfkdj 3 0 7
14 dld 3 0 8
即。结果是上面和下面的锚行和树行。
如何在数据库视图中实现相同的目标？
我的尝试失败，正如我对性能问题所预期的那样：
在上面选择data选择视图with data as
使用上面的视图
select *
from data d
where d.position between (
select d1.position - d.offset
from data d1
where d1.anchor = 1)
and (
select d2.position + d.offset
from data d2
where d2.anchor = 1)
感谢您的任何建议:-)
修订
如果我按照第一条评论中的建议创建视图，那么我会遇到相同的性能问题。 Oracle不使用子查询来限制结果。
以下是我的生产查询的执行计划（请点击图片）
a）SQL
b）查看
以下是我的测试用例的执行计划
-- Create Testdata table with ~ 1,000,000 entries
insert into a_table
(id, descr, a_position_field, anchor_id, horizon_id, a_value)
select level, 'data' || level, mod(level, 10), level, 1, level
from dual
connect by level <= 999999;
insert into anchor_table
(id, a_date)
select level, trunc(sysdate) - 500000 + level
from dual
connect by level <= 999999;
insert into horizon_table (id, offset) values (1, 50);
commit;
-- Create view
create or replace view testdata_vw as
with data as
(select a_table.id,
a_table.descr,
a_table.a_value,
horizon_table.offset,
case
when anchor_table.a_date = trunc(sysdate) then
1
else
0
end as anchor,
row_number() over(order by a_table.a_position_field) as position
from a_table
join anchor_table
on (anchor_table.id = a_table.anchor_id)
join horizon_table
on (horizon_table.id = a_table.horizon_id))
select *
from data d
where d.position between
(select d1.position - d.offset from data d1 where d1.anchor = 1) and
(select d2.position + d.offset from data d2 where d2.anchor = 1);
-- Explain plan of subquery factoring select statement
explain plan for
with data as
(select a_table.id,
a_table.descr,
a_value,
horizon_table.offset,
case
when anchor_table.a_date = trunc(sysdate) then
1
else
0
end as anchor,
row_number() over(order by a_table.a_position_field) as position
from a_table
join anchor_table
on (anchor_table.id = a_table.anchor_id)
join horizon_table
on (horizon_table.id = a_table.horizon_id)
where a_table.a_value between 500000 - 500 and 500000 + 500)
select *
from data d
where d.position between
(select d1.position - d.offset from data d1 where d1.anchor = 1) and
(select d2.position + d.offset from data d2 where d2.anchor = 1);
select plan_table_output
from table(dbms_xplan.display('plan_table', null, null));
/*
Note: Size of SYS_TEMP_0FD9D6628_284C5768 ~ 1000 rows
Plan hash value: 1145408420
----------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 62 | 1791 (2)| 00:00:31 |
| 1 | TEMP TABLE TRANSFORMATION | | | | | |
| 2 | LOAD AS SELECT | SYS_TEMP_0FD9D6628_284C5768 | | | | |
| 3 | WINDOW SORT | | 57 | 6840 | 1785 (2)| 00:00:31 |
|* 4 | HASH JOIN | | 57 | 6840 | 1784 (2)| 00:00:31 |
|* 5 | TABLE ACCESS FULL | A_TABLE | 57 | 4104 | 1193 (2)| 00:00:21 |
| 6 | MERGE JOIN CARTESIAN | | 1189K| 54M| 586 (2)| 00:00:10 |
| 7 | TABLE ACCESS FULL | HORIZON_TABLE | 1 | 26 | 3 (0)| 00:00:01 |
| 8 | BUFFER SORT | | 1189K| 24M| 583 (2)| 00:00:10 |
| 9 | TABLE ACCESS FULL | ANCHOR_TABLE | 1189K| 24M| 583 (2)| 00:00:10 |
|* 10 | FILTER | | | | | |
| 11 | VIEW | | 57 | 3534 | 2 (0)| 00:00:01 |
| 12 | TABLE ACCESS FULL | SYS_TEMP_0FD9D6628_284C5768 | 57 | 4104 | 2 (0)| 00:00:01 |
|* 13 | VIEW | | 57 | 912 | 2 (0)| 00:00:01 |
| 14 | TABLE ACCESS FULL | SYS_TEMP_0FD9D6628_284C5768 | 57 | 4104 | 2 (0)| 00:00:01 |
|* 15 | VIEW | | 57 | 912 | 2 (0)| 00:00:01 |
| 16 | TABLE ACCESS FULL | SYS_TEMP_0FD9D6628_284C5768 | 57 | 4104 | 2 (0)| 00:00:01 |
----------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
4 - access("HORIZON_TABLE"."ID"="A_TABLE"."HORIZON_ID" AND
"ANCHOR_TABLE"."ID"="A_TABLE"."ANCHOR_ID")
5 - filter("A_TABLE"."A_VALUE">=499500 AND "A_TABLE"."A_VALUE"<=500500)
10 - filter("D"."POSITION">= (SELECT "D1"."POSITION"-:B1 FROM (SELECT + CACHE_TEMP_TABLE
("T1") "C0" "ID","C1" "DESCR","C2" "A_VALUE","C3" "OFFSET","C4" "ANCHOR","C5" "POSITION" FROM
"SYS"."SYS_TEMP_0FD9D6628_284C5768" "T1") "D1" WHERE "D1"."ANCHOR"=1) AND "D"."POSITION"<=
(SELECT "D2"."POSITION"+:B2 FROM (SELECT + CACHE_TEMP_TABLE ("T1") "C0" "ID","C1"
"DESCR","C2" "A_VALUE","C3" "OFFSET","C4" "ANCHOR","C5" "POSITION" FROM
"SYS"."SYS_TEMP_0FD9D6628_284C5768" "T1") "D2" WHERE "D2"."ANCHOR"=1))
13 - filter("D1"."ANCHOR"=1)
15 - filter("D2"."ANCHOR"=1)
Note
-----
- dynamic sampling used for this statement (level=4)
*/
-- Explain plan of database view
explain plan for
select *
from testdata_vw
where a_value between 500000 - 500 and 500000 + 500;
select plan_table_output
from table(dbms_xplan.display('plan_table', null, null));
/*
Note: Size of SYS_TEMP_0FD9D662A_284C5768 ~ 1000000 rows
Plan hash value: 1422141561
-------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
-------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 2973 | 180K| | 50324 (1)| 00:14:16 |
| 1 | VIEW | TESTDATA_VW | 2973 | 180K| | 50324 (1)| 00:14:16 |
| 2 | TEMP TABLE TRANSFORMATION | | | | | | |
| 3 | LOAD AS SELECT | SYS_TEMP_0FD9D662A_284C5768 | | | | | |
| 4 | WINDOW SORT | | 1189K| 136M| 147M| 37032 (1)| 00:10:30 |
|* 5 | HASH JOIN | | 1189K| 136M| | 6868 (1)| 00:01:57 |
| 6 | TABLE ACCESS FULL | HORIZON_TABLE | 1 | 26 | | 3 (0)| 00:00:01 |
|* 7 | HASH JOIN | | 1189K| 106M| 38M| 6860 (1)| 00:01:57 |
| 8 | TABLE ACCESS FULL | ANCHOR_TABLE | 1189K| 24M| | 583 (2)| 00:00:10 |
| 9 | TABLE ACCESS FULL | A_TABLE | 1209K| 83M| | 1191 (2)| 00:00:21 |
|* 10 | FILTER | | | | | | |
|* 11 | VIEW | | 1189K| 70M| | 4431 (1)| 00:01:16 |
| 12 | TABLE ACCESS FULL | SYS_TEMP_0FD9D662A_284C5768 | 1189K| 81M| | 4431 (1)| 00:01:16 |
|* 13 | VIEW | | 1189K| 18M| | 4431 (1)| 00:01:16 |
| 14 | TABLE ACCESS FULL | SYS_TEMP_0FD9D662A_284C5768 | 1189K| 81M| | 4431 (1)| 00:01:16 |
|* 15 | VIEW | | 1189K| 18M| | 4431 (1)| 00:01:16 |
| 16 | TABLE ACCESS FULL | SYS_TEMP_0FD9D662A_284C5768 | 1189K| 81M| | 4431 (1)| 00:01:16 |
-------------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
5 - access("HORIZON_TABLE"."ID"="A_TABLE"."HORIZON_ID")
7 - access("ANCHOR_TABLE"."ID"="A_TABLE"."ANCHOR_ID")
10 - filter("D"."POSITION">= (SELECT "D1"."POSITION"-:B1 FROM (SELECT + CACHE_TEMP_TABLE ("T1")
"C0" "ID","C1" "DESCR","C2" "A_VALUE","C3" "OFFSET","C4" "ANCHOR","C5" "POSITION" FROM
"SYS"."SYS_TEMP_0FD9D662A_284C5768" "T1") "D1" WHERE "D1"."ANCHOR"=1) AND "D"."POSITION"<= (SELECT
"D2"."POSITION"+:B2 FROM (SELECT + CACHE_TEMP_TABLE ("T1") "C0" "ID","C1" "DESCR","C2"
"A_VALUE","C3" "OFFSET","C4" "ANCHOR","C5" "POSITION" FROM "SYS"."SYS_TEMP_0FD9D662A_284C5768" "T1") "D2"
WHERE "D2"."ANCHOR"=1))
11 - filter("A_VALUE">=499500 AND "A_VALUE"<=500500)
13 - filter("D1"."ANCHOR"=1)
15 - filter("D2"."ANCHOR"=1)
Note
-----
- dynamic sampling used for this statement (level=4)
*/
sqlfiddle
的计划2 个答案:
答案 0 :(得分：3)
您需要编写一个视图定义，它将a_value的所有可选范围返回为两列，start_a_value和end_a_value，以及属于每个开始/结束范围的所有记录。换句话说，正确的视图定义应该在逻辑上描述| n ^ 3 |在a_table中给出n行的结果集。
然后将该视图查询为：
SELECT * FROM testdata_vw WHERE START_A_VALUE = 4950 AND END_A_VALUE = 5050;
此外，您多次引用＆＃34;数据＆＃34;没必要;可以通过附加的分析功能提供相同的逻辑。
最终视图def：
CREATE OR REPLACE VIEW testdata_vw AS
SELECT *
FROM
(
SELECT T.*,
MAX(CASE WHEN ANCHOR=1 THEN POSITION END)
OVER (PARTITION BY START_A_VALUE, END_A_VALUE) ANCHOR_POS
FROM
(
SELECT S.A_VALUE START_A_VALUE,
E.A_VALUE END_A_VALUE,
B.ID ID,
B.DESCR DESCR,
HORIZON_TABLE.OFFSET OFFSET,
CASE
WHEN ANCHOR_TABLE.A_DATE = TRUNC(SYSDATE)
THEN 1
ELSE 0
END ANCHOR,
ROW_NUMBER()
OVER(PARTITION BY S.A_VALUE, E.A_VALUE
ORDER BY B.A_POSITION_FIELD) POSITION
FROM
A_TABLE S
JOIN A_TABLE E
ON S.A_VALUE<E.A_VALUE
JOIN A_TABLE B
ON B.A_VALUE BETWEEN S.A_VALUE AND E.A_VALUE
JOIN ANCHOR_TABLE
ON ANCHOR_TABLE.ID = B.ANCHOR_ID
JOIN HORIZON_TABLE
ON HORIZON_TABLE.ID = B.HORIZON_ID
) T
) T
WHERE POSITION BETWEEN ANCHOR_POS - OFFSET AND ANCHOR_POS+OFFSET;
编辑：SQL Fiddle with expected execution plan
我在我的数据库中看到了同样的（明智的）计划;如果你得到不同的东西，请发送小提琴链接。
- 使用索引查找在＆＃34; S＆＃34;中查找1行A_TABLE（A_VALUE = 4950）
- 使用索引查找在＆＃34; E＆＃34;中找到1行A_TABLE（A_VALUE = 5050）
- 嵌套循环连接＃1和＃2（1 x 1连接，仍然是1行）
- 来自HORIZON表的FTS 1行
- 笛卡尔加入＃1和＃2（1 x 1，可以使用笛卡儿）。
- 使用索引查找在＆＃34; B＆＃34;中查找~100行A_TABLE，值介于4950和5050之间。
- 笛卡尔加入＃5和＃6（1 x 102，可以使用笛卡儿）。
- FTS ANCHOR_TABLE，哈希加入＃7。
- 分析函数的窗口排序
答案 1 :(得分：1)
您在视图外部有一个谓词，并且您希望在视图中应用。
为此，您可以使用push_pred提示：
select /*+PUSH_PRED(v)*/
*
from
testdata_vw v
where
a_value between 5000 - 50 and 5000 + 50;
编辑：现在我已经看到您使用数据子查询三次了。对于第一次出现，推送谓词是有意义的，但对于d1和d2，它并不是。这是另一个问题。
我该怎么做才能使用两个上下文变量，根据我的需要设置它们并编写查询：
SYS_CONTEXT（＆＃39; my_context_name＆＃39;，＆＃39; var5000＆＃39;）;
create or replace view testdata_vw as
with data as (
select
a_table.id,
a_table.descr,
horizon_table.offset,
case
when anchor_table.a_date = trunc(sysdate) then
1
else
0
end as anchor,
row_number() over(
order by a_table.a_position_field) as position
from a_table
join anchor_table on (anchor_table.id = a_table.anchor_id)
join horizon_table on (horizon_table.id = a_table.horizon_id)
where a_table.a_value between SYS_CONTEXT('my_context_name', 'var5000') - SYS_CONTEXT('my_context_name', 'var50') and SYS_CONTEXT('my_context_name', 'var5000') + SYS_CONTEXT('my_context_name', 'var50')
)
select *
from data d
where d.position between (
select d1.position - d.offset
from data d1
where d1.anchor = 1)
and (
select d2.position + d.offset
from data d2
where d2.anchor = 1) ;
使用它：
dbms_session.set_context ('my_context_name', 'var5000', 5000);
dbms_session.set_context ('my_context_name', 'var50', 50);
select * from testdata_vw;
UPDATE：您可以在评论时使用包变量，而不是上下文变量（可以在会话中使用）。
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