我在一个程序中填写了以下sql的表
SELECT NVL(SUM(COL1), 0),
NVL(SUM(COL2), 0)
INTO v_mytable.COLUMN1,
v_mytable.COLUMN2
FROM t1, t2
WHERE t1.id = t2.id
AND t1.date = t2.date
另外，对于99％的表行，这些列= 0，并且在大多数情况下，当两个列都返回0时，此查询需要很长时间才能执行。
使用异常处理是否更好如下：
BEGIN
SELECT SUM(COL1),
SUM(COL2)
INTO v_mytable.COLUMN1,
v_mytable.COLUMN2
FROM t1, t2
WHERE t1.id = t2.id
AND t1.date = t2.date
EXCEPTION WHEN NO_DATA_FOUND THEN
v_mytable.COLUMN1 := 0 ;
v_mytable.COLUMN2 := 0 ;
END;
感谢。
答案 0 :(得分：7)
这两个块完全不同。如果COL1和/或COL2始终为NULL，则SELECT语句不会抛出NO_DATA_FOUND错误。它只会在v_mytable.COLUMN1和v_mytable.COLUMN2中添加NULL。
你可以做到
SELECT SUM(COL1),
SUM(COL2)
INTO v_mytable.COLUMN1,
v_mytable.COLUMN2
FROM t1, t2
WHERE t1.id = t2.id
AND t1.date = t2.date
v_mytable.COLUMN1 := NVL( v_mytable.COLUMN1, 0 );
v_mytable.COLUMN2 := NVL( v_mytable.COLUMN2, 0 );
然而，我不希望这会更快。
答案 1 :(得分：3)
鉴于这两者之间的选择，我会选择第一个。
我更喜欢使用异常处理程序来处理真正的异常/错误，而不是控制流程。
因人而异。
答案 2 :(得分：2)
如果没有返回任何行，则抛出NO_DATA_FOUND，如果在从查询返回的实际行中返回空值，则抛出NO_DATA_FOUND。这将抛出NO_DATA_FOUND：
select sysdate
into myVariable
from dual
where 1=0;
这不会抛出NO_DATA_FOUND：
select null
into myVariable
from dual;
也就是说，如果你只是想知道col1和col2为null的行，那么你可以考虑在pl / sql中使用集合，并使用批量收集，如：
select sum(col1) as sum_col1, sum(col2) as sum_col2, col3
bulk collect into v_mytable
FROM t1, t2
WHERE t1.id = t2.id
AND t1.date = t2.date
AND col1 is not null
AND col2 is not null
GROUP by col3;
没有循环，一举做好。仅供参考，您可以设置v_mytable，例如：
declare
type t_rec is record
(col1_sum number,
col2_sum number,
col3 number);
v_rec t_rec;
type t_tab is table of v_rec%type;
v_mytable t_tab;
begin
...
稍后你可以循环遍历v_mytable，它只是原始t1，t2连接结果的1％（由于查询中的附加非null子句）。
希望有所帮助。
答案 3 :(得分：2)
如果你停止加入col值为0的行，你的SQL会运行得更快。下面是一个小测试来证明我的观点。
首先创建两个包含100,000行的表，其中99％的行的col值设置为0：
SQL> create table t1 (id,date1,col1)
2 as
3 select level
4 , trunc(sysdate)
5 , case mod(level,100) when 42 then 42 else 0 end
6 from dual
7 connect by level <= 100000
8 /
Table created.
SQL> create table t2 (id,date2,col2)
2 as
3 select level
4 , trunc(sysdate)
5 , case mod(level,100) when 42 then 84 else 0 end
6 from dual
7 connect by level <= 100000
8 /
Table created.
提供基于成本的优化程序表统计信息：
SQL> exec dbms_stats.gather_table_stats(user,'t1')
PL/SQL procedure successfully completed.
SQL> exec dbms_stats.gather_table_stats(user,'t2')
PL/SQL procedure successfully completed.
运行查询时收集统计信息：
SQL> set serveroutput off
SQL> alter session set statistics_level = all
2 /
Session altered.
现在您的查询运行如下：
SQL> SELECT NVL(SUM(t1.COL1), 0)
2 , NVL(SUM(t2.COL2), 0)
3 FROM t1
4 , t2
5 WHERE t1.id = t2.id
6 AND t1.date1 = t2.date2
7 /
NVL(SUM(T1.COL1),0) NVL(SUM(T2.COL2),0)
------------------- -------------------
42000 84000
1 row selected.
SQL> select * from table(dbms_xplan.display_cursor(null,null,'allstats last'))
2 /
PLAN_TABLE_OUTPUT
-----------------------------------------------------------------------------------------------------------------
SQL_ID 6q5h7h8ht5232, child number 0
-------------------------------------
SELECT NVL(SUM(t1.COL1), 0) , NVL(SUM(t2.COL2), 0) FROM t1 , t2 WHERE t1.id = t2.id AND
t1.date1 = t2.date2
Plan hash value: 446739472
-----------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem |
-----------------------------------------------------------------------------------------------------------------
| 1 | SORT AGGREGATE | | 1 | 1 | 1 |00:00:00.37 | 560 | | | |
|* 2 | HASH JOIN | | 1 | 100K| 100K|00:00:00.24 | 560 | 4669K| 1437K| 7612K (0)|
| 3 | TABLE ACCESS FULL| T1 | 1 | 100K| 100K|00:00:00.01 | 280 | | | |
| 4 | TABLE ACCESS FULL| T2 | 1 | 100K| 100K|00:00:00.01 | 280 | | | |
-----------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - access("T1"."ID"="T2"."ID" AND "T1"."DATE1"="T2"."DATE2")
21 rows selected.
你可以看到HASH JOIN需要加入100K行，这是花费大部分时间的地方。现在排除0值：
SQL> SELECT NVL(SUM(t1.COL1), 0)
2 , NVL(SUM(t2.COL2), 0)
3 FROM t1
4 , t2
5 WHERE t1.id = t2.id
6 AND t1.date1 = t2.date2
7 and t1.col1 != 0
8 and t2.col2 != 0
9 /
NVL(SUM(T1.COL1),0) NVL(SUM(T2.COL2),0)
------------------- -------------------
42000 84000
1 row selected.
SQL> select * from table(dbms_xplan.display_cursor(null,null,'allstats last'))
2 /
PLAN_TABLE_OUTPUT
-----------------------------------------------------------------------------------------------------------------
SQL_ID bjr7wrjx5tjvr, child number 0
-------------------------------------
SELECT NVL(SUM(t1.COL1), 0) , NVL(SUM(t2.COL2), 0) FROM t1 , t2 WHERE t1.id = t2.id AND
t1.date1 = t2.date2 and t1.col1 != 0 and t2.col2 != 0
Plan hash value: 446739472
-----------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem |
-----------------------------------------------------------------------------------------------------------------
| 1 | SORT AGGREGATE | | 1 | 1 | 1 |00:00:00.02 | 560 | | | |
|* 2 | HASH JOIN | | 1 | 25000 | 1000 |00:00:00.02 | 560 | 1063K| 1063K| 1466K (0)|
|* 3 | TABLE ACCESS FULL| T1 | 1 | 50000 | 1000 |00:00:00.01 | 280 | | | |
|* 4 | TABLE ACCESS FULL| T2 | 1 | 50000 | 1000 |00:00:00.01 | 280 | | | |
-----------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - access("T1"."ID"="T2"."ID" AND "T1"."DATE1"="T2"."DATE2")
3 - filter("T1"."COL1"<>0)
4 - filter("T2"."COL2"<>0)
23 rows selected.
你可以看到HASH JOIN现在只需加入1000行，导致输出速度更快。
希望这有帮助。
的问候，
罗布。