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HomeDatabaseMysql Tutorial编写SQL需要注意的细节Checklist总结

本周技术研究部(TRD)的一名DBA 对我们编写SQL时的一些问题,进行了汇报讲演,以下是来自它的脚本,我在它讲演的基础上写出了自己想表述的,以便于大家相互交流学习

代码如下:
/*
--注意:准备数据(可略过,非常耗时)
CREATE TABLE CHECK1_T1
(
ID INT,
C1 CHAR(8000)
)

CREATE TABLE CHECK1_T2
(
ID INT,
C1 CHAR(8000)
)

DECLARE @I INT
SET @I=1
WHILE @IBEGIN
INSERT INTO CHECK1_T1 SELECT @I,'C1'
INSERT INTO CHECK1_T2 SELECT 10000+@I,'C1'

SET @I=@I+1
END

CREATE TABLE CHECK2_T1
(
ID INT,
C1 CHAR(8000)
)

DECLARE @I INT
SET @I=1
WHILE @IBEGIN
INSERT INTO CHECK2_T1 SELECT @I,'C1'

SET @I=@I+1
END

INSERT INTO CHECK2_T1 VALUES(10001,'C2')

INSERT INTO CHECK2_T1 VALUES(10002,'C1')

CREATE TABLE CHECK3_T1
(
ID INT,
C1 CHAR(7000)
)

CREATE TABLE CHECK3_T2
(
ID INT,
C1 CHAR(7000)
)

DECLARE @I INT
SET @I=1
WHILE @IBEGIN
IF @I%2 =0
BEGIN
INSERT INTO CHECK3_T1 SELECT @I,'C1'
END
ELSE
BEGIN
INSERT INTO CHECK3_T1 SELECT @I,'C2'
END

IF @I%100=0
BEGIN
INSERT INTO CHECK3_T2 SELECT @I,'C1'
INSERT INTO CHECK3_T2 SELECT @I+50000,'C2'
END
SET @I=@I+1
END


CREATE TABLE CHECK4_T1
(
ID INT,
C1 CHAR(500),
)

DECLARE @I INT
SET @I=1
WHILE @IBEGIN
IF @I%100000 =0
BEGIN
INSERT INTO CHECK4_T1 SELECT @I,'C2'
END
ELSE
BEGIN
INSERT INTO CHECK4_T1 SELECT @I,'C1'
END

SET @I=@I+1
END
CREATE NONCLUSTERED INDEX NCIX_C1 ON CHECK4_T1(C1)

CREATE TABLE CHECK5_T1
(
ID INT,
C1 CHAR(10),
)


DECLARE @I INT
SET @I=1
WHILE @IBEGIN
INSERT INTO CHECK5_T1 SELECT @I,'C1'
IF @I%2=0
BEGIN
INSERT INTO CHECK5_T1 SELECT @I,'C1'
END
SET @I=@I+1
END


*/
--=====================================
--1、 Union all 代替 Union

DBCC DROPCLEANBUFFERS
DBCC FREEPROCCACHE

--测试一:(26s) 执行计划:表扫描->排序->合并联接
SELECT ID,C1 FROM CHECK1_T1 --1W条数据
UNION
SELECT ID,C1 FROM CHECK1_T2 --1W条数据

--测试二: (4s) 执行计划:表扫描->表扫描串联
SELECT ID,C1 FROM CHECK1_T1 --1W条数据
UNION ALL
SELECT ID,C1 FROM CHECK1_T2 --1W条数据

--总结:测试一中的union 排序和去重合并是相当耗时的,如果不要此功能,大数据时最好加上ALL

--=====================================
--2、 Exists 代替 Count(*)
DBCC DROPCLEANBUFFERS
DBCC FREEPROCCACHE

----测试一: (7s) 执行计划:表扫描-> 流聚合-> 计算矢量
DECLARE @COUNT INT
SELECT @COUNT=COUNT(*) FROM CHECK2_T1 WHERE C1='C1' --1W条数据
IF @COUNT>0
BEGIN
PRINT 'S'
END
----测试二: (0s) 执行计划:常量扫描/表扫描-> 嵌套循环-> 计算标量
IF EXISTS(SELECT 1 FROM CHECK2_T1 WHERE C1='C1') --1W条数据
BEGIN
PRINT 'S'
END

--总结:判断是否存在,用Exist即可,没必要用COUNT(*)将表的所有记录统计出来,扫描一次

--=====================================
--3、 IN(Select COL1 From Table)的代替方式
DBCC DROPCLEANBUFFERS
DBCC FREEPROCCACHE

--测试一: (3s)执行计划:表扫描 -> 哈希匹配
SELECT ID,C1 FROM CHECK3_T2 --400行
WHERE ID IN (SELECT ID FROM CHECK3_T1 WHERE C1='C1') --2W行

--测试二:(1s)执行计划:表扫描-> 并行度 -> 位图 -> 排序 -> 合并联接 -> 并行度
SELECT A.ID,A.C1 FROM CHECK3_T2 A
INNER JOIN CHECK3_T1 B ON A.ID=B.ID WHERE B.C1='C1'

--测试三:(3s)执行计划:表扫描-> 哈希匹配
SELECT A.ID,A.C1 FROM CHECK3_T2 A
WHERE EXISTS (SELECT 1 FROM CHECK3_T1 B WHERE B.ID=A.ID AND B.C1='C1')

--总结:能用INNER JOIN 尽量用它,SQL SERVER在查询时会将关联表进行优化

--=====================================
--4、 Not Exists 代替 Not In
--测试一:(8s) 执行计划:表扫描-> 嵌套循环 -> 哈希匹配
SELECT ID,C1 FROM CHECK3_T1 --2W行
WHERE ID NOT IN (SELECT ID FROM CHECK3_T2 WHERE C1='C1') --400行

--测试二:(4s) 执行计划:表扫描-> 哈希匹配
SELECT A.ID,A.C1 FROM CHECK3_T1 A
WHERE NOT EXISTS (SELECT 1 FROM CHECK3_T2 B WHERE B.ID=A.ID AND B.C1='C1')

--总结:尽量不使用NOT IN ,因为会调用嵌套循环,建议使用NOT EXISTS代替NOT IN

--=====================================
--5、 避免在条件列上使用任何函数

DROP TABLE CHECK4_T1

CREATE NONCLUSTERED INDEX NCIX_C1 ON CHECK4_T1(C1) --加上非聚集索引

---测试一:(4s)执行计划: 索引扫描
SELECT * FROM CHECK4_T1 WHERE RTRIM(C1)='C2'

---测试二:(0s)执行计划: 索引查找
SELECT * FROM CHECK4_T1 WHERE C1='C2'

--总结:where条件里对索引字段使用了函数,会使索引查找变成索引扫描,从而查询效率大幅下降

--=====================================
--6、 用sp_executesql执行动态sql

DBCC DROPCLEANBUFFERS
DBCC FREEPROCCACHE

CREATE PROC UP_CHECK5_T1 (
@ID INT
)
AS
SET NOCOUNT ON

DECLARE @count INT,
@sql NVARCHAR(4000)

SET @sql = 'SELECT @count=count(*) FROM CHECK5_T1 WHERE ID = @ID'

EXEC sp_executesql @sql,
N'@count INT OUTPUT, @ID int',
@count OUTPUT,
@ID

PRINT @count


CREATE PROC UP_CHECK5_T2 (
@ID INT
)
AS
SET NOCOUNT ON

DECLARE @sql NVARCHAR(4000)

SET @sql = 'DECLARE @count INT;SELECT @count=count(*) FROM CHECK5_T1 WHERE ID = ' + CAST(@ID AS VARCHAR(10)) + ';PRINT @count'

EXEC(@sql)


---测试一:瞬时
DECLARE @N INT
SET @N=1
WHILE @NBEGIN
EXEC UP_CHECK5_T1 @N
SET @N=@N+1
END

---测试二:2s
DECLARE @N INT
SET @N=1
WHILE @NBEGIN
EXEC UP_CHECK5_T2 @N
SET @N=@N+1
END

CREATE CLUSTERED INDEX CIX_ID ON CHECK5_T1(ID)

DBCC DROPCLEANBUFFERS
DBCC FREEPROCCACHE

--查看缓存计划
SELECT a.size_in_bytes '占用字节数',
total_elapsed_time / execution_count '平均时间',
total_logical_reads / execution_count '逻辑读',
usecounts '重用次数',
SUBSTRING(d.text, (statement_start_offset / 2) + 1, ((CASE statement_end_offset
WHEN -1 THEN DATALENGTH(text)
ELSE statement_end_offset
END - statement_start_offset) / 2) + 1) '语句'
FROM sys.dm_exec_cached_plans a
CROSS apply sys.dm_exec_query_plan(a.plan_handle) c,
sys.dm_exec_query_stats b
CROSS apply sys.dm_exec_sql_text(b.sql_handle) d
WHERE a.plan_handle = b.plan_handle
ORDER BY total_elapsed_time / execution_count DESC;

--总结:通过执行下面缓存计划可以看出,第一种完全使用了缓存计划,查询达到了很好的效果;
--而第二种则将缓存计划浪费了,导致缓存很快被占满,这种做法是相当不可取的

--=====================================
--7、 Left Join 的替代法
--测试一 执行计划:表扫描 -> 哈希匹配
SELECT A.ID,A.C1 FROM CHECK3_T1 A --2W行
LEFT JOIN CHECK3_T2 B ON A.ID=B.ID WHERE B.C1='C1' --400行

--测试二 执行计划:表扫描 -> 哈希匹配
SELECT A.ID,A.C1 FROM CHECK3_T1 A
RIGHT JOIN CHECK3_T2 B ON A.ID=B.ID WHERE a.C1='C1'

--测试三 执行计划:表扫描 -> 哈希匹配
SELECT A.ID,A.C1 FROM CHECK3_T1 A
INNER JOIN CHECK3_T2 B ON A.ID=B.ID WHERE B.C1='C1'

--总结:三条语句,在执行计划上完全一样,都是走的INNER JOIN的计划,
--因为测试一和测试二中,WHERE语句都包含了LEFT 和RIGHT表的字段,SQLSERVER若发现只要有这个表的字段,则会自动按照INNER JOIN进行处理

--补充测试:(1s)执行计划:表扫描-> 并行度 -> 位图 -> 排序 -> 合并联接 -> 并行度
SELECT A.ID,A.C1 FROM CHECK3_T2 A --400行
INNER JOIN CHECK3_T1 B ON A.ID=B.ID WHERE A.C1='C1' --2W行
--总结:这里有一个比较有趣的地方,若主表和关联表数据差别很大时,走的执行计划走的另一条路

--=====================================
--8、 ON(a.id=b.id AND a.tag=3)
--测试一
SELECT A.ID,A.C1 FROM CHECK3_T1 A
INNER JOIN CHECK3_T2 B ON A.ID=B.ID AND A.C1='C1'

--测试二
SELECT A.ID,A.C1 FROM CHECK3_T1 A
INNER JOIN CHECK3_T2 B ON A.ID=B.ID WHERE A.C1='C1'

--总结:内连接:无论是左表和右表的筛选条件都可以放到WHERE子句中

--测试一
SELECT A.ID,A.C1,B.C1 FROM CHECK3_T1 A
LEFT JOIN CHECK3_T2 B ON A.ID=B.ID AND B.C1='C1'

--测试二
SELECT A.ID,A.C1,B.C1 FROM CHECK3_T1 A
LEFT JOIN CHECK3_T2 B ON A.ID=B.ID WHERE B.C1='C1'

--总结:左外连接:当右表中的过滤条件放入ON子句后和WHERE子句后的结果不一样

--=====================================
--9、 赋值给变量,加Top 1
--测试一:(3s) 执行计划:表扫描
DECLARE @ID INT
SELECT @ID=ID FROM CHECK1_T1 WHERE C1='C1'
SELECT @ID

--测试二:(0s)执行计划:表扫描-> 前几行
DECLARE @ID INT
SELECT TOP 1 @ID=ID FROM CHECK1_T1 WHERE C1='C1'
SELECT @ID

--总结:给变量赋值最好都加上TOP 1,一从查询效率上增强,二为了准确性,若表CHECK1_T1有多个值,则会取最后一条记录赋给@ID

--=====================================
--10、 考虑是否适合用CASE语句
DECLARE @S INT=1
SELECT * FROM CHECK5_T1
WHERE C1=(CASE @S WHEN 1 THEN C1 ELSE 'C2' END)

SELECT * FROM CHECK5_T1
WHERE @S=1 OR C1='C2'


/*--=====================================
、检查语句是否需要Distinct. 执行计划:表扫描-> 哈希匹配-> 并行度-> 排序
select distinct c1 from CHECK3_T1
、禁用Select *,指定具体列名
select c1 from CHECK4_T1
select * from CHECK4_T1
、Insert into Table(*),指定具体的列名
、Isnull,没有必要的时候不要对字段使用isnull,同样会产生无法有效利用索引的问题,
和避免在筛选列上使用函数同样的原理。
、嵌套子查询,加上查询条件,确保子查询的结果集最小
--=====================================*/
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