因为项目要求实现一次性同时更新多条不同的记录的需求,和同事讨论了一个比较不错的方案,这里供大家参考下
以下为测试例子。1.首先创建两张临时表并录入测试数据:
代码如下:
create table #temptest1
(
id int,
name1 varchar(50),
age int
)
create table #temptest2
(
id int,
name1 varchar(50),
age int
)
查询出此时的表数据为:
#temptest1 #temptest2
2.现在要将#temptest2中的年龄更新到相应的#temptest1中的年龄。
其实就是让[表1]中ID为1的年龄改成19,同时ID为2的年龄改成20。
当然这里的要求是只用一句SQL,不能用循环。
结果如下:
实现方法如下:
Update t1
Set t1 .age = t2.age
From #temptest1 t1
Join #temptest2 t2
On t1.id = t2.id
(补充)Sql Server 2008 Merge命令写法:
merge into #temptest1 t1
using(select age,id from #temptest2) t2
on t1.id = t2.id
when matched then
update set t1.age = t2.age
是不是挺有趣的Sql。
如何一次性更新多条不同值的记录
标题可能没说清楚,假设有这样两张表:
代码如下:
create table testA(
id number,
eng varchar2(3),
chi varchar2(3)
)
create table testB(
id number,
eng varchar2(3),
chi varchar2(3),
anythingother varchar2(1)
)
现有记录
testA:
ID ENG CHI
===============
1 a 一
2 b 二
3 c 三
testB:
ID ENG CHI ANY....
=================
1 d 四
2 e 五
3 f 六
我想把testB中的记录的ENG,CHI字段更新到testA中去,以ID来对应。
CODE:
SQL> set autot on
SQL> update ta set ta.b=(select tb.b from tb where ta.a=tb.a) where exists (select 1 from tb where ta.a=tb.a);
已更新4行。
已用时间: 00: 00: 00.01
执行计划
----------------------------------------------------------
Plan hash value: 1137212925
--------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------------
| 0 | UPDATE STATEMENT | | 5 | 165 | 20 (30)| 00:00:01 |
| 1 | UPDATE | TA | | | | |
|* 2 | HASH JOIN SEMI | | 5 | 165 | 5 (20)| 00:00:01 |
| 3 | TABLE ACCESS FULL | TA | 5 | 100 | 2 (0)| 00:00:01 |
| 4 | VIEW | VW_SQ_1 | 4 | 52 | 2 (0)| 00:00:01 |
| 5 | TABLE ACCESS FULL| TB | 4 | 52 | 2 (0)| 00:00:01 |
|* 6 | TABLE ACCESS FULL | TB | 1 | 26 | 2 (0)| 00:00:01 |
--------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - access("TA"."A"="ITEM_1")
6 - filter("TB"."A"=:B1)
Note
-----
- dynamic sampling used for this statement (level=2)
统计信息
----------------------------------------------------------
0 recursive calls
4 db block gets
23 consistent gets
0 physical reads
1004 redo size
840 bytes sent via SQL*Net to client
856 bytes received via SQL*Net from client
3 SQL*Net roundtrips to/from client
1 sorts (memory)
0 sorts (disk)
4 rows processed
SQL> update ta set ta.b=(select tb.b from tb where ta.a=tb.a) where ta.a= (select tb.a from tb where ta.a=tb.a);
已更新4行。
已用时间: 00: 00: 00.00
执行计划
----------------------------------------------------------
Plan hash value: 3571861550
----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------
| 0 | UPDATE STATEMENT | | 1 | 20 | 7 (15)| 00:00:01 |
| 1 | UPDATE | TA | | | | |
|* 2 | FILTER | | | | | |
| 3 | TABLE ACCESS FULL| TA | 5 | 100 | 2 (0)| 00:00:01 |
|* 4 | TABLE ACCESS FULL| TB | 1 | 13 | 2 (0)| 00:00:01 |
|* 5 | TABLE ACCESS FULL | TB | 1 | 26 | 2 (0)| 00:00:01 |
----------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - filter("TA"."A"= (SELECT "TB"."A" FROM "TB" "TB" WHERE
"TB"."A"=:B1))
4 - filter("TB"."A"=:B1)
5 - filter("TB"."A"=:B1)
Note
-----
- dynamic sampling used for this statement (level=2)
统计信息
----------------------------------------------------------
11 recursive calls
1 db block gets
53 consistent gets
0 physical reads
588 redo size
840 bytes sent via SQL*Net to client
858 bytes received via SQL*Net from client
3 SQL*Net roundtrips to/from client
1 sorts (memory)
0 sorts (disk)
4 rows processed
如果 create unique index tb_a_uidx on tb(a);
[Copy to clipboard] [ - ]
CODE:
SQL> update (select ta.b tab1 ,tb.b tbb from ta,tb where ta.a=tb.a) set tab1=tbb;
已更新4行。
已用时间: 00: 00: 00.01
执行计划
----------------------------------------------------------
Plan hash value: 1761655026
----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------
| 0 | UPDATE STATEMENT | | 4 | 184 | 5 (20)| 00:00:01 |
| 1 | UPDATE | TA | | | | |
|* 2 | HASH JOIN | | 4 | 184 | 5 (20)| 00:00:01 |
| 3 | TABLE ACCESS FULL| TB | 4 | 104 | 2 (0)| 00:00:01 |
| 4 | TABLE ACCESS FULL| TA | 5 | 100 | 2 (0)| 00:00:01 |
----------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - access("TA"."A"="TB"."A")
Note
-----
- dynamic sampling used for this statement (level=2)
统计信息
----------------------------------------------------------
8 recursive calls
4 db block gets
17 consistent gets
0 physical reads
1004 redo size
840 bytes sent via SQL*Net to client
827 bytes received via SQL*Net from client
3 SQL*Net roundtrips to/from client
3 sorts (memory)
0 sorts (disk)
4 rows processed

MySQL'sBLOBissuitableforstoringbinarydatawithinarelationaldatabase,whileNoSQLoptionslikeMongoDB,Redis,andCassandraofferflexible,scalablesolutionsforunstructureddata.BLOBissimplerbutcanslowdownperformancewithlargedata;NoSQLprovidesbetterscalabilityand

ToaddauserinMySQL,use:CREATEUSER'username'@'host'IDENTIFIEDBY'password';Here'showtodoitsecurely:1)Choosethehostcarefullytocontrolaccess.2)SetresourcelimitswithoptionslikeMAX_QUERIES_PER_HOUR.3)Usestrong,uniquepasswords.4)EnforceSSL/TLSconnectionswith

ToavoidcommonmistakeswithstringdatatypesinMySQL,understandstringtypenuances,choosetherighttype,andmanageencodingandcollationsettingseffectively.1)UseCHARforfixed-lengthstrings,VARCHARforvariable-length,andTEXT/BLOBforlargerdata.2)Setcorrectcharacters

MySQloffersechar, Varchar, text, Anddenumforstringdata.usecharforfixed-Lengthstrings, VarcharerForvariable-Length, text forlarger text, AndenumforenforcingdataAntegritywithaetofvalues.

Optimizing MySQLBLOB requests can be done through the following strategies: 1. Reduce the frequency of BLOB query, use independent requests or delay loading; 2. Select the appropriate BLOB type (such as TINYBLOB); 3. Separate the BLOB data into separate tables; 4. Compress the BLOB data at the application layer; 5. Index the BLOB metadata. These methods can effectively improve performance by combining monitoring, caching and data sharding in actual applications.

Mastering the method of adding MySQL users is crucial for database administrators and developers because it ensures the security and access control of the database. 1) Create a new user using the CREATEUSER command, 2) Assign permissions through the GRANT command, 3) Use FLUSHPRIVILEGES to ensure permissions take effect, 4) Regularly audit and clean user accounts to maintain performance and security.

ChooseCHARforfixed-lengthdata,VARCHARforvariable-lengthdata,andTEXTforlargetextfields.1)CHARisefficientforconsistent-lengthdatalikecodes.2)VARCHARsuitsvariable-lengthdatalikenames,balancingflexibilityandperformance.3)TEXTisidealforlargetextslikeartic

Best practices for handling string data types and indexes in MySQL include: 1) Selecting the appropriate string type, such as CHAR for fixed length, VARCHAR for variable length, and TEXT for large text; 2) Be cautious in indexing, avoid over-indexing, and create indexes for common queries; 3) Use prefix indexes and full-text indexes to optimize long string searches; 4) Regularly monitor and optimize indexes to keep indexes small and efficient. Through these methods, we can balance read and write performance and improve database efficiency.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Dreamweaver CS6
Visual web development tools

WebStorm Mac version
Useful JavaScript development tools

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

mPDF
mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),
