search
HomeDatabaseMysql Tutorial在Oracle中进行大小写不敏感的查询

在Oracle中,命令和对象名称都是大小写不敏感的,因为Oracle在处理语句时,将所有的名称和命令全部转化为大写。但是对于字符串中

在Oracle中,命令和对象名称都是大小写不敏感的,因为Oracle在处理语句时,将所有的名称和命令全部转化为大写。
但是对于字符串中的字符,无论是比较还是排序,都是大小写敏感的。这在Oracle是默认方式,但不是唯一的方式。

下面看一个简单的例子:
SQL> CREATE TABLE T (NAME VARCHAR2(30));
表已创建。
SQL> INSERT INTO T VALUES ('A');
已创建 1 行。
SQL> INSERT INTO T VALUES ('a');
已创建 1 行。
SQL> INSERT INTO T VALUES ('B');
已创建 1 行。
SQL> COMMIT;
提交完成。
SQL> CREATE INDEX IND_T_NAME ON T(NAME);
索引已创建。
看一下默认情况下的排序和查询结果:
SQL> SELECT * FROM T ORDER BY NAME;
NAME
------------------------------
A
B
a
SQL> SELECT * FROM T WHERE NAME = 'A';
NAME
------------------------------
A
这是最正常不过的结果了,下面修改会话默认的排序方式:
SQL> ALTER SESSION SET NLS_SORT = BINARY_CI;
会话已更改。
SQL> SELECT * FROM T ORDER BY NAME;
NAME
------------------------------
A
a
B
SQL> SELECT * FROM T WHERE NAME = 'A';
NAME
------------------------------
A
可以看到,通过设置排序方法为BINARY_CI,已经实现了对排序的大小写不敏感,但是查询语句中仍然是大小写敏感的,下面进一步修改比较方式:
SQL> ALTER SESSION SET NLS_COMP = LINGUISTIC;
会话已更改。
SQL> SELECT * FROM T ORDER BY NAME;
NAME
------------------------------
A
a
B
SQL> SELECT * FROM T WHERE NAME = 'A';
NAME
------------------------------
A
a
现在已经达到了大小写不敏感查询的目的了,这是由于设置比较方式是基于语义的,而不是基于二进制的,而语言方式下A和a是没有区别的。
虽然目的达到了,但是还是要说明一下,,这里虽然实现了对大小写不敏感的查询,但是这个结果的实现与表面看到的现象并不完全相同。
从查询语句上看,似乎只是对NAME进行一下判断就可以了,并未对列进行任何的操作,而实际上并非如此,下面看看这种情况下的执行计划:
SQL> SET AUTOT ON EXP
SQL> SELECT * FROM T WHERE NAME = 'A';
NAME
------------------------------
A
a
执行计划
----------------------------------------------------------
Plan hash value: 1601196873
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 17 | 3 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| T | 1 | 17 | 3 (0)| 00:00:01 |
--------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter(NLSSORT("NAME",'nls_sort=''BINARY_CI''')=HEXTORAW('6100')
)
Note
-----
- dynamic sampling used for this statement
Oracle居然对列进行了操作,将NAME进行了NLSSORT操作,然后判断是否与目标值进行判断。不过Oracle也没有其他的好方法进行处理,对等号右边的常量进行转换固然代价较低,但是SQL的判断条件就由等于变成了IN,这种转换恐怕变化更大。而且还要找到所有其他所有可能转换为目标值的常量,这个操作要比对列进行转换复杂得多。
不过这种方法就存在一个问题,就是Oracle无法使用索引了,一方面是由于对列进行了操作,另一方面是由于Oracle的索引是按照BINARY方式编码存储的。因此这种查询会采用全表扫描的方式。
SQL> SELECT /*+ INDEX(T IND_T_NAME) */ * FROM T WHERE NAME = 'A';
NAME
------------------------------
A
a
执行计划
----------------------------------------------------------
Plan hash value: 1601196873
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 17 | 3 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| T | 1 | 17 | 3 (0)| 00:00:01 |
--------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter(NLSSORT("NAME",'nls_sort=''BINARY_CI''')=HEXTORAW('6100')
)
Note
-----
- dynamic sampling used for this statement
这个情况,可以考虑建立一个函数索引来解决问题:
SQL> CREATE INDEX IND_T_L_NAME ON T(NLSSORT(NAME, 'NLS_SORT=BINARY_CI'));
索引已创建。
SQL> SELECT * FROM T WHERE NAME = 'A';
NAME
------------------------------
A
a
执行计划
----------------------------------------------------------
Plan hash value: 242883967
--------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 17 | 2 (0)| 00:00:01 |
| 1 | TABLE ACCESS BY INDEX ROWID| T | 1 | 17 | 2 (0)| 00:00:01 |
|* 2 | INDEX RANGE SCAN | IND_T_L_NAME | 1 | | 1 (0)| 00:00:01 |
--------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - access(NLSSORT("NAME",'nls_sort=''BINARY_CI''')=HEXTORAW('6100') )
Note
-----
- dynamic sampling used for this statement

linux

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
What Are the Limitations of Using Views in MySQL?What Are the Limitations of Using Views in MySQL?May 14, 2025 am 12:10 AM

MySQLviewshavelimitations:1)Theydon'tsupportallSQLoperations,restrictingdatamanipulationthroughviewswithjoinsorsubqueries.2)Theycanimpactperformance,especiallywithcomplexqueriesorlargedatasets.3)Viewsdon'tstoredata,potentiallyleadingtooutdatedinforma

Securing Your MySQL Database: Adding Users and Granting PrivilegesSecuring Your MySQL Database: Adding Users and Granting PrivilegesMay 14, 2025 am 12:09 AM

ProperusermanagementinMySQLiscrucialforenhancingsecurityandensuringefficientdatabaseoperation.1)UseCREATEUSERtoaddusers,specifyingconnectionsourcewith@'localhost'or@'%'.2)GrantspecificprivilegeswithGRANT,usingleastprivilegeprincipletominimizerisks.3)

What Factors Influence the Number of Triggers I Can Use in MySQL?What Factors Influence the Number of Triggers I Can Use in MySQL?May 14, 2025 am 12:08 AM

MySQLdoesn'timposeahardlimitontriggers,butpracticalfactorsdeterminetheireffectiveuse:1)Serverconfigurationimpactstriggermanagement;2)Complextriggersincreasesystemload;3)Largertablesslowtriggerperformance;4)Highconcurrencycancausetriggercontention;5)M

MySQL: Is it safe to store BLOB?MySQL: Is it safe to store BLOB?May 14, 2025 am 12:07 AM

Yes,it'ssafetostoreBLOBdatainMySQL,butconsiderthesefactors:1)StorageSpace:BLOBscanconsumesignificantspace,potentiallyincreasingcostsandslowingperformance.2)Performance:LargerrowsizesduetoBLOBsmayslowdownqueries.3)BackupandRecovery:Theseprocessescanbe

MySQL: Adding a user through a PHP web interfaceMySQL: Adding a user through a PHP web interfaceMay 14, 2025 am 12:04 AM

Adding MySQL users through the PHP web interface can use MySQLi extensions. The steps are as follows: 1. Connect to the MySQL database and use the MySQLi extension. 2. Create a user, use the CREATEUSER statement, and use the PASSWORD() function to encrypt the password. 3. Prevent SQL injection and use the mysqli_real_escape_string() function to process user input. 4. Assign permissions to new users and use the GRANT statement.

MySQL: BLOB and other no-sql storage, what are the differences?MySQL: BLOB and other no-sql storage, what are the differences?May 13, 2025 am 12:14 AM

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

MySQL Add User: Syntax, Options, and Security Best PracticesMySQL Add User: Syntax, Options, and Security Best PracticesMay 13, 2025 am 12:12 AM

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

MySQL: How to avoid String Data Types common mistakes?MySQL: How to avoid String Data Types common mistakes?May 13, 2025 am 12:09 AM

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

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

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

Hot Article

Hot Tools

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Linux new version

SublimeText3 Linux new version

SublimeText3 Linux latest version

MantisBT

MantisBT

Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

SAP NetWeaver Server Adapter for Eclipse

SAP NetWeaver Server Adapter for Eclipse

Integrate Eclipse with SAP NetWeaver application server.