Oracle SQL 语句in长度不得超过1000
PL/SQL中,表达式/SQL本身的长度是可以达到比较长的长度(50K)左右,如:v_str:=:new.f1||:ndw.f2。。。 ; select :new.f1||:new.
1. IN 子句中的LIST个数最长为1000,超过该数目将报错,这里可转用一个临时表来解决;
2. * CREATE TRIGGER语句文本的字符长度不能超过32KB(触发器中不能使用LONG, LONG RAW 类型;触发器内可以参照LOB 类型列的列值,但不能通过 :NEW 修改LOB列中的数据;)顺便说一下,触发器中的PARENT关键字,只在嵌套表触发器中有效,
3. * 11G以前,DBMS_SQL对输入的SQL长度不能超过32K,原因是输入参数只能是VARCHAR2类型,11G后,可以用CLOB作为输入参数,则取消了这个限制
3. * 一个PL/SQL的包、过程、函数、触发器的大小,,在UNIX上最大是64K,而WINDOWS则是32K大小(32K这个应该不准,看下面的测试)
4. * SQL语句可以有多长?(网友说)Oracle文档说是64K,实际受一些工具的限制会较这个值低,但网友测试发现可以很长,甚至超过1M(我测试过 170K的都没问题)。具体多长,10G也未说明,只是与很多环境有关:数据库配置,磁盘空间,内存多少。。。
5. PL/SQL中,表达式/SQL本身的长度是可以达到比较长的长度(50K)左右,如:v_str:=:new.f1||:ndw.f2。。。 ; select :new.f1||:new.f2。。。 into v_str from dual; 另外发现,如果这样写:v_str := ‘a’||’b’||。。。则允许的表达式长度将大大的减少。如果表达式/SQL过长,超过了一个ORACLE包/过程允许的最大程序长度,则在编译时报 pls-123:program too large错误,这是pl/sql编译器本身的限制造成的,即表达式/SQL的长度在PL/SQL中受限于包/过程的最大大小

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

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

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

Hot Topics











The main role of MySQL in web applications is to store and manage data. 1.MySQL efficiently processes user information, product catalogs, transaction records and other data. 2. Through SQL query, developers can extract information from the database to generate dynamic content. 3.MySQL works based on the client-server model to ensure acceptable query speed.

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

Compared with other programming languages, MySQL is mainly used to store and manage data, while other languages such as Python, Java, and C are used for logical processing and application development. MySQL is known for its high performance, scalability and cross-platform support, suitable for data management needs, while other languages have advantages in their respective fields such as data analytics, enterprise applications, and system programming.

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

The basic operations of MySQL include creating databases, tables, and using SQL to perform CRUD operations on data. 1. Create a database: CREATEDATABASEmy_first_db; 2. Create a table: CREATETABLEbooks(idINTAUTO_INCREMENTPRIMARYKEY, titleVARCHAR(100)NOTNULL, authorVARCHAR(100)NOTNULL, published_yearINT); 3. Insert data: INSERTINTObooks(title, author, published_year)VA

MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.

InnoDBBufferPool reduces disk I/O by caching data and indexing pages, improving database performance. Its working principle includes: 1. Data reading: Read data from BufferPool; 2. Data writing: After modifying the data, write to BufferPool and refresh it to disk regularly; 3. Cache management: Use the LRU algorithm to manage cache pages; 4. Reading mechanism: Load adjacent data pages in advance. By sizing the BufferPool and using multiple instances, database performance can be optimized.

MySQL efficiently manages structured data through table structure and SQL query, and implements inter-table relationships through foreign keys. 1. Define the data format and type when creating a table. 2. Use foreign keys to establish relationships between tables. 3. Improve performance through indexing and query optimization. 4. Regularly backup and monitor databases to ensure data security and performance optimization.
