ORA-01779的处理方法(更新数据处理)
Oracle中试图对一个子查询进行更新时可能会出现ORA-01779错误。该错误的内容为: ORA-01779: cannot modify a column which maps
Oracle中试图对一个子查询进行更新时可能会出现ORA-01779错误。该错误的内容为:
ORA-01779: cannot modify a column which maps to a non-key-preserved table例如,使用以下的更新查询就会出现该错误。
这个错误的意思是,子查询的结果中,更新数据源(test2)的内容不唯一,导致被更新对象(test1)中的一行可能对应数据源(test2)中的多行。 本例中,,test2表的id不唯一,因此test2表中可能存在id相同但是num不相同的数据,这种数据是无法用来更新 test1 的。
解决方法就是保证数据源的唯一性,例如本例中可以为test2.id创建一个唯一索引:
CREATE UNIQUE INDEX test2_idx_001 ON test2 (id);
之后上面的更新就可以执行了。
另外也可以强制 Oracle 执行,方法是加上 BYPASS_UJVC 注释。
BYPASS_UJVC的作用是跳过Oracle的键检查。 这样虽然能够执行了,但是如果test2中存在不唯一的数据,test1就会被更新多次而导致意想不到的结果。

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.

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.

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.
