Oracle的DML操作过程
用户将DML操作的语句通过进程传输给sga中的buffer cache,然后在buffer cache中对所更改的数据块进行更新操作,然后首先由logwr进
DML操作,Oracle所有进程配合执行的过程成!
用户将DML操作的语句通过进程传输给sga中的buffer cache,然后在buffer cache中对所更改的数据块进行更新操作,然后首先由logwr进程将此操作前的数据库传输给undo,将操作玩的数据传输给redo,此过程比较快(redo log为连续写)
然后再由dbwn进程将buffer cache中的脏数据块写入data file这个过程有间隔,这个间隔有ckpt进程来决定。
ckpt进程是如下运行的:
每隔3秒或更频繁写一次,写入控制文件和数据头文件,记录DBWN从SGA写入磁盘的块的位置(SCN(system change number) 系统更改号)
然后ckpt进程每次执行完之后,立刻通知dbwn进程,将现有的脏数据块写入data file
当dbwn进程将脏数据块写入data file后再产生一个检查点(checkpoint)
然后ckpt再次将scn更新到控制文件和data file的头文件中的scn之后,继续通知dbwn将buffer cache中的脏数据块写入到data file和dbwn创建检查点后继续等待ckpt进程的通知
如此循环,便是oracle的dml操作的过程!
后期补充:
另一位网友的介绍:
1、事务开始;
2、在buffer cache中找到需要的数据块,如果没有找到,则从数据文件中载入buffer cache中;
3、事务修改buffer cache的数据块,该数据被标识为“脏数据”,并被写入log buffer中;
4、事务提交,,LGWR进程将log buffer中的“脏数据”写入redo log file中;
5、当发生checkpoint,CKPT进程更新所有数据文件的文件头中的信息,DBWn进程则负责将Buffer Cache中的脏数据写入到数据文件中。
附:checkpoint由ckpt进程触发oracle进行checkpoint动作,将data buffer中的脏块(已经写在redo里记录但是没有写到datafile里的)的内容写入到data file里并释放站用的空间,由dbw后台进程完成,并修改controlfile和datafile的scn.
一般手工执行(alter system checkpoint)是由于要删除某个日志但是该日志里还有没有同步到data file里的内容,就需要手工check point来同步数据,然后就可以drop logfile group n.
相关阅读:
Oracle DML流程
PL/SQL“ ORA-14551: 无法在查询中执行 DML 操作”解决
MySQL常用DDL、DML、DCL语言整理(附样例)
Oracle基本事务和ForAll执行批量DML练习
Oracle DML语句(insert,update,delete) 回滚开销估算

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.
