爱奇艺(iQIYI.COM),原名奇艺,中国第一影视门户。作为国内领先的网络视频播放平台,爱奇艺由全球最大的中文搜索引擎——百度创立,是国内首家专注于提供免费、高清网络视频服务的大型专业网站。 工作地点:北京海淀区海淀北一街2号鸿城拓展大厦11层 工作
爱奇艺(iQIYI.COM),原名奇艺,中国第一影视门户。作为国内领先的网络视频播放平台,爱奇艺由全球最大的中文搜索引擎——百度创立,是国内首家专注于提供免费、高清网络视频服务的大型专业网站。
工作地点:北京海淀区海淀北一街2号鸿城拓展大厦11层
工作职责:
-带领数据库运维小组维护数据库的正常运行和应急响应
-制定和改进应急预案、策略和流程,提高服务运行质量
-配合相关部门完善服务运维体系 ,制定和改进应急预案、策略
-负责团队管理和员工培养,制定部门工作规划,负责相关部门进行沟通与协作
职位要求:
-熟悉MySQL或Oracle数据库的运行机制和体系架构
-精通/熟悉SQL,精通数据库设计
-熟悉Linux/Unix操作系统,具有良好的Shell/Perl编程能力
-抗压能力强,有强烈的责任心,良好的沟通能力
-有专职DBA工作经验优先
有意者请和我联系。
原文地址:[代发]奇艺急招MySQL/ORACLE DBA, 感谢原作者分享。

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.

Key metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.

Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB

MySQL/InnoDB supports four transaction isolation levels: ReadUncommitted, ReadCommitted, RepeatableRead and Serializable. 1.ReadUncommitted allows reading of uncommitted data, which may cause dirty reading. 2. ReadCommitted avoids dirty reading, but non-repeatable reading may occur. 3.RepeatableRead is the default level, avoiding dirty reading and non-repeatable reading, but phantom reading may occur. 4. Serializable avoids all concurrency problems but reduces concurrency. Choosing the appropriate isolation level requires balancing data consistency and performance requirements.

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 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 MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.


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