SLC因为速度快,使用寿命长,一般被用在企业级SSD上。而MLC则多用在消费级市场,如workstation。Fusion-io开发出一种管理MLC闪存
当一个传统的向外扩展的方式对于MySQL来讲变得流行,看看我们不得不扩充哪一方面(便宜的内存?快速存储?更好的电源效率?)将会变得非常有趣。这里确实有很多种选择——我每周大概会遇到一个客户使用Fushion-IO 卡。然而,我却看到了他们一个有趣的选择——他们选择购买一个SSD,当他们每秒仍然能读取很多页的时候(这时,我宁愿选择购买内存来取代),而使用存储驱动器做“写操作”使用。
在这里,我提出几个参考标准来供你确认是否是以上我说的这种情况:
1. 带有BBU的RAID 10硬盘超过8块(所谓BBU,社区的解释是在掉电的情况下,能够cache数据72h,当机器供电正常,再从cache中将数据写入磁盘)
2. Inter SSD X25-E 32GB
3. FushionIO 320GB MLC【1】
Dell PowerEdgeR900
4 QuadCoreIntel(R) Xeon(R) CPU E7320 @ 2.13GHz (16 cores in total)
32GB of RAM
RAID10 on 8disks 2.5” 15K RPMS
FusionIO 160GBSLC
FusionIO 320GBMLC
OS:
CentOS 5.5
XFS filesystem
开始,我们对RAID 10的存储做一个测试以建立一个基线。Y轴是每秒传输的数据(传输速率,它越大越好)。X轴是innodb_buffer_pool_size的大小。
我特地挑选了关于该测试中的三个有趣的点

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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