SQLSERVER中KeyHashValue的作用(上) SQLSERVER中KeyHashValue的作用(下) 原文的标题是:SQLSERVER在索引下如何找到哈希值的随想 现在知道KeyHashValue的作用了,所以就改了标题~ 测试环境:SQLSERVER2005 开发者版 真的不好意思,我做实验的时候到最后还
SQLSERVER中KeyHashValue的作用(上)
SQLSERVER中KeyHashValue的作用(下)
原文的标题是:SQLSERVER在索引下如何找到哈希值的随想
现在知道KeyHashValue的作用了,所以就改了标题~
测试环境:SQLSERVER2005 开发者版
真的不好意思,我做实验的时候到最后还是没有找到这个问题的答案
问题是这样的:
当通过聚集索引查找和非聚集索引查找的时候,通过哈希码来匹配,然后找到相应记录的
既然通过哈希码来匹配,那么就需要一个hash bucket把所有索引页面的所有key/value全部加载到hash bucket
既然要全部加载到hash bucket就需要读取所有的索引页
我的测试脚本,,我使用SET STATISTICS IO ON来测试是否有读取索引页的情况,但是到最后还是找不到规律
master SCANDB SCANDB clusteredtable(c1 INT IDENTITY(1,1), c2 VARCHAR (900)) nonclusteredtable(c1 INT IDENTITY(1,1), c2 VARCHAR (900)) cix_clusteredtable ) ix_nonclusteredtable ) ; ; ) clusteredtable (, 880)) ; ; ) nonclusteredtable (, 880)) clusteredtable nonclusteredtable DBCCResult ( 59 PageFID NVARCHAR(200), 60 PagePID NVARCHAR(200), 61 IAMFID NVARCHAR(200), 62 IAMPID NVARCHAR(200), 63 ObjectID NVARCHAR(200), 64 IndexID NVARCHAR(200), 65 PartitionNumber NVARCHAR(200), 66 PartitionID NVARCHAR(200), 67 iam_chain_type NVARCHAR(200), 68 PageType NVARCHAR(200), 69 IndexLevel NVARCHAR(200), 70 NextPageFID NVARCHAR(200), 71 NextPagePID NVARCHAR(200), 72 PrevPageFID NVARCHAR(200), 73 PrevPagePID NVARCHAR(200) 74 ) .DBCCResult ) .TRACEON(3604,-1) PAGE(SCANDB,1,89,3) DROPCLEANBUFFERS ) IO clusteredtable IO (1 行受影响) 。扫描计数 1,逻辑读取 4 次,物理读取 2 次,预读 0 次,lob 逻辑读取 0 次,lob 物理读取 0 次,lob 预读 0 次。 DROPCLEANBUFFERS ) IO nonclusteredtable IO (1 行受影响) 。扫描计数 1,逻辑读取 5 次,物理读取 1 次,预读 0 次,lob 逻辑读取 0 次,lob 物理读取 0 次,lob 预读 0 次。

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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