最近被一个客户问到了这样一个有趣的问题执行计划在生成过程中使用了那些统计信息呢?针对这个问题,客户也做了一些研究,并给了我下面两篇博文作为切入点。 1. How to Find the Statistics Used to Compile an Execution Plan ( http://sqlblog.com/blogs/p
最近被一个客户问到了这样一个有趣的问题——执行计划在生成过程中使用了那些统计信息呢?针对这个问题,客户也做了一些研究,并给了我下面两篇博文作为切入点。
1. How to Find the Statistics Used to Compile an Execution Plan (
2. Statistics used in a cached query plan (
在查看了这两篇博文后,我把其中的奥秘摘出来跟大家分享一下。
第一篇博文介绍了两个Trace Flag, 9204和9292。这两个Trace Flag是这样解释的:
9204 – 打印出被加载的统计信息
9292 – 打印出从元数据中得到的统计信息的头信息
当然,要看到这些信息,我们还需要打开Trace Flag 3604才能让这些显示出来。以下面的脚本为例,
<ol class="dp-xml"> <li class="alt"><span><span>USE Northwind </span></span></li> <li><span> </span></li> <li class="alt"><span>GO </span></li> <li><span> </span></li> <li class="alt"><span>DBCC FREEPROCCACHE() </span></li> <li><span> </span></li> <li class="alt"><span>GO </span></li> <li><span> </span></li> <li class="alt"><span>DBCC TRACEON(3604, 9292, 9204) </span></li> <li><span> </span></li> <li class="alt"><span>GO </span></li> <li><span> </span></li> <li class="alt"><span> </span></li> <li><span> </span></li> <li class="alt"><span>SELECT Employees.FirstName, COUNT(Orders.OrderID) </span></li> <li><span> </span></li> <li class="alt"><span>FROM Orders </span></li> <li><span> </span></li> <li class="alt"><span>INNER JOIN Employees </span></li> <li><span> </span></li> <li class="alt"> <span> ON </span><span class="attribute">Orders.EmployeeID</span><span> = </span><span class="attribute-value">Employees</span><span>.EmployeeID </span> </li> <li><span> </span></li> <li class="alt"> <span>WHERE </span><span class="attribute">Employees.FirstName</span><span> = </span><span class="attribute-value">'Steven'</span><span> </span> </li> <li><span> </span></li> <li class="alt"><span>GROUP BY Employees.FirstName </span></li> <li><span> </span></li> <li class="alt"><span>GO </span></li> </ol>
其返回结果为:
Stats header loaded: DbName: Northwind, ObjName: Orders, IndexId: 4, ColumnName: EmployeeID, EmptyTable: FALSE
Stats loaded: DbName: Northwind, ObjName: Orders, IndexId: 4, ColumnName: EmployeeID, EmptyTable: FALSE
Stats header loaded: DbName: Northwind, ObjName: Orders, IndexId: 5, ColumnName: EmployeeID, EmptyTable: FALSE
Stats header loaded: DbName: Northwind, ObjName: Employees, IndexId: 1, ColumnName: EmployeeID, EmptyTable: FALSE
Stats loaded: DbName: Northwind, ObjName: Employees, IndexId: 1, ColumnName: EmployeeID, EmptyTable: FALSE
Stats header loaded: DbName: Northwind, ObjName: Employees, IndexId: 4, ColumnName: FirstName, EmptyTable: FALSE
Stats loaded: DbName: Northwind, ObjName: Employees, IndexId: 4, ColumnName: FirstName, EmptyTable: FALSE
FirstName
---------- -----------
Steven 42
从这个SELECT语句中,我们不难看出查询结果应该是员工Steven的First Name和这个员工有的所有的订单Order的数量。表Employees和Orders是用过EmployeeID来联系起来的。所以,在Employees.EmployeeID和Orders.EmployeeID上建立的索引上面的统计信息会被用来产生执行计划。当然除了他们,还应该有在字段Employees.FirstName上的统计信息,因为这个字段上没有索引存在,所以系统会在这里自动生成一个统计信息。
需要注意的是,Trace Flag 9204和9292 只会在这个SELECT语句第一次被编译的时候打印出这些统计信息的记录。如果执行计划已经存在于缓存中,那么这些统计信息的记录则不会被打印出来。只有在用DBCC FREEPROCCACHE(plan_handle)清理了这条语句的缓存计划后,再次执行的时候才会再次被打印出来。
第二篇博文介绍了另一个Trace Flag,8666。这个Trace Flag是这样解释的:
8666 – 将Showplan的详细信息打印出来
这个Trace Flag会将一些关于统计信息的内部信息显示出来。例如,
<ol class="dp-xml"> <li class="alt"><span><span>USE Northwind </span></span></li> <li><span> </span></li> <li class="alt"><span>GO </span></li> <li><span> </span></li> <li class="alt"><span>DBCC FREEPROCCACHE() </span></li> <li><span> </span></li> <li class="alt"><span>GO </span></li> <li><span> </span></li> <li class="alt"><span>DBCC TRACEON(8666) </span></li> <li><span> </span></li> <li class="alt"><span>GO </span></li> <li><span> </span></li> <li class="alt"><span> </span></li> <li><span> </span></li> <li class="alt"><span>SELECT Employees.FirstName, COUNT(Orders.OrderID) </span></li> <li><span> </span></li> <li class="alt"><span>FROM Orders </span></li> <li><span> </span></li> <li class="alt"><span>INNER JOIN Employees </span></li> <li><span> </span></li> <li class="alt"> <span> ON </span><span class="attribute">Orders.EmployeeID</span><span> = </span><span class="attribute-value">Employees</span><span>.EmployeeID </span> </li> <li><span> </span></li> <li class="alt"> <span>WHERE </span><span class="attribute">Employees.FirstName</span><span> = </span><span class="attribute-value">'Steven'</span><span> </span> </li> <li><span> </span></li> <li class="alt"><span>GROUP BY Employees.FirstName </span></li> <li><span> </span></li> <li class="alt"><span>GO </span></li> </ol>

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.

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 is worth learning because it is a powerful open source database management system suitable for data storage, management and analysis. 1) MySQL is a relational database that uses SQL to operate data and is suitable for structured data management. 2) The SQL language is the key to interacting with MySQL and supports CRUD operations. 3) The working principle of MySQL includes client/server architecture, storage engine and query optimizer. 4) Basic usage includes creating databases and tables, and advanced usage involves joining tables using JOIN. 5) Common errors include syntax errors and permission issues, and debugging skills include checking syntax and using EXPLAIN commands. 6) Performance optimization involves the use of indexes, optimization of SQL statements and regular maintenance of databases.

MySQL is suitable for beginners to learn database skills. 1. Install MySQL server and client tools. 2. Understand basic SQL queries, such as SELECT. 3. Master data operations: create tables, insert, update, and delete data. 4. Learn advanced skills: subquery and window functions. 5. Debugging and optimization: Check syntax, use indexes, avoid SELECT*, and use LIMIT.

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.

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SQL is used to interact with MySQL database to realize data addition, deletion, modification, inspection and database design. 1) SQL performs data operations through SELECT, INSERT, UPDATE, DELETE statements; 2) Use CREATE, ALTER, DROP statements for database design and management; 3) Complex queries and data analysis are implemented through SQL to improve business decision-making efficiency.

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


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