SQL Server查询优化策略：提升数据检索效率

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"Sql Server查询优化是Microsoft SQL Server数据库管理系统中的关键要素，它在处理数据存储、管理和访问时发挥着至关重要的作用。本文主要探讨了查询优化技术在Microsoft SQL Server中的应用，该系统以其MS-SQL和Transact-SQL作为主要结构化编程语言，支持关系代数在数据插入、修改、删除和检索等操作中的使用，同时也负责数据访问控制。查询优化涉及SQL Server如何确定并选择最佳执行计划以获得预期结果的过程。最常见的优化需求来自SELECT语句，但其实，除了这些查询，其他对象如索引、视图和统计信息也同样需要优化。索引作为一种性能提升手段，可以加快数据查找速度；视图提供了数据的抽象层，使得查询更加灵活；而统计信息则是SQL Server评估查询效率的重要依据。本文的作者Costel Gabriel CORLĂŢAN、Marius Mihai LAZĂR、Valentina LUCA和Octavian Teodor PETRICICĂ来自罗马尼亚布加勒斯特的经济学院，他们在文中深入介绍了SQL Server查询优化的基本原理和技术，包括成本模型、查询重写、物理执行计划、统计信息收集与维护等内容。关键词包括SQL Server、查询、索引、视图、统计信息以及优化策略。优化过程不仅关注查询效率，还要平衡资源消耗和响应时间，因此需要对查询的复杂性、表的大小、数据分布、硬件配置等因素进行综合考量。通过对SQL Server的合理配置和查询语句的优化，可以显著提升系统的整体性能，确保在大规模数据处理和并发访问场景下的高效运行。总结来说，学习和掌握SQL Server查询优化技巧对于数据库管理员和开发人员来说至关重要，它涉及到数据库设计、查询语句编写、性能监控等多个层面，是实现高效数据管理的关键技术之一。"

36 Query optimization techniques in Microsoft SQL Server

which will be extracted from one or more

tables (in the case of join) is important

when deciding the optimization method of

the query execution. Query optimization is

less efficient when date statistics are not

correctly updated.

The SQL Server query optimizer is based

on cost, meaning that it decides the best

data access mechanism, by type of query,

while applying a selectivity identification

strategy. Each statistic has an index

attached, but there can be manually created

statistics, on columns that do not belong to

any index. Using statistics, the optimizer

can make pretty reasonable estimates

regarding the needed time for the system to

return a set of results.

Indexed column statistics

The utility of an index is entirely

dependent on the indexed column

statistics. Without any statistics, the SQL

Server cost-based query optimizer cannot

decide which is the most efficient way of

using an index. In order to satisfy this

requirement, it automatically creates

statistics on a index key every time the

index is created. The required mechanism

of data extraction in order to keep the cost

low can use changing data. For example, if

a table has a single row that matches some

value which is unique, then using a

nonclustered index makes sense. But if

data changes, when adding a big number of

rows with the same column value

(duplicates), using the same index does not

make any sense.

According to [5], SQL Server utilizes an

efficient algorithm to decide when to

execute the system procedure that updates

the statistics, based on factors such as

number of updates and table size:

- When inserting a line into an empty

table;

- When inserting more than 1000 lines in

a table that already has 1000 rows.

Automatic update of statistics is

recommended in the vast majority of cases,

except for very large table, where statistics

updates can lead to slowing down or

blocking the system. This is an isolated

case and the best decision must be taken

regarding its update.

Statistics update is made using the system

procedure sys.sp_updatestats on an

indexed table or view.

Unindexed column statistics

Sometimes there is the possibility of

executing a query on an unindexed

column. Even in this situation the query

optimizer can take the best decision if it

knows the data distribution of those

columns. As opposed to index statistics,

SQL Server can create statistics regarding

the unindexed columns. Information

regarding data distribution or the

probability of having some value in an

unindexed column can help the optimizer

establish an optimum strategy. SQL Server

benefits of query optimization even when

it cannot use an index to locate the values.

This automatically creates statistics on the

unindexed column when the information

that the system has, helps creating the best

plan, usually when the columns are used in

a predicate(ex: WHERE).

Table 1.4. Query plan

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