Slow SQL Server database query

There are many causes for slow query speed of SQL Server databases. The following are common causes: 1. No index or no index is used (this is the most common problem of slow query and is a defect in programming) 2. Low I/O throughput, resulting in a bottleneck effect. 3. the query is not optimized because no computing column is created. 4. Insufficient memory 5. slow network speed 6. queried data volume

There are many reasons for slow query speed in SQL Server databases. Common causes include: 1. No index or no index is used (this is the most common problem of slow query and is a defect in programming) 2. Low I/O throughput, resulting in a bottleneck effect. 3. the query is not optimized because no computing column is created. 4. Insufficient memory 5. slow network speed 6. queried data volume

There are many reasons for slow query speed in SQL Server databases. The following are common causes:

1. No index or no index is used (this is the most common problem of slow query and is a defect in programming)

2. Low I/O throughput, resulting in a bottleneck effect.

3. the query is not optimized because no computing column is created.

4. Insufficient memory 5. slow network speed 6. The queried data volume is too large (you can use multiple queries to reduce the data volume in other ways)

7. Lock or deadlock (this is also the most common problem of slow query and is a defect in programming)

8. sp_lock and sp_who are active users. The reason is that they read and write competing resources.

9. Unnecessary rows and columns are returned. 10. The query statement is not good and is not optimized.

You can optimize the query by using the following methods:

1. Place data, logs, and indexes on different I/O devices to increase the reading speed. In the past, Tempdb can be placed on RAID0, which is not supported by SQL2000. The larger the data size (size), the more important it is to increase I/O.

2. vertically and horizontally split the table to reduce the table size (sp_spaceuse)

3. upgrade hardware

4. Create an index based on the query conditions, optimize the index, optimize the access mode, and limit the data volume of the result set. Note that the fill factor should be appropriate (preferably the default value 0 ). The index should be as small as possible. Use a column with a small number of bytes to create an index (refer to the index creation). Do not create a single index for fields with a limited number of values, such as gender fields.

5. Increase the network speed.

6. Expand the server memory. Windows 2000 and SQL server 2000 support 4-8 GB memory.

Configure virtual memory: the virtual memory size should be configured based on services running concurrently on the computer. Run Microsoft SQL Server? 2000, you can consider setting the virtual memory size to 1.5 times the physical memory installed on your computer. If you have installed the full-text search feature and intend to run the Microsoft Search Service for full-text indexing and query, consider: set the virtual memory size to at least three times the physical memory installed on the computer. Configure the SQL Server max server memory Server configuration option to 1.5 times the physical memory (half the virtual memory size ).

7. Increase the number of server CPUs. However, you must understand that resources such as memory are more required for concurrent processing of serial processing. Whether to use parallelism or serial travel is automatically evaluated and selected by MsSQL. A single task is divided into multiple tasks and can be run on the processor. For example, if the sort, connection, scan, and group by statements of delayed queries are executed simultaneously, SQL SERVER determines the optimal parallel level based on the system load, complex queries that consume a large amount of CPU are most suitable for parallel processing. However, UPDATE, INSERT, and DELETE operations cannot be processed in parallel.

8. If you use like for query, you cannot simply use index, but the full-text index consumes space. Like 'a % ''when you use the index like'' % a' without the index like ''% a %'', the query time is proportional to the total length of the field value, therefore, the CHAR type cannot be used, but VARCHAR. create a full-text index for a long field value.

9. Separate DB Server and APPLication Server; Separate OLTP and OLAP

10. Distributed partition view can be used to implement Database Server consortium.

A consortium is a group of separately managed servers, but they collaborate to share the processing load of the system. This mechanism of forming Database Server consortium through partition data can expand a group of servers to support the processing needs of large multi-layer Web sites. For more information, see designing a database federation server. (Refer to the SQL Help File ''partition view '')

A. before implementing the partition view, a horizontal partition table must be created.

B. After creating a member table, define a distributed partition view on each Member Server, and each view has the same name. In this way, queries that reference the view name of a distributed partition can run on any Member Server. System operations are the same as if each member server has a copy of the original table, but in fact each server has only one member table and a distributed partition view. The data location is transparent to the application.

11. re-create the index dbcc reindex, dbcc indexdefrag, shrink data and logs dbcc shrinkdb, and dbcc shrinkfile. set to automatically contract logs. For large databases, do not set Automatic database growth, which will reduce the server performance.

The writing of T-SQL is very important. The following lists common points: first, the process of DBMS processing the query plan is as follows:

1. query statement lexical and syntax check 2. submit the statement to the query optimizer of the DBMS 3. Optimize the optimizer in algebra and optimize the access path 4. Generate a query by the Pre-compilation Module planning 5. Submit the execution results to the system at the appropriate time. 6. Finally, return the execution results to the user.

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