sql query performance tuning tips

. Experiments have found that different indexes can be created on the master/slave database without interfering with each other (this is related to replication configuration). This makes it possible to create more optimized indexes based on the different usage patterns of the master and from the database. I saw on a foreign blog that using the dynamic view of SQL Server 2005, indexes are automatically created based on the usage patterns of t

be sorted, or it can be added to a column (like joins or additions). Any non-indexed item in the ORDER BY statement, or a computed expression, will slow down the query. Double-check the order BY statement to find non-indexed items or expressions that degrade performance. The solution to this problem is to rewrite the order BY statement to use the index, or you can establish another index for the column you

With examples and resolution plans, this article shows some tips for improving query efficiency on Microsoft SQL Server. There are many small tips and tricks in programming. Knowing these techniques can extend your ability to optimize your performance. All of our examples i

ObjectiveAn index is one of the most important objects in a relational database and can significantly reduce the consumption of disk I/O and logical reads to improve the lookup performance of a SELECT statement. But it is a double-edged sword, and improper use can affect performance: He needs extra controls to hold the index information, and when the data is updated, it takes some extra overhead to keep the

summary data is based is updated frequently, it is easier to use a view than to write SQL every time 2. Create a ViewThis is how the CREATE view is defined in the MySQL documentation: CREATE [OR REPLACE] [algorithm = {UNDEFINED | MERGE | TempTable}] [definer = {User | Current_User}] [SQL SECURITY {definer | INVOKER}]VIEW view_name [(column_list)]As Select_statement[With [cascaded | LOCAL] CHECK

There should be different filegroups in the database before the partition table is created;Assuming the database name is Df17datapro, create the user table UserID, put the first 500,000 data in the primary filegroup, place the 50~100 in the FG1 filegroup, and put more than 100 in the FG2 filegroup1. Add File group Fg1,fg2ALTER DATABASE Df17datapro ADD FILEGROUP FG1ALTER DATABASE df17dataproadd FILEGROUP fg22. Adding files to a filegroupALTER TABLEDf17dataproADD FILE(NAME=Df17datapro1,filename=

InnoDB storage engine for the x86_64 architecture (AMD Opteron) on Solaris 10, it is important to use the Forcedirectio option to install any data systems that are used to store InnoDB-related files. (The File system installation option is not used by default on Solaris 10/x86_64). Failure to use Forcedirectio can lead to a severe decline in the speed and performance of InnoDB on this platform. · When importing data into InnoDB, be assured that MySQ

union and UnionAll. UnionAll Good 18, pay attention to using distinct, do not use when not necessary, it will make the query slower than the union. Duplicate records are not a problem in the query. 19. Do not return rows or columns that are not required when querying 20. Use sp_configure ' query governor cost limit ' or setquery_governor_cost_limit to limit the

1. Import the trace file into the tableSELECT IDENTITY (BIGINT11 as RowNumber,* into TableNamefrom fn_trace_gettable ('trace.trc'default)2. Querying for statements with large CPU overheadSELECT Top -Total_worker_time/Execution_count asAvg_cpu_cost, Plan_handle, Execution_count, (SELECT SUBSTRING(text, Statement_start_offset/2 + 1, ( Case whenStatement_end_offset= -1 Then LEN(CONVERT(nvarchar(Max),text))* 2 ELSEStatement_end_offsetEND -Statement_start_offset)/2) fro

Recently, the following project encountered an urgent problem, my old horse and young people to fight together. The problem is that many queries are incredibly slow when the pressure data is poured into the database. Said there must be some basic guidelines for performance issues. The order of performance problems tunning 1 Architecture design (software architecture and database design, poor design is alm

execution plan you can see that the performance improvement is still very large. This is the data of the test environment, if the data volume is large, the advantage is more obvious.So for this problem, the cause is that there is a job data processing frequency is relatively high, in the test environment is difficult to locate where there is a problem, and the speed can also be accepted, but in the production environment is always slower, in fact, th

Label:ObjectiveIn the previous article, we analyzed how the query optimizer works, including: detailed operation steps of the query optimizer, analysis of filter conditions, optimization of index items, and other information.In this article we analyze the detection of several key indicator values in the course of our operation.These indicator values are analyzed to analyze the operation of the statement and