MSSQL Query Optimization

There are many reasons for slow query speed. The following are common causes:
1. No index or no index is used (this is the most common problem of slow queryProgramDesign defects)
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. locks or deadlocks (this is also the most common problem of slow query and is a defect in programming) sp_lock and sp_who are viewed by active users because they are competing for read and write 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. Improve 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 the services that run concurrently on the computer. When running Microsoft SQL Server 2000, you can set 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 % 'Use Index
Like '% a' does not use an index
When you use like '% A %' to query, the query time is proportional to the total length of the field value. Therefore, the char type cannot be used, but the varchar type is not used. 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. Rebuild the index DBCC reindex, DBCC indexdefrag, shrink data and log DBCC shrinkdb, and DBCC shrinkfile.
Set automatic log shrinking. Do not set Automatic database growth for large databases, which will reduce server performance.

T-SQL is very well written. The following lists common points:
First, the DBMS processes the query plan as follows:
1. query statement lexical and syntax check
2. submit the statement to the query optimizer of the DBMS.
3. optimizer performs algebra optimization and access path optimization
4. A query plan is generated by the Pre-compilation module.
5. Then, submit it to the system for processing and execution at the appropriate time.
6. Finally, return the execution result to the user.
Next, let's take a look at the data storage structure of SQL Server:
The size of a page is 8 K (8060) bytes, and 8 pages are stored in a disk area according to the B-tree.
Difference between commit and rollback
Rollback: rolls back all things.
Commit: Submit the current transaction.
There is no need to write things in dynamic SQL. If you want to write things, please write them out as follows:
Begin tran
Exec (@ s)
Commit Trans
You can also write dynamic SQL statements as functions or stored procedures.

13. Use the WHERE clause in the SELECT statement to limit the number of returned rows to avoid table scanning. If unnecessary data is returned, the server's I/O resources are wasted, this increases the burden on the network and reduces performance. If the table is large, the table is locked during the table scan and other connections are prohibited from accessing the table. The consequence is serious.
14. SQL statement comments have no impact on execution
15. Try not to use the cursor. It occupies a large amount of resources. If you need row-by-row execution, try to use non-cursor technology, such as loop on the client, using temporary tables, table variables, subqueries, and case statements. The cursor can be classified according to the extraction options it supports:
Forward only
The row must be extracted from the first row to the last row. Fetch next is the only allowed extraction operation and is also the default method.
Rollability
Arbitrary rows can be randomly extracted anywhere in the cursor.
The cursor technology becomes very powerful in SQL2000, and its purpose is to support loops.
There are four concurrent options
Read_only: update cannot be located through the cursor, and there is no lock in the rows that make up the result set.
Optimistic with values: Optimistic Concurrency Control is a standard part of transaction control theory. Optimistic Concurrency control is used in this case. In the interval between opening the cursor and updating the row, there is only a small chance for the second user to update a row. When a cursor is opened with this option, there is no lock to control the rows, which will help maximize its processing capability. If you try to modify a row, the current value of the row is compared with the value obtained from the last row extraction. If any value changes, the server will know that the other person has updated the row and will return an error. If the value is the same, the server executes the modification.
Choose this concurrency option renxiao without any technical support t Wei Cheng jiu Yao Yun Xin yi s t straw sticks to the generation of fans >>??pain =}%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%? BR> optimistic with row versioning: this optimistic concurrency control option is based on Row version control. Use row version control. The table must have a version identifier, which can be used by the server to determine whether the row is changed after the cursor is read. In SQL Server, this performance is provided by the timestamp data type. It is a binary number that indicates the relative sequence of changes in the database. Each database has a global current timestamp value: @ dbts. Every time you change a row with a timestamp column in any way, SQL Server first stores the current @ dbts value in the timestamp column, and then adds the value of @ dbts. If

Tables with timestamp columns are recorded as rows. The server can compare the current timestamp value of a row with the timestamp value stored during the last extraction to determine whether the row has been updated. The server does not need to compare the values of all columns. You only need to compare the timestamp column. If the application requires Optimistic Concurrency Based on Row Version Control for tables without a timestamp column, the cursor is optimistic concurrency control based on the value by default.
Scroll locks
This option implements pessimistic concurrency control. In pessimistic concurrency control, when the row of the database is read into the cursor result set, the application attempts to lock the row of the database. When a server cursor is used, an update lock is placed on the row when it is read into the cursor. If the cursor is opened in the transaction, the update lock of the transaction will be kept until the transaction is committed or rolled back. When the next row is extracted, the cursor lock will be removed. If the cursor is opened outside the transaction, the lock is discarded when the next row is extracted. Therefore, whenever you need full pessimistic concurrency control, the cursor should be opened in the transaction. The update lock prevents any other task from obtaining the update lock or exclusive lock, thus preventing other tasks from updating the row. However, the update lock does not prevent the shared lock, so it does not prevent other tasks from reading rows, unless the second task also requires reading with the update lock.
Scroll lock
Based on the lock prompts specified in the SELECT statement defined by the cursor, these cursor concurrency options can generate a scroll lock. The scroll lock is obtained on each row during extraction and is kept until the next extraction or cursor is closed. The first occurrence prevails. During the next extraction, the server obtains the scroll lock for the Newly Extracted row and releases the scroll lock of the last extracted row. The rolling lock is independent of the transaction lock and can be kept after a commit or rollback operation. If the option to close the cursor when submitting is off, the commit statement does not close any opened cursor, and the scroll lock is retained until it is committed to maintain isolation of the extracted data.
The type of the obtained scroll lock depends on the cursor concurrency option and the lock prompt in the SELECT statement of the cursor.
Lock prompt read-only optimistic value optimistic row version control lock
No prompt not locked Update Not locked
Nolock not locked
Holdlock shared sharing update
Updlock error Update
Tablockx error not locked Update Not locked
Other unlocked and unlocked updates
* Specifying the nolock prompt will make the table with the specified prompt read-only in the cursor.
16. Use profiler to track the query, obtain the time required for the query, and locate the SQL problem. Use the index optimizer to optimize the index.
17. Pay attention to the difference between Union and Union all. Good union all
18. Use distinct unless necessary. Similar to union, it slows down the query. Duplicate records are no problem in the query.
19. Do not return unwanted rows or columns during query.

20. Use sp_configure 'query Governor cost limit 'or set query_governor_cost_limit to limit the resources consumed by the query. When the resource consumed by the evaluation query exceeds the limit, the server automatically cancels the query and kills the query before the query. Set locktime: Set the lock time.

21. Use select Top 100/10 percent to limit the number of rows returned by the user or set rowcount to limit the rows to be operated.
22. Before SQL2000, do not use the following words: "Is null", "<> ","! = ","!> ","! <"," Not "," not exists "," not in "," not like ", and" like '% 100' ", because they do not leave the index and are all table scans. Do not add a function to the column name in the WHERE clause, such as convert and substring. If a function is required, create a computed column and then create an index. you can also change the syntax of where substring (firstname,) = 'M' to where firstname like'm % '(index scan). You must separate the function from the column name. In addition, the index cannot be too large or too large. Not in scans the table multiple times and uses exists, not exists, in, left Outer Join instead, especially the left join. exists is faster than in, and the slowest operation is not. if the column value is null, its index does not work in the past. Now the 2000 optimizer can process it. The same is null, "not", "not exists", "not in" can optimize her, but "<>" cannot be optimized, and no index is used.
23. Use query analyzer to check the SQL statement query plan and evaluate and analyze whether the SQL statement is optimized. Generally, 20% Code It occupies 80% of the resources, and our optimization focuses on these slow points.
24. If the in or query is not indexed, use the display statement to specify the index:
Select * From personmember (Index = ix_title) Where processid in ('male', 'female ')
25. Pre-calculate the results to be queried and place them in the table. Select the results when querying. This was the most important method before sql7.0. For example, hospital hospitalization fee calculation.
26. Appropriate indexes can be used for Min () and max.
27. There is a principle in the database that the code is closer to the data, the better. Therefore, the default is preferred, Which is rules, triggers, and constraint (constraints such as "check" check "unique ......, The maximum length of the data type, etc. are constraints), procedure. This not only requires low maintenance work, high programming quality, and fast execution speed.

28. If you want to insert a large binary value to the image column, use the stored procedure. Do not insert the value using an embedded insert Statement (whether Java is used or not ). In this way, the application first converts the binary value to a string (twice the size), and then converts it to a binary value after the server receives the character. The stored procedure does not have these actions:
Method: Create procedure p_insert as insert into table (fimage) values (@ image ),
Call this stored procedure at the front end to pass in binary parameters, which significantly improves the processing speed.

29. Between is faster in some cases than in, and between can locate the range based on the index faster. Use the query optimizer to see the difference.
Select * From chineseresume where title in ('male', 'female ')
Select * From chineseresume where between 'male' and 'femal'
Is the same. Because in may be more than once, it may be slower sometimes.

30. If it is necessary to create an index for a global or local temporary table, it may increase the speed, but not necessarily because the index also consumes a lot of resources. Its creation is the same as that of the actual table.

31. Do not create useless things, such as wasting resources when generating reports. Use it only when necessary.
32. The or clause can be divided into multiple queries and connected to multiple queries through Union. Their speed is only the same as whether to use a cable
If Union indexes are required for queries, Union all is more efficient. If multiple or statements are not used for queries, rewrite them to the form of union and try to match the indexes. Whether or not indexes are used in a key issue.
33. Use a view as little as possible, which is less efficient. Operations on a view are slower than operations on a table. You can replace it with stored procedure. In particular, do not use nested views. nested views increase the difficulty of searching for original data. Let's look at the essence of the View: it is an optimized SQL statement stored on the server that has produced a query plan. When retrieving data from a single table, do not use a view pointing to multiple tables. Read data directly from the view that only contains the table. Otherwise, unnecessary overhead is added, the query is disturbed. to speed up View query, MSSQL adds the View index function.
34. Do not use distinct or order by unless necessary. These actions can be executed on the client. They increase additional overhead. This is the same as Union and Union all.
Select top 20 Ad. companyName, comid, position, AD. referenceid, worklocation,
Convert (varchar (10), Ad. postdate, 120)
As postdate1, workyear, degreedescription
From jobcn_query.dbo.companyad_query ad
Where referenceid
In ('jcnad00329667 ', 'jcnad132168', 'jcnad00337748 ', 'jcnad00338345', 'jcnad00333138 ', 'jcnad00303570 ',
'Jcnad00303569 ', 'jcnad00303568', 'jcnad00306698 ', 'jcnad00231935', 'jcnad00231933 ', 'jcnad00254567 ',
'Jcnad00254585 ', 'jcnad00254608', 'jcnad00254607 ', 'jcnad00258524', 'jcnad00332379', 'jcnad00268618 ',
'Jcnad00279196 ', 'jcnad00268613 ')
Order by postdate DESC

35. In the post-in nominal value list, place the most frequent values at the beginning and the least value at the end to reduce the number of judgments.

36. When select into is used, it locks the system table (sysobjects, sysindexes, etc.) and blocks access from other connections. When creating a temporary table, use the show statement instead of select.
Drop table t_lxh
Begin tran
Select * into t_lxh from chineseresume where name = 'xyz'
-- Commit
In another connection, select * From sysobjects.
Select into locks the system table, and create table also locks the system table (whether it is a temporary table or a system table ). So never use it in things !!! In this case, use real tables or temporary table variables for temporary tables that are frequently used.
37. Generally, redundant rows can be removed before group by having clauses, so try not to use them for row removal. Their execution sequence should be optimal as follows: Select WHERE clause Selects all appropriate rows, group by is used to group statistical rows, and having clause is used to remove redundant groups. In this way, the consumption of group by having is small, and queries are fast. Grouping and having large data rows consumes a lot of resources. If the purpose of group by is not to include computing, but to group, it is faster to use distinct.
41. Updating multiple records at a time is faster than updating multiple records at a time, that is, batch processing is good.
42. Use less temporary tables and replace them with result sets and table variables. Table variables are better than temporary tables.
43. In SQL2000, calculated fields can be indexed. The following conditions must be met:
A. The expression of calculated fields is definite.
B. Data Types of text, ntext, and image cannot be used.
C. The following options must be prepared:
Ansi_nulls = on, ansi_paddings = on ,.......
44. Try to put data processing on the server to reduce network overhead, such as using stored procedures. Stored procedures are compiled, optimized, organized into an execution plan, and stored in the database as SQL statements. They are a collection of control flow languages and are fast. You can use a temporary stored procedure to execute dynamic SQL statements repeatedly. This process (temporary table) is stored in tempdb.
In the past, because SQL server did not support complex mathematical computing, it had to put this job on another layer to increase network overhead. SQL2000 supports udfs and now supports complex mathematical computing. the return value of a function is not too large, which is costly. User-Defined Functions consume a large amount of resources like the cursor. If a large result is returned, the stored procedure is used.
45. Do not use the same function repeatedly in one sentence, waste resources, and put the result in a variable before calling it faster.
46. The efficiency of select count (*) is low. Try to change the method while exists is fast. Note the differences:
Select count (field of null) from table and select count (field of not null) from table
The returned values are different !!!
47. When the server has enough memory, the number of preparation threads = maximum number of connections + 5, which can maximize the efficiency;
Otherwise, use the number of prepared threads <maximum number of connections to enable the SQL Server thread pool. If the number is equal to the maximum number of connections + 5, the performance of the server is seriously damaged.
48. Access your table in a certain order. If you lock table A and table B first, lock them in this order in all stored procedures. If you first lock table B in a stored procedure and then lock Table A, this may
A deadlock may occur. If the lock sequence is not designed in detail in advance, it is difficult to find deadlocks.

49. Monitor the load of the corresponding hardware through SQL Server Performance Monitor
memory: Page faults/sec counter
if this value increases occasionally, indicates that there was thread competition memory at that time. If it continues high, memory may be the bottleneck.
process:
1.% DPC time indicates the percentage of services received and provided by the processor during the sample interval using the deferred program call (DPC. (DPC is running at a lower priority interval than the standard interval ). Because DPC is executed in privileged mode, the percentage of DPC time is part of the privileged time percentage. These time values are calculated separately and are not part of the total number of interval values. This total number shows the average busy hours as the percentage of instance time.
2.% processor time counter
If the value of this parameter exceeds 95%, the bottleneck is the CPU. You can consider adding a processor or changing a faster processor.
3.% privileged time indicates the percentage of idle processor time used in privileged mode. (Privileged mode is a processing mode designed for operating system components and operating hardware drivers. It allows direct access to hardware and all memory. Another mode is the user mode. It is a finite processing mode designed for applications, Environment subsystems, and integer subsystems. The operating system converts the application thread to the privileged mode to access the Operating System Service ). The privileged time % includes the time when the service is interrupted and the DPC is provided. The high privileged time ratio may be caused by a large number of failed device intervals. This counter displays the average busy hours as part of the sample time.
4.% USER time indicates CPU-consuming database operations, such as sorting and executing Aggregate functions. If the value is very high, you can consider adding an index. Try to use simple table join and horizontally split large tables to reduce the value.

physical disk: curretn disk queue length counter
the value shall not exceed 1.5 of the number of disks ~ 2 times. To improve performance, you can add disks.
sqlserver: cache hit ratio counter
the higher the value, the better. If the duration is lower than 80%, consider increasing the memory. Note that the value of this parameter is accumulated after SQL Server is started. Therefore, after running for a period of time, this value cannot reflect the current value of the system.
40. Analyze select emp_name form employee where salary> 3000 in this statement, if salary is of the float type, the optimizer optimizes it to convert (float, 3000 ), because 3000 is an integer, we should use 3000.0 during programming, instead of waiting for the DBMS to convert at runtime. Conversion of the same character and integer data.
41. query Association and write sequence
select. personmemberid, * From chineseresume A, personmember B where
personmemberid = B. referenceid and. personmemberid = 'jcnprh1_1'
(A = B, B = 'number')
select. personmemberid, * From chineseresume A, personmember B where
. personmemberid = B. referenceid and. personmemberid = 'jcnprh1_1'
and B. referenceid = 'cnprh00001'
(A = B, B = 'number', A = 'number')
select. personmemberid, * From chineseresume A, personmember B where
B. referenceid = 'jcnprh1_1 'and. personmemberid = 'jcnprh1_1'
(B = 'number', A = 'number')

42. (1) if the owner code then is not entered
code1 = 0
code2 = 9999
else
code1 = code2 = owner code
end if
the SQL statement is:
select owner name from p2000 where owner code >=: code1 and owner code <=: code2
(2) if no owner code then is entered
select owner name from p2000
else
code = owner code
select owner code from p2000 where owner code =: code
end if
the first method only uses one SQL statement, and the second method uses two SQL statements. When no owner code is entered, the second method is obviously more efficient than the first method because it has no restrictions. When the owner code is entered, the second method is still more efficient than the first method. It not only lacks one restriction condition, but also is the fastest query operation because of equality. Do not worry about writing programs.

43. The new method for querying pages in jobcn is as follows: Use the performance optimizer to analyze performance bottlenecks.
In terms of network speed, the following methods are effectively optimized. If it is on the CPU or memory, it is better to use the current method. Please differentiate the following methods, indicating that the smaller the index, the better.
Begin
Declare @ local_variable table (FID int identity (1, 1), referenceid varchar (20 ))
Insert into @ local_variable (referenceid)
Select top 100000 referenceid from chineseresume order by referenceid
Select * From @ local_variable where FID> 40 and FID <= 60
End
And
Begin
Declare @ local_variable table (FID int identity (1, 1), referenceid varchar (20 ))
Insert into @ local_variable (referenceid)
Select top 100000 referenceid from chineseresume order by updatedate
Select * From @ local_variable where FID> 40 and FID <= 60
End
Different

Begin
Create Table # temp (FID int identity (1, 1), referenceid varchar (20 ))
Insert into # temp (referenceid)
Select top 100000 referenceid from chineseresume order by updatedate
Select * from # temp where FID> 40 and FID <= 60
Drop table # temp
End