Summary of past work: Common SQL statements and DataBase Query Optimization

It's rare to have time today. I suddenly remembered taking notes from my previous work and remembering the past. At the same time, I sorted out some of the past, which may be just a little thing. regardless of the quality of my work, it may be more of an experience and a meaningful experience for me.

I can't help but feel deeply when I think of the young and promising person who just came to Beijing. Some things and experiences are just a kind of growth.

If you don't talk much about it, simply use the SQL statement:

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SQL Server:
Select * into B from a where 1 = 2

Oracle & MYSQL:
Create Table B as select * from a where 1 = 2

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SQL statement to directly copy data from a table to a new table

Table A structure is used as follows:
Insert into a select * from B

If the structure of Table A does not exist, it is used as follows:
Select * Into A from B

This is the use of sqlserver, but there are other Oracle, the following is the use of Oracle

Table A structure is used as follows:
Insert into a select * from B

If the structure of Table A does not exist, it is used as follows:
Create Table A as select * from B

Difference between Union and Union all:

In the database,UnionAndUnion allThe keywords combine the two results into one, but the two are different in terms of usage and efficiency.

UnionDuplicate records are filtered out after the table link is established. Therefore, after the table link is established, the generated result set is sorted, and duplicate records are deleted before the results are returned.

For example:
Select * From test_union1
Union
Select * From test_union2
This SQL statement extracts the results of two tables at run time, sorts and deletes duplicate records using the sorting space, and finally returns the result set. If the table has a large amount of data, it may cause disk sorting.
WhileUnion allSimply merge the two results and then return them. In this way, if duplicate data exists in the two returned result sets, the returned result sets will contain duplicate data.
In terms of efficiency, Union all is much faster than Union. Therefore, if you can confirm that the two results of the merge do not contain duplicate data, use Union all, as shown below:
Select * From test_union1
Union all
Select * From test_union2

There are two basic rules for query result sets using union:

1. The columns and columns in all queries must be in the same order.

2. Data type must be compatible

Database Query Optimization:

1. To optimize the query, try to avoid full table scanning. First, consider creating an index on the columns involved in where and order.

2. Try to avoid null value determination on the field in the WHERE clause. Otherwise, the engine will discard the index and perform full table scanning, for example:

Select ID from t where num is null

You can set the default value 0 on num to make sure that the num column in the table does not have a null value, and then query it like this:

Select ID from t where num = 0

3. Try to avoid using it in the WHERE clause! = Or <> operator. Otherwise, the engine will discard the index for full table scanning.

4. Try to avoid using or in the WHERE clause to connect to the condition. Otherwise, the engine will discard the index and perform full table scanning, for example:

Select ID from t where num = 10 or num = 20

You can query it as follows:

Select ID from t where num = 10 Union all Select ID from t where num = 20

5. Use in and not in with caution. Otherwise, a full table scan may occur, for example:

Select ID from t where num in (1, 2, 3)

For continuous values, you can use between instead of in:

Select ID from t where num between 1 and 3

6. The following query will also cause a full table scan:

Select ID from t where name like '% ABC %'

To improve efficiency, you can consider full-text search.

7. If a parameter is used in the WHERE clause, a full table scan is performed. BecauseSQLLocal variables are resolved only at runtime, but the optimizer cannot postpone the selection of the access plan to runtime; it must be selected at compilation. However, if an access plan is created during compilation, the value of the variable is still unknown and thus cannot be used as an input for index selection. The following statement performs a full table scan:

Select ID from t wherenum = @ num

You can change it to force query to use the index:

Select ID from T with (index name) wherenum = @ num

8. Avoid performing expression operations on fields in the WHERE clause as much as possible. This will cause the engine to discard the use of indexes for full table scanning. For example:

Select ID from t where num/2 = 100

Should be changed:

Select ID from t where num = 100*2

9. Avoid performing function operations on fields in the WHERE clause as much as possible, which will cause the engine to stop using the index for full table scanning. For example:

Select ID from t where substring (name, 1, 3) = 'abc' -- id whose name starts with ABC Select ID from t where datediff (day, createdate, '2017-11-30 ') = 0 -- '2017-11-30' generated ID

Should be changed:

Select ID from t where name like 'abc %'
Select ID from t where createdate> = '2014-11-30 'and createdate <'2014-12-1'

10. do not perform functions, arithmetic operations, or other expression operations on the left side of "=" in the WHERE clause. Otherwise, the system may not be able to correctly use the index.

11. when using an index field as a condition, if the index is a composite index, you must use the first field in the index as the condition to ensure that the system uses the index, otherwise, the index will not be used, and the field order should be consistent with the index order as much as possible.

12. Do not write meaningless queries. If you need to generate an empty table structure:

Select col1, col2 into # T from t where 1 = 0

This type of code will not return any result set, but will consume system resources, should be changed to this:

Create Table # T (...)

13. In many cases, replacing in with exists is a good choice:

Select num from a where num in (select num from B)

Replace the following statement:

Select num from a where exists (select 1 from B where num = A. Num)

14. not all indexes are valid for queries. SQL queries are optimized based on the data in the table. When there is a large number of duplicate data in the index column, SQL queries may not use indexes, for example, if a table contains sex fields, male and female are almost half of each other, indexing sex does not play a role in query efficiency.

15. the more indexes, the better. Although the index can improve the efficiency of the SELECT statement, it also reduces the efficiency of insert and update, because the insert or update statements may recreate the index, therefore, you need to carefully consider how to create an index, depending on the actual situation. It is recommended that the number of indexes in a table be no more than 6. If there are too many indexes, consider whether the indexes on some columns that are not frequently used are necessary.

16. update the clustered index data column should be avoided as much as possible, because the order of the clustered index data column is the physical storage order of the table records. Once the column value changes, the order of the entire table record will be adjusted, it will consume a considerable amount of resources. If the application system needs to frequently update the clustered index data column, consider whether to create the index as a clustered index.

17. use numeric fields whenever possible. If fields containing only numerical information are not designed as numeric fields, this will reduce query and connection performance and increase storage overhead. This is because the engine compares each character in the string one by one during query and connection processing, and only one comparison is required for the number type.

18. try to use varchar/nvarchar instead of Char/nchar, because the first step is to reduce the storage space of the variable-length field, which can save storage space. Secondly, for queries, searching in a relatively small field is obviously more efficient.

19. Do not use select * from t anywhere, replace "*" with a specific field list, and do not return any fields that are not used.

20. Try to use table variables instead of temporary tables. If the table variable contains a large amount of data, note that the index is very limited (only the primary key index ).

21. Avoid frequent creation and deletion of temporary tables to reduce the consumption of system table resources.

22. Temporary tables are not unavailable. Using them appropriately can make some routines more effective. For example, when you need to reference large tables or a data set in common tables repeatedly. However, it is best to use the export table for one-time events.

23. when creating a temporary table, if a large amount of data is inserted at one time, you can use select into instead of create table to avoid creating a large number of logs to increase the speed. If the data volume is small, to ease system table resources, create table first and then insert.

24. if a temporary table is used, you must explicitly delete all temporary tables at the end of the stored procedure. First truncate the table and then drop the table, so that the system table can be locked for a long time.

25. Avoid using a cursor whenever possible, because the efficiency of the cursor is poor. If the cursor operation has more than 10 thousand rows of data, you should consider rewriting.

26. before using the cursor-based or temporary table method, you should first find a set-based solution to solve the problem. The set-based method is generally more effective.

27. Like a temporary table, the cursor is not unavailable. Using a fast_forward cursor for a small dataset is usually better than other row-by-row processing methods, especially when several tables must be referenced to obtain the required data. A routine that includes "sum" in the result set is usually faster than a cursor. If the development time permits, you can try both the cursor-based method and the set-based method to see which method works better.

28. Set nocount on at the beginning of all stored procedures and triggers, and set nocount off at the end. You do not need to send the done_in_proc message to the client after executing each statement of the stored procedure and trigger.

29. Avoid large transaction operations as much as possible to improve the system concurrency capability.

30. Avoid returning a large amount of data to the client whenever possible. If the data volume is too large, consider whether the corresponding requirements are reasonable.

Let's just leave a souvenir. I have experienced, worked hard, succeeded, or failed a young man. In short, I have never regretted it.