In order to improve query efficiency in sql query, we often take some measures to optimize the query statement. Some methods summarized below can be referred to if necessary.
1. To optimize the query, full table scan should be avoided as much as possible. First, you should consider building indexes on the columns involved in where and order by.
2. Try to avoid the null value judgment of the field in the where clause, otherwise the engine will give up the use of the index and perform a full table scan, such as:
select id from t where num is null
You can set the default value of 0 on num to ensure that There is no null value in the num column in the table, and then query like this:
select id from t where num=0
3. Try to avoid using the != or <> operator in the where clause, otherwise the engine will give up the use of the index and perform a full table scan.
4. Try to avoid using or to join conditions in the where clause, otherwise the engine will give up using the index and perform a full table scan, such as:
select id from t where num=10 or num=20
You can query like this:
select id from t where num=10
union all
select id from t where num=20
5. In and not in should also be used with caution, otherwise it will lead to a full table scan, such as:
select id from t where num in(1,2,3)
For continuous values, if you can use between, do not use in:
select id from t where num between 1 and 3
6. The following query will also result in a full table scan:
select id from t where name like '%abc%'
7. The expression operation on the field in the where clause should be avoided as much as possible, which will cause the engine to give up the use of the index and perform a full table scan. For example:
select id from t where num/2=100
should be changed to:
select id from t where num=100*2
8. The function operation on the field in the where clause should be avoided as much as possible, which will cause the engine to give up the use of the index and perform a full table scan. Such as:
select id from t where substring(name,1,3)='abc'--name starts with abc id
should be changed to:
select id from t where name like 'abc%'
9. Do not perform functions, arithmetic operations or other expression operations on the left side of the "=" in the where clause, otherwise the system may not be able to use the index correctly.
10. When using an index field as a condition, if the index is a composite index, the first field in the index must be used as a condition to ensure that the system can use the index,
otherwise the index will not be used and should be As much as possible, make the field order consistent with the index order.
11. Don't write some meaningless queries. If you need to generate an empty table structure:
select col1,col2 into #t from t where 1=0
This kind of code will not return any result set, but it will consume system resources and should be changed Like this:
create table #t(…)
12. Often it is a good choice to replace in with exists:
select num from a where num in(select num from b)
replace with the following statement:
select num from a where exists(select 1 from b where num=a.num )
13. Not all indexes are valid for queries. SQL optimizes queries based on the data in the table. When a large amount of data in the index column is repeated, the SQL query may not use the index.
For example, there are fields sex, male, The female is almost half and half, so even if an index is built on the sex, it will not affect the query efficiency.
14. The more indexes the better, the index can certainly improve the efficiency of the corresponding select, but it also reduces the efficiency of insert and update,
because the index may be rebuilt during insert or update, so how to build an index needs to be carefully considered. As the case may be.
The number of indexes in a table should not exceed 6. If there are too many indexes, you should consider whether it is necessary to build indexes on some infrequently used columns.
15. Try to use numeric fields. If the fields only contain numeric information, try not to design them as character fields, which will reduce the performance of query and connection and increase the storage overhead.
This is because the engine compares each character of the string one by one when processing queries and joins, whereas only one comparison is required for numbers.
16. Use varchar instead of char as much as possible, because first of all, the storage space of variable-length fields is small, which can save storage space.
Secondly, for queries, the search efficiency in a relatively small field is obviously higher.
17. Do not use select * from t anywhere, replace "*" with a list of specific fields, and do not return any fields that are not used.
18. Avoid frequent creation and deletion of temporary tables to reduce the consumption of system table resources.