19 MySQL database optimization methods

      So in order to cope with the increasing traffic , We need to be right about mysql Make corresponding countermeasures , Further optimization mysql To achieve the desired results .

1、EXPLAIN

do MySQL Optimize , We need to make good use of EXPLAIN see SQL Implementation plan .

Here's a simple example , mark （1、2、3、4、5） The data we need to focus on ：

type Column , Connection type . A good SQL The statement must at least reach range Level . Put an end to it all Level .

key Column , Index name used . If index is not selected , The value is NULL. You can use forced indexing .

key_len Column , Index length .

rows Column , Number of scanning lines . This is an estimate .

extra Column , Detailed instructions . Be careful , Common unfriendly values , as follows ：Using filesort,Using temporary.

2、SQL In the sentence IN Should not contain too many values

MySQL about IN The corresponding optimization has been made , the IN All constants in are stored in an array , And this array is ordered . But if there are more values , The consumption is also relatively large . Another example is ：select id from t where num in(1,2,3) For continuous values , It works between Don't use in 了 ; Or use connections to replace .

3、SELECT The statement must indicate the field name

SELECT* Add a lot of unnecessary consumption （CPU、IO、 Memory 、 network bandwidth ）; Increased the possibility of using overlay indexes ; When the table structure changes , Front break also needs to be updated . So the request is directly in select Followed by the field name .

4、 When only one piece of data is needed , Use limit 1

This is to make EXPLAIN in type Column reach const type

5、 If the sort field does not use an index , Just sort as little as possible

6、 If there is no index for other fields in the constraint , Use less as far as possible or

or In the fields on both sides , If there is a non index field , Other conditions are not index fields , Will cause the query not to go through the index . A lot of times union all Or is it union（ When necessary ） Instead of “or” Will get better results .

7、 As far as possible with union all Instead of union

union and union all The main difference is that the former needs to merge the result set before uniqueness filtering , This involves sorting , A large increase in CPU operation , Increase resource consumption and delay . Of course ,union all The precondition is that there is no duplicate data in the two result sets .

8、 Don't use ORDER BY RAND()

select id from `dynamic` order by rand() limit 1000;

above SQL sentence , It can be optimized to ：

select id from `dynamic` t1 join (select rand() * (select max(id) from `dynamic`) as nid) t2 on t1.id > t2.nidlimit 1000;

9、 distinguish in and exists、not in and not exists

select * from surface A where id in (select id from surface B)

above SQL Statement equivalent

select * from surface A where exists(select * from surface B where surface B.id= surface A.id)

distinguish in and exists Mainly caused the change of driving sequence （ This is the key to performance change ）, If it is exists, Then take the outer table as the driving table , Be interviewed first , If it is IN, Then execute the subquery first . therefore IN It is suitable for the case of large exterior and small interior surface ;EXISTS It is suitable for the case of small appearance and large inner surface .

About not in and not exists, Recommended not exists, It's not just about efficiency ,not in There may be a logical problem . How to write an alternative efficiently not exists Of SQL sentence ？

primary SQL sentence ：

select colname … from A surface where a.id not in (select b.id from B surface )

efficient SQL sentence ：

select colname … from A surface Left join B surface on where a.id = b.id where b.id is null

The result set is shown in the figure below ,A The watch is not in B Table data ：

10、 Use reasonable paging methods to improve the efficiency of paging

select id,name from product limit 866613, 20

Use the above SQL When the statement is paginated , Maybe someone will find out , With the increase of table data , Use it directly limit Paging queries will be slower and slower .

The optimization method is as follows ： You can take the maximum number of lines on the previous page id, And then according to this biggest id To limit the starting point of the next page . Than in this column , The biggest one on the previous page id yes 866612.SQL It can be written as follows ：

select id,name from product where id> 866612 limit 20

11、 Segmented query

In some user selection pages , Maybe some users choose too large a time range , Causing slow queries . The main reason is that there are too many scan lines . It's time to go through the program , Query in sections , Loop traversal , Combine the results for presentation .

As shown in the figure below SQL sentence , Segment query can be used when the number of scanned rows is more than one million ：

12、 To avoid the where Field in the clause null Value judgement

about null The engine will give up using the index and scan the whole table .

13、 Not recommended % Prefix fuzzy query

for example LIKE“%name” perhaps LIKE“%name%”, This kind of query will lead to index failure and full table scanning . But you can use LIKE “name%”.

How to query %name%？

As shown in the figure below , Although give to secret Field added index , But in explain It turns out that it didn't use ：

So how to solve this problem , answer ： Use full text indexing .

We often use select id,fnum,fdst from dynamic_201606 where user_name like '%zhangsan%'; . Such a statement , Ordinary index can't satisfy the query demand . Fortunately, in MySQL in , There is a full-text index to help us .

To create a full-text index SQL Grammar is ：

ALTER TABLE `dynamic_201606` ADD FULLTEXT INDEX `idx_user_name` (`user_name`);

Using full-text indexing SQL The sentence is ：

select id,fnum,fdst from dynamic_201606 where match(user_name) against('zhangsan' in boolean mode);

Be careful ： Before you need to create a full-text index , Please contact the DBA Determine if you can create . At the same time, we need to pay attention to the difference between the writing method of the query statement and the common index .

14、 To avoid the where The clause performs an expression operation on the field

such as ：

select user_id,user_project from user_base where age*2=36;

In the field on the line of arithmetic operations , This will cause the engine to give up using indexes , It is suggested to change it to ：

select user_id,user_project from user_base where age=36/2;

15、 Avoid implicit type conversion

where Clause column Type conversion when the type of the field is inconsistent with the type of the parameter passed in , It is suggested that where Parameter types in .

16、 For federated indexes , Follow the leftmost prefix rule

For example, an index contains fields id、name、school, It can be used directly id Field , It's fine too id、name In this order , however name;school Can't use this index . So when you create a union index, you must pay attention to the order of index fields , Common query fields are placed at the top .

17、 You can use when necessary force index To force the query to go to an index

sometimes MySQL The optimizer takes the index it thinks appropriate to retrieve SQL sentence , But maybe the index it uses is not what we want . At this point, it can be used forceindex To force the optimizer to use the index that we set .

18、 Note the range query statement

For federated indexes , If there are scope queries , such as between、>、< Under equal conditions , It will invalidate the following index fields .

19、 About JOIN Optimize

LEFT JOIN A The table is the driving table ,INNER JOIN MySQL It will automatically find the table with less data to drive the table ,RIGHT JOIN B The table is the driving table .

Be careful ：

1）MySQL There is no full join, It can be solved in the following ways ：

select * from A left join B on B.name = A.namewhere B.name is nullunion allselect * from B;

2） Use as much as possible inner join, avoid left join：

The tables participating in the union query are at least 2 A watch , In general, there are different sizes . If the connection is inner join, In the absence of other filter conditions MySQL Will automatically select the small table as the driving table , however left join In the selection of driving table, we follow the principle of left driving right , namely left join The table on the left is called the drive table .

3） Make good use of indexes ：

The index field of the driven table is used as on Restricted fields for .

4） Use a small watch to drive a large watch ：

It can be seen intuitively from the schematic diagram that if the drive table can be reduced , Reduce the number of loops in nested loops , In order to reduce IO Total amount and CPU The number of operations .

5） Skillfully use STRAIGHT_JOIN：

inner join By MySQL Select driver table , But in some special cases, you need to choose another table as the driving table , Such as the group by、order by etc. 「Using filesort」、「Using temporary」 when .STRAIGHT_JOIN To force the connection order , stay STRAIGHT_JOIN The table name on the left is the drive table , On the right is the driven table . In the use of STRAIGHT_JOIN There is a precondition that the query is an inner join , That is to say inner join. Other links are not recommended STRAIGHT_JOIN, Otherwise, the query result may be inaccurate .

This approach can sometimes reduce 3 Times of time .

above 19 strip MySQL Optimization methods hope to help you oh ~