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Detailed introduction of graphic code of MySql Sql optimization techniques
Detailed introduction of graphic code of MySql Sql optimization techniques
This article mainly introduces the sharing of MySql Sql optimization skills. It is very good and has reference value. Friends in need can refer to it
One day I found a SQL with inner join, although the execution speed is not very slow. (0.1-0.2), but the ideal speed is not reached. The two tables are related, and the related fields are primary keys, and the queried fields are unique indexes.
sql is as follows:
SELECT p_item_token.*, p_item.product_type FROM p_item_token INNER JOIN p_item ON p_item.itemid = p_item_token.itemid WHERE p_item_token.token ='db87a780427d4d02ba2bd49fac8xxx';
In the table p_item_token itemid is the primary key and token is the unique index. itemid in p_item is the primary key
According to the ideal speed, it should be around 0.03s. But the actual value is about 0.2, which is a lot slower.
EXPLAIN directly to see the plan
EXPLAIN SELECT p_item_token.*, p_item.product_type FROM p_item_token INNER JOIN p_item ON p_item.itemid = p_item_token.itemid WHERE p_item_token.token = 'db87a780427d4d02ba2bd49fac8xxx';
Result:
Pay attention to the big red above frame. There are 2w pieces of data in the p_item table, so this is a full table scan.
Not normal.
Add show warnings and take a look. Note: In some cases SHOW WARNINGS will have no results. I don't know the reason yet. It is recommended to run with a local test database.
EXPLAIN SELECT p_item_token.*, p_item.product_type FROM p_item_token INNER JOIN p_item ON p_item.itemid = p_item_token.itemid WHERE p_item_token.token = 'db87a780427d4d02ba2bd49fac8xxx'; SHOW WARNINGS;
Result 2 shows code=1003. There is a sql statement behind it. This statement is the final statement executed by MySQL after rewriting the SQL statement we entered according to the rules.
/* select#1 */
SELECT
'0000eb612d78407a91a9b3854ffffffff' AS `itemid`, /*注:直接按主键把值查出来了*/
'db87a780427d4d02ba2bd49fac8cf98b' AS `token`,
'2016-12-16 10:46:53' AS `create_time`,
'' AS `ftoken`,
`p_db`.`p_item`.`product_type` AS `product_type`
FROM
`p_db`.`p_item_token`
JOIN `p_db`.`p_item`
WHERE
(
(
CONVERT (
`p_db`.`p_item`.`itemid` USING utf8mb4
) = '0000eb612d78407a91a9b3854fffffff'
)
)Weird. Why is there CONVERT in Where? We know that if there is a function on the left side of the equation in the where condition, that is, the field to be queried, it will cause slowness. (My understanding: It is slow because the index is no longer used. The value of the index is the original value, but the processed value is used in this condition.)
Pay attention to this function, means to change the itemid The encoding of this column is converted to utf8mb4. In other words, the encoding of this column is not utf8mb4!
Open the table and change the encoding of the itemid column in both tables to utf8. Run explain again.
Judging from the interpretation results, there is no problem.
Look at the statement in result 2:
/* select#1 */ SELECT '0000eb612d78407a91a9b3854fffffff' AS `itemid`, 'db87a780427d4d02ba2bd49fac8cf98b' AS `token`, '2016-12-16 10:46:53' AS `create_time`, '' AS `ftoken`, 'cxx' AS `product_type` FROM `toy_item_plat`.`p_item_token` JOIN `toy_item_plat`.`p_item` WHERE 1
This select is all constants. Can it be faster?
The execution result is 0.036s. In line with expectations
Experience summary:
explain You can check whether the execution plan meets expectations. If there are large rows, it means that a full table scan has occurred, which will be a performance bottleneck in the future
show warning results, you can see the statement processed by the optimizer. If there is any discrepancy with the original statement, careful comparison and study can reveal the actual problem.
The above is the detailed introduction of the graphic code of MySql Sql optimization skills. For more related content, please pay attention to the PHP Chinese website (www.php.cn)!
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