我目前在 mySQL 的“视图”中收到附加警告，知道这意味着什么吗？

Question

Warning: #1292 Truncated incorrect DOUBLE value: "

错误：警告：#1292 截断不正确的 DOUBLE 值：“

我的“视图”的结构如下：

# | Name    | Type
1  id1       varchar(255)
2  id2       varchar(255)
3  category1 varchar(255)
4  category2 varchar(255)
5  category3 varchar(255)
6  id2name   varchar(255)
7  date1     date
8  date2     date
9  name1     varchar(255)
10 name2     varchar(255)
11 name3     varchar(255)
12 category4 varchar(255)
13 level1     int(11)
14 level2     int(11)
15 levelflex  varchar(255)
16 category5  varchar(255)
17 category6  varchar(255)
18 category7  varchar(21)

SQL 代码：

SELECT
`x`.`id1` AS `id1`,
`x`.`id2` AS `id2`,
`x`.`category1` AS `category1`,
`x`.`category2` AS `category2`,
`x`.`category3` AS `category3`,
`x`.`id2name` AS `id2name`,
`x`.`date1` AS `date1`,
`x`.`date2` AS `date2`,
`x`.`name1` AS `name1`,
`x`.`name2` AS `name2`,
`x`.`name3` AS `name3`,
`x`.`category4` AS `category4`,
`x`.`level1` AS `level1`,
`x`.`level2` AS `level2`,
`x`.`levelflex` AS `levelflex`,
`x`.`category5` AS `category5`,
`x`.`category6` AS `category6`,
`x`.`category7` AS `category7`FROM
(
    (
    SELECT
        `r`.`id1` AS `id1`,
        `d`.`id2` AS `id2`,
        `m`.`subcategory` AS `category1`,
        `n`.`subcategory` AS `category2`,
        `r`.`category3` AS `category3`,
        `d`.`id2name` AS `id2name`,
        `r`.`date1` AS `date1`,
        `d`.`date2` AS `date2`,
        `r`.`name1` AS `name1`,
        `r`.`name2` AS `name2`,
        `r`.`name3` AS `name3`,
        `r`.`category4` AS `category4`,
        `r`.`level1` AS `level1`,
        `d`.`level1` AS `level2`,
        `d`.`level1flex` AS `levelflex`,
        `r`.`category5` AS `category5`,
        `r`.`category6` AS `category6`,
        CAST(
            rank() over(
            PARTITION BY `r`.`id1`
        ORDER BY CASE WHEN
            `m`.`subcategory` = `n`.`subcategory` AND `r`.`level1` = `d`.`level1` THEN 1 WHEN `m`.`subcategory` = `n`.`subcategory` AND `r`.`level1` = `d`.`levelflex` THEN 2 WHEN `m`.`subcategory` <> `n`.`subcategory` AND `r`.`level1` = `d`.`level1` THEN 3 WHEN `m`.`subcategory` <> `n`.`subcategory` AND `r`.`level1` = `d`.`levelflex` THEN 4
        END,
        `d`.`date2`,
        `r`.`id1`
            ) AS CHAR CHARSET utf8mb4) AS `category7`FROM
        (
            (
                (
                    (
                        (
                            (
                                (
                                    (
                                        `Server`.`table1` `d`
                                    JOIN `Server`.`table2` `r`
                                    ON
                                        (
                                            `d`.`category4` = `r`.`category4` AND(
                                                `d`.`level1` = `r`.`level1` AND `r`.`level1` <> 12 AND `r`.`level1` <> 13 OR SUBSTRING_INDEX(`d`.`levelflex`, ',', 1) = `r`.`level1` AND `r`.`level1` <> 12 AND `r`.`level1` <> 13 OR SUBSTRING_INDEX(`d`.`levelflex`, ',', -1) = `r`.`level1` AND `r`.`level1` <> 12 AND `r`.`level1` <> 13
                                            )
                                        )
                                    )
                                JOIN `Server`.`table3` `p`
                                ON
                                    (
                                        `d`.`id2name` = `p`.`newid2name` OR `d`.`id2name` = `p`.`oldid2name`
                                    )
                                )
                            JOIN `Server`.`table4` `m`
                            ON
                                (
                                    `p`.`newid2name` = `m`.`id2name` OR `p`.`oldid2name` = `m`.`id2name`
                                )
                            )
                        JOIN `Server`.`table5` `h`
                        ON
                            (`r`.`category3` = `h`.`category3`)
                        )
                    JOIN `Server`.`table6` `f`
                    ON
                        (`r`.`id1` = `f`.`id1`)
                    )
                LEFT JOIN `Server`.`table7` `e`
                ON
                    (`f`.`id1` = `e`.`id1`)
                )
            JOIN `Server`.`table8` `n`
            ON
                (
                    (
                        `r`.`date1` >= `h`.`subdate1` AND `e`.`subdate1` = `h`.`subdate1` OR `f`.`subdate2` = `h`.`subdate1` AND `r`.`date1` < `h`.`subdate1`
                    ) AND `h`.`id2name` = `n`.`id2name`
                )
            )
        LEFT JOIN `Server`.`table9` `z`
        ON
            (
                `d`.`id2` = `z`.`id2` AND `r`.`id1` = `z`.`id1`
            )
        )
    WHERE
        `z`.`id2` IS NULL
) `x`LEFT JOIN `Server`.`table10` `y`ON
(
    `x`.`id2` = `y`.`id2` AND `x`.`id1` = `y`.`id1`
)
)WHERE
`y`.`id2` IS NULL

总共 44 行的查询也需要大约 15 秒或更长时间。有什么办法可以优化吗？

我也在尝试将数据从视图传输到表。对此有何建议？

显示创建表：

View	Create View	character_set_client	collation_connection
sampleview	CREATE ALGORITHM=UNDEFINED DEFINER=dbadmin@%SQL SECURITY DEFINER VIEWsampleviewAS selectx.id1 AS id1,x.`r...	utf8mb4	utfmb4_unicode_ci

解释选择...：

id	select_type	table	type	possible_keys	key	key_len	ref	rows	Extra
1	PRIMARY	derived2	ALL	NULL	NULL	NULL	NULL	251497948917600
1	PRIMARY	y	ALL	NULL	NULL	NULL	NULL	1	Using where; Using join buffer(flat, BNL join)
2	DERIVED	d	ALL	NULL	NULL	NULL	NULL	106	Using temporary
2	DERIVED	f	ALL	PRIMARY	NULL	NULL	NULL	115	Using join buffer(flat,BNL join)
2	DERIVED	e	eq_ref	PRIMARY	PRIMARY	767	Server.f.id1	1
2	DERIVED	r	eq_ref	PRIMARY	PRIMARY	767	Server.f.id1	1	Using where
2	DERIVED	z	ALL	NULL	NULL	NULL	NULL	1	Using where; Using join buffer (flat, BNL join)
2	DERIVED	p	ALL	NULL	NULL	NULL	NULL	140	Using where; Using join buffer (incremental, BNL join)
2	DERIVED	m	ALL	NULL	NULL	NULL	NULL	198	Using where; Using join buffer (incremental, BNL join)
2	DERIVED	n	ALL	NULL	NULL	NULL	NULL	198	Using join buffer (flat, BNL join)
2	DERIVED	h	ALL	NULL	NULL	NULL	NULL	3759	Using where; Using join buffer (incremental, BNL join)

Answer 1

有 251 个 trillion 行，我怀疑该查询包含意外的“交叉连接”。在VIEW 和VIEW 的使用中检查所有JOIN。

另外，请注意AND 和OR 之间的优先规则。

OR 通常是性能杀手。

（同时，我没有看到关于错误 1292 的任何线索。）

其中一些复合索引可能会有所帮助：

y:  INDEX(id2,  id1)
r:  INDEX(category4)
d:  INDEX(category4)
m:  INDEX(id2name,  subcategory)
n:  INDEX(id2name,  subcategory)
p:  INDEX(newid2name,  oldid2name)
h:  INDEX(category3,  subdate1, id2name)
f:  INDEX(id1,  subdate2)
e:  INDEX(id1,  subdate1)
z:  INDEX(id2,  id1)

部分性能优势在于它们中的大多数是“覆盖”。如需进一步讨论，请为基础表提供SHOW CREATE TABLE 和EXPLAIN SELECT...