优化查询，多表连接
Optimizing query, join of many tables
我有一个 table，我需要在其中连接很多不同的 table。数据集有 140 000 条记录。
示例如下：
SELECT SQL_CALC_FOUND_ROWS e.designation
, e.remark
, e.moment
, e.rpm
, e.cycleK
, c.type
, d.description
, a.PAnr
, b.family
, b.articlenrKronhjul
, b.ratio
, a.oiltype
, a.oiltemp
, a.createdBy
, a.createdDate
FROM testdata_test a
, testdata_gear b
, testdata_damcategory c
, testdata_damage d
, testdata_result e
WHERE a.id = e.test_id
AND e.id = d.result_id
AND a.id = b.test_id
AND c.id = d.category_id
ORDER
BY designation asc
LIMIT 0, 10
平均耗时约 1 秒，如何加快速度？
我一直在尝试在某些列上添加一些索引，但没有太大改进。
有人有什么建议吗？
编辑：
这是我的常规和 JSON 格式的查询计划：
+----+-------------+-------+------+---------------------------------------------------+--------------------------+---------+----------------+------+----------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------------------------------------------+--------------------------+---------+----------------+------+----------------------------------------------------+
| 1 | SIMPLE | a | ALL | PRIMARY | NULL | NULL | NULL | 10617 | Using where; Using temporary; Using filesort |
| 1 | SIMPLE | b | ref | TestData_gear_2e06cda4 | TestData_gear_2e06cda4 | 5 | webappdev.a.id | 1 | NULL |
| 1 | SIMPLE | e | ref | PRIMARY,TestData_result_2e06cda4 | TestData_result_2e06cda4 | 4 | webappdev.a.id | 5 | NULL |
| 1 | SIMPLE | d | ref | TestData_damage_b583a629,TestData_damage_57f06544 | TestData_damage_57f06544 | 4 | webappdev.e.id | 1 | NULL |
| 1 | SIMPLE | c | ALL | PRIMARY | NULL | NULL | NULL | 4 | Using where; Using join buffer (Block Nested Loop)|
+----+-------------+-------+------+---------------------------------------------------+--------------------------+---------+----------------+-------+---------------------------------------------------+
5 rows in set (0.00 sec)
| {
"query_block": {
"select_id": 1,
"ordering_operation": {
"using_temporary_table": true,
"using_filesort": true,
"nested_loop": [
{
"table": {
"table_name": "a",
"access_type": "ALL",
"possible_keys": [
"PRIMARY"
],
"rows": 10617,
"filtered": 100,
"attached_condition": "(`webappdev`.`a`.`id` is not null)"
}
},
{
"table": {
"table_name": "b",
"access_type": "ref",
"possible_keys": [
"TestData_gear_2e06cda4"
],
"key": "TestData_gear_2e06cda4",
"used_key_parts": [
"test_id"
],
"key_length": "5",
"ref": [
"webappdev.a.id"
],
"rows": 1,
"filtered": 100
}
},
{
"table": {
"table_name": "e",
"access_type": "ref",
"possible_keys": [
"PRIMARY",
"TestData_result_2e06cda4"
],
"key": "TestData_result_2e06cda4",
"used_key_parts": [
"test_id"
],
"key_length": "4",
"ref": [
"webappdev.a.id"
],
"rows": 5,
"filtered": 100
}
},
{
"table": {
"table_name": "d",
"access_type": "ref",
"possible_keys": [
"TestData_damage_b583a629",
"TestData_damage_57f06544"
],
"key": "TestData_damage_57f06544",
"used_key_parts": [
"result_id"
],
"key_length": "4",
"ref": [
"webappdev.e.id"
],
"rows": 1,
"filtered": 100
}
},
{
"table": {
"table_name": "c",
"access_type": "ALL",
"possible_keys": [
"PRIMARY"
],
"rows": 4,
"filtered": 75,
"using_join_buffer": "Block Nested Loop",
"attached_condition": "(`webappdev`.`c`.`id` = `webappdev`.`d`.`cate
gory_id`)"
}
}
]
}
}
} |
这是我的 CREATE TABLES 和 tables
的计数
mysql> SHOW CREATE TABLE testdata_test;
| testdata_test | CREATE TABLE `testdata_test` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`PAnr` int(11) NOT NULL,
`projectAcc` varchar(20) DEFAULT NULL,
`reportnr` varchar(20) DEFAULT NULL,
`oiltype` varchar(40) DEFAULT NULL,
`oiltemp` int(11) DEFAULT NULL,
`headline1` varchar(40) DEFAULT NULL,
`headline2` varchar(40) DEFAULT NULL,
`testDescription` longtext,
`TestName` varchar(9) DEFAULT NULL,
`createdBy` varchar(6) NOT NULL,
`createdDate` date NOT NULL,
PRIMARY KEY (`id`),
FULLTEXT KEY `test_index_testdescription` (`testDescription`)
) ENGINE=InnoDB AUTO_INCREMENT=14172 DEFAULT CHARSET=utf8 |
1 row in set (0.00 sec)
mysql> SELECT count(*) FROM testdata_test;
+----------+
| count(*) |
+----------+
| 14161 |
+----------+
1 row in set (0.01 sec)
mysql> SHOW CREATE TABLE testdata_gear;
| testdata_gear | CREATE TABLE `testdata_gear` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`family` varchar(20) NOT NULL,
`articlenrKronhjul` int(11) DEFAULT NULL,
`revisionK` varchar(200) DEFAULT NULL,
`articlenrPinjong` int(11) DEFAULT NULL,
`revisionP` varchar(200) DEFAULT NULL,
`ratio` double DEFAULT NULL,
`geardata` varchar(100) DEFAULT NULL,
`remark` varchar(40) DEFAULT NULL,
`test_id` int(11),
PRIMARY KEY (`id`),
KEY `TestData_gear_2e06cda4` (`test_id`),
CONSTRAINT `TestData_gear_test_id_325c2ab6_fk_TestData_test_id` FOREIGN KEY (`
test_id`) REFERENCES `testdata_test` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=14167 DEFAULT CHARSET=utf8 |
mysql> SELECT count(*) FROM testdata_gear;
+----------+
| count(*) |
+----------+
| 14157 |
+----------+
1 row in set (0.01 sec)
| testdata_result | CREATE TABLE `testdata_result` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`designation` varchar(20) NOT NULL,
`remark` varchar(200) DEFAULT NULL,
`moment` double DEFAULT NULL,
`rpm` int(11) DEFAULT NULL,
`cycleK` int(11) DEFAULT NULL,
`test_id` int(11) NOT NULL,
PRIMARY KEY (`id`),
KEY `test_id_result_index` (`test_id`) USING BTREE,
KEY `result_designation_index` (`designation`) USING BTREE,
CONSTRAINT `TestData_result_test_id_5ed0cbc8_fk_TestData_test_id` FOREIGN KEY
(`test_id`) REFERENCES `testdata_test` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=141382 DEFAULT CHARSET=utf8 |
mysql> SELECT count(*) FROM testdata_result;
+----------+
| count(*) |
+----------+
| 141323 |
+----------+
1 row in set (0.03 sec)
mysql> SHOW CREATE TABLE testdata_damage;
| testdata_damage | CREATE TABLE `testdata_damage` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`description` longtext NOT NULL,
`part` varchar(100) DEFAULT NULL,
`timestamp` datetime(6) NOT NULL,
`category_id` int(11),
`result_id` int(11) NOT NULL,
PRIMARY KEY (`id`),
KEY `TestData_damage_b583a629` (`category_id`),
KEY `TestData_damage_57f06544` (`result_id`),
FULLTEXT KEY `damage_index_description` (`description`),
CONSTRAINT `TestData_damage_category_id_215346e4_fk_TestData_damcategory_id` F
OREIGN KEY (`category_id`) REFERENCES `testdata_damcategory` (`id`),
CONSTRAINT `TestData_damage_result_id_2fb199b2_fk_TestData_result_id` FOREIGN
KEY (`result_id`) REFERENCES `testdata_result` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=141341 DEFAULT CHARSET=utf8 |
mysql> SELECT count(*) FROM testdata_damage;
+----------+
| count(*) |
+----------+
| 141291 |
+----------+
1 row in set (0.04 sec)
mysql> SHOW CREATE TABLE testdata_damcategory;
| testdata_damcategory | CREATE TABLE `testdata_damcategory` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`type` varchar(100) DEFAULT NULL,
PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=6 DEFAULT CHARSET=utf8 |
mysql> SELECT count(*) FROM testdata_damcategory;
+----------+
| count(*) |
+----------+
| 5 |
+----------+
1 row in set (0.00 sec)
SELECT COUNT(*) FROM (
SELECT e.designation
...
) AS x;
+----------+
| COUNT(*) |
+----------+
| 141298 |
+----------+
1 row in set (2.40 sec)¨
编辑：
附指定索引说明
| {
"query_block": {
"select_id": 1,
"ordering_operation": {
"using_temporary_table": true,
"using_filesort": true,
"nested_loop": [
{
"table": {
"table_name": "a",
"access_type": "ALL",
"possible_keys": [
"PRIMARY"
],
"rows": 10617,
"filtered": 100,
"attached_condition": "(`webappdev`.`a`.`id` is not null)"
}
},
{
"table": {
"table_name": "b",
"access_type": "ref",
"possible_keys": [
"TestData_gear_2e06cda4",
"test_id_gear_index"
],
"key": "TestData_gear_2e06cda4",
"used_key_parts": [
"test_id"
],
"key_length": "5",
"ref": [
"webappdev.a.id"
],
"rows": 1,
"filtered": 100
}
},
{
"table": {
"table_name": "e",
"access_type": "ref",
"possible_keys": [
"PRIMARY",
"test_id_result_index"
],
"key": "test_id_result_index",
"used_key_parts": [
"test_id"
],
"key_length": "4",
"ref": [
"webappdev.a.id"
],
"rows": 4,
"filtered": 100
}
},
{
"table": {
"table_name": "d",
"access_type": "ref",
"possible_keys": [
"TestData_damage_b583a629",
"TestData_damage_57f06544",
"result_id_damage_index"
],
"key": "TestData_damage_57f06544",
"used_key_parts": [
"result_id"
],
"key_length": "4",
"ref": [
"webappdev.e.id"
],
"rows": 1,
"filtered": 100
}
},
{
"table": {
"table_name": "c",
"access_type": "ALL",
"possible_keys": [
"PRIMARY"
],
"rows": 4,
"filtered": 75,
"using_join_buffer": "Block Nested Loop",
"attached_condition": "(`webappdev`.`c`.`id` = `webappdev`.`d`.`cate
gory_id`)"
}
}
]
}
}
} |
最终更新：
这是最终成功的查询，将我的查询时间降低到 0.1 秒以下。
SELECT e.designation
, e.remark
, e.moment
, e.rpm
, e.cycleK
, c.type
, d.description
, a.PAnr
, b.family
, b.articlenrKronhjul
, b.ratio
, a.oiltype
, a.oiltemp
, a.createdBy
, a.createdDate
FROM (
SELECT e.id, e.designation, e.remark, e.moment, e.rpm, e.cycleK, e.test_id
FROM testdata_result e
ORDER BY moment asc
LIMIT 10
)e
JOIN testdata_damage AS d ON d.result_id = e.id
JOIN testdata_test AS a ON a.id = e.test_id
JOIN testdata_gear AS b ON a.id = b.test_id
JOIN testdata_damcategory as c ON c.id = d.category_id;
INDEX(designation)
可能会有所帮助。
没有 LIMIT 10 你得到多少行？
请为每个 table 提供 SHOW CREATE TABLE，以便我们进一步讨论。
编辑
没关系。 141K 行的结果集，包括 LONGTEXT 将需要时间。你很幸运，只需要一秒钟左右。有很多东西要铲。磁盘走得这么快；网络只有这么快。导致它成为 "slow" 的不是查询或索引；这是请求。
您可以用 141K 行做什么？当然，您不会将所有这些都显示给用户。如果你正在以某种方式咀嚼它们，那肯定需要几秒钟，这意味着查询只是总时间的一部分。
我建议使用索引以避免执行文件排序——但我没有注意到它是 LONGTEXT，因此使用常规索引无效。 FULLTEXT 索引没有排序。底线：我的 INDEX(designation) 没用。
基本上没有办法加快查询速度目前。如果您需要一次获取 10 行，可能有一些技巧（不涉及 OFFSET）可以使它更好地工作。
乍一看，我认为 SQL_CALC_FOUND_ROWS 正在阻止任何加速查询的尝试。这要求所有 JOINs 都完成。在我之前的回答中，我希望在 10 行后短路评估。那是不可能的。
因此，"right" 解决方案涉及更改应用程序以执行有关计数的操作。
- 摆脱它（并说服用户他们并不真正需要它）；
- 将其缓存在某处（每晚？）；
- 近似值
如果在删除 SQL_CALC_FOUND_ROWS 后，您仍然无法优化，请执行以下操作：
SELECT ...
FROM (
SELECT e.id, e.remark, e.moment, e.rpm, e.cycleK
FROM result
ORDER BY designation -- check that there is a plain INDEX on this
LIMIT 10
) ON e
JOIN damage AS d ON d.result_id = e.id -- check for INDEX(result_id)
JOIN ... (the rest of the tables other than `e`)
ORDER BY designation -- yes, this redundancy is necessary
此编码 'trick' 是将 LIMIT（或 GROUP BY）移动到子查询中以减少在执行 JOINs 时要处理的行数。这不是 JOINing 很多行，然后扔掉其中的大部分。
我有一个 table，我需要在其中连接很多不同的 table。数据集有 140 000 条记录。
示例如下：
SELECT SQL_CALC_FOUND_ROWS e.designation
, e.remark
, e.moment
, e.rpm
, e.cycleK
, c.type
, d.description
, a.PAnr
, b.family
, b.articlenrKronhjul
, b.ratio
, a.oiltype
, a.oiltemp
, a.createdBy
, a.createdDate
FROM testdata_test a
, testdata_gear b
, testdata_damcategory c
, testdata_damage d
, testdata_result e
WHERE a.id = e.test_id
AND e.id = d.result_id
AND a.id = b.test_id
AND c.id = d.category_id
ORDER
BY designation asc
LIMIT 0, 10
平均耗时约 1 秒，如何加快速度？ 我一直在尝试在某些列上添加一些索引，但没有太大改进。
有人有什么建议吗？
编辑：
这是我的常规和 JSON 格式的查询计划：
+----+-------------+-------+------+---------------------------------------------------+--------------------------+---------+----------------+------+----------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------------------------------------------+--------------------------+---------+----------------+------+----------------------------------------------------+
| 1 | SIMPLE | a | ALL | PRIMARY | NULL | NULL | NULL | 10617 | Using where; Using temporary; Using filesort |
| 1 | SIMPLE | b | ref | TestData_gear_2e06cda4 | TestData_gear_2e06cda4 | 5 | webappdev.a.id | 1 | NULL |
| 1 | SIMPLE | e | ref | PRIMARY,TestData_result_2e06cda4 | TestData_result_2e06cda4 | 4 | webappdev.a.id | 5 | NULL |
| 1 | SIMPLE | d | ref | TestData_damage_b583a629,TestData_damage_57f06544 | TestData_damage_57f06544 | 4 | webappdev.e.id | 1 | NULL |
| 1 | SIMPLE | c | ALL | PRIMARY | NULL | NULL | NULL | 4 | Using where; Using join buffer (Block Nested Loop)|
+----+-------------+-------+------+---------------------------------------------------+--------------------------+---------+----------------+-------+---------------------------------------------------+
5 rows in set (0.00 sec)
| {
"query_block": {
"select_id": 1,
"ordering_operation": {
"using_temporary_table": true,
"using_filesort": true,
"nested_loop": [
{
"table": {
"table_name": "a",
"access_type": "ALL",
"possible_keys": [
"PRIMARY"
],
"rows": 10617,
"filtered": 100,
"attached_condition": "(`webappdev`.`a`.`id` is not null)"
}
},
{
"table": {
"table_name": "b",
"access_type": "ref",
"possible_keys": [
"TestData_gear_2e06cda4"
],
"key": "TestData_gear_2e06cda4",
"used_key_parts": [
"test_id"
],
"key_length": "5",
"ref": [
"webappdev.a.id"
],
"rows": 1,
"filtered": 100
}
},
{
"table": {
"table_name": "e",
"access_type": "ref",
"possible_keys": [
"PRIMARY",
"TestData_result_2e06cda4"
],
"key": "TestData_result_2e06cda4",
"used_key_parts": [
"test_id"
],
"key_length": "4",
"ref": [
"webappdev.a.id"
],
"rows": 5,
"filtered": 100
}
},
{
"table": {
"table_name": "d",
"access_type": "ref",
"possible_keys": [
"TestData_damage_b583a629",
"TestData_damage_57f06544"
],
"key": "TestData_damage_57f06544",
"used_key_parts": [
"result_id"
],
"key_length": "4",
"ref": [
"webappdev.e.id"
],
"rows": 1,
"filtered": 100
}
},
{
"table": {
"table_name": "c",
"access_type": "ALL",
"possible_keys": [
"PRIMARY"
],
"rows": 4,
"filtered": 75,
"using_join_buffer": "Block Nested Loop",
"attached_condition": "(`webappdev`.`c`.`id` = `webappdev`.`d`.`cate
gory_id`)"
}
}
]
}
}
} |
这是我的 CREATE TABLES 和 tables
的计数mysql> SHOW CREATE TABLE testdata_test;
| testdata_test | CREATE TABLE `testdata_test` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`PAnr` int(11) NOT NULL,
`projectAcc` varchar(20) DEFAULT NULL,
`reportnr` varchar(20) DEFAULT NULL,
`oiltype` varchar(40) DEFAULT NULL,
`oiltemp` int(11) DEFAULT NULL,
`headline1` varchar(40) DEFAULT NULL,
`headline2` varchar(40) DEFAULT NULL,
`testDescription` longtext,
`TestName` varchar(9) DEFAULT NULL,
`createdBy` varchar(6) NOT NULL,
`createdDate` date NOT NULL,
PRIMARY KEY (`id`),
FULLTEXT KEY `test_index_testdescription` (`testDescription`)
) ENGINE=InnoDB AUTO_INCREMENT=14172 DEFAULT CHARSET=utf8 |
1 row in set (0.00 sec)
mysql> SELECT count(*) FROM testdata_test;
+----------+
| count(*) |
+----------+
| 14161 |
+----------+
1 row in set (0.01 sec)
mysql> SHOW CREATE TABLE testdata_gear;
| testdata_gear | CREATE TABLE `testdata_gear` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`family` varchar(20) NOT NULL,
`articlenrKronhjul` int(11) DEFAULT NULL,
`revisionK` varchar(200) DEFAULT NULL,
`articlenrPinjong` int(11) DEFAULT NULL,
`revisionP` varchar(200) DEFAULT NULL,
`ratio` double DEFAULT NULL,
`geardata` varchar(100) DEFAULT NULL,
`remark` varchar(40) DEFAULT NULL,
`test_id` int(11),
PRIMARY KEY (`id`),
KEY `TestData_gear_2e06cda4` (`test_id`),
CONSTRAINT `TestData_gear_test_id_325c2ab6_fk_TestData_test_id` FOREIGN KEY (`
test_id`) REFERENCES `testdata_test` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=14167 DEFAULT CHARSET=utf8 |
mysql> SELECT count(*) FROM testdata_gear;
+----------+
| count(*) |
+----------+
| 14157 |
+----------+
1 row in set (0.01 sec)
| testdata_result | CREATE TABLE `testdata_result` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`designation` varchar(20) NOT NULL,
`remark` varchar(200) DEFAULT NULL,
`moment` double DEFAULT NULL,
`rpm` int(11) DEFAULT NULL,
`cycleK` int(11) DEFAULT NULL,
`test_id` int(11) NOT NULL,
PRIMARY KEY (`id`),
KEY `test_id_result_index` (`test_id`) USING BTREE,
KEY `result_designation_index` (`designation`) USING BTREE,
CONSTRAINT `TestData_result_test_id_5ed0cbc8_fk_TestData_test_id` FOREIGN KEY
(`test_id`) REFERENCES `testdata_test` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=141382 DEFAULT CHARSET=utf8 |
mysql> SELECT count(*) FROM testdata_result;
+----------+
| count(*) |
+----------+
| 141323 |
+----------+
1 row in set (0.03 sec)
mysql> SHOW CREATE TABLE testdata_damage;
| testdata_damage | CREATE TABLE `testdata_damage` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`description` longtext NOT NULL,
`part` varchar(100) DEFAULT NULL,
`timestamp` datetime(6) NOT NULL,
`category_id` int(11),
`result_id` int(11) NOT NULL,
PRIMARY KEY (`id`),
KEY `TestData_damage_b583a629` (`category_id`),
KEY `TestData_damage_57f06544` (`result_id`),
FULLTEXT KEY `damage_index_description` (`description`),
CONSTRAINT `TestData_damage_category_id_215346e4_fk_TestData_damcategory_id` F
OREIGN KEY (`category_id`) REFERENCES `testdata_damcategory` (`id`),
CONSTRAINT `TestData_damage_result_id_2fb199b2_fk_TestData_result_id` FOREIGN
KEY (`result_id`) REFERENCES `testdata_result` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=141341 DEFAULT CHARSET=utf8 |
mysql> SELECT count(*) FROM testdata_damage;
+----------+
| count(*) |
+----------+
| 141291 |
+----------+
1 row in set (0.04 sec)
mysql> SHOW CREATE TABLE testdata_damcategory;
| testdata_damcategory | CREATE TABLE `testdata_damcategory` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`type` varchar(100) DEFAULT NULL,
PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=6 DEFAULT CHARSET=utf8 |
mysql> SELECT count(*) FROM testdata_damcategory;
+----------+
| count(*) |
+----------+
| 5 |
+----------+
1 row in set (0.00 sec)
SELECT COUNT(*) FROM (
SELECT e.designation
...
) AS x;
+----------+
| COUNT(*) |
+----------+
| 141298 |
+----------+
1 row in set (2.40 sec)¨
编辑： 附指定索引说明
| {
"query_block": {
"select_id": 1,
"ordering_operation": {
"using_temporary_table": true,
"using_filesort": true,
"nested_loop": [
{
"table": {
"table_name": "a",
"access_type": "ALL",
"possible_keys": [
"PRIMARY"
],
"rows": 10617,
"filtered": 100,
"attached_condition": "(`webappdev`.`a`.`id` is not null)"
}
},
{
"table": {
"table_name": "b",
"access_type": "ref",
"possible_keys": [
"TestData_gear_2e06cda4",
"test_id_gear_index"
],
"key": "TestData_gear_2e06cda4",
"used_key_parts": [
"test_id"
],
"key_length": "5",
"ref": [
"webappdev.a.id"
],
"rows": 1,
"filtered": 100
}
},
{
"table": {
"table_name": "e",
"access_type": "ref",
"possible_keys": [
"PRIMARY",
"test_id_result_index"
],
"key": "test_id_result_index",
"used_key_parts": [
"test_id"
],
"key_length": "4",
"ref": [
"webappdev.a.id"
],
"rows": 4,
"filtered": 100
}
},
{
"table": {
"table_name": "d",
"access_type": "ref",
"possible_keys": [
"TestData_damage_b583a629",
"TestData_damage_57f06544",
"result_id_damage_index"
],
"key": "TestData_damage_57f06544",
"used_key_parts": [
"result_id"
],
"key_length": "4",
"ref": [
"webappdev.e.id"
],
"rows": 1,
"filtered": 100
}
},
{
"table": {
"table_name": "c",
"access_type": "ALL",
"possible_keys": [
"PRIMARY"
],
"rows": 4,
"filtered": 75,
"using_join_buffer": "Block Nested Loop",
"attached_condition": "(`webappdev`.`c`.`id` = `webappdev`.`d`.`cate
gory_id`)"
}
}
]
}
}
} |
最终更新： 这是最终成功的查询，将我的查询时间降低到 0.1 秒以下。
SELECT e.designation
, e.remark
, e.moment
, e.rpm
, e.cycleK
, c.type
, d.description
, a.PAnr
, b.family
, b.articlenrKronhjul
, b.ratio
, a.oiltype
, a.oiltemp
, a.createdBy
, a.createdDate
FROM (
SELECT e.id, e.designation, e.remark, e.moment, e.rpm, e.cycleK, e.test_id
FROM testdata_result e
ORDER BY moment asc
LIMIT 10
)e
JOIN testdata_damage AS d ON d.result_id = e.id
JOIN testdata_test AS a ON a.id = e.test_id
JOIN testdata_gear AS b ON a.id = b.test_id
JOIN testdata_damcategory as c ON c.id = d.category_id;
INDEX(designation)
可能会有所帮助。
没有 LIMIT 10 你得到多少行？
请为每个 table 提供 SHOW CREATE TABLE，以便我们进一步讨论。
编辑
没关系。 141K 行的结果集，包括 LONGTEXT 将需要时间。你很幸运，只需要一秒钟左右。有很多东西要铲。磁盘走得这么快；网络只有这么快。导致它成为 "slow" 的不是查询或索引；这是请求。
您可以用 141K 行做什么？当然，您不会将所有这些都显示给用户。如果你正在以某种方式咀嚼它们，那肯定需要几秒钟，这意味着查询只是总时间的一部分。
我建议使用索引以避免执行文件排序——但我没有注意到它是 LONGTEXT，因此使用常规索引无效。 FULLTEXT 索引没有排序。底线：我的 INDEX(designation) 没用。
基本上没有办法加快查询速度目前。如果您需要一次获取 10 行，可能有一些技巧（不涉及 OFFSET）可以使它更好地工作。
乍一看，我认为 SQL_CALC_FOUND_ROWS 正在阻止任何加速查询的尝试。这要求所有 JOINs 都完成。在我之前的回答中，我希望在 10 行后短路评估。那是不可能的。
因此，"right" 解决方案涉及更改应用程序以执行有关计数的操作。
- 摆脱它（并说服用户他们并不真正需要它）；
- 将其缓存在某处（每晚？）；
- 近似值
如果在删除 SQL_CALC_FOUND_ROWS 后，您仍然无法优化，请执行以下操作：
SELECT ...
FROM (
SELECT e.id, e.remark, e.moment, e.rpm, e.cycleK
FROM result
ORDER BY designation -- check that there is a plain INDEX on this
LIMIT 10
) ON e
JOIN damage AS d ON d.result_id = e.id -- check for INDEX(result_id)
JOIN ... (the rest of the tables other than `e`)
ORDER BY designation -- yes, this redundancy is necessary
此编码 'trick' 是将 LIMIT（或 GROUP BY）移动到子查询中以减少在执行 JOINs 时要处理的行数。这不是 JOINing 很多行，然后扔掉其中的大部分。