CREATE TABLE `files` (
`did` int(10) unsigned NOT NULL DEFAULT '0',
`filename` varbinary(200) NOT NULL,
`ext` varbinary(5) DEFAULT NULL,
`fsize` double DEFAULT NULL,
`filetime` datetime DEFAULT NULL,
PRIMARY KEY (`did`,`filename`),
KEY `fe` (`filetime`,`ext`), -- This?
KEY `ef` (`ext`,`filetime`) -- or This?
) ENGINE=InnoDB DEFAULT CHARSET=utf8 ;
表格中有一百万行。文件时间大多不同。有一定数量的ext
值。因此,filetime
具有较高的基数,ext
的基数较低。
该查询涉及ext
和filetime
:
WHERE ext = '...'
AND filetime BETWEEN ... AND ...
这两个指标中的哪一个更好?为什么?
答案 0 :(得分:6)
首先,让我们FORCE INDEX
选择ef
或fe
。时间太短,无法清楚地了解哪个更快,但`EXPLAIN显示出差异:
首先强制filetime
上的范围。 (注意:WHERE
中的顺序没有影响。)
mysql> EXPLAIN SELECT COUNT(*), AVG(fsize)
FROM files FORCE INDEX(fe)
WHERE ext = 'gif' AND filetime >= '2015-01-01'
AND filetime < '2015-01-01' + INTERVAL 1 MONTH;
+----+-------------+-------+-------+---------------+------+---------+------+-------+-----------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+---------------+------+---------+------+-------+-----------------------+
| 1 | SIMPLE | files | range | fe | fe | 14 | NULL | 16684 | Using index condition |
+----+-------------+-------+-------+---------------+------+---------+------+-------+-----------------------+
首先强制低基数ext
:
mysql> EXPLAIN SELECT COUNT(*), AVG(fsize)
FROM files FORCE INDEX(ef)
WHERE ext = 'gif' AND filetime >= '2015-01-01'
AND filetime < '2015-01-01' + INTERVAL 1 MONTH;
+----+-------------+-------+-------+---------------+------+---------+------+------+-----------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+---------------+------+---------+------+------+-----------------------+
| 1 | SIMPLE | files | range | ef | ef | 14 | NULL | 538 | Using index condition |
+----+-------------+-------+-------+---------------+------+---------+------+------+-----------------------+
显然,rows
说ef
更好。但是,让我们检查优化器跟踪。产量相当笨重;我只展示有趣的部分。不需要FORCE
;跟踪将显示两个选项然后选择更好。
...
"potential_range_indices": [
...
{
"index": "fe",
"usable": true,
"key_parts": [
"filetime",
"ext",
"did",
"filename"
]
},
{
"index": "ef",
"usable": true,
"key_parts": [
"ext",
"filetime",
"did",
"filename"
]
}
],
...
"analyzing_range_alternatives": {
"range_scan_alternatives": [
{
"index": "fe",
"ranges": [
"2015-01-01 00:00:00 <= filetime < 2015-02-01 00:00:00"
],
"index_dives_for_eq_ranges": true,
"rowid_ordered": false,
"using_mrr": false,
"index_only": false,
"rows": 16684,
"cost": 20022, <-- Here's the critical number
"chosen": true
},
{
"index": "ef",
"ranges": [
"gif <= ext <= gif AND 2015-01-01 00:00:00 <= filetime < 2015-02-01 00:00:00"
],
"index_dives_for_eq_ranges": true,
"rowid_ordered": false,
"using_mrr": false,
"index_only": false,
"rows": 538,
"cost": 646.61, <-- Here's the critical number
"chosen": true
}
],
...
"attached_conditions_computation": [
{
"access_type_changed": {
"table": "`files`",
"index": "ef",
"old_type": "ref",
"new_type": "range",
"cause": "uses_more_keyparts" <-- Also interesting
}
}
使用fe
(范围列第一个),可以使用范围,但估计扫描16684行捕获ext='gif'
。
使用ef
(低基数ext
优先),它可以使用索引的两列并在BTree中更有效地向下钻取。然后它发现了大约538行,所有这些行对查询都很有用 - 不需要进一步过滤。
结论:
INDEX(filetime, ext)
仅使用第一列。INDEX(ext, filetime)
使用了两列。=
测试首先中涉及的列放在索引中,而不考虑基数。(&#34;使用索引条件&#34;意味着存储引擎(InnoDB)将使用超出用于过滤的索引的列。&#34;)