我从英国的地名网站（http://download.geonames.org/export/dump/）获得一个数据库转储。它包含大约60000条记录。
表结构如下：
CREATE TABLE `geoname` (
`geonameid` INT(11) NOT NULL,
`name` VARCHAR(200) NULL DEFAULT NULL,
`asciiname` VARCHAR(200) NULL DEFAULT NULL COLLATE 'utf8_unicode_ci',
`preferredname` VARCHAR(200) NULL DEFAULT NULL,
`alternatenames` VARCHAR(10000) NULL DEFAULT NULL COLLATE `utf8_unicode_ci',
`latitude` DECIMAL(10,7) NULL DEFAULT NULL,
`longitude` DECIMAL(10,7) NULL DEFAULT NULL,
`feature_class` CHAR(1) NULL DEFAULT NULL,
`feature_code` VARCHAR(10) NULL DEFAULT NULL,
`country_code` VARCHAR(2) NULL DEFAULT NULL COLLATE 'utf8_unicode_ci',
`cc2` VARCHAR(60) NULL DEFAULT NULL,
`admin1` VARCHAR(20) NULL DEFAULT NULL COLLATE 'utf8_unicode_ci',
`admin2` VARCHAR(80) NULL DEFAULT NULL COLLATE 'utf8_unicode_ci',
`admin3` VARCHAR(20) NULL DEFAULT NULL,
`admin4` VARCHAR(20) NULL DEFAULT NULL,
`population` INT(11) NULL DEFAULT NULL,
`elevation` INT(11) NULL DEFAULT NULL,
`gtopo30` INT(11) NULL DEFAULT NULL,
`timezone` VARCHAR(40) NULL DEFAULT NULL,
`moddate` DATETIME NULL DEFAULT NULL,
PRIMARY KEY (`geonameid`),
INDEX `geoname_name_idx` (`name`),
INDEX `geoname_preferredname_idx` (`preferredname`),
INDEX `geoname_admin1_idx` (`admin1`),
INDEX `geoname_admin2_idx` (`admin2`),
INDEX `geoname_admin3_idx` (`admin3`),
INDEX `geoname_admin4_idx` (`admin4`),
INDEX `geoname_feature_code_idx` (`feature_code`),
INDEX `geoname_feature_class_idx` (`feature_class`)
)
COLLATE='utf8_general_ci'
ENGINE=InnoDB
;
我已将索引添加到要在查询中使用的列。该查询用于自动完成功能，但执行时间很长-下面的查询花了26.72秒，对于自动完成功能却很差：
mysql> SELECT t0.preferredname,
-> t4.preferredname AS town,
-> t3.preferredname AS county,
-> t2.preferredname AS district,
-> t1.preferredname AS admin1,
-> MIN(t0.geonameid)
-> FROM geoname t0
-> LEFT JOIN geoname t1 ON t1.admin1 = t0.admin1 AND t1.feature_code = 'ADM1'
-> LEFT JOIN geoname t2 ON t2.admin2 = t0.admin2 AND t2.feature_code = 'ADM2'
-> LEFT JOIN geoname t3 ON t3.admin3 = t0.admin3 AND t3.feature_code = 'ADM3'
-> LEFT JOIN geoname t4 ON t4.admin4 = t0.admin4 AND t4.feature_code = 'ADM4'
-> WHERE t0.feature_class IN ('P', 'A')
-> AND t0.preferredname LIKE 'preston%'
-> GROUP BY t0.preferredname,
-> t4.preferredname,
-> t3.preferredname,
-> t2.preferredname,
-> t1.preferredname;
+------------------------------+--------------------+--------------------------------+---------------------+----------+-------------------+
| preferredname | town | county | district | admin1 | MIN(t0.geonameid) |
+------------------------------+--------------------+--------------------------------+---------------------+----------+-------------------+
| Preston | NULL | Ellingham | Northumberland | England | 2639911 |
| Preston | NULL | Preston | District of Rutland | England | 2639914 |
| Preston | NULL | Preston | East Yorkshire | England | 2639913 |
| Preston | NULL | Preston District | Lancashire | England | 2639912 |
| Preston | NULL | Weymouth and Portland District | Dorset | England | 2639922 |
| Preston | Dymock | Forest of Dean District | Gloucestershire | England | 2639916 |
| Preston | Preston | Cotswold District | Gloucestershire | England | 2639918 |
| Preston | Preston | Dover District | Kent | England | 2639920 |
| Preston | Preston | North Hertfordshire District | Hertfordshire | England | 2639917 |
| Preston Bagot | Preston Bagot | Stratford-on-Avon District | Warwickshire | England | 2639910 |
| Preston Bisset | Preston Bissett | Aylesbury Vale | Buckinghamshire | England | 2639909 |
| Preston Bissett | Preston Bissett | Aylesbury Vale | Buckinghamshire | England | 7299788 |
| Preston Brook | NULL | Preston Brook | Borough of Halton | England | 7296534 |
| Preston Candover | Preston Candover | Basingstoke and Deane District | Hampshire | England | 2639908 |
| Preston Capes | Preston Capes | Daventry District | Northamptonshire | England | 2639907 |
| Preston District | NULL | Preston District | Lancashire | England | 7290581 |
| Preston Gubbals | NULL | Pimhill | Shropshire | England | 2639906 |
| Preston on Stour | Preston on Stour | Stratford-on-Avon District | Warwickshire | England | 7299630 |
| Preston on the Hill | NULL | Preston Brook | Borough of Halton | England | 2639904 |
| Preston on Wye | NULL | Preston on Wye | Herefordshire | England | 2639903 |
| Preston Park | NULL | NULL | Brighton and Hove | England | 2639921 |
| Preston Patrick | Preston Patrick | South Lakeland District | Cumbria | England | 7298113 |
| Preston Richard | Preston Richard | South Lakeland District | Cumbria | England | 7300167 |
| Preston Road | NULL | Brent | Greater London | England | 2639919 |
| Preston St Mary | Preston St. Mary | Babergh District | Suffolk | England | 2639915 |
| Preston St. Mary | Preston St. Mary | Babergh District | Suffolk | England | 7301329 |
| Preston upon the Weald Moors | NULL | Preston upon the Weald Moors | Telford and Wrekin | England | 2639900 |
| Preston Wynne | NULL | Preston Wynne | Herefordshire | England | 2639899 |
| Preston-on-Tees | NULL | Preston-on-Tees | Stockton-on-Tees | England | 7299560 |
| Preston-under-Scar | Preston-under-Scar | Richmondshire District | North Yorkshire | England | 7291664 |
| Prestonpans | NULL | NULL | East Lothian | Scotland | 2639902 |
+------------------------------+--------------------+--------------------------------+---------------------+----------+-------------------+
31 rows in set (26.72 sec)
mysql>
在上面的查询中使用事件探查器时，我得到以下信息：
mysql> select substring_index(event_name,'/',-1) as Status, truncate((timer_end-timer_start)/1000000000000,6) as Duration from performance_schema.events_stages_history_long where event_id>=8215932 and event_id<=9810811;
+----------------------+-----------+
| Status | Duration |
+----------------------+-----------+
| starting | 0.000198 |
| checking permissions | 0.000004 |
| checking permissions | 0.000001 |
| checking permissions | 0.000001 |
| checking permissions | 0.000001 |
| checking permissions | 0.000005 |
| Opening tables | 0.000044 |
| init | 0.000088 |
| System lock | 0.000013 |
| optimizing | 0.000022 |
| statistics | 0.075318 |
| preparing | 0.000059 |
| Creating tmp table | 0.000082 |
| Sorting result | 0.000014 |
| executing | 0.000003 |
| Sending data | 24.472337 |
| Creating sort index | 0.000292 |
| end | 0.000007 |
| query end | 0.000022 |
| removing tmp table | 0.000118 |
| closing tables | 0.000024 |
| freeing items | 0.000278 |
| cleaning up | 0.000001 |
+----------------------+-----------+
23 rows in set (0.00 sec)
使用Explain运行查询时，我得到以下信息：
mysql> EXPLAIN SELECT t0.preferredname,
-> t4.preferredname AS town,
-> t3.preferredname AS county,
-> t2.preferredname AS district,
-> t1.preferredname AS admin1,
-> MIN(t0.geonameid)
-> FROM geoname t0
-> LEFT JOIN geoname t1 ON t1.admin1 = t0.admin1 AND t1.feature_code = 'ADM1'
-> LEFT JOIN geoname t2 ON t2.admin2 = t0.admin2 AND t2.feature_code = 'ADM2'
-> LEFT JOIN geoname t3 ON t3.admin3 = t0.admin3 AND t3.feature_code = 'ADM3'
-> LEFT JOIN geoname t4 ON t4.admin4 = t0.admin4 AND t4.feature_code = 'ADM4'
-> WHERE t0.feature_class IN ('P', 'A')
-> AND t0.preferredname LIKE 'preston%'
-> GROUP BY t0.preferredname,
-> t4.preferredname,
-> t3.preferredname,
-> t2.preferredname,
-> t1.preferredname;
+----+-------------+-------+------------+-------+-----------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+-----------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
| 1 | SIMPLE | t0 | NULL | range | geoname_preferredname_idx,geoname_feature_class_idx | geoname_preferredname_idx | 603 | NULL | 55 | 70.01 | Using index condition; Using where; Using temporary; Using filesort |
| 1 | SIMPLE | t1 | NULL | ref | geoname_admin1_idx,geoname_feature_code_idx | geoname_feature_code_idx | 33 | const | 4 | 100.00 | Using where |
| 1 | SIMPLE | t2 | NULL | ref | geoname_admin2_idx,geoname_feature_code_idx | geoname_feature_code_idx | 33 | const | 185 | 100.00 | Using where |
| 1 | SIMPLE | t3 | NULL | ref | geoname_admin3_idx,geoname_feature_code_idx | geoname_admin3_idx | 63 | test.t0.admin3 | 14 | 100.00 | Using where |
| 1 | SIMPLE | t4 | NULL | ref | geoname_admin4_idx,geoname_feature_code_idx | geoname_admin4_idx | 63 | test.t0.admin4 | 7 | 100.00 | Using where |
+----+-------------+-------+------------+-------+-----------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
5 rows in set, 1 warning (0.06 sec)
请注意，我正在使用group by子句，因为数据在子级别具有重复的名称。
如何优化此查询？任何建议提示和技巧将不胜感激。
答案 0 :(得分：3)
我想您希望检索与用户提供的不完整搜索字符串匹配的地区，然后加入行政管辖区以提供更具信息性的自动完成功能。
这里的技巧是快速检索候选位置。这样的子查询可以解决问题。
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class IN ('P', 'A')
AND preferredname LIKE 'preston%'
这是您查找操作的核心。可以通过
上的复合覆盖指数来加速CREATE INDEX lookup1
ON geonames(feature_class, preferredname, admin1, admin2, admin3, admin4);
尝试此查询。看看它是否足够快（亚秒级）。如果不是，请尝试以下变体：
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class ='P'
AND preferredname LIKE 'preston%'
UNION ALL
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class ='A'
AND preferredname LIKE 'preston%'
MySQL的查询计划器可以将索引随机访问到第一行，然后通过顺序扫描索引来检索它需要的所有内容。
然后，在JOIN操作中使用该子查询的结果集。现在，您只需要处理联接中少量的相关行，而不必处理整个混乱。
SELECT t0.preferredname,
t4.preferredname AS town,
t3.preferredname AS county,
t2.preferredname AS district,
t1.preferredname AS admin1,
MIN(t0.geonameid) geonameid
FROM (
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class IN ='P'
AND preferredname LIKE 'preston%'
UNION ALL
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class ='A'
AND preferredname LIKE 'preston%'
) t0
LEFT JOIN geoname t1 ON t1.admin1 = t0.admin1 AND t1.feature_code = 'ADM1'
LEFT JOIN geoname t2 ON t2.admin2 = t0.admin2 AND t2.feature_code = 'ADM2'
LEFT JOIN geoname t3 ON t3.admin3 = t0.admin3 AND t3.feature_code = 'ADM3'
LEFT JOIN geoname t4 ON t4.admin4 = t0.admin4 AND t4.feature_code = 'ADM4'
GROUP BY t0.preferredname,
t4.preferredname,
t3.preferredname,
t2.preferredname,
t1.preferredname
专业提示：许多单列索引很少会在多个过滤条件下加快查询的速度，尤其是使用LIKE 'something%'之类的范围过滤器时。适当的多列索引会更有帮助。
答案 1 :(得分：2)
我认为您应该先更改表格。
asciiname，feature_class，feature_code，country_code，cc2，adminN，timezone的排序规则到latin1_general_ci。这样可以减少数据和索引的数据存储需求，并允许服务器在执行查询时将更多数据放入缓冲区。
您必须将population数据类型更改为INTEGER UNSIGNED （整数），因为当前某些记录的数据可能已被截断（检查“国家联合体”的值）。
您还可以考虑将moddate更改为DATE，将elevation和gtopo30更改为SMALLINT以进一步降低存储要求。
然后，您需要从以下位置更改索引geoname_admin1_idx：
INDEX `geoname_admin1_idx` (`admin1`)
收件人：
INDEX `geoname_admin1_idx` (`feature_code`, `admin1`)
对其他geoname_adminN_idx索引执行相同的操作。 这将使服务器更快地加入查询。
这些更改带来了巨大的变化，并且在不修改查询的情况下，我的系统上的查询执行时间从8秒减少到几乎为零（0.1秒）。
说明这些修改后的结果：
mysql> explain
-> SELECT t0.preferredname,
-> t4.preferredname AS town,
-> t3.preferredname AS county,
-> t2.preferredname AS district,
-> t1.preferredname AS admin1
-> , MIN(t0.geonameid)
-> FROM geoname t0
-> LEFT JOIN geoname t1 ON t1.admin1 = t0.admin1 AND t1.feature_code = 'ADM1'
-> LEFT JOIN geoname t2 ON t2.admin2 = t0.admin2 AND t2.feature_code = 'ADM2'
-> LEFT JOIN geoname t3 ON t3.admin3 = t0.admin3 AND t3.feature_code = 'ADM3'
-> LEFT JOIN geoname t4 ON t4.admin4 = t0.admin4 AND t4.feature_code = 'ADM4'
-> WHERE t0.feature_class IN ('P', 'A')
-> AND t0.preferredname LIKE 'preston%'
-> GROUP BY t0.preferredname,
-> t4.preferredname,
-> t3.preferredname,
-> t2.preferredname,
-> t1.preferredname;
+----+-------------+-------+------------+-------+-----------------------------------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+-----------------------------------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
| 1 | SIMPLE | t0 | NULL | range | geoname_preferredname_idx,geoname_feature_class_idx | geoname_preferredname_idx | 803 | NULL | 55 | 68.74 | Using index condition; Using where; Using temporary; Using filesort |
| 1 | SIMPLE | t1 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx | geoname_admin2_idx | 13 | const | 4 | 100.00 | Using where |
| 1 | SIMPLE | t2 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx | geoname_admin2_idx | 96 | const,test.t0.admin2 | 10 | 100.00 | NULL |
| 1 | SIMPLE | t3 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx | geoname_admin3_idx | 36 | const,test.t0.admin3 | 4 | 100.00 | NULL |
| 1 | SIMPLE | t4 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx | geoname_admin4_idx | 36 | const,test.t0.admin4 | 3 | 100.00 | NULL |
+----+-------------+-------+------------+-------+-----------------------------------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
检查key_len，ref，行和其他有关联接表的信息。
您使用的查询也可能会受益于索引（feature_class，preferredname）。 这里用索引来解释：
+----+-------------+-------+------------+-------+------------------------------------------------------------------------------------------------------+-----------------------------------------+---------+----------------------+------+----------+--------------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+------------------------------------------------------------------------------------------------------+-----------------------------------------+---------+----------------------+------+----------+--------------------------------------------------------+
| 1 | SIMPLE | t0 | NULL | range | geoname_preferredname_idx,geoname_feature_class_idx,geoname_feature_class_preferredname_idx | geoname_feature_class_preferredname_idx | 805 | NULL | 42 | 100.00 | Using index condition; Using temporary; Using filesort |
| 1 | SIMPLE | t1 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx,geoname_feature_code_idx | geoname_admin2_idx | 13 | const | 4 | 100.00 | Using where |
| 1 | SIMPLE | t2 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx,geoname_feature_code_idx | geoname_admin2_idx | 96 | const,test.t0.admin2 | 12 | 100.00 | NULL |
| 1 | SIMPLE | t3 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx,geoname_feature_code_idx | geoname_admin3_idx | 36 | const,test.t0.admin3 | 4 | 100.00 | NULL |
| 1 | SIMPLE | t4 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx,geoname_feature_code_idx | geoname_admin4_idx | 36 | const,test.t0.admin4 | 3 | 100.00 | NULL |
+----+-------------+-------+------------+-------+------------------------------------------------------------------------------------------------------+-----------------------------------------+---------+----------------------+------+----------+--------------------------------------------------------+