优化地理距离相关的MySQL查询

本文介绍了优化地理距离相关的MySQL查询的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我有以下MySQL查询：

I have the following MySQL query:

SELECT a.*, ( 3959 * acos( cos( radians('47.3909') ) * cos( radians( a.lat ) ) * cos( radians( a.lng ) - radians('-122.2637') ) + sin( radians('47.3909') ) * sin( radians( a.lat ) ) ) ) AS distance FROM zip_codes AS a ORDER BY distance ASC LIMIT 1;

这将获取我的 zip_codes 离我指定的坐标最近的表。

This will get me the zip code in my zip_codes table that is nearest to the coordinates I have specified.

然而，这运行得很慢！大约1秒钟。所有类似的查询也会持续1秒左右。我想知道我是否可以优化我的表结构或查询来改善查询时间。

However, this is running pretty slow! Around 1 second. All similar queries run around 1 second as well. I am wondering if I can optimize either my table structure or the query to improve the query time.

这是我的 zip_codes的架构 table：

This is the schema of my zip_codes table:

CREATE TABLE `zip_codes` ( `zip` varchar(10) COLLATE utf8_unicode_ci NOT NULL, `city` varchar(64) CHARACTER SET utf8 DEFAULT NULL, `state` char(2) CHARACTER SET utf8 DEFAULT NULL, `type` char(1) CHARACTER SET utf8 DEFAULT NULL, `timezone` int(11) DEFAULT NULL, `lat` varchar(255) CHARACTER SET utf8 DEFAULT NULL, `lng` varchar(255) CHARACTER SET utf8 DEFAULT NULL, `country` varchar(2) COLLATE utf8_unicode_ci DEFAULT '', PRIMARY KEY (`zip`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci ROW_FORMAT=COMPACT;

UPDATE 我更改了 lat的字段类型和 lng 到DECIMAL并且查询现在实际上需要更长时间，令人惊讶！

UPDATE I changed the field type for lat and lng to DECIMAL and the queries are actually taking longer now, surprisingly!

推荐答案

好的，所以我要警告你，这绝对不是一个完美的解决方案，并且有以下缺点：

ok, so I have to warn you that this is definitely not a perfect solution and has the following drawbacks:

它不适用于美国的所有点。例如，如果您在阿拉斯加的某处选择一个点，距离表格中的每个邮政编码中心不超过50公里，它将不返回任何内容

it does not work for all points in the US. For example, if you select a point somewhere in Alaska, further than 50 km from every of the ZIP code centers in the table, it will return nothing

它需要MyISAM存储引擎

it requires MyISAM storage engine

包含硬编码值（请参阅第1点~50 km）。它不完全是50公里，与经度不同。

in includes hardcoded values (see ~50 km in the 1st point). It's not exactly 50km and varies from the longitude.

先决条件：

鉴于您发送的转储，您应该启动以下查询：

Given the dump you sent, you should launch the following queries:

ALTER TABLE `zip_codes` ENGINE=MYISAM; -- changing your storage engine to MyISAM. It supports spatial indexes in MySQL ALTER TABLE `zip_codes` ADD `pt` POINT NOT NULL; -- adding POINT() spatial datatype for zip cetner. Eventually, you may remove the old lat/lng decimal columns ALTER TABLE `zip_codes` ADD `region` POLYGON NOT NULL; -- adding a rectangle over the center of the zip code. See below, this is something to utilize spatial index later in ST_Intersects function // update the new columns with respective values UPDATE `zip_codes` SET `pt` = POINT(lat,lng); UPDATE `zip_codes` SET `region` = GEOMFROMTEXT(CONCAT('POLYGON((',lat-0.5,' ',lng-0.5,', ',lat+0.5,' ',lng-0.5,', ',lat+0.5,' ',lng+0.5,', ',lat-0.5,' ',lng+0.5,', ',lat-0.5,' ',lng-0.5,'))')); -- 0.5 is 0.5 degrees hardcode. There is a better approach and it's better to write a MySQL function that will increase the MBR with certain step until there is intersection (see my point #1 above, this is the best solution) // create indexes on the newly created columns ALTER TABLE `zip_codes` ADD SPATIAL INDEX(`region`); ALTER TABLE `zip_codes` ADD SPATIAL INDEX(`pt`);

新查询

SELECT SQL_NO_CACHE zip,ST_Distance(`pt`,POINT('47.3909','-122.2637')) AS dst FROM `zip_codes` WHERE ST_Intersects(POINT('47.3909','-122.2637'),`region`) ORDER BY `dst` LIMIT 1;

在我的机器上需要大约0.011秒，这要好得多。

on my machine it takes about 0.011 seconds, which is much better.

但是再次看到我在更新声明附近的评论，你应该考虑两件事：

But again, see my comment above near the update statement, you should consider two things:

编写一个函数，该函数将增加最小边界矩形，步长为0.5度（例如），直到有交叉点

移动到PostgreSQL + PostGIS扩展。如果你处理那些需要空间扩展的记录，那就更强大了