从数据库中消除重复的城市

发布于 2024-11-03 12:47:52 字数 2670 浏览 1 评论 0原文

背景

超过 5300 个重复行:

"id","latitude","longitude","country","region","city"
"2143220","41.3513889","68.9444444","KZ","10","Abay"
"2143218","40.8991667","68.5433333","KZ","10","Abay"
"1919381","33.8166667","49.6333333","IR","34","Ab Barik"
"1919377","35.6833333","50.1833333","IR","19","Ab Barik"
"1919432","29.55","55.5122222","IR","29","`Abbasabad"
"1919430","27.4263889","57.5725","IR","29","`Abbasabad"
"1919413","28.0011111","58.9005556","IR","12","`Abbasabad"
"1919435","36.5641667","61.14","IR","30","`Abbasabad"
"1919433","31.8988889","58.9211111","IR","30","`Abbasabad"
"1919422","33.8666667","48.3","IR","23","`Abbasabad"
"1919420","33.4658333","49.6219444","IR","23","`Abbasabad"
"1919438","33.5333333","49.9833333","IR","34","`Abbasabad"
"1919423","33.7619444","49.0747222","IR","24","`Abbasabad"
"1919419","34.2833333","49.2333333","IR","19","`Abbasabad"
"1919439","35.8833333","52.15","IR","35","`Abbasabad"
"1919417","35.9333333","52.95","IR","17","`Abbasabad"
"1919427","35.7341667","51.4377778","IR","26","`Abbasabad"
"1919425","35.1386111","51.6283333","IR","26","`Abbasabad"
"1919713","30.3705556","56.07","IR","29","`Abdolabad"
"1919711","27.9833333","57.7244444","IR","29","`Abdolabad"
"1919716","35.6025","59.2322222","IR","30","`Abdolabad"
"1919714","34.2197222","56.5447222","IR","30","`Abdolabad"

其他详细信息:

  • PostgreSQL 8.4 数据库
  • Linux

问题

有些值是明显重复的(“Abay”是因为区域匹配,“Ab Barik”是因为两个位置非常接近),其他值则不那么明显(并且甚至可能不是实际的重复项):

"1919430","27.4263889","57.5725","IR","29","`Abbasabad"
"1919435","36.5641667","61.14","IR","30","`Abbasabad"

目标是消除所有重复项。

问题

给定一个值表,例如上述 CSV 数据:

  • 您将如何消除重复项?
  • 您会使用哪些以地理为中心的 PostgreSQL 函数?
  • 您还会使用什么其他标准来哄骗重复项?

更新

半工作示例代码以选择同一国家/地区内距离很近(10 公里以内)的重复城市名称:

select
  c1.country, c1.name, c1.region_id, c2.region_id, c1.latitude_decimal, c1.longitude_decimal, c2.latitude_decimal, c2.longitude_decimal
from
  climate.maxmind_city c1,
  climate.maxmind_city c2
where
  c1.country = 'BE' and
  c1.id <> c2.id and
  c1.country = c2.country and
  c1.name = c2.name and
  (c1.latitude_decimal <> c2.latitude_decimal or c1.longitude_decimal <> c2.longitude_decimal) and
  earth_distance(
    ll_to_earth( c1.latitude_decimal, c1.longitude_decimal ),
    ll_to_earth( c2.latitude_decimal, c2.longitude_decimal ) ) <= 10
order by
  country, name

想法

两阶段方法:

  1. 通过删除 min( 来消除明显的重复项(相同的国家/地区、地区和城市名称) ID)。
  2. 消除那些彼此距离很近、具有相同名字和国家的人。这可能会消除一些合法城市,但几乎不会产生任何后果。

谢谢你!

Background

Over 5300 duplicate rows:

"id","latitude","longitude","country","region","city"
"2143220","41.3513889","68.9444444","KZ","10","Abay"
"2143218","40.8991667","68.5433333","KZ","10","Abay"
"1919381","33.8166667","49.6333333","IR","34","Ab Barik"
"1919377","35.6833333","50.1833333","IR","19","Ab Barik"
"1919432","29.55","55.5122222","IR","29","`Abbasabad"
"1919430","27.4263889","57.5725","IR","29","`Abbasabad"
"1919413","28.0011111","58.9005556","IR","12","`Abbasabad"
"1919435","36.5641667","61.14","IR","30","`Abbasabad"
"1919433","31.8988889","58.9211111","IR","30","`Abbasabad"
"1919422","33.8666667","48.3","IR","23","`Abbasabad"
"1919420","33.4658333","49.6219444","IR","23","`Abbasabad"
"1919438","33.5333333","49.9833333","IR","34","`Abbasabad"
"1919423","33.7619444","49.0747222","IR","24","`Abbasabad"
"1919419","34.2833333","49.2333333","IR","19","`Abbasabad"
"1919439","35.8833333","52.15","IR","35","`Abbasabad"
"1919417","35.9333333","52.95","IR","17","`Abbasabad"
"1919427","35.7341667","51.4377778","IR","26","`Abbasabad"
"1919425","35.1386111","51.6283333","IR","26","`Abbasabad"
"1919713","30.3705556","56.07","IR","29","`Abdolabad"
"1919711","27.9833333","57.7244444","IR","29","`Abdolabad"
"1919716","35.6025","59.2322222","IR","30","`Abdolabad"
"1919714","34.2197222","56.5447222","IR","30","`Abdolabad"

Additional details:

  • PostgreSQL 8.4 Database
  • Linux

Problem

Some values are obvious duplicates ("Abay" because the regions match and "Ab Barik" because the two locations are within such close proximity), others are not so obvious (and might not even be actual duplicates):

"1919430","27.4263889","57.5725","IR","29","`Abbasabad"
"1919435","36.5641667","61.14","IR","30","`Abbasabad"

The goal is to eliminate all duplicates.

Questions

Given a table of values such as the above CSV data:

  • How would you eliminate duplicates?
  • What geo-centric PostgreSQL functions would you use?
  • What other criteria would you use to wheedle down the duplicates?

Update

Semi-working example code to select duplicate city names within the same country that are in close proximity (within 10 km):

select
  c1.country, c1.name, c1.region_id, c2.region_id, c1.latitude_decimal, c1.longitude_decimal, c2.latitude_decimal, c2.longitude_decimal
from
  climate.maxmind_city c1,
  climate.maxmind_city c2
where
  c1.country = 'BE' and
  c1.id <> c2.id and
  c1.country = c2.country and
  c1.name = c2.name and
  (c1.latitude_decimal <> c2.latitude_decimal or c1.longitude_decimal <> c2.longitude_decimal) and
  earth_distance(
    ll_to_earth( c1.latitude_decimal, c1.longitude_decimal ),
    ll_to_earth( c2.latitude_decimal, c2.longitude_decimal ) ) <= 10
order by
  country, name

Ideas

Two phase approach:

  1. Eliminate the obvious duplicates (same country, region, and city name) by removing the min(id).
  2. Eliminate those within close proximity of each other, having the same name and country. This could remove some legitimate cities, but hardly any of consequence.

Thank you!

如果你对这篇内容有疑问,欢迎到本站社区发帖提问 参与讨论,获取更多帮助,或者扫码二维码加入 Web 技术交流群。

扫码二维码加入Web技术交流群

发布评论

需要 登录 才能够评论, 你可以免费 注册 一个本站的账号。

评论(3

微凉 2024-11-10 12:47:52

查找重复项很简单:

select
  max(id) as this_should_stay,
  latitude,
  longitude,
  country,
  region,
  city
FROM
  your_table
group by
  latitude,
  longitude,
  country,
  region,
  city
having count(*) > 1;

添加代码以基于此删除重复项很简单:

delete from your_table where id not in (
    select
      max(id) as this_should_stay
    FROM
      your_table
    group by
      latitude,
      longitude,
      country,
      region,
      city
)

请注意删除查询中缺少having。

Finding duplicates is simple:

select
  max(id) as this_should_stay,
  latitude,
  longitude,
  country,
  region,
  city
FROM
  your_table
group by
  latitude,
  longitude,
  country,
  region,
  city
having count(*) > 1;

Adding code to remove duplicates based on this is simple:

delete from your_table where id not in (
    select
      max(id) as this_should_stay
    FROM
      your_table
    group by
      latitude,
      longitude,
      country,
      region,
      city
)

note lack of having in the delete query.

追我者格杀勿论 2024-11-10 12:47:52

这将删除与同一国家/地区同名城市非常接近的第二个城市:

delete from climate.maxmind_city mc where id in (
select
  max(c1.id)
from
  climate.maxmind_city c1,
  climate.maxmind_city c2
where
  c1.id <> c2.id and
  c1.country = c2.country and
  c1.name = c2.name and
  earth_distance(
    ll_to_earth( c1.latitude_decimal, c1.longitude_decimal ),
    ll_to_earth( c2.latitude_decimal, c2.longitude_decimal ) ) <= 35
group by
  c1.country, c1.name
order by
  c1.country, c1.name
)

This deletes the second city within close proximity to a city of the same name in the same country:

delete from climate.maxmind_city mc where id in (
select
  max(c1.id)
from
  climate.maxmind_city c1,
  climate.maxmind_city c2
where
  c1.id <> c2.id and
  c1.country = c2.country and
  c1.name = c2.name and
  earth_distance(
    ll_to_earth( c1.latitude_decimal, c1.longitude_decimal ),
    ll_to_earth( c2.latitude_decimal, c2.longitude_decimal ) ) <= 35
group by
  c1.country, c1.name
order by
  c1.country, c1.name
)
小镇女孩 2024-11-10 12:47:52

如果您的数据已通过 CSV 文件并使用代码 (PHP) 导入,那么您可以使用 PHP 代码中的放置条件来防止重复输入。如果您插入的城市已经存在,则使循环继续到下一条记录并跳过当前记录。

如果您按照这种方式将数据导入数据库,请尝试此操作。

谢谢。

if your data have been imported thru CSV files and with the code (PHP) then you can prevent duplicates entry with the putting condition in PHP code. if the city you inserted is already exist then make loop continue to next record and skip current record.

try this if you are follow this way to import data in database..

Thanks.

~没有更多了~
我们使用 Cookies 和其他技术来定制您的体验包括您的登录状态等。通过阅读我们的 隐私政策 了解更多相关信息。 单击 接受 或继续使用网站,即表示您同意使用 Cookies 和您的相关数据。
原文