IP2Location™ LITE IP-COUNTRY-REGION-CITY-LATITUDE-LONGITUDE Database

소개 풍모 데이터베이스 필드 데이터베이스 설정 샘플 데이터베이스 AMI 및 이미지 SDK 및 라이브러리 무료 도구/플러그인

소개

IP2Location LITE Database

이 데이터베이스는 몇 가지 간단한 단계로 모든 IP 주소의 국가, 지역 또는 주, 도시, 위도 및 경도를 결정하는 솔루션을 제공합니다. 먼저 웹 서버의 네트워킹 프로토콜 또는 서버 측 변수에서 IP 주소를 검색합니다. 다음으로, 데이터베이스 쿼리 속도를 높이기 위해 IP 주소를 10 진수 형식의 IP 번호로 변환합니다. 마지막으로 IP2Location ™ 데이터베이스에서 IP 번호를 역방향 조회하여 정확한 지리적 위치를 찾아냅니다.

이 데이터의 사용을 다음과 같이 언급하여 저작자 표시가 필요한 개인 또는 상업적 용도로 무료입니다.

높은 데이터 정확도, 더 많은 기록 및 고객 지원을 원하시면 상업용 버전 을 받으십시오. 자세한 내용은 제품 비교 페이지 를 방문하십시오.

Let's explore this database which provides a valuable resource of geolocation data for free now!

Sign Up For Free

풍모

IP 주소를 국가, 지역 또는 주, 도시, 위도 및 경도로 변환합니다.

현재 버전 April 2025
다음 업데이트 May 2025
IPv4 데이터베이스 크기 BIN: 70.63 MB
CSV: 285.09 MB (3,030,196 행)
IPv6 데이터베이스 크기 BIN: 153.84 MB
CSV: 673.56 MB (5,436,314 행)
정렬 및 이진 (BIN)
ASCII 텍스트 파일 (CSV)

데이터베이스 필드

이름 유형 기술
ip_from INT (10)† / DECIMAL (39,0)†† 첫 번째 IP 주소는 넷 블록을 보여줍니다.
ip_to INT (10)† / DECIMAL (39,0)†† 마지막 IP 주소는 넷 블록을 보여줍니다.
country_code CHAR(2) ISO 3166을 기반으로 한 2 자리 국가 코드입니다.
country_name VARCHAR(64) ISO 3166에 따른 국가 이름입니다.
region_name VARCHAR(128) 지역 또는 주 이름.
city_name VARCHAR(128) 도시 이름.
latitude DOUBLE††† 도시 위도. 도시를 알 수없는 경우 기본값은 수도 위도입니다.
longitude DOUBLE††† 도시 경도. 도시를 알 수없는 경우 기본값은 수도 경도입니다.

† IPv4
†† IPv6
††† Latitude and Longitude are often near the center of population. These values are not precise and should not be used to identify a particular address or household.

데이터베이스 설정

다음은 IPv4 및 IPv6 데이터 모두에 대한 데이터베이스를 설정하는 단계입니다.

데이터베이스 생성
CREATE DATABASE ip2location;
USE ip2location;
CREATE TABLE `ip2location_db5`(
	`ip_from` INT(10) UNSIGNED,
	`ip_to` INT(10) UNSIGNED,
	`country_code` CHAR(2),
	`country_name` VARCHAR(64),
	`region_name` VARCHAR(128),
	`city_name` VARCHAR(128),
	`latitude` DOUBLE,
	`longitude` DOUBLE,
	PRIMARY KEY (`ip_to`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8 COLLATE=utf8_bin;
데이터베이스 가져 오기
LOAD DATA LOCAL
	INFILE 'IP2LOCATION-LITE-DB5.CSV'
INTO TABLE
	`ip2location_db5`
FIELDS TERMINATED BY ','
ENCLOSED BY '"'
LINES TERMINATED BY '\r\n'
IGNORE 0 LINES;
데이터베이스 생성
CREATE DATABASE ip2location
GO

USE ip2location
GO

CREATE TABLE [ip2location].[dbo].[ip2location_db5](
	[ip_from] bigint NOT NULL,
	[ip_to] bigint NOT NULL,
	[country_code] nvarchar(2) NOT NULL,
	[country_name] nvarchar(64) NOT NULL,
	[region_name] nvarchar(128) NOT NULL,
	[city_name] nvarchar(128) NOT NULL,
	[latitude] float NOT NULL,
	[longitude] float NOT NULL
) ON [PRIMARY]
GO

CREATE CLUSTERED INDEX [ip_to] ON [ip2location].[dbo].[ip2location_db5]([ip_to]) ON [PRIMARY]
GO
데이터베이스 가져 오기
BULK INSERT [ip2location].[dbo].[ip2location_db5]
FROM '{PATH TO IP2LOCATION-LITE-DB5.CSV}'
WITH
(
	FORMATFILE = '{PATH TO DB5.FMT}'
)
GO

참고 : 아래의 FMT 코드를 복사하여 컴퓨터에 DB5.FMT라는 파일로 저장해야합니다. 

12.0
9
1 SQLCHAR 0 1 "\"" 0 first_double_quote  Latin1_General_CI_AI
2 SQLCHAR 0 20 "\",\"" 1 ip_from "",
3 SQLCHAR 0 20 "\",\"" 2 ip_to "",
4 SQLCHAR 0 2 "\",\"" 3 country_code Latin1_General_CI_AI,
5 SQLCHAR 0 64 "\",\"" 4 country_name Latin1_General_CI_AI,
6 SQLCHAR 0 128 "\",\"" 5 region_name Latin1_General_CI_AI,
7 SQLCHAR 0 128 "\",\"" 6 city_name Latin1_General_CI_AI,
8 SQLCHAR 0 20 "\",\"" 7 latitude "",
9 SQLCHAR 0 20 "\",\"" 8 longitude ""

데이터베이스 생성
CREATE DATABASE ip2location WITH ENCODING 'UTF8';
\c ip2location
CREATE TABLE ip2location_db5(
	ip_from bigint NOT NULL,
	ip_to bigint NOT NULL,
	country_code character(2) NOT NULL,
	country_name character varying(64) NOT NULL,
	region_name character varying(128) NOT NULL,
	city_name character varying(128) NOT NULL,
	latitude real NOT NULL,
	longitude real NOT NULL,
	CONSTRAINT ip2location_db1_pkey PRIMARY KEY (ip_from, ip_to)
);
데이터베이스 가져 오기
COPY ip2location_db5 FROM 'IP2LOCATION-LITE-DB5.CSV' WITH CSV QUOTE AS '"';
데이터베이스 가져 오기
mongoimport -u USERNAME -p PASSWORD --authenticationDatabase admin --drop --db ip2location --collection ip2location_db5 --type csv --file "IP2LOCATION-LITE-DB5.CSV" --fields ip_from,ip_to,country_code,country_name,region_name,city_name,latitude,longitude
데이터베이스 생성
CREATE DATABASE ip2location;
USE ip2location;
CREATE TABLE `ip2location_db5_ipv6`(
	`ip_from` DECIMAL(39,0) UNSIGNED,
	`ip_to` DECIMAL(39,0) UNSIGNED,
	`country_code` CHAR(2),
	`country_name` VARCHAR(64),
	`region_name` VARCHAR(128),
	`city_name` VARCHAR(128),
	`latitude` DOUBLE,
	`longitude` DOUBLE,
	PRIMARY KEY (`ip_to`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8 COLLATE=utf8_bin;
데이터베이스 가져 오기
LOAD DATA LOCAL
	INFILE 'IP2LOCATION-LITE-DB5.IPV6.CSV'
INTO TABLE
	`ip2location_db5_ipv6`
FIELDS TERMINATED BY ','
ENCLOSED BY '"'
LINES TERMINATED BY '\r\n'
IGNORE 0 LINES;
데이터베이스 생성
CREATE DATABASE ip2location
GO

USE ip2location
GO

CREATE TABLE [ip2location].[dbo].[ip2location_db5_ipv6](
	[ip_from] char(39) NOT NULL,
	[ip_to] char(39) NOT NULL,
	[country_code] nvarchar(2) NOT NULL,
	[country_name] nvarchar(64) NOT NULL,
	[region_name] nvarchar(128) NOT NULL,
	[city_name] nvarchar(128) NOT NULL,
	[latitude] float NOT NULL,
	[longitude] float NOT NULL
) ON [PRIMARY]
GO

CREATE CLUSTERED INDEX [ip_to] ON [ip2location].[dbo].[ip2location_db5_ipv6]([ip_to]) ON [PRIMARY]
GO
데이터베이스 가져 오기
BULK INSERT [ip2location].[dbo].[ip2location_db5_ipv6]
FROM '{PATH TO IP2LOCATION-LITE-DB5.IPV6.CSV}'
WITH
(
	FORMATFILE = '{PATH TO DB5.FMT}'
)
GO

참고 : 아래의 FMT 코드를 복사하여 컴퓨터에 DB5.FMT라는 파일로 저장해야합니다. FMT 코드의 첫 번째 줄은 bcp의 버전을 나타냅니다. 설치된 MS-SQL에 따라 버전을 변경하십시오. 

12.0
9
1 SQLCHAR 0 1 "\"" 0 first_double_quote  Latin1_General_CI_AI
2 SQLCHAR 0 39 "\",\"" 1 ip_from "",
3 SQLCHAR 0 39 "\",\"" 2 ip_to "",
4 SQLCHAR 0 2 "\",\"" 3 country_code Latin1_General_CI_AI,
5 SQLCHAR 0 64 "\",\"" 4 country_name Latin1_General_CI_AI,
6 SQLCHAR 0 128 "\",\"" 5 region_name Latin1_General_CI_AI,
7 SQLCHAR 0 128 "\",\"" 6 city_name Latin1_General_CI_AI,
8 SQLCHAR 0 20 "\",\"" 7 latitude "",
9 SQLCHAR 0 20 "\",\"" 8 longitude ""

데이터베이스 생성
CREATE DATABASE ip2location WITH ENCODING 'UTF8';
\c ip2location
CREATE TABLE ip2location_db5_ipv6(
	ip_from decimal(39,0) NOT NULL,
	ip_to decimal(39,0) NOT NULL,
	country_code character(2) NOT NULL,
	country_name character varying(64) NOT NULL,
	region_name character varying(128) NOT NULL,
	city_name character varying(128) NOT NULL,
	latitude real NOT NULL,
	longitude real NOT NULL,
	CONSTRAINT ip2location_db1_pkey PRIMARY KEY (ip_from, ip_to)
);
데이터베이스 가져 오기
COPY ip2location_db5_ipv6 FROM 'IP2LOCATION-LITE-DB5.IPV6.CSV' WITH CSV QUOTE AS '"';
데이터베이스 가져 오기
mongoimport -u USERNAME -p PASSWORD --authenticationDatabase admin --drop --db ip2location --collection ip2location_db5_ipv6 --type csv --file "IP2LOCATION-LITE-DB5.IPV6.CSV" --fields ip_from,ip_to,country_code,country_name,region_name,city_name,latitude,longitude

샘플 데이터베이스

아래는 참고용 샘플 데이터베이스입니다. 


"ip_from","ip_to","country_code","country_name","region_name","city_name","latitude","longitude"
"0","16777215","-","-","-","-","0.000000","0.000000"
"16777216","16777471","AU","Australia","Queensland","Brisbane","-27.467540","153.028090"
"16777472","16778239","CN","China","Fujian","Fuzhou","26.061390","119.306110"
"16778240","16778495","AU","Australia","Victoria","Melbourne","-37.814007","144.963171"
"16778496","16778751","AU","Australia","Queensland","Warren","-23.500000","150.283330"
"16778752","16779007","AU","Australia","Victoria","Melbourne","-37.814007","144.963171"
"16779008","16779263","AU","Australia","Queensland","Warren","-23.500000","150.283330"
"16779264","16781311","CN","China","Guangdong","Guangzhou","23.127361","113.264570"
"16781312","16785407","JP","Japan","Tokyo","Tokyo","35.689497","139.692317"
"16785408","16793599","CN","China","Guangdong","Guangzhou","23.127361","113.264570"
"16793600","16794367","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16794368","16794623","JP","Japan","Hiroshima","Nuno","34.533330","132.400000"
"16794624","16794879","JP","Japan","Miyagi","Sendai","38.266990","140.867133"
"16794880","16795647","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16795648","16795903","JP","Japan","Hiroshima","Niho","34.369940","132.493950"
"16795904","16797695","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16797696","16797951","JP","Japan","Shimane","Izumo","35.367000","132.767000"
"16797952","16798207","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16798208","16798463","JP","Japan","Shimane","Matsue","35.467000","133.050000"
"16798464","16798719","JP","Japan","Tottori","Kurayoshi","35.433000","133.817000"
"16798720","16798975","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16798976","16799231","JP","Japan","Shimane","Matsue","35.467000","133.050000"
"16799232","16799487","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16799488","16799999","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16800000","16800255","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16800256","16800511","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16800512","16800767","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16800768","16801023","JP","Japan","Tottori","Yonago","35.432738","133.333399"
"16801024","16801279","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16801280","16801535","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16801536","16801791","JP","Japan","Tottori","Kurayoshi","35.433000","133.817000"
"16801792","16802047","JP","Japan","Tottori","Yonago","35.432738","133.333399"
"16802048","16802303","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16802304","16802815","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16802816","16803071","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16803072","16803327","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16803328","16803583","JP","Japan","Shimane","Izumo","35.367000","132.767000"
"16803584","16803839","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16803840","16804095","JP","Japan","Tottori","Yonago","35.432738","133.333399"
"16804096","16804351","JP","Japan","Shimane","Matsue","35.467000","133.050000"
"16804352","16804607","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16804608","16804863","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16804864","16805119","JP","Japan","Shimane","Izumo","35.367000","132.767000"
"16805120","16805375","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16805376","16805631","JP","Japan","Shimane","Izumo","35.367000","132.767000"
"16805632","16805887","JP","Japan","Shimane","Matsue","35.467000","133.050000"
"16805888","16806143","JP","Japan","Tottori","Yonago","35.432738","133.333399"
"16806144","16806399","JP","Japan","Tottori","Kurayoshi","35.433000","133.817000"
"16806400","16806655","JP","Japan","Yamaguchi","Shimonoseki","33.950000","130.933000"
"16806656","16806911","JP","Japan","Yamaguchi","Iwakuni","34.150000","132.183000"
"16806912","16807167","JP","Japan","Shimane","Matsue","35.467000","133.050000"
"16807168","16807423","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16807424","16807679","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16807680","16808447","JP","Japan","Shimane","Matsue","35.467000","133.050000"
"16808448","16808703","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16808704","16808959","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16808960","16809215","JP","Japan","Yamaguchi","Shimonoseki","33.950000","130.933000"
"16809216","16809471","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16809472","16809727","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16809728","16809983","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16809984","16810239","TH","Thailand","Chiang Rai","Pa Daet","19.504800","99.992430"
"16810240","16810495","TH","Thailand","Krung Thep Maha Nakhon","Bangkok","13.749976","100.516819"
"16810496","16810751","TH","Thailand","Phetchaburi","Phetchaburi","13.111890","99.944670"
"16810752","16811007","TH","Thailand","Songkhla","Songkhla","7.198820","100.595100"
"16811008","16811263","TH","Thailand","Suphan Buri","Don Chedi","14.634970","100.020970"
"16811264","16811519","TH","Thailand","Krung Thep Maha Nakhon","Bangkok","13.749976","100.516819"
"16811520","16811775","TH","Thailand","Ratchaburi","Ratchaburi","13.536710","99.817120"
"16811776","16812031","TH","Thailand","Chiang Rai","Wiang Chai","19.883610","99.933140"
"16812032","16812287","TH","Thailand","Prachuap Khiri Khan","Kui Buri","12.082830","99.854310"
"16812288","16812543","TH","Thailand","Trang","Ratsada","7.974670","99.633530"
"16812544","16812799","TH","Thailand","Nakhon Sawan","Takhli","15.263360","100.343780"
"16812800","16813567","TH","Thailand","Krung Thep Maha Nakhon","Bangkok","13.749976","100.516819"
"16813568","16813823","TH","Thailand","Phetchaburi","Phetchaburi","13.111890","99.944670"
"16813824","16814079","TH","Thailand","Krung Thep Maha Nakhon","Bangkok","13.749976","100.516819"
"16814080","16814335","TH","Thailand","Surat Thani","Koh Tao","10.098080","99.838090"
"16814336","16814591","TH","Thailand","Phatthalung","Phatthalung","7.617860","100.077920"
"16814592","16815103","TH","Thailand","Surat Thani","Ko Samui","9.535670","99.935670"
"16815104","16815359","TH","Thailand","Nakhon Si Thammarat","Thung Song","8.164530","99.680390"
"16815360","16815615","TH","Thailand","Phangnga","Takua Pa","8.870500","98.343830"
"16815616","16815871","TH","Thailand","Surat Thani","Ko Samui","9.535670","99.935670"
"16815872","16816127","TH","Thailand","Surat Thani","Koh Tao","10.098080","99.838090"
"16816128","16816383","TH","Thailand","Phangnga","Ko Yao","8.110140","98.592310"
"16816384","16816639","TH","Thailand","Phatthalung","Phatthalung","7.617860","100.077920"
"16816640","16816895","TH","Thailand","Surat Thani","Koh Tao","10.098080","99.838090"
"16816896","16817151","TH","Thailand","Surat Thani","Ko Pha Ngan","9.719450","99.995110"
"16817152","16817407","TH","Thailand","Surat Thani","Koh Tao","10.098080","99.838090"
"16817408","16817663","TH","Thailand","Krabi","Ban Ao Nang","8.045800","98.810350"
"16817664","16817919","TH","Thailand","Trang","Palian","7.172280","99.686330"
"16817920","16818175","TH","Thailand","Krabi","Ban Ao Nang","8.045800","98.810350"
"16818176","16818431","TH","Thailand","Surat Thani","Chaiya","9.386240","99.198610"
"16818432","16818943","TH","Thailand","Surat Thani","Ko Samui","9.535670","99.935670"
"16818944","16819199","TH","Thailand","Phangnga","Ban Phru Nai","7.933330","98.583330"
"16819200","16819455","TH","Thailand","Phatthalung","Khuan Khanun","7.734700","100.009310"
"16819456","16819711","TH","Thailand","Chiang Mai","San Pa Tong","18.628280","98.895720"
"16819712","16820223","TH","Thailand","Surat Thani","Ko Pha Ngan","9.719450","99.995110"
"16820224","16820479","TH","Thailand","Phetchaburi","Cha-am","12.800135","99.966107"
"16820480","16820735","TH","Thailand","Krung Thep Maha Nakhon","Bangkok","13.749976","100.516819"
"16820736","16820991","TH","Thailand","Surat Thani","Ko Samui","9.535670","99.935670"
"16820992","16821247","TH","Thailand","Phra Nakhon Si Ayutthaya","Wang Noi","14.226890","100.715500"
"16821248","16821759","TH","Thailand","Phatthalung","Phatthalung","7.617860","100.077920"
"16821760","16822015","TH","Thailand","Phangnga","Kapong","8.696970","98.409140"

AMI 및 이미지

IP2Location은 데이터베이스를 쉽게 설정할 수 있도록 사전 구성되고 바로 실행할 수있는 무료 AMI 및 이미지를 제공합니다.

Amazon Web Services
Docker Images

특허

데이터베이스 라이센스에 대한 일반 약관 을 검토하십시오.

기타

기사 및 튜토리얼

IP2Location ™ IP 주소 지리적 위치 데이터베이스

Commercial Edition에서는 IP 주소 조회 이상의 것을 얻을 수 있습니다.

  • 더 나은 데이터 정확도
  • 최신 데이터베이스에 액세스
  • 이메일을 통한 추가 수준의 지원
지금 업그레이드
더 알아보기
Product Upgrade
Sign Up Pop Out

Geolocate Your Visitors Location

Enhance your applications with essential geolocation data by using our FREE databases.

Get Started For Free Now