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create_population_cities.sql
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110 lines (107 loc) · 6.93 KB
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/* @create_population_cities.sql */
/* Data about 100 Largest cities in the world (2016) */
/* Table: cities */
CREATE TABLE IF NOT EXISTS cities (idCity INTEGER PRIMARY KEY,
name CHAR(40),
country CHAR(40),
population INTEGER);
INSERT INTO cities VALUES(1, 'Tokyo–Yokohama', 'Japan', 37843000);
INSERT INTO cities VALUES(2, 'Jakarta (Jabodetabek)', 'Indonesia', 30539000);
INSERT INTO cities VALUES(3, 'Delhi', 'India', 24998000);
INSERT INTO cities VALUES(4, 'Manila (Metro Manila)', 'Philippines', 24123000);
INSERT INTO cities VALUES(5, 'Seoul–Gyeonggi–Incheon (Sudogwon)', 'South Korea', 23480000);
INSERT INTO cities VALUES(6, 'Shanghai', 'China', 23416000);
INSERT INTO cities VALUES(7, 'Karachi', 'Pakistan', 22123000);
INSERT INTO cities VALUES(8, 'Beijing', 'China', 21009000);
INSERT INTO cities VALUES(9, 'New York City', 'United States of America', 20630000);
INSERT INTO cities VALUES(10, 'Guangzhou–Foshan (Guangfo)', 'China', 20597000);
INSERT INTO cities VALUES(11, 'São Paulo', 'Brazil', 20365000);
INSERT INTO cities VALUES(12, 'Mexico City (Valley of Mexico)', 'Mexico', 20063000);
INSERT INTO cities VALUES(13, 'Mumbai ', 'India', 17712000);
INSERT INTO cities VALUES(14, 'Osaka–Kobe–Kyoto (Keihanshin)', 'Japan', 17444000);
INSERT INTO cities VALUES(15, 'Moscow', 'Russia', 16170000);
INSERT INTO cities VALUES(16, 'Dhaka', 'Bangladesh', 15669000);
INSERT INTO cities VALUES(17, 'Greater Cairo', 'Egypt', 15600000);
INSERT INTO cities VALUES(18, 'Los Angeles', 'United States of America', 15058000);
INSERT INTO cities VALUES(19, 'Bangkok', 'Thailand', 14998000);
INSERT INTO cities VALUES(20, 'Kolkata', 'India', 14667000);
INSERT INTO cities VALUES(21, 'Buenos Aires', 'Argentina', 14122000);
INSERT INTO cities VALUES(22, 'Tehran', 'Iran', 13532000);
INSERT INTO cities VALUES(23, 'Istanbul', 'Turkey', 13287000);
INSERT INTO cities VALUES(24, 'Lagos', 'Nigeria', 13123000);
INSERT INTO cities VALUES(25, 'Shenzhen', 'China', 12084000);
INSERT INTO cities VALUES(26, 'Rio de Janeiro', 'Brazil', 11727000);
INSERT INTO cities VALUES(27, 'Kinshasa', 'Democratic Republic of the Congo', 11587000);
INSERT INTO cities VALUES(28, 'Tianjin', 'China', 10920000);
INSERT INTO cities VALUES(29, 'Paris', 'France', 10858000);
INSERT INTO cities VALUES(30, 'Lima', 'Peru', 10750000);
INSERT INTO cities VALUES(31, 'Chengdu', 'China', 10376000);
INSERT INTO cities VALUES(32, 'London', 'United Kingdom', 10236000);
INSERT INTO cities VALUES(33, 'Nagoya ', 'Japan', 10177000);
INSERT INTO cities VALUES(34, 'Lahore', 'Pakistan', 10052000);
INSERT INTO cities VALUES(35, 'Chennai', 'India', 9714000);
INSERT INTO cities VALUES(36, 'Chicago', 'United States of America', 9156000);
INSERT INTO cities VALUES(37, 'Bogotá', 'Colombia', 8991000);
INSERT INTO cities VALUES(38, 'Ho Chi Minh City (Saigon)', 'Vietnam', 8957000);
INSERT INTO cities VALUES(39, 'Hyderabad', 'India', 8754000);
INSERT INTO cities VALUES(40, 'Bengaluru', 'India', 8728906);
INSERT INTO cities VALUES(41, 'Dongguan', 'China', 8442000);
INSERT INTO cities VALUES(42, 'Johannesburg–East Rand', 'South Africa', 8432000);
INSERT INTO cities VALUES(43, 'Wuhan', 'China', 7509000);
INSERT INTO cities VALUES(44, 'Taipei', 'Taiwan', 7438000);
INSERT INTO cities VALUES(45, 'Hangzhou', 'China', 7275000);
INSERT INTO cities VALUES(46, 'Hong Kong', 'China', 7246000);
INSERT INTO cities VALUES(47, 'Chongqing', 'China', 7217000);
INSERT INTO cities VALUES(48, 'Ahmedabad', 'India', 7186000);
INSERT INTO cities VALUES(49, 'Kuala Lumpur (Klang Valley)', 'Malaysia', 7088000);
INSERT INTO cities VALUES(50, 'Quanzhou', 'China', 6710000);
INSERT INTO cities VALUES(51, 'Essen–Düsseldorf (Ruhr Area)', 'Germany', 6679000);
INSERT INTO cities VALUES(52, 'Baghdad', 'Iraq', 6625000);
INSERT INTO cities VALUES(53, 'Toronto', 'Canada', 6456000);
INSERT INTO cities VALUES(54, 'Santiago', 'Chile', 6225000);
INSERT INTO cities VALUES(55, 'Dallas–Fort Worth', 'United States of America', 6174000);
INSERT INTO cities VALUES(56, 'Madrid', 'Spain', 6171000);
INSERT INTO cities VALUES(57, 'Nanjing', 'China', 6155000);
INSERT INTO cities VALUES(58, 'Shenyang', 'China', 6078000);
INSERT INTO cities VALUES(59, 'Xi an–Xianyang', 'China', 5977000);
INSERT INTO cities VALUES(60, 'San Francisco–San Jose', 'United States of America', 5929000);
INSERT INTO cities VALUES(61, 'Luanda', 'Angola', 5899000);
INSERT INTO cities VALUES(62, 'Qingdao–Jimo', 'China', 5816000);
INSERT INTO cities VALUES(63, 'Houston', 'United States of America', 5764000);
INSERT INTO cities VALUES(64, 'Miami', 'United States of America', 5764000);
INSERT INTO cities VALUES(65, 'Bandung', 'Indonesia', 5695000);
INSERT INTO cities VALUES(66, 'Riyadh', 'Saudi Arabia', 5666000);
INSERT INTO cities VALUES(67, 'Pune', 'India', 5631000);
INSERT INTO cities VALUES(68, 'Singapore', 'Singapore', 5624000);
INSERT INTO cities VALUES(69, 'Philadelphia', 'United States of America', 5570000);
INSERT INTO cities VALUES(70, 'Surat', 'India', 5447000);
INSERT INTO cities VALUES(71, 'Milan', 'Italy', 5257000);
INSERT INTO cities VALUES(72, 'Suzhou', 'China', 5246000);
INSERT INTO cities VALUES(73, 'Saint Petersburg', 'Russia', 5126000);
INSERT INTO cities VALUES(74, 'Khartoum', 'Sudan', 5125000);
INSERT INTO cities VALUES(75, 'Atlanta', 'United States of America', 5015000);
INSERT INTO cities VALUES(76, 'Zhengzhou–Xingyang', 'China', 4942000);
INSERT INTO cities VALUES(77, 'Washington, D.C.', 'United States of America', 4889000);
INSERT INTO cities VALUES(78, 'Surabaya', 'Indonesia', 4881000);
INSERT INTO cities VALUES(79, 'Harbin', 'China', 4815000);
INSERT INTO cities VALUES(80, 'Abidjan', 'Ivory Coast', 4800000);
INSERT INTO cities VALUES(81, 'Yangon (Rangoon)', 'Myanmar', 4800000);
INSERT INTO cities VALUES(82, 'Nairobi', 'Kenya', 4738000);
INSERT INTO cities VALUES(83, 'Barcelona', 'Spain', 4693000);
INSERT INTO cities VALUES(84, 'Alexandria', 'Egypt', 4689000);
INSERT INTO cities VALUES(85, 'Kabul', 'Afghanistan', 4635000);
INSERT INTO cities VALUES(86, 'Guadalajara', 'Mexico', 4603000);
INSERT INTO cities VALUES(87, 'Ankara', 'Turkey', 4538000);
INSERT INTO cities VALUES(88, 'Belo Horizonte', 'Brazil', 4517000);
INSERT INTO cities VALUES(89, 'Boston', 'United States of America', 4478000);
INSERT INTO cities VALUES(90, 'Xiamen', 'China', 4420000);
INSERT INTO cities VALUES(91, 'Kuwait City', 'Kuwait', 4283000);
INSERT INTO cities VALUES(92, 'Dar es Salaam', 'Tanzania', 4219000);
INSERT INTO cities VALUES(93, 'Phoenix', 'United States of America', 4194000);
INSERT INTO cities VALUES(94, 'Dalian', 'China', 4183000);
INSERT INTO cities VALUES(95, 'Accra', 'Ghana', 4145000);
INSERT INTO cities VALUES(96, 'Monterrey', 'Mexico', 4083000);
INSERT INTO cities VALUES(97, 'Berlin', 'Germany', 4069000);
INSERT INTO cities VALUES(98, 'Sydney', 'Australia', 4036000);
INSERT INTO cities VALUES(99, 'Fuzhou', 'China', 3962000);
INSERT INTO cities VALUES(100, 'Medan', 'Indonesia', 3942000);