From 8be42ca58416e23338e1d53b4f3b13ac835de80e Mon Sep 17 00:00:00 2001 From: wangjiahao <1522128093@qq.com> Date: Thu, 26 Aug 2021 16:34:38 +0800 Subject: [PATCH] =?UTF-8?q?refactro:=E6=9B=B4=E6=8D=A2demo?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../db/migration/V24__new_demo_panel.sql | 700 ++++++++++++------ 1 file changed, 462 insertions(+), 238 deletions(-) diff --git a/backend/src/main/resources/db/migration/V24__new_demo_panel.sql b/backend/src/main/resources/db/migration/V24__new_demo_panel.sql index 07475d8105..4009a8d2d3 100644 --- a/backend/src/main/resources/db/migration/V24__new_demo_panel.sql +++ b/backend/src/main/resources/db/migration/V24__new_demo_panel.sql @@ -1,296 +1,520 @@ -DROP TABLE IF EXISTS `ds_0f02aaa4_0f30_43d9_b05e_bed746c3c56e`; -CREATE TABLE `ds_0f02aaa4_0f30_43d9_b05e_bed746c3c56e` ( - `dataease_uuid` VARCHAR(50) NULL DEFAULT NULL, - `C_7e687515fc569cc19b4e7e9f882ae87e` VARCHAR(2000) NULL DEFAULT NULL, - `C_c7f2d4339c0b8a3db34212b0987e5038` DOUBLE NULL DEFAULT NULL, - `C_64a513b0097ced14a2291054a8260394` DOUBLE NULL DEFAULT NULL, - `C_cd6582f225497d1495f2b473220ae85d` DOUBLE NULL DEFAULT NULL, - `C_185616188c012181aaca0a092c50b0fc` DOUBLE NULL DEFAULT NULL, - `C_94c1225e5a57bb2da2fe0578a7789da7` DOUBLE NULL DEFAULT NULL, - `C_a08fe595bbb49a862bfab24964098dbb` DOUBLE NULL DEFAULT NULL, - `C_246d81170669bcac7711e9a9783289f5` DOUBLE NULL DEFAULT NULL, - `C_a2f4f848a7e4df2891fa9d8d8aa06bcf` DOUBLE NULL DEFAULT NULL, - `C_6bf465698bea29d70f1674bbbe31f4c0` DOUBLE NULL DEFAULT NULL, - `C_ff76506222f44df3390353c228b22628` DOUBLE NULL DEFAULT NULL, - `C_2cac4a8ae080bfefadfe646aa812acfd` DOUBLE NULL DEFAULT NULL, - `C_df1a259dae8f1e50abe72347084c5331` DOUBLE NULL DEFAULT NULL, - `C_f09755e9bfc002b64aa74490cf276c96` DOUBLE NULL DEFAULT NULL, - `C_0adc32d4ef8e0e07966189cd8fb9b78b` DOUBLE NULL DEFAULT NULL, - `C_75a049727e9f72e3f633009d03eda149` DOUBLE NULL DEFAULT NULL, - `C_d3bf9f229ba0033b231e006ed8be7c05` DOUBLE NULL DEFAULT NULL, - `C_836f4ccdc99a860318ce16e6c516a0bb` DOUBLE NULL DEFAULT NULL, - `C_e7a3833f9bbe133b64f6f1ce69a5b693` DOUBLE NULL DEFAULT NULL, - `C_aba589acab27bb78f3881c40996207b0` DOUBLE NULL DEFAULT NULL, - `C_6480d83c469d2e9a04c6fcbbb2aef22a` DOUBLE NULL DEFAULT NULL -) ENGINE = InnoDB COMMENT = 'OLAP'; + +SET NAMES utf8mb4; +SET FOREIGN_KEY_CHECKS = 0; -- ---------------------------- --- Records of ds_0f02aaa4_0f30_43d9_b05e_bed746c3c56e +-- Table structure for demo_gdp_2021 +-- ---------------------------- +DROP TABLE IF EXISTS `demo_gdp_2021`; +CREATE TABLE `demo_gdp_2021` ( + `id` int(11) NOT NULL AUTO_INCREMENT, + `2021GDP)` varchar(255) DEFAULT NULL, + `2020GDP` varchar(255) DEFAULT NULL, + `increase` varchar(255) DEFAULT NULL, + PRIMARY KEY (`id`) +) ENGINE=InnoDB AUTO_INCREMENT=10 DEFAULT CHARSET=utf8; + +-- ---------------------------- +-- Records of demo_gdp_2021 -- ---------------------------- BEGIN; -INSERT INTO `ds_0f02aaa4_0f30_43d9_b05e_bed746c3c56e` VALUES ('071bcb9d05e5d635a041cc137e82636b', '少儿抚养比(%)', 26.2, 23.8, 23.7, 23.4, 22.9, 22.6, 22.5, 22.2, 22.2, 22.1, 22.3, 25.3, 26, 26.8, 27.3, 28.1, 30.3, 31.4, 31.9, 32), ('3899d55a0108fa4a8c18d0e03f26454d', '年末总人口(万人)', 141178, 141008, 140541, 140011, 139232, 138326, 137646, 136726, 135922, 134916, 134091, 133450, 132802, 132129, 131448, 130756, 129988, 129227, 128453, 127627), ('843739797700278faa4f8a66da8f8961', '0-14岁人口(万人)', 25412, 23661, 23751, 23522, 23252, 22858, 22712, 22423, 22427, 22261, 22259, 24688, 25232, 25633, 26027, 26543, 27947, 28559, 28773, 28716), ('6a64b843a81e7be91d9bd637599884da', '老年抚养比(%)', 19.7, 17.8, 16.8, 15.9, 15, 14.3, 13.7, 13.1, 12.7, 12.3, 11.9, 11.6, 11.3, 11.1, 11, 10.7, 10.7, 10.7, 10.4, 10.1), ('03415ffb6e99884ea4972543a9abffa0', '总抚养比(%)', 45.9, 41.5, 40.4, 39.2, 37.9, 37, 36.1, 35.3, 34.9, 34.4, 34.2, 36.9, 37.4, 37.9, 38.3, 38.8, 41, 42, 42.2, 42), ('afb6445b840b44342fea46cfb0031ad2', '15-64岁人口(万人)', 96707, 99622, 100065, 100528, 100943, 100992, 101032, 101041, 100718, 100378, 99898, 97419, 96547, 95794, 95037, 94144, 92161, 90976, 90302, 89849), ('dc7665e11286d349ba4e11004d461465', '65岁及以上人口(万人)', 19059, 17725, 16724, 15961, 15037, 14476, 13902, 13262, 12777, 12277, 11934, 11343, 11023, 10702, 10384, 10068, 9879, 9692, 9377, 9062); +INSERT INTO `demo_gdp_2021` VALUES (1, '532167', '463324.76', '12.7'); COMMIT; -- ---------------------------- --- Table structure for ds_9f607520_ce57_4218_8541_afbcce3c999a +-- Table structure for demo_gdp_by_city -- ---------------------------- -DROP TABLE IF EXISTS `ds_9f607520_ce57_4218_8541_afbcce3c999a`; -CREATE TABLE `ds_9f607520_ce57_4218_8541_afbcce3c999a` ( - `dataease_uuid` VARCHAR(50) NULL DEFAULT NULL, - `C_7e687515fc569cc19b4e7e9f882ae87e` VARCHAR(2000) NULL DEFAULT NULL, - `C_c8a6175cad267d0e55f492df1963a0d8` BIGINT NULL DEFAULT NULL, - `C_59836f86eb5ec2a585215d30dc8918d2` BIGINT NULL DEFAULT NULL, - `C_5ff621cebecfdacd10108dd1ea27f241` BIGINT NULL DEFAULT NULL, - `C_b49ec02a6f00a8f201afb0c2a72f42a9` BIGINT NULL DEFAULT NULL, - `C_6c922468ced282192c2ec5cabc6948fe` BIGINT NULL DEFAULT NULL -) ENGINE = InnoDB COMMENT = 'OLAP'; +DROP TABLE IF EXISTS `demo_gdp_by_city`; +CREATE TABLE `demo_gdp_by_city` ( + `id` int(11) NOT NULL AUTO_INCREMENT, + `province` varchar(255) DEFAULT NULL, + `city` varchar(255) DEFAULT NULL, + `gdp` double(255,2) DEFAULT NULL, + PRIMARY KEY (`id`) +) ENGINE=InnoDB AUTO_INCREMENT=309 DEFAULT CHARSET=utf8; -- ---------------------------- --- Records of ds_9f607520_ce57_4218_8541_afbcce3c999a +-- Records of demo_gdp_by_city -- ---------------------------- BEGIN; -INSERT INTO `ds_9f607520_ce57_4218_8541_afbcce3c999a` VALUES ('078ffa99f0e15800e9221e0d533742a6', '2018年', 140541, 71864, 68677, 86433, 54108), ('5a0919c8fab03e52bb604d3db2acd273', '2015年', 138326, 70857, 67469, 79302, 59024), ('a3bf9754dc13948368b27aba06bd4c42', '2012年', 135922, 69660, 66262, 72175, 63747), ('2c281ba899067d70533afd4d6da9da35', '2010年', 134091, 68748, 65343, 66978, 67113), ('7083e9fcbaad70e38afde464b115e5f1', '2017年', 140011, 71650, 68361, 84343, 55668), ('f1640fc097b52f4402df70f42526218a', '2001年', 127627, 65672, 61955, 48064, 79563), ('3ac3bde91e19a48dd8135e79425ab9ce', '2019年', 141008, 72039, 68969, 88426, 52582), ('475fbbee0f808c97482397a892111f59', '2006年', 131448, 67728, 63720, 58288, 73160), ('5359965fd484df231cffa42b88e258c4', '2011年', 134916, 69161, 65755, 69927, 64989), ('a3718c41ef4a0e7ddc36b600a03cd8a1', '2003年', 129227, 66556, 62671, 52376, 76851), ('7cfb67e0a3869ce6296c34282dcdd840', '2020年', 141178, 72334, 68844, 90199, 50979), ('88f4410f9c3931946b250d9cbd547e92', '2013年', 136726, 70063, 66663, 74502, 62224), ('3a48099d3715ffda1ea8383a92183b5a', '2009年', 133450, 68647, 64803, 64512, 68938), ('4cba4854092a90ef45f9985427f0bde6', '2002年', 128453, 66115, 62338, 50212, 78241), ('9e8e948a54c95e5f4d36e55df4fbd185', '2016年', 139232, 71307, 67925, 81924, 57308), ('a06bcd4dbd0280f62f861d79ae63ccd8', '2008年', 132802, 68357, 64445, 62403, 70399), ('64e80ada938479c630fc10c71a0665db', '2014年', 137646, 70522, 67124, 76738, 60908), ('7635e3b68f1898f78d0696f94eb3ba70', '2007年', 132129, 68048, 64081, 60633, 71496), ('ad55eafac00297112ef8f346dd7a59bd', '2004年', 129988, 66976, 63012, 54283, 75705), ('d1221b0c446705cc8453144026181e4b', '2005年', 130756, 67375, 63381, 56212, 74544); +INSERT INTO `demo_gdp_by_city` VALUES (1, '广东省', '深圳市', 14324.47); +INSERT INTO `demo_gdp_by_city` VALUES (2, '广东省', '广州市', 13101.89); +INSERT INTO `demo_gdp_by_city` VALUES (3, '广东省', '佛山市', 5474.12); +INSERT INTO `demo_gdp_by_city` VALUES (4, '广东省', '东莞市', 5000.11); +INSERT INTO `demo_gdp_by_city` VALUES (5, '广东省', '惠州市', 2226.58); +INSERT INTO `demo_gdp_by_city` VALUES (6, '广东省', '珠海市', 1841.47); +INSERT INTO `demo_gdp_by_city` VALUES (7, '广东省', '茂名市', 1660.62); +INSERT INTO `demo_gdp_by_city` VALUES (8, '广东省', '江门市', 1656.57); +INSERT INTO `demo_gdp_by_city` VALUES (9, '广东省', '中山市', 1651.20); +INSERT INTO `demo_gdp_by_city` VALUES (10, '广东省', '湛江市', 1620.41); +INSERT INTO `demo_gdp_by_city` VALUES (11, '广东省', '汕头市', 1377.60); +INSERT INTO `demo_gdp_by_city` VALUES (12, '广东省', '肇庆市', 1125.57); +INSERT INTO `demo_gdp_by_city` VALUES (13, '广东省', '揭阳市', 1034.39); +INSERT INTO `demo_gdp_by_city` VALUES (14, '广东省', '清远市', 900.40); +INSERT INTO `demo_gdp_by_city` VALUES (15, '广东省', '阳江市', 719.32); +INSERT INTO `demo_gdp_by_city` VALUES (16, '广东省', '韶关市', 709.06); +INSERT INTO `demo_gdp_by_city` VALUES (17, '广东省', '梅州市', 603.30); +INSERT INTO `demo_gdp_by_city` VALUES (18, '广东省', '汕尾市', 587.62); +INSERT INTO `demo_gdp_by_city` VALUES (19, '广东省', '潮州市', 575.88); +INSERT INTO `demo_gdp_by_city` VALUES (20, '广东省', '河源市', 546.35); +INSERT INTO `demo_gdp_by_city` VALUES (21, '广东省', '云浮市', 489.34); +INSERT INTO `demo_gdp_by_city` VALUES (22, '江苏省', '苏州市', 10684.66); +INSERT INTO `demo_gdp_by_city` VALUES (23, '江苏省', '南京市', 7622.77); +INSERT INTO `demo_gdp_by_city` VALUES (24, '江苏省', '无锡市', 6499.21); +INSERT INTO `demo_gdp_by_city` VALUES (25, '江苏省', '南通市', 5483.17); +INSERT INTO `demo_gdp_by_city` VALUES (26, '江苏省', '常州市', 4089.00); +INSERT INTO `demo_gdp_by_city` VALUES (27, '江苏省', '徐州市', 3607.39); +INSERT INTO `demo_gdp_by_city` VALUES (28, '江苏省', '扬州市', 3064.78); +INSERT INTO `demo_gdp_by_city` VALUES (29, '江苏省', '盐城市', 3045.00); +INSERT INTO `demo_gdp_by_city` VALUES (30, '江苏省', '泰州市', 2860.04); +INSERT INTO `demo_gdp_by_city` VALUES (31, '江苏省', '镇江市', 2389.90); +INSERT INTO `demo_gdp_by_city` VALUES (32, '江苏省', '淮安市', 2174.46); +INSERT INTO `demo_gdp_by_city` VALUES (33, '江苏省', '连云港市', 1716.80); +INSERT INTO `demo_gdp_by_city` VALUES (34, '江苏省', '宿迁市', 1653.19); +INSERT INTO `demo_gdp_by_city` VALUES (35, '山东省', '青岛市', 6539.21); +INSERT INTO `demo_gdp_by_city` VALUES (36, '山东省', '济南市', 5198.75); +INSERT INTO `demo_gdp_by_city` VALUES (37, '山东省', '烟台市', 3918.38); +INSERT INTO `demo_gdp_by_city` VALUES (38, '山东省', '潍坊市', 3269.30); +INSERT INTO `demo_gdp_by_city` VALUES (39, '山东省', '临沂市', 2552.90); +INSERT INTO `demo_gdp_by_city` VALUES (40, '山东省', '济宁市', 2379.66); +INSERT INTO `demo_gdp_by_city` VALUES (41, '山东省', '淄博市', 2003.92); +INSERT INTO `demo_gdp_by_city` VALUES (42, '山东省', '菏泽市', 1927.21); +INSERT INTO `demo_gdp_by_city` VALUES (43, '山东省', '德州市', 1663.27); +INSERT INTO `demo_gdp_by_city` VALUES (44, '山东省', '东营市', 1617.45); +INSERT INTO `demo_gdp_by_city` VALUES (45, '山东省', '威海市', 1516.02); +INSERT INTO `demo_gdp_by_city` VALUES (46, '山东省', '泰安市', 1474.50); +INSERT INTO `demo_gdp_by_city` VALUES (47, '山东省', '滨州市', 1328.25); +INSERT INTO `demo_gdp_by_city` VALUES (48, '山东省', '聊城市', 1257.97); +INSERT INTO `demo_gdp_by_city` VALUES (49, '山东省', '日照市', 1037.35); +INSERT INTO `demo_gdp_by_city` VALUES (50, '山东省', '枣庄市', 926.11); +INSERT INTO `demo_gdp_by_city` VALUES (51, '浙江省', '杭州市', 8656.03); +INSERT INTO `demo_gdp_by_city` VALUES (52, '浙江省', '宁波市', 6640.59); +INSERT INTO `demo_gdp_by_city` VALUES (53, '浙江省', '温州市', 3644.23); +INSERT INTO `demo_gdp_by_city` VALUES (54, '浙江省', '绍兴市', 3188.61); +INSERT INTO `demo_gdp_by_city` VALUES (55, '浙江省', '嘉兴市', 2942.14); +INSERT INTO `demo_gdp_by_city` VALUES (56, '浙江省', '台州市', 2722.97); +INSERT INTO `demo_gdp_by_city` VALUES (57, '浙江省', '金华市', 2506.37); +INSERT INTO `demo_gdp_by_city` VALUES (58, '浙江省', '湖州市', 1712.68); +INSERT INTO `demo_gdp_by_city` VALUES (59, '浙江省', '衢州市', 874.25); +INSERT INTO `demo_gdp_by_city` VALUES (60, '浙江省', '丽水市', 830.04); +INSERT INTO `demo_gdp_by_city` VALUES (61, '浙江省', '舟山市', 796.93); +INSERT INTO `demo_gdp_by_city` VALUES (62, '河南省', '郑州市', 6314.90); +INSERT INTO `demo_gdp_by_city` VALUES (63, '河南省', '洛阳市', 2369.99); +INSERT INTO `demo_gdp_by_city` VALUES (64, '河南省', '南阳市', 2063.56); +INSERT INTO `demo_gdp_by_city` VALUES (65, '河南省', '周口市', 1710.45); +INSERT INTO `demo_gdp_by_city` VALUES (66, '河南省', '新乡市', 1537.91); +INSERT INTO `demo_gdp_by_city` VALUES (67, '河南省', '商丘市', 1481.44); +INSERT INTO `demo_gdp_by_city` VALUES (68, '河南省', '信阳市', 1429.81); +INSERT INTO `demo_gdp_by_city` VALUES (69, '河南省', '平顶山市', 1288.61); +INSERT INTO `demo_gdp_by_city` VALUES (70, '河南省', '开封市', 1242.11); +INSERT INTO `demo_gdp_by_city` VALUES (71, '河南省', '安阳市', 1176.30); +INSERT INTO `demo_gdp_by_city` VALUES (72, '河南省', '濮阳市', 842.31); +INSERT INTO `demo_gdp_by_city` VALUES (73, '河南省', '三门峡市', 735.39); +INSERT INTO `demo_gdp_by_city` VALUES (74, '河南省', '鹤壁市', 526.56); +INSERT INTO `demo_gdp_by_city` VALUES (75, '四川省', '成都市', 9602.72); +INSERT INTO `demo_gdp_by_city` VALUES (76, '四川省', '绵阳市', 1546.17); +INSERT INTO `demo_gdp_by_city` VALUES (77, '四川省', '宜宾市', 1381.79); +INSERT INTO `demo_gdp_by_city` VALUES (78, '四川省', '德阳市', 1228.69); +INSERT INTO `demo_gdp_by_city` VALUES (79, '四川省', '南充市', 1143.36); +INSERT INTO `demo_gdp_by_city` VALUES (80, '四川省', '泸州市', 1122.80); +INSERT INTO `demo_gdp_by_city` VALUES (81, '四川省', '达州市', 1061.60); +INSERT INTO `demo_gdp_by_city` VALUES (82, '四川省', '乐山市', 1005.89); +INSERT INTO `demo_gdp_by_city` VALUES (83, '四川省', '凉山州', 912.81); +INSERT INTO `demo_gdp_by_city` VALUES (84, '四川省', '内江市', 744.07); +INSERT INTO `demo_gdp_by_city` VALUES (85, '四川省', '自贡市', 740.07); +INSERT INTO `demo_gdp_by_city` VALUES (86, '四川省', '眉山市', 738.99); +INSERT INTO `demo_gdp_by_city` VALUES (87, '四川省', '遂宁市', 718.16); +INSERT INTO `demo_gdp_by_city` VALUES (88, '四川省', '广安市', 655.90); +INSERT INTO `demo_gdp_by_city` VALUES (89, '四川省', '攀枝花市', 561.96); +INSERT INTO `demo_gdp_by_city` VALUES (90, '四川省', '广元市', 505.01); +INSERT INTO `demo_gdp_by_city` VALUES (91, '四川省', '资阳市', 426.90); +INSERT INTO `demo_gdp_by_city` VALUES (92, '四川省', '雅安市', 380.47); +INSERT INTO `demo_gdp_by_city` VALUES (93, '四川省', '巴中市', 377.87); +INSERT INTO `demo_gdp_by_city` VALUES (94, '四川省', '阿坝州', 196.06); +INSERT INTO `demo_gdp_by_city` VALUES (95, '四川省', '甘孜州', 181.07); +INSERT INTO `demo_gdp_by_city` VALUES (96, '福建省', '泉州市', 5362.71); +INSERT INTO `demo_gdp_by_city` VALUES (97, '福建省', '福州市', 5011.09); +INSERT INTO `demo_gdp_by_city` VALUES (98, '福建省', '厦门市', 3399.85); +INSERT INTO `demo_gdp_by_city` VALUES (99, '福建省', '漳州市', 2422.86); +INSERT INTO `demo_gdp_by_city` VALUES (100, '福建省', '龙岩市', 1487.09); +INSERT INTO `demo_gdp_by_city` VALUES (101, '福建省', '莆田市', 1486.50); +INSERT INTO `demo_gdp_by_city` VALUES (102, '福建省', '宁德市', 1467.20); +INSERT INTO `demo_gdp_by_city` VALUES (103, '福建省', '三明市', 1316.52); +INSERT INTO `demo_gdp_by_city` VALUES (104, '福建省', '南平市', 945.49); +INSERT INTO `demo_gdp_by_city` VALUES (105, '湖北省', '武汉市', 8251.50); +INSERT INTO `demo_gdp_by_city` VALUES (106, '湖北省', '襄阳市', 2377.58); +INSERT INTO `demo_gdp_by_city` VALUES (107, '湖北省', '宜昌市', 2166.61); +INSERT INTO `demo_gdp_by_city` VALUES (108, '湖北省', '荆州市', 1235.90); +INSERT INTO `demo_gdp_by_city` VALUES (109, '湖北省', '孝感市', 1169.08); +INSERT INTO `demo_gdp_by_city` VALUES (110, '湖北省', '黄冈市', 1082.32); +INSERT INTO `demo_gdp_by_city` VALUES (111, '湖北省', '十堰市', 1022.40); +INSERT INTO `demo_gdp_by_city` VALUES (112, '湖北省', '荆门市', 976.61); +INSERT INTO `demo_gdp_by_city` VALUES (113, '湖北省', '黄石市', 871.44); +INSERT INTO `demo_gdp_by_city` VALUES (114, '湖北省', '咸宁市', 802.81); +INSERT INTO `demo_gdp_by_city` VALUES (115, '湖北省', '随州市', 584.34); +INSERT INTO `demo_gdp_by_city` VALUES (116, '湖北省', '恩施市', 569.02); +INSERT INTO `demo_gdp_by_city` VALUES (117, '湖北省', '鄂州市', 539.59); +INSERT INTO `demo_gdp_by_city` VALUES (118, '湖北省', '潜江市', 396.68); +INSERT INTO `demo_gdp_by_city` VALUES (119, '湖北省', '仙桃市', 383.11); +INSERT INTO `demo_gdp_by_city` VALUES (120, '湖北省', '天门市', 303.11); +INSERT INTO `demo_gdp_by_city` VALUES (121, '湖南省', '长沙市', 6365.76); +INSERT INTO `demo_gdp_by_city` VALUES (122, '湖南省', '岳阳市', 1980.08); +INSERT INTO `demo_gdp_by_city` VALUES (123, '湖南省', '常德市', 1885.30); +INSERT INTO `demo_gdp_by_city` VALUES (124, '湖南省', '衡阳市', 1802.70); +INSERT INTO `demo_gdp_by_city` VALUES (125, '湖南省', '株洲市', 1604.50); +INSERT INTO `demo_gdp_by_city` VALUES (126, '湖南省', '郴州市', 1298.11); +INSERT INTO `demo_gdp_by_city` VALUES (127, '湖南省', '湘潭市', 1209.90); +INSERT INTO `demo_gdp_by_city` VALUES (128, '湖南省', '邵阳市', 1130.19); +INSERT INTO `demo_gdp_by_city` VALUES (129, '湖南省', '永州市', 1064.84); +INSERT INTO `demo_gdp_by_city` VALUES (130, '湖南省', '益阳市', 937.69); +INSERT INTO `demo_gdp_by_city` VALUES (131, '湖南省', '娄底市', 870.80); +INSERT INTO `demo_gdp_by_city` VALUES (132, '湖南省', '怀化市', 861.65); +INSERT INTO `demo_gdp_by_city` VALUES (133, '湖南省', '湘西州', 372.10); +INSERT INTO `demo_gdp_by_city` VALUES (134, '湖南省', '张家界市', 287.50); +INSERT INTO `demo_gdp_by_city` VALUES (135, '安徽省', '合肥市', 5203.46); +INSERT INTO `demo_gdp_by_city` VALUES (136, '安徽省', '芜湖市', 2038.15); +INSERT INTO `demo_gdp_by_city` VALUES (137, '安徽省', '滁州市', 1664.70); +INSERT INTO `demo_gdp_by_city` VALUES (138, '安徽省', '阜阳市', 1489.10); +INSERT INTO `demo_gdp_by_city` VALUES (139, '安徽省', '安庆市', 1314.30); +INSERT INTO `demo_gdp_by_city` VALUES (140, '安徽省', '马鞍山市', 1221.99); +INSERT INTO `demo_gdp_by_city` VALUES (141, '安徽省', '宿州市', 1074.80); +INSERT INTO `demo_gdp_by_city` VALUES (142, '安徽省', '蚌埠市', 1042.94); +INSERT INTO `demo_gdp_by_city` VALUES (143, '安徽省', '亳州市', 971.05); +INSERT INTO `demo_gdp_by_city` VALUES (144, '安徽省', '六安市', 912.70); +INSERT INTO `demo_gdp_by_city` VALUES (145, '安徽省', '宣城市', 877.20); +INSERT INTO `demo_gdp_by_city` VALUES (146, '安徽省', '淮南市', 693.70); +INSERT INTO `demo_gdp_by_city` VALUES (147, '安徽省', '淮北市', 588.00); +INSERT INTO `demo_gdp_by_city` VALUES (148, '安徽省', '铜陵市', 542.35); +INSERT INTO `demo_gdp_by_city` VALUES (149, '安徽省', '池州市', 480.40); +INSERT INTO `demo_gdp_by_city` VALUES (150, '安徽省', '黄山市', 450.93); +INSERT INTO `demo_gdp_by_city` VALUES (151, '上海市', '上海市', 20102.00); +INSERT INTO `demo_gdp_by_city` VALUES (152, '重庆市', '重庆市', 12903.00); +INSERT INTO `demo_gdp_by_city` VALUES (153, '北京市', '北京市', 19228.00); +INSERT INTO `demo_gdp_by_city` VALUES (154, '河北省', '唐山市', 3805.40); +INSERT INTO `demo_gdp_by_city` VALUES (155, '河北省', '石家庄市', 3164.10); +INSERT INTO `demo_gdp_by_city` VALUES (156, '河北省', '沧州市', 1992.20); +INSERT INTO `demo_gdp_by_city` VALUES (157, '河北省', '邯郸市', 1990.80); +INSERT INTO `demo_gdp_by_city` VALUES (158, '河北省', '保定市', 1929.00); +INSERT INTO `demo_gdp_by_city` VALUES (159, '河北省', '廊坊市', 1440.70); +INSERT INTO `demo_gdp_by_city` VALUES (160, '河北省', '邢台市', 1073.70); +INSERT INTO `demo_gdp_by_city` VALUES (161, '河北省', '秦皇岛市', 930.04); +INSERT INTO `demo_gdp_by_city` VALUES (162, '河北省', '衡水市', 762.40); +INSERT INTO `demo_gdp_by_city` VALUES (163, '河北省', '张家口市', 753.70); +INSERT INTO `demo_gdp_by_city` VALUES (164, '河北省', '承德市', 718.60); +INSERT INTO `demo_gdp_by_city` VALUES (165, '河北省', '定州市', 193.40); +INSERT INTO `demo_gdp_by_city` VALUES (166, '江西省', '南昌市', 3155.75); +INSERT INTO `demo_gdp_by_city` VALUES (167, '江西省', '赣州市', 1966.76); +INSERT INTO `demo_gdp_by_city` VALUES (168, '江西省', '九江市', 1780.56); +INSERT INTO `demo_gdp_by_city` VALUES (169, '江西省', '宜春市', 1517.09); +INSERT INTO `demo_gdp_by_city` VALUES (170, '江西省', '上饶市', 1411.99); +INSERT INTO `demo_gdp_by_city` VALUES (171, '江西省', '吉安市', 1179.88); +INSERT INTO `demo_gdp_by_city` VALUES (172, '江西省', '抚州市', 827.60); +INSERT INTO `demo_gdp_by_city` VALUES (173, '江西省', '新余市', 542.58); +INSERT INTO `demo_gdp_by_city` VALUES (174, '江西省', '鹰潭市', 540.79); +INSERT INTO `demo_gdp_by_city` VALUES (175, '江西省', '萍乡市', 529.16); +INSERT INTO `demo_gdp_by_city` VALUES (176, '江西省', '景德镇市', 525.06); +INSERT INTO `demo_gdp_by_city` VALUES (177, '陕西省', '西安市', 5099.62); +INSERT INTO `demo_gdp_by_city` VALUES (178, '陕西省', '榆林市', 2212.76); +INSERT INTO `demo_gdp_by_city` VALUES (179, '陕西省', '宝鸡市', 1144.28); +INSERT INTO `demo_gdp_by_city` VALUES (180, '陕西省', '咸阳市', 1118.44); +INSERT INTO `demo_gdp_by_city` VALUES (181, '陕西省', '渭南市', 937.51); +INSERT INTO `demo_gdp_by_city` VALUES (182, '陕西省', '延安市', 861.87); +INSERT INTO `demo_gdp_by_city` VALUES (183, '陕西省', '汉中市', 848.74); +INSERT INTO `demo_gdp_by_city` VALUES (184, '陕西省', '安康市', 577.20); +INSERT INTO `demo_gdp_by_city` VALUES (185, '陕西省', '商洛市', 375.27); +INSERT INTO `demo_gdp_by_city` VALUES (186, '陕西省', '铜川市', 201.47); +INSERT INTO `demo_gdp_by_city` VALUES (187, '陕西省', '杨凌区', 77.57); +INSERT INTO `demo_gdp_by_city` VALUES (188, '云南省', '昆明市', 3620.37); +INSERT INTO `demo_gdp_by_city` VALUES (189, '云南省', '曲靖市', 1497.73); +INSERT INTO `demo_gdp_by_city` VALUES (190, '云南省', '红河州', 1299.71); +INSERT INTO `demo_gdp_by_city` VALUES (191, '云南省', '玉溪市', 1139.82); +INSERT INTO `demo_gdp_by_city` VALUES (192, '云南省', '楚雄州', 725.31); +INSERT INTO `demo_gdp_by_city` VALUES (193, '云南省', '大理州', 710.74); +INSERT INTO `demo_gdp_by_city` VALUES (194, '云南省', '昭通市', 660.91); +INSERT INTO `demo_gdp_by_city` VALUES (195, '云南省', '文山州', 580.70); +INSERT INTO `demo_gdp_by_city` VALUES (196, '云南省', '保山市', 514.21); +INSERT INTO `demo_gdp_by_city` VALUES (197, '云南省', '普洱市', 449.18); +INSERT INTO `demo_gdp_by_city` VALUES (198, '云南省', '临沧市', 383.82); +INSERT INTO `demo_gdp_by_city` VALUES (199, '云南省', '西双版纳州', 307.87); +INSERT INTO `demo_gdp_by_city` VALUES (200, '云南省', '德宏州', 284.23); +INSERT INTO `demo_gdp_by_city` VALUES (201, '云南省', '丽江市', 264.16); +INSERT INTO `demo_gdp_by_city` VALUES (202, '云南省', '迪庆州', 143.27); +INSERT INTO `demo_gdp_by_city` VALUES (203, '云南省', '怒江州', 98.19); +INSERT INTO `demo_gdp_by_city` VALUES (204, '辽宁省', '大连市', 3632.40); +INSERT INTO `demo_gdp_by_city` VALUES (205, '辽宁省', '沈阳市', 3303.60); +INSERT INTO `demo_gdp_by_city` VALUES (206, '辽宁省', '鞍山市', 879.60); +INSERT INTO `demo_gdp_by_city` VALUES (207, '辽宁省', '盘锦市', 674.70); +INSERT INTO `demo_gdp_by_city` VALUES (208, '辽宁省', '营口市', 660.20); +INSERT INTO `demo_gdp_by_city` VALUES (209, '辽宁省', '锦州市', 533.60); +INSERT INTO `demo_gdp_by_city` VALUES (210, '辽宁省', '朝阳市', 422.40); +INSERT INTO `demo_gdp_by_city` VALUES (211, '辽宁省', '本溪市', 417.60); +INSERT INTO `demo_gdp_by_city` VALUES (212, '辽宁省', '抚顺市', 398.80); +INSERT INTO `demo_gdp_by_city` VALUES (213, '辽宁省', '辽阳市', 387.30); +INSERT INTO `demo_gdp_by_city` VALUES (214, '辽宁省', '丹东市', 381.60); +INSERT INTO `demo_gdp_by_city` VALUES (215, '辽宁省', '葫芦岛市', 375.10); +INSERT INTO `demo_gdp_by_city` VALUES (216, '辽宁省', '铁岭市', 322.40); +INSERT INTO `demo_gdp_by_city` VALUES (217, '辽宁省', '阜新市', 251.90); +INSERT INTO `demo_gdp_by_city` VALUES (218, '广西壮族自治区', '南宁市', 1199.24); +INSERT INTO `demo_gdp_by_city` VALUES (219, '广西壮族自治区', '柳州市', 742.12); +INSERT INTO `demo_gdp_by_city` VALUES (220, '广西壮族自治区', '桂林市', 541.48); +INSERT INTO `demo_gdp_by_city` VALUES (221, '广西壮族自治区', '玉林市', 441.76); +INSERT INTO `demo_gdp_by_city` VALUES (222, '广西壮族自治区', '贵港市', 368.41); +INSERT INTO `demo_gdp_by_city` VALUES (223, '广西壮族自治区', '百色市', 338.81); +INSERT INTO `demo_gdp_by_city` VALUES (224, '广西壮族自治区', '钦州市', 328.68); +INSERT INTO `demo_gdp_by_city` VALUES (225, '广西壮族自治区', '北海市', 326.35); +INSERT INTO `demo_gdp_by_city` VALUES (226, '广西壮族自治区', '梧州市', 255.16); +INSERT INTO `demo_gdp_by_city` VALUES (227, '广西壮族自治区', '河池市', 225.03); +INSERT INTO `demo_gdp_by_city` VALUES (228, '广西壮族自治区', '崇左市', 207.51); +INSERT INTO `demo_gdp_by_city` VALUES (229, '广西壮族自治区', '防城港市', 199.82); +INSERT INTO `demo_gdp_by_city` VALUES (230, '广西壮族自治区', '贺州市', 183.58); +INSERT INTO `demo_gdp_by_city` VALUES (231, '广西壮族自治区', '来宾市', 167.14); +INSERT INTO `demo_gdp_by_city` VALUES (232, '山西省', '太原市', 2181.81); +INSERT INTO `demo_gdp_by_city` VALUES (233, '山西省', '长治市', 978.10); +INSERT INTO `demo_gdp_by_city` VALUES (234, '山西省', '运城市', 869.60); +INSERT INTO `demo_gdp_by_city` VALUES (235, '山西省', '吕梁市', 837.50); +INSERT INTO `demo_gdp_by_city` VALUES (236, '山西省', '晋城市', 820.80); +INSERT INTO `demo_gdp_by_city` VALUES (237, '山西省', '临汾市', 798.10); +INSERT INTO `demo_gdp_by_city` VALUES (238, '山西省', '晋中市', 785.60); +INSERT INTO `demo_gdp_by_city` VALUES (239, '山西省', '大同市', 760.10); +INSERT INTO `demo_gdp_by_city` VALUES (240, '山西省', '朔州市', 592.30); +INSERT INTO `demo_gdp_by_city` VALUES (241, '山西省', '忻州市', 580.80); +INSERT INTO `demo_gdp_by_city` VALUES (242, '山西省', '阳泉市', 402.10); +INSERT INTO `demo_gdp_by_city` VALUES (243, '内蒙古自治区', '鄂尔多斯', 2039.89); +INSERT INTO `demo_gdp_by_city` VALUES (244, '内蒙古自治区', '包头', 1627.00); +INSERT INTO `demo_gdp_by_city` VALUES (245, '内蒙古自治区', '呼和浩特', 1539.00); +INSERT INTO `demo_gdp_by_city` VALUES (246, '内蒙古自治区', '赤峰', 848.30); +INSERT INTO `demo_gdp_by_city` VALUES (247, '内蒙古自治区', '呼伦贝尔', 502.42); +INSERT INTO `demo_gdp_by_city` VALUES (248, '内蒙古自治区', '锡林郭勒', 408.42); +INSERT INTO `demo_gdp_by_city` VALUES (249, '内蒙古自治区', '巴彦淖尔', 399.90); +INSERT INTO `demo_gdp_by_city` VALUES (250, '内蒙古自治区', '乌兰察布', 397.40); +INSERT INTO `demo_gdp_by_city` VALUES (251, '内蒙古自治区', '乌海', 319.45); +INSERT INTO `demo_gdp_by_city` VALUES (252, '内蒙古自治区', '兴安', 231.06); +INSERT INTO `demo_gdp_by_city` VALUES (253, '贵州省', '贵阳市', 2042.15); +INSERT INTO `demo_gdp_by_city` VALUES (254, '贵州省', '遵义市', 1971.75); +INSERT INTO `demo_gdp_by_city` VALUES (255, '贵州省', '毕节市', 1019.23); +INSERT INTO `demo_gdp_by_city` VALUES (256, '贵州省', '黔南市', 838.60); +INSERT INTO `demo_gdp_by_city` VALUES (257, '贵州省', '六盘水市', 728.22); +INSERT INTO `demo_gdp_by_city` VALUES (258, '贵州省', '铜仁市', 702.01); +INSERT INTO `demo_gdp_by_city` VALUES (259, '贵州省', '黔西南', 683.28); +INSERT INTO `demo_gdp_by_city` VALUES (260, '贵州省', '黔东南', 549.44); +INSERT INTO `demo_gdp_by_city` VALUES (261, '贵州省', '安顺市', 540.80); +INSERT INTO `demo_gdp_by_city` VALUES (262, '天津市', '天津市', 7309.00); +INSERT INTO `demo_gdp_by_city` VALUES (263, '吉林省', '长春市', 3435.51); +INSERT INTO `demo_gdp_by_city` VALUES (264, '吉林省', '吉林市', 698.05); +INSERT INTO `demo_gdp_by_city` VALUES (265, '吉林省', '延边州', 379.85); +INSERT INTO `demo_gdp_by_city` VALUES (266, '吉林省', '松原市', 342.26); +INSERT INTO `demo_gdp_by_city` VALUES (267, '吉林省', '通化市', 337.79); +INSERT INTO `demo_gdp_by_city` VALUES (268, '吉林省', '四平市', 255.27); +INSERT INTO `demo_gdp_by_city` VALUES (269, '吉林省', '白城市', 220.47); +INSERT INTO `demo_gdp_by_city` VALUES (270, '吉林省', '辽源市', 209.80); +INSERT INTO `demo_gdp_by_city` VALUES (271, '吉林省', '白山市', 196.01); +INSERT INTO `demo_gdp_by_city` VALUES (272, '黑龙江省', NULL, 5990.00); +INSERT INTO `demo_gdp_by_city` VALUES (273, '甘肃省', '兰州市', 1628.39); +INSERT INTO `demo_gdp_by_city` VALUES (274, '甘肃省', '庆阳市', 373.30); +INSERT INTO `demo_gdp_by_city` VALUES (275, '甘肃省', '天水市', 333.80); +INSERT INTO `demo_gdp_by_city` VALUES (276, '甘肃省', '酒泉市', 326.10); +INSERT INTO `demo_gdp_by_city` VALUES (277, '甘肃省', '白银市', 263.08); +INSERT INTO `demo_gdp_by_city` VALUES (278, '甘肃省', '武威市', 256.12); +INSERT INTO `demo_gdp_by_city` VALUES (279, '甘肃省', '陇南市', 238.00); +INSERT INTO `demo_gdp_by_city` VALUES (280, '甘肃省', '平凉市', 233.20); +INSERT INTO `demo_gdp_by_city` VALUES (281, '甘肃省', '张掖市', 232.95); +INSERT INTO `demo_gdp_by_city` VALUES (282, '甘肃省', '定西市', 215.10); +INSERT INTO `demo_gdp_by_city` VALUES (283, '甘肃省', '金昌市', 207.11); +INSERT INTO `demo_gdp_by_city` VALUES (284, '甘肃省', '临夏州', 169.90); +INSERT INTO `demo_gdp_by_city` VALUES (285, '甘肃省', '嘉峪关市', 158.00); +INSERT INTO `demo_gdp_by_city` VALUES (286, '甘肃省', '甘南州', 113.12); +INSERT INTO `demo_gdp_by_city` VALUES (287, '海南省', '海口市', 861.81); +INSERT INTO `demo_gdp_by_city` VALUES (288, '海南省', '三亚市', 399.80); +INSERT INTO `demo_gdp_by_city` VALUES (289, '海南省', '儋州市', 188.57); +INSERT INTO `demo_gdp_by_city` VALUES (290, '海南省', '洋浦', 185.03); +INSERT INTO `demo_gdp_by_city` VALUES (291, '海南省', '澄迈县', 184.92); +INSERT INTO `demo_gdp_by_city` VALUES (292, '海南省', '琼海市', 147.97); +INSERT INTO `demo_gdp_by_city` VALUES (293, '海南省', '文昌市', 145.41); +INSERT INTO `demo_gdp_by_city` VALUES (294, '海南省', '万宁市', 126.81); +INSERT INTO `demo_gdp_by_city` VALUES (295, '海南省', '临高县', 106.13); +INSERT INTO `demo_gdp_by_city` VALUES (296, '海南省', '东方市', 104.26); +INSERT INTO `demo_gdp_by_city` VALUES (297, '海南省', '陵水县', 101.74); +INSERT INTO `demo_gdp_by_city` VALUES (298, '海南省', '乐东县', 79.02); +INSERT INTO `demo_gdp_by_city` VALUES (299, '海南省', '昌江县', 65.56); +INSERT INTO `demo_gdp_by_city` VALUES (300, '海南省', '定安县', 52.37); +INSERT INTO `demo_gdp_by_city` VALUES (301, '海南省', '屯昌县', 42.14); +INSERT INTO `demo_gdp_by_city` VALUES (302, '海南省', '保亭县', 26.87); +INSERT INTO `demo_gdp_by_city` VALUES (303, '海南省', '琼中县', 25.16); +INSERT INTO `demo_gdp_by_city` VALUES (304, '海南省', '白沙县', 24.87); +INSERT INTO `demo_gdp_by_city` VALUES (305, '海南省', '五指山市', 15.87); +INSERT INTO `demo_gdp_by_city` VALUES (306, '青海省', NULL, 1557.00); +INSERT INTO `demo_gdp_by_city` VALUES (307, '新疆维吾尔自治区', NULL, 7329.00); +INSERT INTO `demo_gdp_by_city` VALUES (308, '西藏自治区', NULL, 926.05); COMMIT; -- ---------------------------- --- Table structure for ds_3228159e_6bc2_4f22_908c_97e48de64bb1 +-- Table structure for demo_gdp_by_city_top10 -- ---------------------------- -DROP TABLE IF EXISTS `ds_3228159e_6bc2_4f22_908c_97e48de64bb1`; -CREATE TABLE `ds_3228159e_6bc2_4f22_908c_97e48de64bb1` ( - `dataease_uuid` VARCHAR(50) NULL DEFAULT NULL, - `C_7e687515fc569cc19b4e7e9f882ae87e` VARCHAR(2000) NULL DEFAULT NULL, - `C_796d4f300bdb84d32e5af293d0a55d0a` BIGINT NULL DEFAULT NULL, - `C_1ac09d719896555bd1e6f26505fe2cc9` BIGINT NULL DEFAULT NULL, - `C_1ab1341da0ac7cf6475ccfc8e5d4890c` BIGINT NULL DEFAULT NULL, - `C_68b48f068432ea055c8dd528ab0548f9` BIGINT NULL DEFAULT NULL, - `C_c50d83986f203b1ae0a7ce42faea516a` BIGINT NULL DEFAULT NULL, - `C_a11b6c9bee6500646cdb00cd76412a40` BIGINT NULL DEFAULT NULL -) ENGINE = InnoDB COMMENT = 'OLAP'; +DROP TABLE IF EXISTS `demo_gdp_by_city_top10`; +CREATE TABLE `demo_gdp_by_city_top10` ( + `id` int(11) NOT NULL DEFAULT '0', + `province` varchar(255) DEFAULT NULL, + `city` varchar(255) DEFAULT NULL, + `gdp` double(255,2) DEFAULT NULL +) ENGINE=InnoDB DEFAULT CHARSET=utf8; -- ---------------------------- --- Records of ds_3228159e_6bc2_4f22_908c_97e48de64bb1 +-- Records of demo_gdp_by_city_top10 -- ---------------------------- BEGIN; -INSERT INTO `ds_3228159e_6bc2_4f22_908c_97e48de64bb1` VALUES ('a75cff1b25a212497b20d572fa0192ef', '2013年', 934935, 474125, 460810, 43002, 11997, 31005), ('40c44ea8292d40fa10aa82085f1ee93b', '2014年', 938993, 475585, 463408, 46210, 11914, 34296), ('9c48886eb131f65ab4d21742404e6fc7', '2015年', 17790430, 9011377, 8779053, 964050, 260677, 703374), ('80a07ab0f2233f1af4a42bcaa6586898', '2018年', 951685, 481358, 470327, 47007, 11641, 35366), ('a048ea7426d69bee451dec44762e3dbd', '2017年', 952893, 482331, 470561, 46221, 11668, 34554), ('a45f9d8cae235bddad38806129dd1f87', '2011年', 956619, 484840, 471779, 49876, 13240, 36636), ('1cabb0cfc23ba6ffa14c9030299c0efe', '2012年', 939526, 476037, 463489, 46619, 12699, 33920), ('f56b990a6ded5358427a463dcfebf2fd', '2019年', 908609, 459235, 449374, 41696, 10185, 31511), ('41102c3c0b49375655e44157a4d45e5d', '2016年', 965321, 488944, 476376, 50980, 13402, 37578); +INSERT INTO `demo_gdp_by_city_top10` VALUES (151, '上海市', '上海市', 20102.00); +INSERT INTO `demo_gdp_by_city_top10` VALUES (153, '北京市', '北京市', 19228.00); +INSERT INTO `demo_gdp_by_city_top10` VALUES (1, '广东省', '深圳市', 14324.47); +INSERT INTO `demo_gdp_by_city_top10` VALUES (2, '广东省', '广州市', 13101.89); +INSERT INTO `demo_gdp_by_city_top10` VALUES (152, '重庆市', '重庆市', 12903.00); +INSERT INTO `demo_gdp_by_city_top10` VALUES (22, '江苏省', '苏州市', 10684.66); +INSERT INTO `demo_gdp_by_city_top10` VALUES (75, '四川省', '成都市', 9602.72); +INSERT INTO `demo_gdp_by_city_top10` VALUES (51, '浙江省', '杭州市', 8656.03); +INSERT INTO `demo_gdp_by_city_top10` VALUES (105, '湖北省', '武汉市', 8251.50); +INSERT INTO `demo_gdp_by_city_top10` VALUES (23, '江苏省', '南京市', 7622.77); COMMIT; -- ---------------------------- --- Table structure for ds_a6e341c1_8b38_4a27_b812_22ec8f0cc2c7 +-- Table structure for demo_gdp_by_industry -- ---------------------------- -DROP TABLE IF EXISTS `ds_a6e341c1_8b38_4a27_b812_22ec8f0cc2c7`; -CREATE TABLE `ds_a6e341c1_8b38_4a27_b812_22ec8f0cc2c7` ( - `dataease_uuid` VARCHAR(50) NULL DEFAULT NULL, - `C_7e687515fc569cc19b4e7e9f882ae87e` VARCHAR(2000) NULL DEFAULT NULL, - `C_c7f2d4339c0b8a3db34212b0987e5038` BIGINT NULL DEFAULT NULL, - `C_64a513b0097ced14a2291054a8260394` BIGINT NULL DEFAULT NULL, - `C_cd6582f225497d1495f2b473220ae85d` BIGINT NULL DEFAULT NULL, - `C_185616188c012181aaca0a092c50b0fc` BIGINT NULL DEFAULT NULL, - `C_94c1225e5a57bb2da2fe0578a7789da7` BIGINT NULL DEFAULT NULL, - `C_a08fe595bbb49a862bfab24964098dbb` BIGINT NULL DEFAULT NULL, - `C_246d81170669bcac7711e9a9783289f5` BIGINT NULL DEFAULT NULL, - `C_a2f4f848a7e4df2891fa9d8d8aa06bcf` BIGINT NULL DEFAULT NULL, - `C_6bf465698bea29d70f1674bbbe31f4c0` BIGINT NULL DEFAULT NULL, - `C_ff76506222f44df3390353c228b22628` BIGINT NULL DEFAULT NULL, - `C_2cac4a8ae080bfefadfe646aa812acfd` BIGINT NULL DEFAULT NULL, - `C_df1a259dae8f1e50abe72347084c5331` BIGINT NULL DEFAULT NULL, - `C_f09755e9bfc002b64aa74490cf276c96` BIGINT NULL DEFAULT NULL, - `C_0adc32d4ef8e0e07966189cd8fb9b78b` BIGINT NULL DEFAULT NULL, - `C_75a049727e9f72e3f633009d03eda149` BIGINT NULL DEFAULT NULL, - `C_d3bf9f229ba0033b231e006ed8be7c05` BIGINT NULL DEFAULT NULL, - `C_836f4ccdc99a860318ce16e6c516a0bb` BIGINT NULL DEFAULT NULL, - `C_e7a3833f9bbe133b64f6f1ce69a5b693` BIGINT NULL DEFAULT NULL, - `C_aba589acab27bb78f3881c40996207b0` BIGINT NULL DEFAULT NULL, - `C_6480d83c469d2e9a04c6fcbbb2aef22a` BIGINT NULL DEFAULT NULL -) ENGINE = InnoDB COMMENT = 'OLAP'; +DROP TABLE IF EXISTS `demo_gdp_by_industry`; +CREATE TABLE `demo_gdp_by_industry` ( + `id` int(11) NOT NULL AUTO_INCREMENT, + `industry` varchar(255) DEFAULT NULL, + `GDP` varchar(255) DEFAULT NULL, + PRIMARY KEY (`id`) +) ENGINE=InnoDB AUTO_INCREMENT=4 DEFAULT CHARSET=utf8; -- ---------------------------- --- Records of ds_a6e341c1_8b38_4a27_b812_22ec8f0cc2c7 +-- Records of demo_gdp_by_industry -- ---------------------------- BEGIN; -INSERT INTO `ds_a6e341c1_8b38_4a27_b812_22ec8f0cc2c7` VALUES ('c6f6d07e7e1d35439206eacd59e2019b', '女性人口(万人)', 68844, 68969, 68677, 68361, 67925, 67469, 67124, 66663, 66262, 65755, 65343, 64803, 64445, 64081, 63720, 63381, 63012, 62671, 62338, 61955), ('3899d55a0108fa4a8c18d0e03f26454d', '年末总人口(万人)', 141178, 141008, 140541, 140011, 139232, 138326, 137646, 136726, 135922, 134916, 134091, 133450, 132802, 132129, 131448, 130756, 129988, 129227, 128453, 127627), ('095720d7dc5fdcae3b49aab333799481', '男性人口(万人)', 72334, 72039, 71864, 71650, 71307, 70857, 70522, 70063, 69660, 69161, 68748, 68647, 68357, 68048, 67728, 67375, 66976, 66556, 66115, 65672), ('dbc2f55e1d480646a962afc8a0a6f45b', '城镇人口(万人)', 90199, 88426, 86433, 84343, 81924, 79302, 76738, 74502, 72175, 69927, 66978, 64512, 62403, 60633, 58288, 56212, 54283, 52376, 50212, 48064), ('ad4cc912350c695816e10d2869449127', '乡村人口(万人)', 50979, 52582, 54108, 55668, 57308, 59024, 60908, 62224, 63747, 64989, 67113, 68938, 70399, 71496, 73160, 74544, 75705, 76851, 78241, 79563); +INSERT INTO `demo_gdp_by_industry` VALUES (1, '第一产业', '28402'); +INSERT INTO `demo_gdp_by_industry` VALUES (2, '第二产业', '207154'); +INSERT INTO `demo_gdp_by_industry` VALUES (3, '第三产业', '296611'); COMMIT; -- ---------------------------- --- Table structure for ds_c56d7462_6334_4583_a617_b249b2299ed1 +-- Table structure for demo_gdp_district_top100 -- ---------------------------- -DROP TABLE IF EXISTS `ds_c56d7462_6334_4583_a617_b249b2299ed1`; -CREATE TABLE `ds_c56d7462_6334_4583_a617_b249b2299ed1` ( - `dataease_uuid` VARCHAR(50) NULL DEFAULT NULL, - `C_7e687515fc569cc19b4e7e9f882ae87e` VARCHAR(2000) NULL DEFAULT NULL, - `C_81d05006f98cda946b1841b62baa325e` DOUBLE NULL DEFAULT NULL, - `C_c8230ecc2d6c679f281a0d35c96b0bd0` DOUBLE NULL DEFAULT NULL, - `C_31d627c22a1dd33f024f153f3be50cb0` DOUBLE NULL DEFAULT NULL -) ENGINE = InnoDB COMMENT = 'OLAP'; +DROP TABLE IF EXISTS `demo_gdp_district_top100`; +CREATE TABLE `demo_gdp_district_top100` ( + `id` int(11) NOT NULL AUTO_INCREMENT, + `province` varchar(255) DEFAULT NULL, + `num` int(255) DEFAULT NULL, + PRIMARY KEY (`id`) +) ENGINE=InnoDB AUTO_INCREMENT=17 DEFAULT CHARSET=utf8; -- ---------------------------- --- Records of ds_c56d7462_6334_4583_a617_b249b2299ed1 +-- Records of demo_gdp_district_top100 -- ---------------------------- BEGIN; -INSERT INTO `ds_c56d7462_6334_4583_a617_b249b2299ed1` VALUES ('1569781ef6fac96fe59e2d1bf652b361', '2017年', 12.64, 7.06, 5.58), ('e655070f51fc27e6c288f61e8ef4cb63', '2019年', 10.41, 7.09, 3.32), ('ead36d129c5fed495ec69e44722fcd26', '2015年', 11.99, 7.07, 4.93), ('9234e33c36fb313b6d089a13fa99b790', '2014年', 13.83, 7.12, 6.71), ('bb7673deb4474b703246b5d5f297b4bd', '2003年', 12.41, 6.4, 6.01), ('ef0e7df47ddc4c01b4de0e4e486ad221', '2011年', 13.27, 7.14, 6.13), ('22032ac55cc6dc0bc1c9d44b7eae6f6b', '2004年', 12.29, 6.42, 5.87), ('e0b743d1f98de028b27fd8fc884d5d08', '2016年', 13.57, 7.04, 6.53), ('e23d6e46badaf53e224c45c5d386caed', '2020年', 8.52, 7.07, 1.45), ('fb91a1e83d2622d3fa68ac9b7125963d', '2018年', 10.86, 7.08, 3.7800000000000002), ('35593399dae93661194eb352046f771c', '2005年', 12.4, 6.51, 5.89), ('d059e8599ac39778398095a44ce2f4ae', '2013年', 13.03, 7.13, 5.9), ('1b66a0e7a55df05c279fdfec540736d4', '2007年', 12.1, 6.93, 5.17), ('a5ff2a623dfcc5c806896247f9b798ca', '2002年', 12.86, 6.41, 6.45), ('f3b6bfab66386e33dd8938738cfedb02', '2001年', 13.38, 6.43, 6.95), ('23ff7d6d5a125f301970a4ae4a29a146', '2008年', 12.14, 7.06, 5.08), ('43663d71302ec511c41855a10395decb', '2012年', 14.57, 7.13, 7.43), ('981429835d0e416e02d90c0e1ebce890', '2010年', 11.9, 7.11, 4.79), ('bea0e7c56fcc842044273dcbe73b0369', '2006年', 12.09, 6.8100000000000005, 5.28), ('aa2ef2555addcf6fc0c38be5b71b9034', '2009年', 11.95, 7.08, 4.87); +INSERT INTO `demo_gdp_district_top100` VALUES (1, '江苏省', 26); +INSERT INTO `demo_gdp_district_top100` VALUES (2, '山东省', 13); +INSERT INTO `demo_gdp_district_top100` VALUES (3, '福建省', 9); +INSERT INTO `demo_gdp_district_top100` VALUES (4, '浙江省', 18); +INSERT INTO `demo_gdp_district_top100` VALUES (5, '广东省', 4); +INSERT INTO `demo_gdp_district_top100` VALUES (6, '湖南省', 5); +INSERT INTO `demo_gdp_district_top100` VALUES (7, '湖北省', 7); +INSERT INTO `demo_gdp_district_top100` VALUES (8, '河南省', 7); +INSERT INTO `demo_gdp_district_top100` VALUES (9, '新疆维吾尔族自治区', 1); +INSERT INTO `demo_gdp_district_top100` VALUES (10, '安徽省', 2); +INSERT INTO `demo_gdp_district_top100` VALUES (11, '河北省', 2); +INSERT INTO `demo_gdp_district_top100` VALUES (12, '内蒙古自治区', 2); +INSERT INTO `demo_gdp_district_top100` VALUES (13, '辽宁省', 1); +INSERT INTO `demo_gdp_district_top100` VALUES (14, '江西省', 1); +INSERT INTO `demo_gdp_district_top100` VALUES (15, '陕西省', 1); +INSERT INTO `demo_gdp_district_top100` VALUES (16, '贵州省', 1); COMMIT; -- ---------------------------- --- Table structure for ds_fdf177f8_8cdd_4e85_86c6_8adac50b0531 +-- Table structure for demo_gdp_history -- ---------------------------- -DROP TABLE IF EXISTS `ds_fdf177f8_8cdd_4e85_86c6_8adac50b0531`; -CREATE TABLE `ds_fdf177f8_8cdd_4e85_86c6_8adac50b0531` ( - `dataease_uuid` VARCHAR(50) NULL DEFAULT NULL, - `C_7e687515fc569cc19b4e7e9f882ae87e` VARCHAR(2000) NULL DEFAULT NULL, - `C_a08fe595bbb49a862bfab24964098dbb` DOUBLE NULL DEFAULT NULL, - `C_2cac4a8ae080bfefadfe646aa812acfd` DOUBLE NULL DEFAULT NULL -) ENGINE = InnoDB COMMENT = 'OLAP'; +DROP TABLE IF EXISTS `demo_gdp_history`; +CREATE TABLE `demo_gdp_history` ( + `id` int(11) NOT NULL AUTO_INCREMENT, + `year` varchar(255) DEFAULT NULL, + `gdp` double(255,2) DEFAULT NULL, + `percent` double(255,2) DEFAULT NULL, + PRIMARY KEY (`id`) +) ENGINE=InnoDB AUTO_INCREMENT=11 DEFAULT CHARSET=utf8; -- ---------------------------- --- Records of ds_fdf177f8_8cdd_4e85_86c6_8adac50b0531 +-- Records of demo_gdp_history -- ---------------------------- BEGIN; -INSERT INTO `ds_fdf177f8_8cdd_4e85_86c6_8adac50b0531` VALUES ('174acf692d798f82d896b1001a62c28e', '平均预期寿命(岁)', 76.34, 74.83), ('bef17b1d7c510de0964d3f92c0b973c1', '女性平均预期寿命(岁)', 79.43, 77.37), ('091b7cd687bc3c00977342c5633cfe2d', '男性平均预期寿命(岁)', 73.64, 72.38); +INSERT INTO `demo_gdp_history` VALUES (1, '2020', 14.72, 17.38); +INSERT INTO `demo_gdp_history` VALUES (2, '2019', 14.28, 16.46); +INSERT INTO `demo_gdp_history` VALUES (3, '2018', 13.89, 16.41); +INSERT INTO `demo_gdp_history` VALUES (4, '2017', 12.31, 15.59); +INSERT INTO `demo_gdp_history` VALUES (5, '2016', 11.23, 15.29); +INSERT INTO `demo_gdp_history` VALUES (6, '2015', 11.06, 15.44); +INSERT INTO `demo_gdp_history` VALUES (7, '2014', 10.48, 13.97); +INSERT INTO `demo_gdp_history` VALUES (8, '2013', 9.57, 13.24); +INSERT INTO `demo_gdp_history` VALUES (9, '2012', 8.53, 12.26); +INSERT INTO `demo_gdp_history` VALUES (10, '2011', 7.55, 11.20); COMMIT; +SET FOREIGN_KEY_CHECKS = 1; + + +INSERT INTO `panel_group` (`id`, `name`, `pid`, `level`, `node_type`, `create_by`, `create_time`, `panel_type`, `panel_style`, `panel_data`, `source`, `extend1`, `extend2`, `remark`) VALUES ('117f679e-8355-4645-a692-47e2009cbc0d', '2021年全国GDP数据', '308b5d60-ceb4-465d-9bad-cf901f2d38f1', 1, 'panel', 'admin', 1629365845683, 'self', 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NULL, NULL, NULL, NULL); + + +INSERT INTO `panel_view` (`id`, `panel_id`, `chart_view_id`, `content`, `create_by`, `create_time`, `update_by`, `update_time`) VALUES ('7583dc0d-058d-11ec-a2b0-0242ac130003', '117f679e-8355-4645-a692-47e2009cbc0d', '84b444e1-0088-44f9-acdc-cc39018413bc', NULL, NULL, NULL, NULL, NULL); +INSERT INTO `panel_view` (`id`, `panel_id`, `chart_view_id`, `content`, `create_by`, `create_time`, `update_by`, `update_time`) VALUES ('7583deb5-058d-11ec-a2b0-0242ac130003', '117f679e-8355-4645-a692-47e2009cbc0d', 'c68db172-2df2-4aa2-aad6-077cf1684e14', NULL, NULL, NULL, NULL, NULL); +INSERT INTO `panel_view` (`id`, `panel_id`, `chart_view_id`, `content`, `create_by`, `create_time`, `update_by`, `update_time`) VALUES ('7583df2c-058d-11ec-a2b0-0242ac130003', '117f679e-8355-4645-a692-47e2009cbc0d', 'f8d62b2b-b99a-4b6c-8378-d7c2ec4ea766', NULL, NULL, NULL, NULL, NULL); +INSERT INTO `panel_view` (`id`, `panel_id`, `chart_view_id`, `content`, `create_by`, `create_time`, 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NULL, 3, 0, 1, 2, 1629365603090); +INSERT INTO `dataset_table_field` (`id`, `table_id`, `origin_name`, `name`, `dataease_name`, `group_type`, `type`, `size`, `de_type`, `de_type_format`, `de_extract_type`, `ext_field`, `checked`, `column_index`, `last_sync_time`) VALUES ('680e8e5a-58c8-4760-b151-9e3c0b998621', 'caf2de01-1dd6-4ea5-a0aa-a53a6bb84ebb', 'province', 'province', 'C_53aad639aca4b5c010927cf610c3ff9c', 'd', 'VARCHAR', 255, 0, NULL, 0, 0, 1, 0, 1629365603090); +INSERT INTO `dataset_table_field` (`id`, `table_id`, `origin_name`, `name`, `dataease_name`, `group_type`, `type`, `size`, `de_type`, `de_type_format`, `de_extract_type`, `ext_field`, `checked`, `column_index`, `last_sync_time`) VALUES ('df68fb8f-0e7e-4b69-90e6-28550f955ebf', 'caf2de01-1dd6-4ea5-a0aa-a53a6bb84ebb', 'city', 'city', 'C_4ed5d2eaed1a1fadcc41ad1d58ed603e', 'd', 'VARCHAR', 255, 0, NULL, 0, 0, 1, 1, 1629365603090); +INSERT INTO `dataset_table_field` (`id`, `table_id`, `origin_name`, `name`, `dataease_name`, 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'VARCHAR', 255, 3, NULL, 0, 0, 1, 2, 1629442921534); +INSERT INTO `dataset_table_field` (`id`, `table_id`, `origin_name`, `name`, `dataease_name`, `group_type`, `type`, `size`, `de_type`, `de_type_format`, `de_extract_type`, `ext_field`, `checked`, `column_index`, `last_sync_time`) VALUES ('bafcb837-24a2-4f94-9d6b-7ce163bd7fbc', '99f30713-29ab-4378-941c-bb99182d927a', 'industry', 'industry', 'C_94074ce331b5db47060fd2d8009503a8', 'd', 'VARCHAR', 255, 0, NULL, 0, 0, 1, 1, 1629442921534); +INSERT INTO `dataset_table_field` (`id`, `table_id`, `origin_name`, `name`, `dataease_name`, `group_type`, `type`, `size`, `de_type`, `de_type_format`, `de_extract_type`, `ext_field`, `checked`, `column_index`, `last_sync_time`) VALUES ('30d6a427-95af-4478-93ff-81511023d193', '5d91825c-8a0a-4c90-aba1-f58cff216561', 'city', 'city', 'C_4ed5d2eaed1a1fadcc41ad1d58ed603e', 'd', 'VARCHAR', 255, 0, NULL, 0, 0, 1, 2, 1629451475515); +INSERT INTO `dataset_table_field` (`id`, `table_id`, `origin_name`, `name`, 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'C_2ad1fe944da8f2d91df2181ed189d3df', 'q', 'VARCHAR', 255, 3, NULL, 0, 0, 1, 2, 1629442921465); +INSERT INTO `dataset_table_field` (`id`, `table_id`, `origin_name`, `name`, `dataease_name`, `group_type`, `type`, `size`, `de_type`, `de_type_format`, `de_extract_type`, `ext_field`, `checked`, `column_index`, `last_sync_time`) VALUES ('5358bb6f-9ddc-4f8d-8e68-c5ea030af0bb', '3e1cf23c-5620-4a59-93b0-e4cae81b47ae', 'increase', 'increase', 'C_11198b294adbcf089f9d27990258fd22', 'q', 'VARCHAR', 255, 3, NULL, 0, 0, 1, 3, 1629442921465); +INSERT INTO `dataset_table_field` (`id`, `table_id`, `origin_name`, `name`, `dataease_name`, `group_type`, `type`, `size`, `de_type`, `de_type_format`, `de_extract_type`, `ext_field`, `checked`, `column_index`, `last_sync_time`) VALUES ('58a7ee7d-6753-400a-a22b-1aa7d16b1648', '3e1cf23c-5620-4a59-93b0-e4cae81b47ae', '2021GDP)', '2021GDP)', 'C_e62745cee7a4ffbf5dbfa70cdd73c7b7', 'q', 'VARCHAR', 255, 3, NULL, 0, 0, 1, 1, 1629442921465); +INSERT INTO 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