标签：
开发环境：spark：2.2.0
工具：IDEA
OS:Windows
数据文件：
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509A4C4B1DB1,其他,2018-07-12 14:04:16,2018-07-12 14:04:16,2018-07-12 14:04:16,未知,僵尸屏,0 525209C36338,其他,2018-07-12 14:04:51,2018-07-12 14:04:51,2018-07-12 14:04:51,未知-未知,广播,0 5433CB96997F,其他,2018-07-12 13:59:13,2018-07-12 13:59:13,2018-07-12 14:06:31,北京市-朝阳区,国贸CBD小屏组,438 54E1AD20F608,其他,2018-07-12 14:01:36,2018-07-12 14:01:36,2018-07-12 14:01:36,未知,僵尸屏,0 561A59EE2CA3,其他,2018-07-12 14:01:06,2018-07-12 14:01:06,2018-07-12 14:01:06,未知-未知,广播,0 568E02029CD4,其他,2018-07-12 14:02:29,2018-07-12 14:02:29,2018-07-12 14:02:29,未知-未知,广播,0 56D6904E6497,其他,2018-07-12 14:06:41,2018-07-12 14:06:41,2018-07-12 14:06:41,未知-未知,广播,0 5820B14FD8E3,其他,2018-07-12 13:59:10,2018-07-12 13:59:10,2018-07-12 14:06:09,未知,僵尸屏,419 5A29F8E9DD99,其他,2018-07-12 14:02:07,2018-07-12 14:02:07,2018-07-12 14:02:07,未知-未知,广播,0 5A6CEECC9C0F,其他,2018-07-12 14:03:46,2018-07-12 14:03:46,2018-07-12 14:03:46,未知-未知,广播,0 5A71A4822891,其他,2018-07-12 14:01:08,2018-07-12 14:01:08,2018-07-12 14:01:09,未知-未知,广播,1 5CADCF77DB62,Apple,2018-07-12 14:01:55,2018-07-12 14:01:55,2018-07-12 14:05:32,未知,僵尸屏,217 5CE0C5127190,其他,2018-07-12 13:59:04,2018-07-12 13:59:04,2018-07-12 14:06:05,四川省-成都市,人民南路跳伞塔数码大厦屏,421 5CE0C519E727,其他,2018-07-12 14:00:32,2018-07-12 14:00:32,2018-07-12 14:05:22,四川省-成都市,人民南路跳伞塔数码大厦屏,290 5CE0C519E74A,其他,2018-07-12 13:58:56,2018-07-12 13:58:56,2018-07-12 14:06:41,未知,僵尸屏,465 5CE0C519E777,其他,2018-07-12 13:59:17,2018-07-12 13:59:17,2018-07-12 14:06:08,北京市-朝阳区,国贸CBD小屏组,411 60F81DAC5A68,Apple,2018-07-12 13:59:03,2018-07-12 13:59:03,2018-07-12 14:06:35,未知,僵尸屏,452 617461010802,其他,2018-07-12 13:59:53,2018-07-12 13:59:53,2018-07-12 13:59:53,未知,僵尸屏,0 626126E68717,其他,2018-07-12 14:04:59,2018-07-12 14:04:59,2018-07-12 14:04:59,未知-未知,广播,0 62A0A77197ED,其他,2018-07-12 14:01:37,2018-07-12 14:01:37,2018-07-12 14:01:37,未知-未知,广播,0 64A2F924BBF5,其他,2018-07-12 13:58:54,2018-07-12 13:58:54,2018-07-12 14:04:57,北京市-朝阳区,国贸CBD小屏组,363 64B0A61B5116,Apple,2018-07-12 13:59:03,2018-07-12 13:59:03,2018-07-12 14:06:21,北京市-朝阳区,国贸CBD小屏组,438 66499E6E806C,其他,2018-07-12 13:59:04,2018-07-12 13:59:04,2018-07-12 13:59:04,未知-未知,广播,0 66FACD823429,其他,2018-07-12 14:04:03,2018-07-12 14:04:03,2018-07-12 14:04:04,未知-未知,广播,1 68AB1E1E476B,其他,2018-07-12 14:03:27,2018-07-12 14:03:27,2018-07-12 14:03:28,未知-未知,广播,1 68DBCA4B2398,Apple,2018-07-12 14:01:09,2018-07-12 14:01:09,2018-07-12 14:01:09,北京市-朝阳区,国贸CBD小屏组,0 68F728099B93,其他,2018-07-12 13:58:57,2018-07-12 13:58:57,2018-07-12 14:04:29,未知,僵尸屏,332 68F72809A006,其他,2018-07-12 14:01:56,2018-07-12 14:01:56,2018-07-12 14:01:56,未知,僵尸屏,0 68F7281D8047,其他,2018-07-12 13:58:54,2018-07-12 13:58:54,2018-07-12 14:04:19,未知,僵尸屏,325 68F7283626B2,其他,2018-07-12 13:58:54,2018-07-12 13:58:54,2018-07-12 14:06:39,未知,僵尸屏,465 68F7288D4ECE,其他,2018-07-12 14:04:16,2018-07-12 14:04:16,2018-07-12 14:04:22,未知,僵尸屏,6 68F728A1D100,其他,2018-07-12 13:59:30,2018-07-12 13:59:30,2018-07-12 14:04:29,未知,僵尸屏,299 68F728BA1A3F,其他,2018-07-12 13:59:07,2018-07-12 13:59:07,2018-07-12 14:05:50,未知,僵尸屏,403 68F728C18AFE,其他,2018-07-12 13:59:10,2018-07-12 13:59:10,2018-07-12 13:59:10,未知,僵尸屏,0 68F728C23AC3,其他,2018-07-12 14:02:45,2018-07-12 14:02:45,2018-07-12 14:06:35,未知,僵尸屏,230 6A2B0D59EED7,其他,2018-07-12 14:04:28,2018-07-12 14:04:28,2018-07-12 14:04:28,未知-未知,广播,0 6AB4554CF30C,其他,2018-07-12 14:02:38,2018-07-12 14:02:38,2018-07-12 14:02:38,未知-未知,广播,0 6C72E73965AC,Apple,2018-07-12 13:59:15,2018-07-12 13:59:15,2018-07-12 14:00:50,未知-未知,广播,95 6C72E7594DEB,Apple,2018-07-12 14:02:32,2018-07-12 14:02:32,2018-07-12 14:02:34,北京市-朝阳区,国贸CBD小屏组,2 6CC217226B22,其他,2018-07-12 14:00:25,2018-07-12 14:00:25,2018-07-12 14:02:54,未知,僵尸屏,149 6EC677CF6B23,其他,2018-07-12 14:01:45,2018-07-12 14:01:45,2018-07-12 14:01:45,未知-未知,广播,0 70480F1BE7A8,Apple,2018-07-12 13:58:59,2018-07-12 13:58:59,2018-07-12 14:05:43,未知-未知,广播,404 70480F476EC1,Apple,2018-07-12 14:01:24,2018-07-12 14:01:24,2018-07-12 14:06:29,北京市-朝阳区,国贸CBD小屏组,305 70F08783BECD,Apple,2018-07-12 13:58:54,2018-07-12 13:58:54,2018-07-12 14:06:38,北京市-朝阳区,国贸CBD小屏组,464 727D7D76FEB1,其他,2018-07-12 14:02:22,2018-07-12 14:02:22,2018-07-12 14:02:23,未知-未知,广播,1 74A528BCAABD,HUAWEI,2018-07-12 13:58:55,2018-07-12 13:58:55,2018-07-12 14:04:32,北京市-朝阳区,国贸CBD小屏组,337 7673F615363F,其他,2018-07-12 14:02:11,2018-07-12 14:02:11,2018-07-12 14:02:11,未知-未知,广播,0 7811DC483347,Xiaomi,2018-07-12 13:59:14,2018-07-12 13:59:14,2018-07-12 14:01:04,未知,僵尸屏,110 784F43BD2CE3,Apple,2018-07-12 13:59:24,2018-07-12 13:59:24,2018-07-12 14:01:18,未知,僵尸屏,114 784F43C1618D,Apple,2018-07-12 13:59:25,2018-07-12 13:59:25,2018-07-12 14:05:55,北京市-朝阳区,国贸CBD小屏组,390 78ACC0B47587,其他,2018-07-12 13:59:00,2018-07-12 13:59:00,2018-07-12 14:05:27,未知,僵尸屏,387 78E3B5D20296,其他,2018-07-12 13:59:20,2018-07-12 13:59:20,2018-07-12 13:59:20,未知,僵尸屏,0 78E7D1C2B47E,其他,2018-07-12 14:04:19,2018-07-12 14:04:19,2018-07-12 14:04:19,未知,僵尸屏,0 78E7D1C58D0E,其他,2018-07-12 14:02:48,2018-07-12 14:02:48,2018-07-12 14:02:48,未知,僵尸屏,0 78E7D1C58E24,其他,2018-07-12 14:01:23,2018-07-12 14:01:23,2018-07-12 14:01:23,未知,僵尸屏,0 78E7D1D92219,其他,2018-07-12 14:01:40,2018-07-12 14:01:40,2018-07-12 14:03:53,未知,僵尸屏,133 78E7D1D92235,其他,2018-07-12 14:02:38,2018-07-12 14:02:38,2018-07-12 14:02:38,未知,僵尸屏,0 7A8210E5CA96,其他,2018-07-12 14:01:38,2018-07-12 14:01:38,2018-07-12 14:01:39,未知-未知,广播,1 7AB3CDEF05D4,其他,2018-07-12 14:04:48,2018-07-12 14:04:48,2018-07-12 14:05:10,未知-未知,广播,22 7E35C9726EBF,其他,2018-07-12 14:03:33,2018-07-12 14:03:33,2018-07-12 14:03:33,未知-未知,广播,0 7E4AE2267C39,其他,2018-07-12 14:05:54,2018-07-12 14:05:54,2018-07-12 14:05:55,未知-未知,广播,1 7EA6AEC5D494,其他,2018-07-12 14:03:16,2018-07-12 14:03:16,2018-07-12 14:03:22,未知-未知,广播,6 7EFEA9FDAD1D,其他,2018-07-12 13:58:52,2018-07-12 13:58:52,2018-07-12 13:58:58,未知-未知,广播,6 80717A5D00E7,HUAWEI,2018-07-12 14:00:16,2018-07-12 14:00:16,2018-07-12 14:06:01,未知,僵尸屏,345 8243455B963D,其他,2018-07-12 14:02:35,2018-07-12 14:02:35,2018-07-12 14:02:35,未知-未知,广播,0 826AD7ABB8A8,其他,2018-07-12 14:02:18,2018-07-12 14:02:18,2018-07-12 14:02:19,未知-未知,广播,1 8441678BFAA3,其他,2018-07-12 14:03:35,2018-07-12 14:03:35,2018-07-12 14:03:41,北京市-朝阳区,国贸CBD小屏组,6 865CAED88A76,其他,2018-07-12 14:06:04,2018-07-12 14:06:04,2018-07-12 14:06:05,未知-未知,广播,1 86714590D43F,其他,2018-07-12 14:05:58,2018-07-12 14:05:58,2018-07-12 14:05:58,未知-未知,广播,0 86814B2B907F,其他,2018-07-12 14:03:34,2018-07-12 14:03:34,2018-07-12 14:03:34,未知-未知,广播,0 86E5DF74D12A,其他,2018-07-12 14:01:10,2018-07-12 14:01:10,2018-07-12 14:01:45,未知-未知,广播,35 8AF35338839D,其他,2018-07-12 14:03:43,2018-07-12 14:03:43,2018-07-12 14:03:43,未知-未知,广播,0 8C34FD58DAEA,HUAWEI,2018-07-12 13:59:49,2018-07-12 13:59:49,2018-07-12 14:04:24,北京市-朝阳区,国贸CBD小屏组,275 8CA9823E26DC,其他,2018-07-12 13:59:02,2018-07-12 13:59:02,2018-07-12 14:06:42,未知,僵尸屏,460 8CDCD42DDE4D,其他,2018-07-12 13:59:10,2018-07-12 13:59:10,2018-07-12 14:05:30,未知,僵尸屏,380 8CDCD42DDE61,其他,2018-07-12 14:04:32,2018-07-12 14:04:32,2018-07-12 14:04:32,未知,僵尸屏,0 8CDCD4301844,其他,2018-07-12 14:00:57,2018-07-12 14:00:57,2018-07-12 14:00:57,未知,僵尸屏,0 8CDCD4301AB3,其他,2018-07-12 14:02:12,2018-07-12 14:02:12,2018-07-12 14:04:22,未知,僵尸屏,130 8CDCD4301B1D,其他,2018-07-12 14:02:12,2018-07-12 14:02:12,2018-07-12 14:02:25,未知,僵尸屏,13 8CDCD4301B2E,其他,2018-07-12 14:00:48,2018-07-12 14:00:48,2018-07-12 14:06:19,未知,僵尸屏,331 8CDCD4311C78,其他,2018-07-12 13:59:17,2018-07-12 13:59:17,2018-07-12 13:59:17,未知,僵尸屏,0 8CDCD4334EB8,其他,2018-07-12 14:02:35,2018-07-12 14:02:35,2018-07-12 14:02:35,未知,僵尸屏,0 8CDCD4334F37,其他,2018-07-12 14:00:35,2018-07-12 14:00:35,2018-07-12 14:05:27,未知,僵尸屏,292 8CDCD4334F6A,其他,2018-07-12 13:59:07,2018-07-12 13:59:07,2018-07-12 14:05:11,未知,僵尸屏,364 8E26F8DC15EE,其他,2018-07-12 13:59:08,2018-07-12 13:59:08,2018-07-12 13:59:08,未知-未知,广播,0 8E5F2226CD50,其他,2018-07-12 14:01:46,2018-07-12 14:01:46,2018-07-12 14:01:46,未知-未知,广播,0 9202D3982BA3,其他,2018-07-12 14:03:27,2018-07-12 14:03:27,2018-07-12 14:03:40,未知-未知,广播,13 963075096988,其他,2018-07-12 14:05:06,2018-07-12 14:05:06,2018-07-12 14:05:06,未知-未知,广播,0 985AEBC6B4DF,Apple,2018-07-12 14:00:09,2018-07-12 14:00:09,2018-07-12 14:00:09,未知,僵尸屏,0 9C2EA1FADCD1,其他,2018-07-12 13:59:28,2018-07-12 13:59:28,2018-07-12 14:06:31,未知-未知,广播,423 9C443D1952FA,其他,2018-07-12 13:59:07,2018-07-12 13:59:07,2018-07-12 14:06:33,未知,僵尸屏,446 9CA5C0BD6F6D,vivo,2018-07-12 14:00:00,2018-07-12 14:00:00,2018-07-12 14:00:45,四川省-成都市,人民南路跳伞塔数码大厦屏,45 9CB6D00D99FD,其他,2018-07-12 13:58:58,2018-07-12 13:58:58,2018-07-12 14:06:37,未知-未知,广播,459 9CE33F33F576,其他,2018-07-12 14:03:32,2018-07-12 14:03:32,2018-07-12 14:03:49,北京市-朝阳区,国贸CBD小屏组,17 9CF48E3335F5,Apple,2018-07-12 14:01:13,2018-07-12 14:01:13,2018-07-12 14:06:33,北京市-朝阳区,国贸CBD小屏组,320 9CF48E43079E,Apple,2018-07-12 13:59:01,2018-07-12 13:59:01,2018-07-12 14:06:07,未知,僵尸屏,426 9CFC01682E78,Apple,2018-07-12 14:03:18,2018-07-12 14:03:18,2018-07-12 14:03:18,北京市-朝阳区,国贸CBD小屏组,0 9E7EE62C840B,其他,2018-07-12 14:06:13,2018-07-12 14:06:13,2018-07-12 14:06:14,未知-未知,广播,1 9E850CB1C147,其他,2018-07-12 14:05:22,2018-07-12 14:05:22,2018-07-12 14:05:22,未知-未知,广播,0 9ED082F4539F,其他,2018-07-12 13:59:15,2018-07-12 13:59:15,2018-07-12 13:59:15,未知-未知,广播,0 A0086F310909,HUAWEI,2018-07-12 13:59:47,2018-07-12 13:59:47,2018-07-12 14:05:54,北京市-朝阳区,国贸CBD小屏组,367 A0086F31090A,HUAWEI,2018-07-12 13:58:56,2018-07-12 13:58:56,2018-07-12 14:06:37,北京市-海定区,中关村鼎好电子大厦屏,461 A0086F31090E,HUAWEI,2018-07-12 13:58:53,2018-07-12 13:58:53,2018-07-12 14:06:09,北京市-朝阳区,国贸CBD小屏组,436 A057E36FD3E6,其他,2018-07-12 13:58:54,2018-07-12 13:58:54,2018-07-12 14:05:55,北京市-朝阳区,国贸CBD小屏组,421 A20D43A7B97D,其他,2018-07-12 14:03:12,2018-07-12 14:03:12,2018-07-12 14:05:36,未知-未知,广播,144 A211DDAB06FB,其他,2018-07-12 13:59:02,2018-07-12 13:59:02,2018-07-12 13:59:02,未知-未知,广播,0 A2578286415A,其他,2018-07-12 14:02:38,2018-07-12 14:02:38,2018-07-12 14:02:38,未知-未知,广播,0 A25FA9400829,其他,2018-07-12 14:06:43,2018-07-12 14:06:43,2018-07-12 14:06:44,未知-未知,广播,1 A41731F375EB,HonHai,2018-07-12 14:03:03,2018-07-12 14:03:03,2018-07-12 14:03:03,未知-未知,广播,0 A493FE3F6F08,其他,2018-07-12 13:58:52,2018-07-12 13:58:52,2018-07-12 14:06:43,未知,僵尸屏,471 A4CAA00A81C7,HUAWEI,2018-07-12 14:05:27,2018-07-12 14:05:27,2018-07-12 14:05:27,未知,僵尸屏,0 A679D542B052,其他,2018-07-12 14:02:35,2018-07-12 14:02:35,2018-07-12 14:02:35,未知-未知,广播,0 A67E6B8751A9,其他,2018-07-12 14:06:35,2018-07-12 14:06:35,2018-07-12 14:06:35,未知-未知,广播,0 A6FFFFFF404A,其他,2018-07-12 14:04:32,2018-07-12 14:04:32,2018-07-12 14:04:32,北京市-朝阳区,国贸CBD小屏组,0 A8667F624EE6,Apple,2018-07-12 14:00:33,2018-07-12 14:00:33,2018-07-12 14:00:33,北京市-朝阳区,国贸CBD小屏组,0 A8FFFFFF404A,其他,2018-07-12 14:00:01,2018-07-12 14:00:01,2018-07-12 14:00:01,北京市-海定区,中关村鼎好电子大厦屏,0 A9FFFFFF6F08,其他,2018-07-12 14:01:43,2018-07-12 14:01:43,2018-07-12 14:01:43,北京市-朝阳区,国贸CBD小屏组,0 AACCBD34BAD6,其他,2018-07-12 14:04:01,2018-07-12 14:04:01,2018-07-12 14:04:01,未知-未知,广播,0 AAE7B712600A,其他,2018-07-12 14:03:17,2018-07-12 14:03:17,2018-07-12 14:03:20,未知-未知,广播,3 AAFFFFFF6F08,其他,2018-07-12 14:02:00,2018-07-12 14:02:00,2018-07-12 14:03:26,北京市-朝阳区,国贸CBD小屏组,86 ABFFFFFF6F08,其他,2018-07-12 14:01:04,2018-07-12 14:01:04,2018-07-12 14:02:24,北京市-朝阳区,国贸CBD小屏组,80 ACFFFFFF404A,其他,2018-07-12 14:00:36,2018-07-12 14:00:36,2018-07-12 14:00:36,未知,僵尸屏,0 ADFFFFFF6F08,其他,2018-07-12 14:01:45,2018-07-12 14:01:45,2018-07-12 14:01:45,北京市-朝阳区,国贸CBD小屏组,0 AE3DA8C9C025,其他,2018-07-12 14:03:24,2018-07-12 14:03:24,2018-07-12 14:03:40,未知-未知,广播,16 AE862332942D,其他,2018-07-12 14:06:33,2018-07-12 14:06:33,2018-07-12 14:06:34,未知-未知,广播,1 AE8AD572A19E,其他,2018-07-12 14:04:15,2018-07-12 14:04:15,2018-07-12 14:04:15,未知-未知,广播,0 AEFFFFFF404A,其他,2018-07-12 14:02:50,2018-07-12 14:02:50,2018-07-12 14:02:50,北京市-海定区,中关村鼎好电子大厦屏,0 AEFFFFFF6F08,其他,2018-07-12 14:01:17,2018-07-12 14:01:17,2018-07-12 14:05:44,北京市-朝阳区,国贸CBD小屏组,267 AFFFFFFF404A,其他,2018-07-12 14:04:21,2018-07-12 14:04:21,2018-07-12 14:04:21,北京市-朝阳区,国贸CBD小屏组,0 AFFFFFFF6F08,其他,2018-07-12 14:00:13,2018-07-12 14:00:13,2018-07-12 14:06:26,北京市-朝阳区,国贸CBD小屏组,373 B0FFFFFF404A,其他,2018-07-12 13:59:22,2018-07-12 13:59:22,2018-07-12 14:06:15,北京市-海定区,中关村鼎好电子大厦屏,413 B0FFFFFF6F08,其他,2018-07-12 14:00:14,2018-07-12 14:00:14,2018-07-12 14:05:21,北京市-海定区,中关村鼎好电子大厦屏,307 B1FFFFFF404A,其他,2018-07-12 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23:56:44,2018-07-12 23:56:44,2018-07-12 23:56:44,四川省-成都市,人民南路跳伞塔数码大厦屏,6538 B8C1114A7B9B,其他,2018-07-12 20:06:43,2018-07-12 20:06:43,2018-07-12 20:20:40,四川省-成都市,人民南路跳伞塔数码大厦屏,837 B8C1114A7B9B,其他,2018-07-12 23:56:44,2018-07-12 23:56:44,2018-07-12 23:56:44,四川省-成都市,人民南路跳伞塔数码大厦屏,6538 B8E8563BA0A4,Apple,2018-07-12 13:59:49,2018-07-12 13:59:49,2018-07-12 14:04:24,北京市-朝阳区,国贸CBD小屏组,275 B8FFFFFF6F08,其他,2018-07-12 13:59:19,2018-07-12 13:59:19,2018-07-12 13:59:19,未知,僵尸屏,0 BAD91D9B892E,其他,2018-07-12 14:06:33,2018-07-12 14:06:33,2018-07-12 14:06:33,未知-未知,广播,0 BAFFFFFF404A,其他,2018-07-12 14:06:04,2018-07-12 14:06:04,2018-07-12 14:06:04,未知,僵尸屏,0 BAFFFFFF6F08,其他,2018-07-12 14:02:20,2018-07-12 14:02:20,2018-07-12 14:02:20,未知,僵尸屏,0 BC4CC49649F0,Apple,2018-07-12 14:03:11,2018-07-12 14:03:11,2018-07-12 14:05:26,未知-未知,广播,135 BC6C214D948A,Apple,2018-07-12 13:59:16,2018-07-12 13:59:16,2018-07-12 13:59:49,北京市-朝阳区,国贸CBD小屏组,33 C254A0267912,其他,2018-07-12 14:05:40,2018-07-12 14:05:40,2018-07-12 14:05:40,未知-未知,广播,0 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14:03:03,2018-07-12 14:03:03,2018-07-12 14:03:03,未知-未知,广播,0 DAA1194730E4,其他,2018-07-12 14:00:04,2018-07-12 14:00:04,2018-07-12 14:00:04,未知-未知,广播,0 DAA1194831E5,其他,2018-07-12 14:03:15,2018-07-12 14:03:15,2018-07-12 14:03:15,未知-未知,广播,0 DAA1194A31E5,其他,2018-07-12 14:02:41,2018-07-12 14:02:41,2018-07-12 14:02:41,未知-未知,广播,0 DAA1194FDD91,其他,2018-07-12 14:02:53,2018-07-12 14:02:53,2018-07-12 14:02:53,未知-未知,广播,0 DAA11954BCA7,其他,2018-07-12 14:00:28,2018-07-12 14:00:28,2018-07-12 14:00:28,未知-未知,广播,0 DAA11957CCFF,其他,2018-07-12 14:03:22,2018-07-12 14:03:22,2018-07-12 14:03:22,未知-未知,广播,0 DAA119585408,其他,2018-07-12 14:04:05,2018-07-12 14:04:05,2018-07-12 14:04:05,未知-未知,广播,0 DAA1195B570B,其他,2018-07-12 14:01:09,2018-07-12 14:01:09,2018-07-12 14:01:09,未知-未知,广播,0 DAA1195EB569,其他,2018-07-12 14:04:05,2018-07-12 14:04:05,2018-07-12 14:04:05,未知-未知,广播,0 DAA1195F13C7,其他,2018-07-12 14:01:09,2018-07-12 14:01:09,2018-07-12 14:01:09,未知-未知,广播,0 DAA119604934,其他,2018-07-12 13:59:39,2018-07-12 13:59:39,2018-07-12 13:59:39,未知-未知,广播,0 DAA11971ECA0,其他,2018-07-12 14:03:03,2018-07-12 14:03:03,2018-07-12 14:03:03,未知-未知,广播,0 DAA119755E49,其他,2018-07-12 14:01:19,2018-07-12 14:01:19,2018-07-12 14:01:19,未知-未知,广播,0 DAA11979F6AA,其他,2018-07-12 14:04:16,2018-07-12 14:04:16,2018-07-12 14:04:16,未知-未知,广播,0 DAA1197C782C,其他,2018-07-12 14:03:29,2018-07-12 14:03:29,2018-07-12 14:03:29,未知-未知,广播,0 DAA11981570B,其他,2018-07-12 14:05:01,2018-07-12 14:05:01,2018-07-12 14:05:01,未知-未知,广播,0 DAA1198B5455,其他,2018-07-12 14:02:07,2018-07-12 14:02:07,2018-07-12 14:02:07,未知-未知,广播,0 DAA1198E772B,其他,2018-07-12 14:00:16,2018-07-12 14:00:16,2018-07-12 14:00:16,未知-未知,广播,0 DAA1199042DF,其他,2018-07-12 14:03:30,2018-07-12 14:03:30,2018-07-12 14:03:30,未知-未知,广播,0 DAA11991301B,其他,2018-07-12 14:04:16,2018-07-12 14:04:16,2018-07-12 14:04:16,未知-未知,广播,0 DAA1199E01C9,其他,2018-07-12 14:00:24,2018-07-12 14:00:24,2018-07-12 14:00:25,未知-未知,广播,1 DAA119A05408,其他,2018-07-12 14:02:41,2018-07-12 14:02:41,2018-07-12 14:02:41,未知-未知,广播,0 DAA119A3792D,其他,2018-07-12 14:04:39,2018-07-12 14:04:39,2018-07-12 14:04:39,未知-未知,广播,0 DAA119A69A4E,其他,2018-07-12 14:02:52,2018-07-12 14:02:52,2018-07-12 14:02:52,未知-未知,广播,0 DAA119A9590D,其他,2018-07-12 14:04:39,2018-07-12 14:04:39,2018-07-12 14:04:39,未知-未知,广播,0 DAA119A9B66A,其他,2018-07-12 14:03:15,2018-07-12 14:03:15,2018-07-12 14:03:15,未知-未知,广播,0 DAA119ABDC90,其他,2018-07-12 14:04:39,2018-07-12 14:04:39,2018-07-12 14:04:39,未知-未知,广播,0 DAA119B76954,其他,2018-07-12 14:04:17,2018-07-12 14:04:17,2018-07-12 14:04:17,未知-未知,广播,0 DAA119BA6E22,其他,2018-07-12 14:03:15,2018-07-12 14:03:15,2018-07-12 14:03:15,未知-未知,广播,0 DAA119BC8135,其他,2018-07-12 14:04:05,2018-07-12 14:04:05,2018-07-12 14:04:05,未知-未知,广播,0 DAA119BD004F,其他,2018-07-12 14:00:17,2018-07-12 14:00:17,2018-07-12 14:00:17,未知-未知,广播,0 DAA119BD03EE,其他,2018-07-12 14:04:39,2018-07-12 14:04:39,2018-07-12 14:04:39,未知-未知,广播,0 DAA119BF50C4,其他,2018-07-12 14:02:39,2018-07-12 14:02:39,2018-07-12 14:02:39,未知-未知,广播,0 DAA119C0CDB8,其他,2018-07-12 14:01:19,2018-07-12 14:01:19,2018-07-12 14:01:19,未知-未知,广播,0 DAA119C1BD71,其他,2018-07-12 14:02:53,2018-07-12 14:02:53,2018-07-12 14:02:53,未知-未知,广播,0 DAA119C7EA99,其他,2018-07-12 14:03:37,2018-07-12 14:03:37,2018-07-12 14:03:38,未知-未知,广播,1 DAA119C86C24,其他,2018-07-12 14:01:02,2018-07-12 14:01:02,2018-07-12 14:01:02,未知-未知,广播,0 DAA119CEECA0,其他,2018-07-12 14:02:41,2018-07-12 14:02:41,2018-07-12 14:02:41,未知-未知,广播,0 DAA119D24D01,其他,2018-07-12 14:05:01,2018-07-12 14:05:01,2018-07-12 14:05:01,未知-未知,广播,0 DAA119DB32E6,其他,2018-07-12 14:02:53,2018-07-12 14:02:53,2018-07-12 14:02:53,未知-未知,广播,0 DAA119DE1822,其他,2018-07-12 14:02:22,2018-07-12 14:02:22,2018-07-12 14:02:22,未知-未知,广播,0 DAA119DEFEB2,其他,2018-07-12 13:59:39,2018-07-12 13:59:39,2018-07-12 13:59:39,未知-未知,广播,0 DAA119E29246,其他,2018-07-12 14:03:03,2018-07-12 14:03:03,2018-07-12 14:03:03,未知-未知,广播,0 DAA119E4CB7F,其他,2018-07-12 14:05:01,2018-07-12 14:05:01,2018-07-12 14:05:01,未知-未知,广播,0 DAA119E6984C,其他,2018-07-12 14:02:28,2018-07-12 14:02:28,2018-07-12 14:02:28,未知-未知,广播,0 DAA119E69A17,其他,2018-07-12 14:03:03,2018-07-12 14:03:03,2018-07-12 14:03:03,未知-未知,广播,0 DAA119E85004,其他,2018-07-12 14:05:01,2018-07-12 14:05:01,2018-07-12 14:05:01,未知-未知,广播,0 DAA119E9B964,其他,2018-07-12 14:00:02,2018-07-12 14:00:02,2018-07-12 14:00:03,未知-未知,广播,1 DAA119ED6A1E,其他,2018-07-12 14:05:01,2018-07-12 14:05:01,2018-07-12 14:05:01,未知-未知,广播,0 DAA119F111C5,其他,2018-07-12 13:59:39,2018-07-12 13:59:39,2018-07-12 13:59:39,未知-未知,广播,0 DAA119F3DA46,其他,2018-07-12 14:00:46,2018-07-12 14:00:46,2018-07-12 14:00:46,未知-未知,广播,0 DAA119F3EFA3,其他,2018-07-12 14:01:09,2018-07-12 14:01:09,2018-07-12 14:01:09,未知-未知,广播,0 DAA119F6D200,其他,2018-07-12 14:00:31,2018-07-12 14:00:31,2018-07-12 14:00:32,未知-未知,广播,1 DAA119F6DF93,其他,2018-07-12 14:00:16,2018-07-12 14:00:16,2018-07-12 14:00:16,未知-未知,广播,0 DAA119FE7089,其他,2018-07-12 14:01:21,2018-07-12 14:01:21,2018-07-12 14:01:22,未知-未知,广播,1 DC53604C66C0,其他,2018-07-12 13:59:16,2018-07-12 13:59:16,2018-07-12 14:06:33,未知-未知,广播,437 DE2E36FEE82E,其他,2018-07-12 14:00:38,2018-07-12 14:00:38,2018-07-12 14:00:56,未知-未知,广播,18 DEF19D23F154,其他,2018-07-12 14:02:38,2018-07-12 14:02:38,2018-07-12 14:02:38,未知-未知,广播,0 E006E6CE8F97,HonHai,2018-07-12 14:00:50,2018-07-12 14:00:50,2018-07-12 14:05:50,未知-未知,广播,300 E006E6CE9A0E,HonHai,2018-07-12 13:58:58,2018-07-12 13:58:58,2018-07-12 14:06:33,未知,僵尸屏,455 E6D5C72EA645,其他,2018-07-12 14:02:57,2018-07-12 14:02:57,2018-07-12 14:02:57,未知-未知,广播,0 E6F613C30991,其他,2018-07-12 13:59:05,2018-07-12 13:59:05,2018-07-12 13:59:05,未知-未知,广播,0 E8802EF16712,Apple,2018-07-12 14:01:12,2018-07-12 14:01:12,2018-07-12 14:05:36,未知,僵尸屏,264 E8B1FC4CA239,其他,2018-07-12 13:59:06,2018-07-12 13:59:06,2018-07-12 14:05:48,未知-未知,广播,402 E8B1FC5A879B,其他,2018-07-12 13:59:36,2018-07-12 13:59:36,2018-07-12 14:06:37,未知-未知,广播,421 E8B1FC5AC445,其他,2018-07-12 14:03:26,2018-07-12 14:03:26,2018-07-12 14:05:03,北京市-朝阳区,国贸CBD小屏组,97 E8B1FCAD1F4C,其他,2018-07-12 13:58:53,2018-07-12 13:58:53,2018-07-12 14:05:32,未知,僵尸屏,399 EAB17D786FE8,其他,2018-07-12 14:03:29,2018-07-12 14:03:29,2018-07-12 14:03:29,未知-未知,广播,0 EAD3476C79EA,其他,2018-07-12 14:03:22,2018-07-12 14:03:22,2018-07-12 14:03:22,未知-未知,广播,0 EAD6E82234FE,其他,2018-07-12 14:01:56,2018-07-12 14:01:56,2018-07-12 14:01:56,未知-未知,广播,0 EE170A33F722,其他,2018-07-12 14:01:48,2018-07-12 14:01:48,2018-07-12 14:01:48,未知-未知,广播,0 F0B4290F5DEC,Xiaomi,2018-07-12 14:01:56,2018-07-12 14:01:56,2018-07-12 14:04:32,未知,僵尸屏,156 F0B429CDDA00,Xiaomi,2018-07-12 13:59:14,2018-07-12 13:59:14,2018-07-12 14:06:33,未知,僵尸屏,439 F2231510B8B8,其他,2018-07-12 14:03:23,2018-07-12 14:03:23,2018-07-12 14:03:23,未知-未知,广播,0 F242B220867E,其他,2018-07-12 13:59:00,2018-07-12 13:59:00,2018-07-12 13:59:00,未知-未知,广播,0 F48C500B6F6C,其他,2018-07-12 13:59:38,2018-07-12 13:59:38,2018-07-12 14:01:37,未知,僵尸屏,119 F60F8D888CED,其他,2018-07-12 13:59:16,2018-07-12 13:59:16,2018-07-12 13:59:16,未知-未知,广播,0 F6E4DA3E9024,其他,2018-07-12 14:06:05,2018-07-12 14:06:05,2018-07-12 14:06:05,未知-未知,广播,0 F6F3B944683D,其他,2018-07-12 14:02:04,2018-07-12 14:02:04,2018-07-12 14:02:04,未知-未知,广播,0 FA5360AD50CC,其他,2018-07-12 14:02:15,2018-07-12 14:02:15,2018-07-12 14:02:15,未知-未知,广播,0 FA8B4C2A31A4,其他,2018-07-12 14:05:52,2018-07-12 14:05:52,2018-07-12 14:05:53,未知-未知,广播,1 FCD848C807B5,Apple,2018-07-12 14:00:41,2018-07-12 14:00:41,2018-07-12 14:06:32,北京市-朝阳区,国贸CBD小屏组,351 FE305C782386,其他,2018-07-12 14:02:50,2018-07-12 14:02:50,2018-07-12 14:02:50,未知-未知,广播,0 FE519EDD25D9,其他,2018-07-12 14:03:31,2018-07-12 14:03:31,2018-07-12 14:03:31,未知-未知,广播,0 FEC0608F30DC,其他,2018-07-12 14:02:51,2018-07-12 14:02:51,2018-07-12 14:02:51,未知-未知,广播,0 FEDE7582DCAF,其他,2018-07-12 14:01:12,2018-07-12 14:01:12,2018-07-12 14:01:12,未知-未知,广播,0 FEEBB23B99E6,其他,2018-07-12 14:01:56,2018-07-12 14:01:56,2018-07-12 14:01:56,未知-未知,广播,0
本次所有示例的函数有：
1 // misc non-aggregate functions
2 expression[Abs]("abs"),
3 expression[Coalesce]("coalesce"),
4 expression[Explode]("explode"),
5 expression[Greatest]("greatest"),
6 expression[If]("if"),
7 expression[Inline]("inline"),
8 expression[IsNaN]("isnan"),
9 expression[IfNull]("ifnull"),
10 expression[IsNull]("isnull"),
11 expression[IsNotNull]("isnotnull"),
12 expression[Least]("least"),
13 expression[NaNvl]("nanvl"),
14 expression[NullIf]("nullif"),
15 expression[Nvl]("nvl"),
16 expression[Nvl2]("nvl2"),
17 expression[PosExplode]("posexplode"),
18 expression[Rand]("rand"),
19 expression[Randn]("randn"),
20 expression[Stack]("stack"),
21 expression[CaseWhen]("when"),
22
23 // math functions
24 expression[Acos]("acos"),
25 expression[Asin]("asin"),
26 expression[Atan]("atan"),
27 expression[Atan2]("atan2"),
28 expression[Bin]("bin"),
29 expression[BRound]("bround"),
30 expression[Cbrt]("cbrt"),
31 expression[Ceil]("ceil"),
32 expression[Ceil]("ceiling"),
33 expression[Cos]("cos"),
34 expression[Cosh]("cosh"),
35 expression[Conv]("conv"),
36 expression[ToDegrees]("degrees"),
37 expression[EulerNumber]("e"),
38 expression[Exp]("exp"),
39 expression[Expm1]("expm1"),
40 expression[Floor]("floor"),
41 expression[Factorial]("factorial"),
42 expression[Hex]("hex"),
43 expression[Hypot]("hypot"),
44 expression[Logarithm]("log"),
45 expression[Log10]("log10"),
46 expression[Log1p]("log1p"),
47 expression[Log2]("log2"),
48 expression[Log]("ln"),
49 expression[UnaryMinus]("negative"),
50 expression[Pi]("pi"),
51 expression[Pmod]("pmod"),
52 expression[UnaryPositive]("positive"),
53 expression[Pow]("pow"),
54 expression[Pow]("power"),
55 expression[ToRadians]("radians"),
56 expression[Rint]("rint"),
57 expression[Round]("round"),
58 expression[ShiftLeft]("shiftleft"),
59 expression[ShiftRight]("shiftright"),
60 expression[ShiftRightUnsigned]("shiftrightunsigned"),
61 expression[Signum]("sign"),
62 expression[Signum]("signum"),
63 expression[Sin]("sin"),
64 expression[Sinh]("sinh"),
65 expression[StringToMap]("str_to_map"),
66 expression[Sqrt]("sqrt"),
67 expression[Tan]("tan"),
68 expression[Tanh]("tanh"),
69
70 expression[Add]("+"),
71 expression[Subtract]("-"),
72 expression[Multiply]("*"),
73 expression[Divide]("/"),
74 expression[Remainder]("%"),
75
76 // aggregate functions
77 expression[HyperLogLogPlusPlus]("approx_count_distinct"),
78 expression[Average]("avg"),
79 expression[Corr]("corr"),
80 expression[Count]("count"),
81 expression[CovPopulation]("covar_pop"),
82 expression[CovSample]("covar_samp"),
83 expression[First]("first"),
84 expression[First]("first_value"),
85 expression[Kurtosis]("kurtosis"),
86 expression[Last]("last"),
87 expression[Last]("last_value"),
88 expression[Max]("max"),
89 expression[Average]("mean"),
90 expression[Min]("min"),
91 expression[Percentile]("percentile"),
92 expression[Skewness]("skewness"),
93 expression[ApproximatePercentile]("percentile_approx"),
94 expression[ApproximatePercentile]("approx_percentile"),
95 expression[StddevSamp]("std"),
96 expression[StddevSamp]("stddev"),
97 expression[StddevPop]("stddev_pop"),
98 expression[StddevSamp]("stddev_samp"),
99 expression[Sum]("sum"),
100 expression[VarianceSamp]("variance"),
101 expression[VariancePop]("var_pop"),
102 expression[VarianceSamp]("var_samp"),
103 expression[CollectList]("collect_list"),
104 expression[CollectSet]("collect_set"),
105
106 // string functions
107 expression[Ascii]("ascii"),
108 expression[Base64]("base64"),
109 expression[Concat]("concat"),
110 expression[ConcatWs]("concat_ws"),
111 expression[Decode]("decode"),
112 expression[Elt]("elt"),
113 expression[Encode]("encode"),
114 expression[FindInSet]("find_in_set"),
115 expression[FormatNumber]("format_number"),
116 expression[FormatString]("format_string"),
117 expression[GetJsonObject]("get_json_object"),
118 expression[InitCap]("initcap"),
119 expression[StringInstr]("instr"),
120 expression[Lower]("lcase"),
121 expression[Length]("length"),
122 expression[Levenshtein]("levenshtein"),
123 expression[Like]("like"),
124 expression[Lower]("lower"),
125 expression[StringLocate]("locate"),
126 expression[StringLPad]("lpad"),
127 expression[StringTrimLeft]("ltrim"),
128 expression[JsonTuple]("json_tuple"),
129 expression[ParseUrl]("parse_url"),
130 expression[FormatString]("printf"),
131 expression[RegExpExtract]("regexp_extract"),
132 expression[RegExpReplace]("regexp_replace"),
133 expression[StringRepeat]("repeat"),
134 expression[StringReverse]("reverse"),
135 expression[RLike]("rlike"),
136 expression[StringRPad]("rpad"),
137 expression[StringTrimRight]("rtrim"),
138 expression[Sentences]("sentences"),
139 expression[SoundEx]("soundex"),
140 expression[StringSpace]("space"),
141 expression[StringSplit]("split"),
142 expression[Substring]("substr"),
143 expression[Substring]("substring"),
144 expression[SubstringIndex]("substring_index"),
145 expression[StringTranslate]("translate"),
146 expression[StringTrim]("trim"),
147 expression[Upper]("ucase"),
148 expression[UnBase64]("unbase64"),
149 expression[Unhex]("unhex"),
150 expression[Upper]("upper"),
151 expression[XPathList]("xpath"),
152 expression[XPathBoolean]("xpath_boolean"),
153 expression[XPathDouble]("xpath_double"),
154 expression[XPathDouble]("xpath_number"),
155 expression[XPathFloat]("xpath_float"),
156 expression[XPathInt]("xpath_int"),
157 expression[XPathLong]("xpath_long"),
158 expression[XPathShort]("xpath_short"),
159 expression[XPathString]("xpath_string"),
160
161 // datetime functions
162 expression[AddMonths]("add_months"),
163 expression[CurrentDate]("current_date"),
164 expression[CurrentTimestamp]("current_timestamp"),
165 expression[DateDiff]("datediff"),
166 expression[DateAdd]("date_add"),
167 expression[DateFormatClass]("date_format"),
168 expression[DateSub]("date_sub"),
169 expression[DayOfMonth]("day"),
170 expression[DayOfYear]("dayofyear"),
171 expression[DayOfMonth]("dayofmonth"),
172 expression[FromUnixTime]("from_unixtime"),
173 expression[FromUTCTimestamp]("from_utc_timestamp"),
174 expression[Hour]("hour"),
175 expression[LastDay]("last_day"),
176 expression[Minute]("minute"),
177 expression[Month]("month"),
178 expression[MonthsBetween]("months_between"),
179 expression[NextDay]("next_day"),
180 expression[CurrentTimestamp]("now"),
181 expression[Quarter]("quarter"),
182 expression[Second]("second"),
183 expression[ToDate]("to_date"),
184 expression[ToUnixTimestamp]("to_unix_timestamp"),
185 expression[ToUTCTimestamp]("to_utc_timestamp"),
186 expression[TruncDate]("trunc"),
187 expression[UnixTimestamp]("unix_timestamp"),
188 expression[WeekOfYear]("weekofyear"),
189 expression[Year]("year"),
190 expression[TimeWindow]("window"),
191
192 // collection functions
193 expression[CreateArray]("array"),
194 expression[ArrayContains]("array_contains"),
195 expression[CreateMap]("map"),
196 expression[CreateNamedStruct]("named_struct"),
197 expression[MapKeys]("map_keys"),
198 expression[MapValues]("map_values"),
199 expression[Size]("size"),
200 expression[SortArray]("sort_array"),
201 CreateStruct.registryEntry,
202
203 // misc functions
204 expression[AssertTrue]("assert_true"),
205 expression[Crc32]("crc32"),
206 expression[Md5]("md5"),
207 expression[Murmur3Hash]("hash"),
208 expression[Sha1]("sha"),
209 expression[Sha1]("sha1"),
210 expression[Sha2]("sha2"),
211 expression[SparkPartitionID]("spark_partition_id"),
212 expression[InputFileName]("input_file_name"),
213 expression[MonotonicallyIncreasingID]("monotonically_increasing_id"),
214 expression[CurrentDatabase]("current_database"),
215 expression[CallMethodViaReflection]("reflect"),
216 expression[CallMethodViaReflection]("java_method"),
217
218 // grouping sets
219 expression[Cube]("cube"),
220 expression[Rollup]("rollup"),
221 expression[Grouping]("grouping"),
222 expression[GroupingID]("grouping_id"),
223
224 // window functions
225 expression[Lead]("lead"),
226 expression[Lag]("lag"),
227 expression[RowNumber]("row_number"),
228 expression[CumeDist]("cume_dist"),
229 expression[NTile]("ntile"),
230 expression[Rank]("rank"),
231 expression[DenseRank]("dense_rank"),
232 expression[PercentRank]("percent_rank"),
233
234 // predicates
235 expression[And]("and"),
236 expression[In]("in"),
237 expression[Not]("not"),
238 expression[Or]("or"),
239
240 // comparison operators
241 expression[EqualNullSafe]("<=>"),
242 expression[EqualTo]("="),
243 expression[EqualTo]("=="),
244 expression[GreaterThan](">"),
245 expression[GreaterThanOrEqual](">="),
246 expression[LessThan]("<"),
247 expression[LessThanOrEqual]("<="),
248 expression[Not]("!"),
249
250 // bitwise
251 expression[BitwiseAnd]("&"),
252 expression[BitwiseNot]("~"),
253 expression[BitwiseOr]("|"),
254 expression[BitwiseXor]("^"),
255
256 // Cast aliases (SPARK-16730)
257 castAlias("boolean", BooleanType),
258 castAlias("tinyint", ByteType),
259 castAlias("smallint", ShortType),
260 castAlias("int", IntegerType),
261 castAlias("bigint", LongType),
262 castAlias("float", FloatType),
263 castAlias("double", DoubleType),
264 castAlias("decimal", DecimalType.USER_DEFAULT),
265 castAlias("date", DateType),
266 castAlias("timestamp", TimestampType),
267 castAlias("binary", BinaryType),
268 castAlias("string", StringType)
Start
import org.apache.spark.sql
import org.apache.spark.sql.functions._
object Query { val ssc = new sql.SparkSession .Builder() .appName("query") .master("local[2]") .getOrCreate() ssc.conf.set("spark.sql.shuffle.partitions", 6) ssc.conf.set("spark.executor.memory", "6g") ssc.sparkContext.setLogLevel("error")
def main(args:Array[String]):Unit = {
//读入文件并将其转换为DF val fileName = "file:///E:\\工作\\WifiData\\data\\" + args(0) + "visit.txt" val df_1 = ssc.read.option("headler", "false").option("inferschema", "true").csv(fileName) .toDF("mac", "phone_brand", "enter_time", "first_time", "last_time", "region", "screen", "stay_long")
}
注：在使用函数的时候最好要导入org.apache.spark.sql.functions._这个包
import ssc.implicits._（这个包在实际写sql的时候将其导入）
一、混合非聚合函数(misc non-aggregate functions)
1、abs：绝对值
import ssc.implicits._
df_1.selectExpr("abs(stay_long) as res_abs").show(5)
2、coalesce：返回第一列部位空的列值，源码解释如下:
/**Returns the first column that is not null, or null if all inputs are null.
* For example, `coalesce(a, b, c)` will return a if a is not null,
* or b if a is null and b is not null, or c if both a and b are null but c is not null.
import ssc.implicits._
df_1.selectExpr("coalesce(mac,screen,stay_long) as res_colesce").show(5)//手动将第一条记录的第一个字段置为空，则显示第二个字段值
3、explode：Creates a new row for each element in the given array or map column.
3.1、有些时候我们需要使用sparksql来解析一些json文件，对于常规的无嵌套的json文件来说，比如：
{"name":"Michael"}
{"name":"Andy","age":30}
{"name":"Justin","age":19}
val fileName = "E:\\工作\\WifiData\\data\\" + startDate + "visit.txt"
val df_numFile = ssc.read.json("file:///" + fileName)
df_numFile.select("*").show()
我们直接使用ssc.read.json("path")的方式进行读取，之后可以直接进行相关的sql进行查询。
但是对于嵌套类型的json文件，就感觉到有点吃力了，比如：
{"name":"Michael", "age":25,"myScore":[{"score1":19,"score2":23},{"score1":58,"score2":50}]}
{"name":"Andy", "age":30,"myScore":[{"score1":29,"score2":33},{"score1":38,"score2":52},{"score1":88,"score2":71}]}
{"name":"Justin", "age":19,"myScore":[{"score1":39,"score2":43},{"score1":28,"score2":53}]}
val fileName = "E:\\工作\\WifiData\\data\\" + startDate + "visit.txt"
val df_numFile = ssc.read.json("file:///" + fileName)
df_numFile.select("*").show()
然而，这并不是我们想要的，这里explode函数有有用处了，将上面的代码修改一下
val fileName = "E:\\工作\\WifiData\\data\\" + startDate + "visit.txt"
val df_numFile = ssc.read.json("file:///" + fileName)
val df_score = df_numFile.select(df_numFile("name"),explode(df_numFile("myScore"))).toDF("name","myScore")
val dfMyScore = df_score.select("name","myScore.score1","myScore.score2")
咦？好像少点啥，age字段呢，给丢了，加上，一个都不能少不是：
val fileName = "E:\\工作\\WifiData\\data\\" + startDate + "visit.txt"
val df_numFile = ssc.read.json("file:///" + fileName)
val df_score = df_numFile.select(df_numFile("name"),df_numFile("age"),explode(df_numFile("myScore"))).toDF("name","myScore")
val dfMyScore = df_score.select("name","age","myScore.score1","myScore.score2")
dfMyScore.select("*").show()
//这会应该全了吧，试试...
什么情况？报错了，列名数量不匹配，在来修改
val fileName = "E:\\工作\\WifiData\\data\\" + startDate + "visit.txt"
val df_numFile = ssc.read.json("file:///" + fileName)
val df_score = df_numFile.select(df_numFile("name"),df_numFile("age"),explode(df_numFile("myScore"))).toDF("name","age","myScore")
val dfMyScore = df_score.select("name","age","myScore.score1","myScore.score2")
dfMyScore.select("*").show()
//再试一下...
这会得到了正确的结果。
3.2、explode还可以将单列扩展成多行
参数可以是Array，可以是Map
总结：explode该函数将指定 字段转换成DF的时候，是对应的整个表的列而不是该函数里面的字段对应里面的列数，这句话听起来比较绕口，把我自己都绕蒙了，还是得根据实例来理解
当然explod还有其他的用法，比如Arrya、map等类型的数据操作，后期我会在补上
4、greatest：求列表中的最大值
源码解释：(Returns the greatest value of the list of values, skipping null values.This function takes at least 2 parameters. It will return null iff all parameters are null.)
注意：必须是同类型的才可以比较
df_1.select(greatest("enter_time","first_time","last_time") as("greatest")).show(3)
5、if:用于条件判断
源码解释：Returns valueTrue when testCondition is true, returns valueFalseOrNull otherwise.
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select enter_time,first_time,last_time,if(stay_long = 0,'x','y') as type from d1
""".stripMargin).show(3)
6、inline：
7、isnan：判断字段值是否为空
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select isnan(screen) as isnull,first_time,last_time,if(isnan(mac),1,2) as type from d1
""".stripMargin).show(3)
二、字符函数
1、ascii(string str)：返回str中第一个字符的ascii值
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,ascii(mac) as after_convert
|from d1
""".stripMargin).show(3, false)
2、base64(column str):将str列进行base64编码作为字符串返回，与unbase64对应
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,base64(mac) as after_convert
|from d1
""".stripMargin).show(3, false)
3、concat(string str1,string str2...)：将多个字符串拼接为一个字符串
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,concat(mac,first_time) as after_convert
|from d1
""".stripMargin).show(3, false)
4、concat_ws:使用指定的连接符将多个字符拼接为一个字符
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,first_time,concat_ws('-',mac,first_time) as after_convert
|from d1
""".stripMargin).show(3, false)
5、encode(value:column,charset:string):转码，character支持的格式有：US-ASCII,ISO-8859-1,UTF-8,UTF-16BE,UTF-16LE,UTF-16
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,first_time,encode(mac,'ISO-8859-1') as after_convert
|from d1
""".stripMargin).show(3, false)
6、decode(value:column,charset:string):使用charset编码格式进行解码，支持的格式有：US-ASCII,ISO-8859-1,UTF-8,UTF-16BE,UTF-16LE,UTF-16
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,first_time,decode(encode(mac,'iso-8859-1'),'iso-8859-1') as after_convert
|from d1
""".stripMargin).show(3, false)
7、format_number(value:column,Int:d)：实现对数字进行格式化，例如四舍五入保留d位小数,column必须是数组，不能是字符串
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,format_number(3.1415926,3) as after_convert
|from d1
""".stripMargin).show(3, false)
8、format_string(format:string,argument:column*):将column按照format进行格式化
目前我还不知道有么用处
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,format_string('%s',mac) as after_convert
|from d1
""".stripMargin).show(3, false)
9、get_json_object():
10、initcap(column:str):将str字段的首个字母大写
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,initcap('asdfSDFcasdfASDf') as after_convert
|from d1
""".stripMargin).show(3, false)
11、lower，upper:转大写，转小写
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,lower(mac) as lower,upper(mac) as upper
|from d1
""".stripMargin).show(3, false)
12、instr(str:column,substring:String)：返回substring在str中第一次出现的位置(索引从1开始)
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,instr(mac,'D') as after_convert
|from d1
""".stripMargin).show(3, false)
13、length：返回字符串的长度
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,length(mac) as after_convert
|from d1
""".stripMargin).show(3, false)
14、 levenshtein(l:column,r:column):计算两个字符串之间的编辑距离
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,first_time,levenshtein(mac,first_time) as after_convert
|from d1
""".stripMargin).show(3, false)
15、locate(substr:string,str:column,pos:Int):
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,first_time,locate('E',mac) as after_convert_1,locate('D',mac,8) as after_convert_2
|from d1
""".stripMargin).show(3, false)
16、lpad:左补齐
rpad:右补齐
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,lpad(mac,20,'--') as left,rpad(mac,20,'--') as right
|from d1
""".stripMargin).show(3, false)
17、ltrim、ltrim、trim:去除做空格，去除有空格，去除左右两边的空格
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select mac,ltrim(mac) as ltrim,trim(mac) as rtrim,trim(mac) as trim
|from d1
""".stripMargin).show(4, false)
18、
三、日期函数
1、add_months：将指定时间字段的月份加指定的月份数
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,add_months(first_time,3) as after_add from d1
""".stripMargin).show(3)
2、current_date:获取当前的日期
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,current_date() as current from d1
""".stripMargin).show(3)
3、current_timestamp：获取当前的时间
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,current_timestamp() as current_time from d1
""".stripMargin).show(3,false)
4、datediff(a,b)：返回日期a与日期b的时间差，结果是天数
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,current_timestamp() as current_time,datediff(first_time,current_timestamp) as diff from d1
""".stripMargin).show(3,false)
5、date_add:指定天数之后的某几天
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,date_add(first_time,3) as after_add from d1
""".stripMargin).show(3,false)
6、date_format:将日期字段(timestamp类型)格式化为想要的格式
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,
|date_format(first_time,'yyyy-MM-dd') as date,
|date_format(first_time,'yyyy') as year,
|date_format(first_time,'MM') as month,
|date_format(first_time,'dd') as day,
|date_format(first_time,'HH:mm:ss') as time,
|date_format(first_time,'HH') as hour,
|date_format(first_time,'mm') as minute,
|date_format(first_time,'ss') as seconds
|from d1
""".stripMargin).show(3,false)
7、date_sub:返回日期的前几天
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,date_sub(first_time,3) as sub
|from d1
""".stripMargin).show(3,false)
8、day:返回日期中的天
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,day(first_time) as sub
|from d1
""".stripMargin).show(3,false)
}
9、dayofyear：返回给定时间中day是这一年中的第几天，返回一个数字
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,dayofyear(first_time) as day
|from d1
""".stripMargin).show(3,false)
10、dayofmonth：返回给定时间中的天是该月的第几天
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,dayofmonth(first_time) as month
|from d1
""".stripMargin).show(3,false)
11、from_unixtime:
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,from_unixtime(tm,'yyyy-MM-dd HH:mm:ss') as after_convert
|from d1
""".stripMargin).show(3,false)
注：这里的tm必须是时间秒数，例如(1250111000)
12、from_utc_timestamp ：如果给定的时间戳并非UTC，则将其转化成指定时区下的时间戳
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,from_utc_timestamp(first_time,'PST') as after_convert //将first_time(默认是UTC时区时间)转换为PST时区的时间戳
|from d1
""".stripMargin).show(3,false)
13、hour：返回指定时间戳的小时
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,hour(first_time) as after_convert
|from d1
""".stripMargin).show(3,false)
14、last_day:返回给定时间戳的当月的最后一天的日期
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,last_day(first_time) as after_convert
|from d1
""".stripMargin).show(3,false)
15、minute：返回指定时间戳的分钟数
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,minute(first_time) as after_convert
|from d1
""".stripMargin).show(3,false)
16、month：返回指定时间戳的月
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,month(first_time) as after_convert
|from d1
""".stripMargin).show(3,false)
17、months_between：返回两个时间戳月份的时间差
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select enter_time,first_time,months_between(enter_time,first_time) as after_convert
|from d1
""".stripMargin).show(3,false)
18、next_day:返回指定时间戳的一周之后的这天
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,next_day(first_time，,'TU') as after_convert //返回first_time开始，下周的星期二的日期
|from d1
""".stripMargin).show(3,false)
19、now:放回当前的时间戳
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,now() as after_convert
|from d1
""".stripMargin).show(3,false)
20、quarter：返回指定时间戳是在该年中的第几个季度
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,quarter(first_time) as after_convert
|from d1
""".stripMargin).show(3,false)
21、second：返回给定时间戳的秒数
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,second(first_time) as after_convert
|from d1
""".stripMargin).show(3,false)
22、to_date：返回时间字符串的日期部分
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,to_date(first_time) as after_convert
|from d1
""".stripMargin).show(3,false)
23、to_unix_timestamp:根据提供的字符串格式转换成Unix时间
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,to_unix_timestamp('16/Mar/2017:12:25:01 +0800','dd/MMM/yyyy:HH:mm:ss Z') as after_convert
|from d1
""".stripMargin).show(3,false)
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,to_unix_timestamp(first_time,'yyyy-MM-dd HH:mm:ss') as after_convert
|from d1
""".stripMargin).show(3,false)
24、to_utc_timestamp:将指定的时间戳转换为UTC下的时间戳
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,to_utc_timestamp(first_time,'yyyy-MM-dd HH:mm:ss') as after_convert
|from d1
""".stripMargin).show(3,false)
25、trunc：返回指定时间最开始的年份或是月份（只支持MONTH/MON/MM,YEAR/YYYY/YY）
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,trunc(first_time,'MM') as after_convert
|from d1
""".stripMargin).show(3,false)
26、unix_timestamp:转换时间字符串格式yyyy-MM-dd HH:mm:dd 到unix时间(秒),如果不加参数的话，则获取的是当前的时间的unix时间
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,unix_timestamp(first_time) as after_convert
|from d1
""".stripMargin).show(3,false)
27、weekofyear：返回指定的时间戳是该年中第几周
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,weekofyear(first_time) as after_convert
|from d1
""".stripMargin).show(3,false)
28、year：返回指定时间戳中的年
df_1.createOrReplaceTempView("d1")
ssc.sql(
"""
|select first_time,year(first_time) as after_convert
|from d1
""".stripMargin).show(3,false)
29、window：
四、聚合函数
五、数学函数
六、类型转换函数
标签： 来源： https://www.cnblogs.com/Gxiaobai/p/9678218.html
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