Teradata 如何 select 第一次出现
Teradata how to select first occurrent
我有一个table类似于下图。在这个 table 中，我在 SESS_KEY 中有一些重复项。我只想要没有重复的行，或者如果有重复的行，我只想要 CALL_TRNSF_FLG 设置为 1 的行。我有手动创建 INCLUDE 字段来显示我想要的列 (1)。我怎样才能做到这一点？
感谢您的帮助！
示例数据如下：
INCLUDE SESS_KEY SESS_CALL_ST_DT_TS CONN_ID TLK_DUR HLD_DUR AFT_CALL_WRK_DUR TRNSF_TLK_TM TRNSF_HLD_TM TRNSF_ACW_TM CALL_TRNSF_FLG
0 24067A16-A24A-45BE-E3AA-7E0BFE7ECDA5 7/25/2016 9:07 0141028541267da5 918 57 26 ? ? ? 0
1 24067A16-A24A-45BE-E3AA-7E0BFE7ECDA5 7/25/2016 9:07 0521028304ed75f8 236 0 3 918 57 26 1
0 49FFAB03-C19C-4291-6BAB-267CC95E27CF 7/6/2016 17:25 014102854125f060 278 0 130 ? ? ? 0
1 49FFAB03-C19C-4291-6BAB-267CC95E27CF 7/6/2016 17:25 0521028304e98111 391 0 8 278 0 130 1
0 7CCBBF2F-6FBC-4812-BAB1-4E258B88C20A 7/12/2016 11:34 05200282b0814531 269 0 190 406 0 124 1
1 7CCBBF2F-6FBC-4812-BAB1-4E258B88C20A 7/12/2016 11:34 013b028225ed6484 406 0 124 ? ? ? 0
0 CA32F05E-5C8A-4849-63A4-15B2342081B8 7/6/2016 11:38 02420282b06776f9 256 0 114 297 0 67 1
1 CA32F05E-5C8A-4849-63A4-15B2342081B8 7/6/2016 11:38 014102854125ea06 297 0 67 ? ? ? 0
0 E75EF405-1C0D-45E4-EC97-88D3CD7B5E55 7/5/2016 15:03 1.41E+214 2,691 0 255 ? ? ? 0
1 E75EF405-1C0D-45E4-EC97-88D3CD7B5E55 7/5/2016 15:03 0243028304ee14a5 314 0 9 2,691 0 255 1
1 04F8CC43-710B-4E4D-D8A1-DAC45FB3FF24 7/19/2016 16:49 1.41E+14 123 100 43 ? ? ? 0
1 0AFB6070-9D95-47B0-B0AF-D34ED70FCE8E 7/22/2016 14:20 0243028304f1ffca 335 239 79 ? ? ? 0
1 13581E6A-A568-4993-098C-05233CF293AE 7/15/2016 11:22 014102854126375a 196 150 258 ? ? ? 0
1 1A6AE4BE-1858-4CB3-83B1-CFF7A9E88EF9 7/8/2016 19:09 02420282b068325e 120 0 0 ? ? ? 0
1 24CE6C11-AF85-4770-53B4-FE20200339DF 7/28/2016 12:47 0243028304f3401b 181 0 0 107 0 48 1
1 293F85F4-34BC-44B1-43B5-A6B3B8886FC8 7/1/2016 8:33 0521028304e8778e 70 0 21 149 0 1 1
1 2BD0216A-B3F3-4597-1CBD-095F8D291736 7/7/2016 8:41 0243028304ee83b2 1,037 0 187 ? ? ? 0
1 2C774BE2-5B26-47C0-B69F-69B04A63F879 7/25/2016 18:26 013b028225edd637 1,481 0 110 ? ? ? 0
1 3F43720B-B6AE-4335-4FB5-9275A952989F 7/11/2016 11:08 013b028225ed5830 155 0 0 ? ? ? 0
1 41B056DC-8D3F-425D-BD9E-10A3EB0E944D 7/27/2016 11:13 05200282b084c5d5 34 0 0 ? ? ? 0
1 420483AD-8586-45C7-68AB-675E50EF2B92 7/5/2016 11:03 013b028225ed2765 1,320 0 283 ? ? ? 0
1 43A14051-6EAA-4251-3FA1-F2FBAE6DB643 7/23/2016 12:16 05200282b083f410 359 0 143 ? ? ? 0
1 494F3EA9-EA47-4F7B-C795-61B8B23DA0FA 7/21/2016 9:27 02420282b06ac6c3 0 0 0 ? ? ? 0
1 4D743557-DE09-4007-D58C-EFB09EF6713C 7/29/2016 17:19 05200282b085844a 951 361 240 ? ? ? 0
1 546C0FD0-5445-44F8-0789-1FA62BB57CDB 7/15/2016 18:14 1.41E+59 686 0 60 ? ? ? 0
1 5487C587-D37C-4E5C-9A88-87A3978996CD 7/28/2016 18:51 014102854126a96d 833 0 534 ? ? ? 0
1 5AB8D65A-28C7-4CAD-5796-3A7B720A47F7 7/20/2016 8:56 0141028541265a9f 274 111 381 ? ? ? 0
1 6866B3F8-F953-43BF-9089-B1FE699DEE07 7/19/2016 16:25 05200282b0830349 35 0 180 ? ? ? 0
1 6A4566B3-71B9-47BB-75BC-37B6E644D704 7/19/2016 10:14 02420282b06a3d7b 0 0 0 ? ? ? 0
1 72D17A78-FA5D-42DA-E39A-F7B950C15E22 7/5/2016 18:05 02420282b0675679 606 0 167 ? ? ? 0
1 73657A2A-34B7-4921-E691-49827E46128D 7/20/2016 11:02 02420282b06a8ae8 31 0 264 ? ? ? 0
1 7520F825-DA7B-4D5F-7AA9-3ADD9AAC5BE7 7/5/2016 18:53 05200282b07fd5df 354 0 20 ? ? ? 0
1 76DA5FB6-3EDD-45E1-B8BB-C70EA1CB4E53 7/1/2016 10:07 0243028304ed7c74 132 0 20 105 0 66 1
1 810B9E66-AA32-4BB0-128D-8E3FFC86EB0E 7/22/2016 13:37 013b028225edc13d 1,621 109 34 ? ? ? 0
1 81402352-DE71-45E4-4EAD-C1FFE20F8288 7/11/2016 9:28 0521028304ea456a 38 0 0 71 0 0 1
1 81EA3AD7-B721-4718-9AB0-6FB005252F64 7/12/2016 17:15 013b028225ed6ad5 812 129 60 ? ? ? 0
1 870632C0-4D80-41DC-AD84-12972DBC5AF2 7/23/2016 14:20 0243028304f229ee 1,084 0 5 ? ? ? 0
1 886919E7-80DB-4E2C-D5B2-8B83420F4D27 7/26/2016 19:22 0243028304f2da42 533 465 155 ? ? ? 0
1 8A18B8A2-1405-446B-71BA-A3FBAC816C12 7/8/2016 16:13 013b028225ed4f72 318 237 0 ? ? ? 0
1 8A54DAD7-2745-4BFB-22BE-BF479C1A8710 7/7/2016 15:25 02420282b067da6c 42 0 94 104 0 38 1
1 8D5EB433-2D50-4A67-00AC-E768A549B56E 7/26/2016 14:35 0521028304edf692 55 0 0 ? ? ? 0
1 8F222904-EC4E-4395-D496-A25FB408AD95 7/29/2016 17:09 0243028304f3a5f0 88 0 137 ? ? ? 0
1 9310922F-D545-4E78-42B2-E1B508F5A436 7/7/2016 12:23 02420282b067c625 155 2 15 ? ? ? 1
1 A605BF7A-50E6-4114-1981-7B3988079B7E 7/6/2016 16:56 02420282b0679dfa 89 0 293 ? ? ? 0
1 AA23384F-C4DA-4357-3DAF-7CD8337831DD 7/9/2016 11:20 014102854126082a 138 0 210 ? ? ? 0
1 AF5AD7E2-7584-4ACD-B28E-1AB2DB87BDAA 7/21/2016 17:36 0243028304f1cda6 0 0 0 ? ? ? 0
1 B66D3851-83BE-4E0E-7D9B-1719E378905D 7/19/2016 12:41 0243028304f122cd 81 0 0 ? ? ? 0
1 BB2FA3CD-AB6D-42BD-3CB7-EEC27E3403BF 7/15/2016 14:38 0243028304f0753e 65 0 195 92 3 29 1
1 BBA4031A-7876-4614-F9BC-718A6D8A16A7 7/13/2016 17:42 0521028304eb1a47 163 0 85 ? ? ? 0
1 BCF2B7D8-CBD0-497F-EEA7-FDEC46EFEEBE 7/7/2016 12:09 0521028304e9acaa 44 0 8 ? ? ? 0
1 BE9386B6-424E-40F9-67A1-A56EF6C18B77 7/27/2016 20:03 013b028225edecc5 1 0 0 ? ? ? 0
1 C0F0EF71-F52B-4D10-E9B4-DA1AF4343CC7 7/11/2016 15:21 05200282b08111ee 49 0 61 368 0 597 1
1 C84FCA28-2372-4F8B-52B1-4BC5E9AD128B 7/19/2016 13:06 013b028225eda06c 59 0 32 162 0 0 1
1 C8B3CC50-DEC3-4F24-D0A2-E32A03AFA786 7/13/2016 13:22 05200282b0819c4d 126 0 0 ? ? ? 0
1 CC119F61-A70F-4DB3-7C8C-DCE9A1C3BCB5 7/27/2016 9:48 02420282b06c1330 0 0 0 ? ? ? 0
1 D57D43C7-F9F0-42B9-C6B6-23B1414D9F12 7/14/2016 15:04 05200282b081ee2a 36 0 17 ? ? ? 0
1 E438B480-8F98-469C-3899-E6F10DD1F755 7/5/2016 20:12 02420282b0675cea 3,874 163 7 ? ? ? 0
1 F223F1F4-F50D-41F6-DA9F-46EA2972F394 7/27/2016 20:13 05200282b084f966 417 0 6 ? ? ? 0
1 FB3B0CB1-89D8-4B47-E4BA-465E57D52B0D 7/14/2016 14:21 02420282b0695b07 138 0 2 ? ? ? 0
您可以像这样过滤您想要的行：
WHERE
CONN_ID NOT IN (
SELECT
MIN(CONN_ID)
FROM
<<your_table>>
GROUP BY
SESS_KEY
HAVING
count(*) > 1
)
假设，那对：sess_key，conn_id 是唯一的。否则，您应该找到唯一的一组列并按它进行过滤。
您好
您可以查询，
Using JOINS
select t1.* from table_name t1
join
(select count(*),SESS_KEYfrom table_name
group by SESS_KEYhaving count(*) > 1 ) t2
on t1.SESS_KEY=t2.SESS_KEY;
Using WHERE clause
select t1.* from table_name t1,
(select count(*),SESS_KEYfrom table_name
group by SESS_KEYhaving count(*) > 1 ) t2
where t1.SESS_KEY=t2.SESS_KEY;
这为您提供了 SESS_KEY 列中的所有重复项
To Update
merge into table_name t1
using
(select count(*),SESS_KEYfrom table_name
group by SESS_KEYhaving count(*) > 1 ) t2
on t1.SESS_KEY=t2.SESS_KEY
when matched then
update set
CALL_TRNSF_FLG=1;
使用 MERGE 语句更新 table
SELECT *
FROM tab
QUALIFY
-- rows that does not have duplicates
COUNT(*)
OVER (PARTITION BY SESS_KEY) = 1
-- the ones with CALL_TRNSF_FLG set to 1
OR CALL_TRNSF_FLG = 1
如果 CALL_TRNSF_FLG = 1 可能有多行，而您每个会话只需要一行：
QUALIFY
ROW_NUMBER(*)
OVER (PARTITION BY SESS_KEY
ORDER BY CALL_TRNSF_FLG DESC) = 1
我有一个table类似于下图。在这个 table 中，我在 SESS_KEY 中有一些重复项。我只想要没有重复的行，或者如果有重复的行，我只想要 CALL_TRNSF_FLG 设置为 1 的行。我有手动创建 INCLUDE 字段来显示我想要的列 (1)。我怎样才能做到这一点？
感谢您的帮助！
示例数据如下：
INCLUDE SESS_KEY SESS_CALL_ST_DT_TS CONN_ID TLK_DUR HLD_DUR AFT_CALL_WRK_DUR TRNSF_TLK_TM TRNSF_HLD_TM TRNSF_ACW_TM CALL_TRNSF_FLG
0 24067A16-A24A-45BE-E3AA-7E0BFE7ECDA5 7/25/2016 9:07 0141028541267da5 918 57 26 ? ? ? 0
1 24067A16-A24A-45BE-E3AA-7E0BFE7ECDA5 7/25/2016 9:07 0521028304ed75f8 236 0 3 918 57 26 1
0 49FFAB03-C19C-4291-6BAB-267CC95E27CF 7/6/2016 17:25 014102854125f060 278 0 130 ? ? ? 0
1 49FFAB03-C19C-4291-6BAB-267CC95E27CF 7/6/2016 17:25 0521028304e98111 391 0 8 278 0 130 1
0 7CCBBF2F-6FBC-4812-BAB1-4E258B88C20A 7/12/2016 11:34 05200282b0814531 269 0 190 406 0 124 1
1 7CCBBF2F-6FBC-4812-BAB1-4E258B88C20A 7/12/2016 11:34 013b028225ed6484 406 0 124 ? ? ? 0
0 CA32F05E-5C8A-4849-63A4-15B2342081B8 7/6/2016 11:38 02420282b06776f9 256 0 114 297 0 67 1
1 CA32F05E-5C8A-4849-63A4-15B2342081B8 7/6/2016 11:38 014102854125ea06 297 0 67 ? ? ? 0
0 E75EF405-1C0D-45E4-EC97-88D3CD7B5E55 7/5/2016 15:03 1.41E+214 2,691 0 255 ? ? ? 0
1 E75EF405-1C0D-45E4-EC97-88D3CD7B5E55 7/5/2016 15:03 0243028304ee14a5 314 0 9 2,691 0 255 1
1 04F8CC43-710B-4E4D-D8A1-DAC45FB3FF24 7/19/2016 16:49 1.41E+14 123 100 43 ? ? ? 0
1 0AFB6070-9D95-47B0-B0AF-D34ED70FCE8E 7/22/2016 14:20 0243028304f1ffca 335 239 79 ? ? ? 0
1 13581E6A-A568-4993-098C-05233CF293AE 7/15/2016 11:22 014102854126375a 196 150 258 ? ? ? 0
1 1A6AE4BE-1858-4CB3-83B1-CFF7A9E88EF9 7/8/2016 19:09 02420282b068325e 120 0 0 ? ? ? 0
1 24CE6C11-AF85-4770-53B4-FE20200339DF 7/28/2016 12:47 0243028304f3401b 181 0 0 107 0 48 1
1 293F85F4-34BC-44B1-43B5-A6B3B8886FC8 7/1/2016 8:33 0521028304e8778e 70 0 21 149 0 1 1
1 2BD0216A-B3F3-4597-1CBD-095F8D291736 7/7/2016 8:41 0243028304ee83b2 1,037 0 187 ? ? ? 0
1 2C774BE2-5B26-47C0-B69F-69B04A63F879 7/25/2016 18:26 013b028225edd637 1,481 0 110 ? ? ? 0
1 3F43720B-B6AE-4335-4FB5-9275A952989F 7/11/2016 11:08 013b028225ed5830 155 0 0 ? ? ? 0
1 41B056DC-8D3F-425D-BD9E-10A3EB0E944D 7/27/2016 11:13 05200282b084c5d5 34 0 0 ? ? ? 0
1 420483AD-8586-45C7-68AB-675E50EF2B92 7/5/2016 11:03 013b028225ed2765 1,320 0 283 ? ? ? 0
1 43A14051-6EAA-4251-3FA1-F2FBAE6DB643 7/23/2016 12:16 05200282b083f410 359 0 143 ? ? ? 0
1 494F3EA9-EA47-4F7B-C795-61B8B23DA0FA 7/21/2016 9:27 02420282b06ac6c3 0 0 0 ? ? ? 0
1 4D743557-DE09-4007-D58C-EFB09EF6713C 7/29/2016 17:19 05200282b085844a 951 361 240 ? ? ? 0
1 546C0FD0-5445-44F8-0789-1FA62BB57CDB 7/15/2016 18:14 1.41E+59 686 0 60 ? ? ? 0
1 5487C587-D37C-4E5C-9A88-87A3978996CD 7/28/2016 18:51 014102854126a96d 833 0 534 ? ? ? 0
1 5AB8D65A-28C7-4CAD-5796-3A7B720A47F7 7/20/2016 8:56 0141028541265a9f 274 111 381 ? ? ? 0
1 6866B3F8-F953-43BF-9089-B1FE699DEE07 7/19/2016 16:25 05200282b0830349 35 0 180 ? ? ? 0
1 6A4566B3-71B9-47BB-75BC-37B6E644D704 7/19/2016 10:14 02420282b06a3d7b 0 0 0 ? ? ? 0
1 72D17A78-FA5D-42DA-E39A-F7B950C15E22 7/5/2016 18:05 02420282b0675679 606 0 167 ? ? ? 0
1 73657A2A-34B7-4921-E691-49827E46128D 7/20/2016 11:02 02420282b06a8ae8 31 0 264 ? ? ? 0
1 7520F825-DA7B-4D5F-7AA9-3ADD9AAC5BE7 7/5/2016 18:53 05200282b07fd5df 354 0 20 ? ? ? 0
1 76DA5FB6-3EDD-45E1-B8BB-C70EA1CB4E53 7/1/2016 10:07 0243028304ed7c74 132 0 20 105 0 66 1
1 810B9E66-AA32-4BB0-128D-8E3FFC86EB0E 7/22/2016 13:37 013b028225edc13d 1,621 109 34 ? ? ? 0
1 81402352-DE71-45E4-4EAD-C1FFE20F8288 7/11/2016 9:28 0521028304ea456a 38 0 0 71 0 0 1
1 81EA3AD7-B721-4718-9AB0-6FB005252F64 7/12/2016 17:15 013b028225ed6ad5 812 129 60 ? ? ? 0
1 870632C0-4D80-41DC-AD84-12972DBC5AF2 7/23/2016 14:20 0243028304f229ee 1,084 0 5 ? ? ? 0
1 886919E7-80DB-4E2C-D5B2-8B83420F4D27 7/26/2016 19:22 0243028304f2da42 533 465 155 ? ? ? 0
1 8A18B8A2-1405-446B-71BA-A3FBAC816C12 7/8/2016 16:13 013b028225ed4f72 318 237 0 ? ? ? 0
1 8A54DAD7-2745-4BFB-22BE-BF479C1A8710 7/7/2016 15:25 02420282b067da6c 42 0 94 104 0 38 1
1 8D5EB433-2D50-4A67-00AC-E768A549B56E 7/26/2016 14:35 0521028304edf692 55 0 0 ? ? ? 0
1 8F222904-EC4E-4395-D496-A25FB408AD95 7/29/2016 17:09 0243028304f3a5f0 88 0 137 ? ? ? 0
1 9310922F-D545-4E78-42B2-E1B508F5A436 7/7/2016 12:23 02420282b067c625 155 2 15 ? ? ? 1
1 A605BF7A-50E6-4114-1981-7B3988079B7E 7/6/2016 16:56 02420282b0679dfa 89 0 293 ? ? ? 0
1 AA23384F-C4DA-4357-3DAF-7CD8337831DD 7/9/2016 11:20 014102854126082a 138 0 210 ? ? ? 0
1 AF5AD7E2-7584-4ACD-B28E-1AB2DB87BDAA 7/21/2016 17:36 0243028304f1cda6 0 0 0 ? ? ? 0
1 B66D3851-83BE-4E0E-7D9B-1719E378905D 7/19/2016 12:41 0243028304f122cd 81 0 0 ? ? ? 0
1 BB2FA3CD-AB6D-42BD-3CB7-EEC27E3403BF 7/15/2016 14:38 0243028304f0753e 65 0 195 92 3 29 1
1 BBA4031A-7876-4614-F9BC-718A6D8A16A7 7/13/2016 17:42 0521028304eb1a47 163 0 85 ? ? ? 0
1 BCF2B7D8-CBD0-497F-EEA7-FDEC46EFEEBE 7/7/2016 12:09 0521028304e9acaa 44 0 8 ? ? ? 0
1 BE9386B6-424E-40F9-67A1-A56EF6C18B77 7/27/2016 20:03 013b028225edecc5 1 0 0 ? ? ? 0
1 C0F0EF71-F52B-4D10-E9B4-DA1AF4343CC7 7/11/2016 15:21 05200282b08111ee 49 0 61 368 0 597 1
1 C84FCA28-2372-4F8B-52B1-4BC5E9AD128B 7/19/2016 13:06 013b028225eda06c 59 0 32 162 0 0 1
1 C8B3CC50-DEC3-4F24-D0A2-E32A03AFA786 7/13/2016 13:22 05200282b0819c4d 126 0 0 ? ? ? 0
1 CC119F61-A70F-4DB3-7C8C-DCE9A1C3BCB5 7/27/2016 9:48 02420282b06c1330 0 0 0 ? ? ? 0
1 D57D43C7-F9F0-42B9-C6B6-23B1414D9F12 7/14/2016 15:04 05200282b081ee2a 36 0 17 ? ? ? 0
1 E438B480-8F98-469C-3899-E6F10DD1F755 7/5/2016 20:12 02420282b0675cea 3,874 163 7 ? ? ? 0
1 F223F1F4-F50D-41F6-DA9F-46EA2972F394 7/27/2016 20:13 05200282b084f966 417 0 6 ? ? ? 0
1 FB3B0CB1-89D8-4B47-E4BA-465E57D52B0D 7/14/2016 14:21 02420282b0695b07 138 0 2 ? ? ? 0
您可以像这样过滤您想要的行：
WHERE
CONN_ID NOT IN (
SELECT
MIN(CONN_ID)
FROM
<<your_table>>
GROUP BY
SESS_KEY
HAVING
count(*) > 1
)
假设，那对：sess_key，conn_id 是唯一的。否则，您应该找到唯一的一组列并按它进行过滤。
您好
您可以查询，
Using JOINS
select t1.* from table_name t1
join
(select count(*),SESS_KEYfrom table_name
group by SESS_KEYhaving count(*) > 1 ) t2
on t1.SESS_KEY=t2.SESS_KEY;
Using WHERE clause
select t1.* from table_name t1,
(select count(*),SESS_KEYfrom table_name
group by SESS_KEYhaving count(*) > 1 ) t2
where t1.SESS_KEY=t2.SESS_KEY;
这为您提供了 SESS_KEY 列中的所有重复项
To Update
merge into table_name t1
using
(select count(*),SESS_KEYfrom table_name
group by SESS_KEYhaving count(*) > 1 ) t2
on t1.SESS_KEY=t2.SESS_KEY
when matched then
update set
CALL_TRNSF_FLG=1;
使用 MERGE 语句更新 table
SELECT *
FROM tab
QUALIFY
-- rows that does not have duplicates
COUNT(*)
OVER (PARTITION BY SESS_KEY) = 1
-- the ones with CALL_TRNSF_FLG set to 1
OR CALL_TRNSF_FLG = 1
如果 CALL_TRNSF_FLG = 1 可能有多行，而您每个会话只需要一行：
QUALIFY
ROW_NUMBER(*)
OVER (PARTITION BY SESS_KEY
ORDER BY CALL_TRNSF_FLG DESC) = 1