scd2 table implementation in google bigquery












0















I am trying to create a SCD (slowly changing dimension) type 2 table in BigQuery without using any DML's



test schema :



id | date | name | valid_from | valid_to | flag



I need to capture the name changes for a specific id.



Thanks,










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    0















    I am trying to create a SCD (slowly changing dimension) type 2 table in BigQuery without using any DML's



    test schema :



    id | date | name | valid_from | valid_to | flag



    I need to capture the name changes for a specific id.



    Thanks,










    share|improve this question



























      0












      0








      0








      I am trying to create a SCD (slowly changing dimension) type 2 table in BigQuery without using any DML's



      test schema :



      id | date | name | valid_from | valid_to | flag



      I need to capture the name changes for a specific id.



      Thanks,










      share|improve this question
















      I am trying to create a SCD (slowly changing dimension) type 2 table in BigQuery without using any DML's



      test schema :



      id | date | name | valid_from | valid_to | flag



      I need to capture the name changes for a specific id.



      Thanks,







      google-bigquery scd2






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      share|improve this question








      edited Nov 26 '18 at 6:30









      TeeKea

      3,22851932




      3,22851932










      asked Nov 25 '18 at 19:21









      dineshachantadineshachanta

      211




      211
























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          You can create artificially date partitioned tables to achieve this. This way, each date's data is unique and can be accessed by `select distinct column from `dataset.table$yyyymmdd;` or for all the history, just do select distinct column from dataset.table;. Also, you can always overwrite/append to a given date's partition without harming others.






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            You can create artificially date partitioned tables to achieve this. This way, each date's data is unique and can be accessed by `select distinct column from `dataset.table$yyyymmdd;` or for all the history, just do select distinct column from dataset.table;. Also, you can always overwrite/append to a given date's partition without harming others.






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              You can create artificially date partitioned tables to achieve this. This way, each date's data is unique and can be accessed by `select distinct column from `dataset.table$yyyymmdd;` or for all the history, just do select distinct column from dataset.table;. Also, you can always overwrite/append to a given date's partition without harming others.






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                1







                You can create artificially date partitioned tables to achieve this. This way, each date's data is unique and can be accessed by `select distinct column from `dataset.table$yyyymmdd;` or for all the history, just do select distinct column from dataset.table;. Also, you can always overwrite/append to a given date's partition without harming others.






                share|improve this answer













                You can create artificially date partitioned tables to achieve this. This way, each date's data is unique and can be accessed by `select distinct column from `dataset.table$yyyymmdd;` or for all the history, just do select distinct column from dataset.table;. Also, you can always overwrite/append to a given date's partition without harming others.







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                answered Nov 26 '18 at 0:52









                khankhan

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                2,12493053
































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