I let you know a specific comportment when we use partitioned tables in BigQuery (date column).
I hope that someone can help me!
My use case :
My source table is partitioned by Date (basket_sales_date is a date type).
I add it in my datasource. Tableau detect a "Datetime" for this column and affect the Date type (in data panel).
I create my first worksheet, just with number of records and a filter on this date (range of date).
But ! The SQL generated by Tableau contains automatically a "cast( basket_sales_date as TIMESTAMP)".
SELECT SUM(CAST(1 AS INT64)) AS `sum_Number_of_Records_ok`,
1.1000000000000001 AS `X__alias__0`
WHERE (CAST(`basket_sales_date` AS TIMESTAMP) = CAST(DATE('2018-02-10') AS TIMESTAMP))
GROUP BY 2
In BigQuery, all partitions are processed (because there is a transformation on the column). If i remove (manually) the cast function in BigQuery, we process only the used partition.
For a big table, it's a problem. The query is more costly and is executed with more long time.
So my question, How to change the behavior?
Tableau seem doesn't support partitioned tables by Date and proposed "Wildcard tables" (i deduce by the screenshot but it's not written).
In my case, is there a solution ? (with same structure table / without Wildcard tables)
Others informations :
BigQuery : Standard SQL / Partitioned table
My Tableau Desktop version : 2018.2
Tests with "Continuous or Discrete Date"
Thanks for reading me