This s a followup question regarding Jordans answer here: Weird error in BigQuery
I was using to query reference table within \"Table_Query\" for quit some time. Now
The "simple" way I see is split it to two steps
Step 1 - build list that will be used to filter table_id's
SELECT GROUP_CONCAT_UNQUOTED(
CONCAT('"',"MyTable_",STRING(Year*100+Month),'"')
) TBL_NAME_LIST
FROM DWH.Dim_Periods P
CROSS JOIN DWH.Campaigns AS LC
WHERE ID IN ("86254e5a-b856-3b5a-85e1-0f5ab3ff20d6")
AND DATE(P.Date) BETWEEN DATE(StartCampaignDate) AND DATE(EndCampaignDate)
Note the change in your query to transform result to list that you will use in step 2
Step 2 - final query
SELECT
*
FROM
TABLE_QUERY([MyProject:MyDataSet],
'table_id IN (<paste list (TBL_NAME_LIST) built in first query>)')
Above steps are easy to implement in any client you potentially using
If you use it from within BigQuery Web UI - this makes you do a little extra manual "moves" that you might not be happy about
My answer is obvious and you most likely have this already as an option, but wanted to mention
This is not ideal solution. But it seems to do the job.
In my previous query I passed the IDs List as a parameter in an external process that constructed the query. I wanted this process to be unaware to any logic implemented in the query.
Eventually we came up with this solution:
Instead of passing a list of IDs, we pass a JSON that contains the relevant meta data for each ID. We parse this JSON within the Table_Query() function. So instead of querying a physical reference table, we query some sort of a "table variable" that we have put in a JSON.
Below is a sample query that runs on the public dataset that demonstrates this solution.
SELECT
YEAR,
COUNT (*) CNT
FROM
TABLE_QUERY([fh-bigquery:weather_gsod], 'table_id in
(Select table_id
From
(Select table_id,concat(Right(table_id,4),"0101") as TBL_Date from [fh-bigquery:weather_gsod.__TABLES_SUMMARY__]
where table_id Contains "gsod"
)TBLs
CROSS JOIN
(select
Regexp_Replace(Regexp_extract(SPLIT(DatesInput,"},{"),r"\"fromDate\":\"(\d\d\d\d-\d\d-\d\d)\""),"-","") as fromDate,
Regexp_Replace(Regexp_extract(SPLIT(DatesInput,"},{"),r"\"toDate\":\"(\d\d\d\d-\d\d-\d\d)\""),"-","") as toDate,
FROM
(Select
"[
{
\"CycleID\":\"123456\",
\"fromDate\":\"1929-01-01\",
\"toDate\":\"1950-01-10\"
},{
\"CycleID\":\"123456\",
\"fromDate\":\"1970-02-01\",
\"toDate\":\"2000-02-10\"
}
]"
as DatesInput)) RefDates
WHERE TBLs.TBL_Date>=RefDates.fromDate
AND TBLs.TBL_Date<=RefDates.toDate
)')
GROUP BY
YEAR
ORDER BY
YEAR
This solution is not ideal as it requires an external process to be aware of the data stored in the reference tables. Ideally the BigQuery team will re-enable this very useful functionality.