First of all, you should optimize the transformations in Power Query for speed when you import data. Second, the source should be fast itself and this, in turn, calls for SQL optimization (if the source is a SQL query/sproc or a view). If this does not work, then, and only then, should you turn to the DQ mode.
@dhananjay_pbi Are these tables coming from 2 different databases? If yes, then it is not possible, for DQ to work there should be a single SQL request to a database, in your case PQ has to fetch data from both databases and merge them in PQ.
Thanks @AntrikshSharma & @daXtreme for your response. Let me eloborate complete scenatio that I am trying to achieve so that you could recommend optimum solution suppored by power bi.
We are trying to use power bi client in frontend to display reports. User should be able to update schedule dates and visualize updated report. We use Power BI rest api to refresh dataset & report.
We are using DB – Azure Databricks – SQL Endpoint
Frontend – React app with power bi client integration
Schedule table (record count – approx. 5 Million)
ScheduleID | Start_Date | End_Date | Region |
1 | Nov-15-2022 | Nov-20-2022 | R1 |
2 | Nov-15-2022 | Nov-25-2022 | R1 |
3 | Nov-20-2022 | Nov-30-2022 | R1 |
4 | Dec-20-2022 | Dec-25-2022 | R1 |
5 | Dec-20-2022 | Dec-25-2022 | R2 |
PlannedSchedule table (updated by user through frontend app)
ScenarioID | Planned_Start_Date | Planned_End_Date | ScheduleID (FK) |
S1 | Nov-17-2022 | Nov-22-2022 | 1 |
S1 | Nov-17-2022 | Nov-27-2022 | 2 |
S2 | Nov-20-2022 | Nov-30-2022 | 3 |
Power BI report View:
Filter1
Scenario ID
(Blank)
S1 - Selected
S2
Filter2
Region
(Blank)
R1 - Selected
R2
Result
Planned Schedules (S1 selected)
ScheduleID | Planned_Start_Date | Planned_End_Date | Remarks |
1 | Nov-17-2022 | Nov-22-2022 | Fetch dates from PlannedSchedule table |
2 | Nov-17-2022 | Nov-27-2022 | Fetch dates from PlannedSchedule table |
3 | Nov-20-2022 | Nov-30-2022 | Fetch dates from Schedule table |
4 | Dec-20-2022 | Dec-25-2022 | Fetch dates from Schedule table |
Filter1
Scenario ID
(Blank)
S1
S2 - Selected
Filter2
Region (Single Select & Mandatory)
R1 - Selected
R2
Result
Planned Schedules (S2 selected)
ScheduleID | Planned_Start_Date | Planned_End_Date | Remarks |
1 | Nov-15-2022 | Nov-20-2022 | Fetch dates from Schedule table |
2 | Nov-15-2022 | Nov-25-2022 | Fetch dates from Schedule table |
3 | Nov-20-2022 | Nov-30-2022 | Fetch dates from PlannedSchedule table |
4 | Dec-20-2022 | Dec-25-2022 | Fetch dates from Schedule table |
Approach 1: I tried creating view with left join but was not able to get this result so tried using SQL Table function in azure databricks
CREATE FUNCTION schedule_forecast(SCENARIO_ID STRING)
RETURNS TABLE(ScheduleID STRING, PLANNED_ START_DATE, PLANNED_FINISH_DATE)
RETURN SELECT
s.ID,
ps.PLANNED_ START_DATE,
ps.PLANNED_ END_DATE,
FROM schedule as s
LEFT JOIN Planned_Schedule as ps ON s.ID = ps.ID AND ps. SCENARIO_ID = schedule_forecast. SCENARIO_ID;
Able to get expected result
select * from schedule_forecast ('S1')
select * from schedule_forecast ('S2')
I was hoping, Power Bi allows me to direct query based on SQL table function based on scenario filter as dynamic parameter. But This function is not showing up in power bi source navigator. Would this approach supported in power bi?
Approach 2:
Direct query to Schedule
Direct query to PlannedSchedule
Merge query as new and display expected result as above. This works but Merged query is changing to storage mode hence Its required to refresh.
Approach 3: Use partitioning concept to refresh dataset partially. I have not tried this yet. Let me know if this is only the option do achieve this result.
Approach 4: Use Import mode and refresh dataset but it takes around 20-30 mins.
Thanks,
Best Regards
Dhananjay
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