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Hi Everyone,
Please can someone help out?
I have an existing dashboard that refreshes on an hourly basis. Our data source is MySQL which is an OLTP database. The dashboard has been working fine until recently (last week) when it started failing with this error message on the service;
Error Message:
"Before the data import for finished, its data source timed out. Double-check whether that data source can process import queries and if it can, try again."
I thought it was an issue with the data Load capacity. I went to the Desktop to refresh and realized that my data load takes forever before timing out. So, it keeps showing "Waiting for the DB/Table_name" before timing out. I went to the power query side to see what the issue was. I could connect to the MySQL database and preview the data. Filter the data table with other columns but not the DateTime column. When I try filtering the table using the Datetime column, this message will show at the bottom right of the query editor panel "Waiting for the DB/Table_name" and after a while, it will bring out a Fatal error message (from the image).
I tried connecting to other tables from other MySQL databases, and everything looks okay. I could filter the table using the DateTime column easily. Please, why am I having an issue with this particular database and table?
I checked, and we are using the latest gateway and power bi version. I have also increased the Maximum memory used per simultaneous evaluation on the Data Load option. The issue still persists.
Datasource: MySQL database:
@ribisht17 Thanks for responding.
No transformations so far have been done on the dataset imported.
Just connecting to the data source and trying to filter down to the current week's data.
I'm not certain why this issue is peculiar to this particular table and not the others.
Checked some other tables I have access to, and it filtered down to the current week.
As per this post https://community.powerbi.com/t5/Desktop/Double-check-whether-that-data-source-can-process-import-qu... it is boiling down to performance.
Regards,
Ritesh
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