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Resolved! slow Fetching results by client in databricks SQL calling from Azure Compute Instance (AML)
I'm using `databricks-sql-connector` in python3.8 to connect to an Azure SQL Wharehouse inside an Azure Machine Learning Compute Instance.I have this large result query, looking at the `query history` I check the time spent on doing the query, and se...
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So I made some few tests. Since you said that the Databricks SQL driver wasn't made to retrieve that amount of data. I went on Spark.I fired up a small spark cluster, the query was as fast as on SQL Warehouse, then I did a df.write.parquet("/my_path/...
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- 8065 Views
- 8 replies
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Resolved! mlflow RESOURCE_ALREADY_EXISTS
I tried to log some run in my Databricks Workspace and I'm facing the following error: RESOURCE_ALREADY_EXISTS when I try to log any run.I could replicate the error with the following code:import mlflow import mlflow.sklearn from mlflow.tracking impo...
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Hi @Miguel Ángel Fernández it’s not recommended to “link” the Databricks and AML workspaces, as we are seeing more problems. You can refer to the instructions found below for using MLflow with AML. https://docs.microsoft.com/en-us/azure/machine-l...
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