Databricks Community

@Santhanalakshmi Manoharan​  Was this issue resolved, Am also getting same error, any guidance would be of great help.Appreciate your help.

@Kumar Shanu​ :The error you are seeing (API request to endpoint /api/2.0/mlflow/runs/create failed with error code 404 != 200) suggests that the API endpoint you are trying to access is not found. This could be due to several reasons, such as incorr...

@Debayan Mukherjee​ Issue resolved, looks cloud team have not updated required security groups that has been shared, after revisiting them we are able to find missing security groups and added them

@Ammar Ammar​ :The error message you're seeing suggests that the Delta Lake transaction log for the common model's test table has been truncated or deleted, either manually or due to the retention policies set in your cluster. This can happen if the ...

@Dip Kundu​ :It seems like the error you are facing is related to sparklyr, which is used to interact with Apache Spark from R, and not directly related to mlflow. The error message suggests that an object could not be found, but it's not clear which...

Yes, it is possible to configure the Hive Catalog in Databricks to return full descriptions of tables with large multi-column structs.One way to achieve this is to increase the value of the Hive configuration property "hive.metastore.client.record.ma...

Autoloader doesn't support changing the source path for running job so if you change your source path your stream fails because the source path has changed. However, if you really want to change the path you can change it by using the new checkpoint ...

@Ryoji Kuwae Neto​ :To use the --archives parameter with a conda environment in Databricks, you can follow these steps:1) Create a conda environment for your project and export it as a .tar.gz file:conda create --name myenv conda activate myenv conda...

Hi @Vishnu P​, could you please share the full stack trace? Also, observe how the workers memory utilizing?

@Cristian Martinez​ :The error you are seeing is occurring because the DoubleType class has not been imported. To fix this, add the following line to the top of your code to import DoubleType:from pyspark.sql.types import DoubleTypeThis should resolv...

@Jonas Lindberg​ :To address the issues you are facing with model serialization and versioning, I would recommend the following approach:Use MLflow to manage the lifecycle of your models, including versioning, deployment, and monitoring. MLflow is an...

@Cristian Martinez​ :In Databricks, you need to import the necessary classes from the pyspark.sql.types module in order to use them in your code. To fix the NameError you're encountering with the label "name 'DoubleType' is not defined" in Exercise 2...

@orian hindi​ :Regarding your questions:Q1: The error message you are seeing is likely related to a segmentation fault, which can occur due to various reasons such as memory access violations or stack overflows. It could be caused by several factors,...