Databricks Community

jeremy98 · 10 hours ago

Hi community,
I was running a workflow based on different tasks but also taking into account the existed cluster to execute those tasks, but I was getting error in configurations:

run failed with error message Library installation failed for library due to user error for whl: "/Workspace/Users/<user-mail>/.bundle/data_pipelines/stg/files/dist/data_pipelines-0.0.1-py3-none-any.whl" Error messages: Library installation attempted on the driver node of cluster 1213-225649-fslmwxpk and failed. User tried to install a wheel, but pip could not build the wheel successfully. Please check your wheel package contents and dependencies.. Error code: WHEEL_BUILD_ERROR. Error message: org.apache.spark.SparkException: Process List(/bin/su, libraries, -c, bash /local_disk0/.ephemeral_nfs/cluster_libraries/python/python_start_clusterwide.sh /local_disk0/.ephemeral_nfs/cluster_libraries/python/bin/pip install --upgrade /local_disk0/tmp/addedFilec83cde1956f94fb68ad0f2e34cd4b42013465877465959137763/rnc_data_pipelines-0.0.1-py3-none-any.whl --disable-pip-version-check) exited with code 1. ... *WARNING: message truncated. Skipped 3389 bytes of output**

How solve this error? And how to see the entire warning?

Walter_C · 8 hours ago

You can do it by following steps in https://docs.databricks.com/en/compute/serverless/dependencies.html

View solution in original post

Walter_C · 9 hours ago

Ensure that the wheel package you are trying to install is correctly built and that all its dependencies are properly specified. You can do this by inspecting the setup.py or pyproject.toml file in your package.

Conflicts between different versions of dependencies can cause installation failures. Make sure that the dependencies specified in your wheel file do not conflict with other libraries installed on the cluster. For example, if your package requires a specific version of numpy, ensure that this version is compatible with other installed packages.

jeremy98 · 9 hours ago

Hello,
I solved the problem directly removing pandas and numpy. It is difficult because needs to be matched with the version of a current cluster installed.

But, if I want to run in a serveless mode, https://github.com/databricks/cli/issues/1621, based on this how do I need to specify the environment my wheel etc. I don't understand..