Azure Databricks MDS write ops in error: MapInPandas write_mds gives message Spark higher-order functions are not supported in Unity Catalog
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bug
- Dominant language
- Python
- Stars
- 1.6k
- Forks
- 206
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Description
Environment
Azure Databricks 14.3 LTS used on a distributed cluster.
To reproduce
Steps to reproduce the behavior:
- Code as follow:
d = {
'code': ['test', 'test', 'test'],
'age': ['test', 'test', 'test'],
'id': ['ib4', '7h!', '67h']
}
df_test = ps.DataFrame(data=d).to_spark()
mds_kwargs = {
'out': 'test',
'columns': {
'code': 'str',
'age': 'str',
'id': 'str',
},
'keep_local': True
}
dataframe_to_mds(
dataframe=df_test,
merge_index=True,
mds_kwargs=mds_kwargs
)
Expected behavior
The script should result in a write op that writes the created DataFrame on the Unity Catalog / local persistence in the MDS format.
Additional context
Documentation is not accessible today, we are using version 0.7.x .
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the distributed-cluster example through dataframe_to_mds, focusing on the MapInPandas/write_mds path and the Unity Catalog error. Confirm that the DataFrame can be written to Unity Catalog or local persistence in MDS format without the reported higher-order-functions message.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, spark
- Domain
- data-engineering
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100