zhengruifeng opened a new pull request, #46636:
URL: https://github.com/apache/spark/pull/46636
### What changes were proposed in this pull request?
Drop internal metadata in `DataFrame.schema`
### Why are the changes needed?
Internal metadata might be leaked in both Spark Connect and Spark Classic,
e.g. in Spark Classic
```
In [9]: spark.range(10).select(sf.lit(1).alias("key"),
"id").groupBy("key").agg(sf.max("id")).schema.json()
Out[9]:
'{"fields":[{"metadata":{},"name":"key","nullable":false,"type":"integer"},{"metadata":{"__autoGeneratedAlias":"true"},"name":"max(id)","nullable":true,"type":"long"}],"type":"struct"}'
```
What make it worse is that internal metadata maybe leaked in different
cases, so need to add additional `_drop_meta` in Pandas APIs to make assertions
work.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
CI
### Was this patch authored or co-authored using generative AI tooling?
No
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