GitHub user liancheng opened a pull request:
https://github.com/apache/spark/pull/8228
[SPARK-10005] [SQL] Fixes schema merging for nested structs
In case of schema merging, we only handled first level fields when
converting Parquet groups to `InternalRow`s. Nested struct fields are not
properly handled.
For example, the schema of a Parquet file to be read can be:
```
message individual {
required group f1 {
optional binary f11 (utf8);
}
}
```
while the global schema is:
```
message global {
required group f1 {
optional binary f11 (utf8);
optional int32 f12;
}
}
```
This PR fixes this issue by padding missing fields when creating actual
converters.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/liancheng/spark
spark-10005/nested-schema-merging
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/8228.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #8228
----
commit 63eb7644223a65edf3ca507c3a1604f01b61de22
Author: Cheng Lian <[email protected]>
Date: 2015-08-16T11:14:55Z
Fixes schema merging for nested structs
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