Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/18865#discussion_r136159299
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/json/JsonFileFormat.scala
---
@@ -114,7 +114,16 @@ class JsonFileFormat extends TextBasedFileFormat with
DataSourceRegister {
}
(file: PartitionedFile) => {
- val parser = new JacksonParser(actualSchema, parsedOptions)
+ // SPARK-21610: when the `requiredSchema` only contains
`_corrupt_record`,
--- End diff --
Your usage scenario makes sense to me. The contents of `_corrupt_record `
depends on the fields our parser passed. The workaround is you can save your
output to the cache or a physical table.
```Scala
val df = dfFromFile.cache()
df.filter($"_corrupt_record".isNull).drop("_corrupt_record").show()
df.filter($"_corrupt_record".isNotNull).select("_corrupt_record").show()
```
My current suggestion is to capture the empty actual schema and issue an
error with a reasonable workaround message. Users can at least know what
happened and how to fix the issue.
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