cfmcgrady commented on a change in pull request #33212:
URL: https://github.com/apache/spark/pull/33212#discussion_r667593496
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/json/JacksonParser.scala
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@@ -418,6 +426,19 @@ class JacksonParser(
}
}
+ // When the input schema is setting to `nullable = false`, make sure the
field is not null.
+ var index = 0
+ while (badRecordException.isEmpty && !skipRow && index < schema.length) {
+ if (!schema(index).nullable && row.isNullAt(index)) {
+ throw new IllegalSchemaArgumentException(
+ s"the null value found when parsing non-nullable field
${schema(index).name}.")
+ }
+ if (!checkedIndexSet.contains(index)) {
+ skipRow = structFilters.skipRow(row, index)
Review comment:
yes, when the input JSON string contains the missing value field,
`JacksonParser` should be able to skip rows through this null value field.
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