maropu commented on a change in pull request #23665: [SPARK-26745][SQL] Skip
empty lines in JSON-derived DataFrames when skipParsing optimization in effect
URL: https://github.com/apache/spark/pull/23665#discussion_r251270647
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/FailureSafeParser.scala
##########
@@ -55,11 +56,15 @@ class FailureSafeParser[IN](
def parse(input: IN): Iterator[InternalRow] = {
try {
- if (skipParsing) {
- Iterator.single(InternalRow.empty)
- } else {
- rawParser.apply(input).toIterator.map(row => toResultRow(Some(row), ()
=> null))
- }
+ if (skipParsing) {
+ if (unparsedRecordIsNonEmpty(input)) {
+ Iterator.single(InternalRow.empty)
+ } else {
+ Iterator.empty
+ }
+ } else {
+ rawParser.apply(input).toIterator.map(row => toResultRow(Some(row), ()
=> null))
+ }
Review comment:
We need to modify this file? Since this is a issue in json stuffs, I think
its better to handle this case in the json parser side. Can't we do handle this
in the same way with CSV one?, e.g.,
https://github.com/apache/spark/blob/3a17c6a06bc4e8a6cae506a61d3d83696d378607/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/UnivocityParser.scala#L333
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