HyukjinKwon 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_r251373443
##########
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)) {
Review comment:
I agree with that our JSON / CSV have some holes about parsing, counting,
column pruning (in particular when it's malformed), etc. I was thinking about
whitelisting the problems and behaviours at 3.0.0.
I don't think this behaviour was noticed to reviewers when #21909 was merged
at that time while this is pretty critical to discuss as you said above. Let's
do this again probably with whitelisting behaviours clearly. I think we should
avoid this forth and back with the doc.
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