sumitsu 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_r251273243
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/FailureSafeParser.scala
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@@ -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:
One of my earlier revisions [worked in the way you
suggest](https://github.com/sumitsu/spark/blob/13942b8da17d7e58e690b7a8b27c1a3fe20be135/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/json/JsonDataSource.scala#L132-L160)
(if I've understood your point correctly); I changed it in order to avoid
redundant empty-line filtering in the case where the full parser has to run
anyway (i.e. where `skipParsing == false`).
What do you think? Is that a valid optimization, or is it better to do it on
the JSON side as in 13942b8 to avoid changes to `FailureSafeParser`?
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