cloud-fan 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_r251502380
##########
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:
```
[{...}, {...}] => 2
[] => 0
{...} => 1
# empty string => 0
```
I think the key here is, one line can produce 0 or 1 or more records, how to
speed it up when we only care about counts? It looks to me that we can enable
the count optimization only for `{...}`, and fallback to parsing for other
cases. @MaxGekk do you think this is applicable? If it's a simple fix, let's
do it for branch 2.4 as well, otherwise +1 for reverting it from 2.4 and re-do
it at master.
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