ted-jenks commented on code in PR #39927:
URL: https://github.com/apache/spark/pull/39927#discussion_r1098550628
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVExprUtils.scala:
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@@ -21,38 +21,34 @@ import org.apache.commons.lang3.StringUtils
object CSVExprUtils {
/**
- * Filter ignorable rows for CSV iterator (lines empty and starting with
`comment`).
+ * Filter ignorable rows starting with `comment`.
* This is currently being used in CSV reading path and CSV schema inference.
*/
- def filterCommentAndEmpty(iter: Iterator[String], options: CSVOptions):
Iterator[String] = {
+ def filterComment(iter: Iterator[String], options: CSVOptions):
Iterator[String] = {
if (options.isCommentSet) {
val commentPrefix = options.comment.toString
- iter.filter { line =>
- line.trim.nonEmpty && !line.startsWith(commentPrefix)
- }
+ iter.dropWhile(_.startsWith(commentPrefix)
} else {
- iter.filter(_.trim.nonEmpty)
Review Comment:
I've addressed this now, things a bit more consistent. Only `CSVUtils` is
concerned with the `Dataset[String]` case and the CSV file reads are concerned
with `CSVExprUtils`. Would be interested to see what you think of this as I was
very confused when trying to do some CSV work to find blank lines were not in
fact removed here.
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