HyukjinKwon commented on a change in pull request #26973: [SPARK-30323][SQL]
Support filters pushdown in CSV datasource
URL: https://github.com/apache/spark/pull/26973#discussion_r366151938
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/UnivocityParser.scala
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@@ -204,15 +234,15 @@ class UnivocityParser(
* Parses a single CSV string and turns it into either one resulting row or
no row (if the
* the record is malformed).
*/
- def parse(input: String): InternalRow = doParse(input)
+ def parse(input: String): Seq[InternalRow] = doParse(input)
private val getToken = if (options.columnPruning) {
(tokens: Array[String], index: Int) => tokens(index)
} else {
(tokens: Array[String], index: Int) => tokens(tokenIndexArr(index))
}
- private def convert(tokens: Array[String]): InternalRow = {
+ private def convert(tokens: Array[String]): Seq[InternalRow] = {
Review comment:
`def parse(input: String): Seq[InternalRow] = doParse(input)` seems like it
can return multiple records whereas it's always one or none. It's really
confusing and I don't think it's a good idea to sacrifice readability here.
Can we use `Option` here and fix `FailureSafeParser`'s `rawParser` signature
to, for instance, `rawParser: IN => GenTraversableOnce[InternalRow]`?
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