Github user wojtek-szymanski commented on a diff in the pull request:
https://github.com/apache/spark/pull/17068#discussion_r104317488
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVDataSource.scala
---
@@ -133,8 +133,19 @@ object TextInputCSVDataSource extends CSVDataSource {
sparkSession: SparkSession,
inputPaths: Seq[FileStatus],
parsedOptions: CSVOptions): Option[StructType] = {
- val csv: Dataset[String] = createBaseDataset(sparkSession, inputPaths,
parsedOptions)
- val firstLine: String = CSVUtils.filterCommentAndEmpty(csv,
parsedOptions).first()
+ val csv = createBaseDataset(sparkSession, inputPaths, parsedOptions)
+ CSVUtils.filterCommentAndEmpty(csv, parsedOptions)
+ .take(1)
+ .headOption
+ .map(firstLine => infer(sparkSession, parsedOptions, csv, firstLine))
+ .orElse(Some(StructType(Seq())))
--- End diff --
I would suggest that we use pattern matching in order to make it more
verbose and avoid code like this:
if (maybeFirstRow.isDefined) {
val firstRow = maybeFirstRow.get
I also touched `WholeFileCSVDataSource` to unify both implementations.
What's your opinion?
Regarding code de-duplication, I fully agree, that it should be done in
separate PR.
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