amandeep-sharma commented on a change in pull request #31545:
URL: https://github.com/apache/spark/pull/31545#discussion_r584049545
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
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@@ -395,9 +395,9 @@ final class DataFrameNaFunctions private[sql](df:
DataFrame) {
private def fillMap(values: Seq[(String, Any)]): DataFrame = {
// Error handling
- values.foreach { case (colName, replaceValue) =>
+ val resolved = values.map { case (colName, replaceValue) =>
// Check column name exists
- df.resolve(colName)
+ val resolvedColumn = df.resolve(colName)
Review comment:
Above mentioned approach will not work if the null-fill map has
qualified column name(dfAlias.columnName) as below.
Eg:
`def payment = spark.read.format("csv").option("header", "true")
.schema(paymentSchema)
.load("Payment.csv").as("payment")
`
payment.na.fill(Map("payment.`Customer.Id`" -> -1))
.show()
`
Also, column name quoted with back-tick(`) will also not work.
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