[GitHub] [spark] cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do not replace Zeros when replacing NaNs
cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do
not replace Zeros when replacing NaNs
URL: https://github.com/apache/spark/pull/26738#discussion_r361891660
##
File path:
sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
##
@@ -456,7 +456,7 @@ final class DataFrameNaFunctions private[sql](df:
DataFrame) {
val keyExpr = df.col(col.name).expr
def buildExpr(v: Any) = Cast(Literal(v), keyExpr.dataType)
val branches = replacementMap.flatMap { case (source, target) =>
- Seq(buildExpr(source), buildExpr(target))
+ Seq(Literal(source), buildExpr(target))
Review comment:
The new behavior makes more sense, but I agree that the PR description needs
update to reflect all the changes. cc @johnhany97
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[GitHub] [spark] cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do not replace Zeros when replacing NaNs
cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do
not replace Zeros when replacing NaNs
URL: https://github.com/apache/spark/pull/26738#discussion_r353164427
##
File path:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
##
@@ -404,4 +412,48 @@ class DataFrameNaFunctionsSuite extends QueryTest with
SharedSparkSession {
df.na.drop("any"),
Row("5", "6", "6") :: Nil)
}
+
+ test("replace nan with float") {
+checkAnswer(
+ createNaNDF().na.replace("*", Map(
+Float.NaN -> 10f
+ )),
+ Row(1, new java.lang.Long(1), new java.lang.Short("1"),
+new java.lang.Byte("1"), new java.lang.Float(1.0), 1.0) ::
+ Row(0, new java.lang.Long(0), new java.lang.Short("0"),
+new java.lang.Byte("0"), new java.lang.Float(10), new
java.lang.Double(10)) :: Nil)
+ }
+
+ test("replace nan with double") {
+checkAnswer(
+ createNaNDF().na.replace("*", Map(
+Double.NaN -> 10.toDouble
+ )),
+ Row(1, new java.lang.Long(1), new java.lang.Short("1"),
Review comment:
ditto
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[GitHub] [spark] cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do not replace Zeros when replacing NaNs
cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do
not replace Zeros when replacing NaNs
URL: https://github.com/apache/spark/pull/26738#discussion_r353164364
##
File path:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
##
@@ -404,4 +412,48 @@ class DataFrameNaFunctionsSuite extends QueryTest with
SharedSparkSession {
df.na.drop("any"),
Row("5", "6", "6") :: Nil)
}
+
+ test("replace nan with float") {
+checkAnswer(
+ createNaNDF().na.replace("*", Map(
+Float.NaN -> 10f
+ )),
+ Row(1, new java.lang.Long(1), new java.lang.Short("1"),
Review comment:
nit: can we use `1L`, `1.toShort`, etc. here too?
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[GitHub] [spark] cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do not replace Zeros when replacing NaNs
cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do
not replace Zeros when replacing NaNs
URL: https://github.com/apache/spark/pull/26738#discussion_r353132269
##
File path:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
##
@@ -37,6 +37,16 @@ class DataFrameNaFunctionsSuite extends QueryTest with
SharedSparkSession {
).toDF("name", "age", "height")
}
+ def createNaNDF(): DataFrame = {
+Seq[(java.lang.Integer, java.lang.Long, java.lang.Short,
+ java.lang.Byte, java.lang.Float, java.lang.Double)](
Review comment:
OK we can keep the type declaration, but can we use `1L`, `1.toShort`, etc.
when writing the values?
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[GitHub] [spark] cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do not replace Zeros when replacing NaNs
cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do
not replace Zeros when replacing NaNs
URL: https://github.com/apache/spark/pull/26738#discussion_r353117839
##
File path:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
##
@@ -37,6 +37,16 @@ class DataFrameNaFunctionsSuite extends QueryTest with
SharedSparkSession {
).toDF("name", "age", "height")
}
+ def createNaNDF(): DataFrame = {
+Seq[(java.lang.Integer, java.lang.Long, java.lang.Short,
+ java.lang.Byte, java.lang.Float, java.lang.Double)](
Review comment:
Do we have to use boxed type? how about
```
Seq((1, 1L, 1.toShort, 1.toByte, 1.0f, 1.0), (0, 0L, ...)).toDF...
```
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[GitHub] [spark] cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do not replace Zeros when replacing NaNs
cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do
not replace Zeros when replacing NaNs
URL: https://github.com/apache/spark/pull/26738#discussion_r353117371
##
File path:
sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
##
@@ -455,8 +455,8 @@ final class DataFrameNaFunctions private[sql](df:
DataFrame) {
private def replaceCol(col: StructField, replacementMap: Map[_, _]): Column
= {
val keyExpr = df.col(col.name).expr
def buildExpr(v: Any) = Cast(Literal(v), keyExpr.dataType)
-val branches = replacementMap.flatMap { case (source, target) =>
- Seq(buildExpr(source), buildExpr(target))
+val branches = replacementMap.flatMap { case (src, target) =>
+Seq(Literal(src), buildExpr(target))
Review comment:
nit: the previous 2 space indentation is corrected.
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[GitHub] [spark] cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do not replace Zeros when replacing NaNs
cloud-fan commented on a change in pull request #26738: [SPARK-30082][SQL] Do
not replace Zeros when replacing NaNs
URL: https://github.com/apache/spark/pull/26738#discussion_r353008601
##
File path:
sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
##
@@ -456,11 +456,23 @@ final class DataFrameNaFunctions private[sql](df:
DataFrame) {
val keyExpr = df.col(col.name).expr
def buildExpr(v: Any) = Cast(Literal(v), keyExpr.dataType)
val branches = replacementMap.flatMap { case (source, target) =>
- Seq(buildExpr(source), buildExpr(target))
+ if (isNaN(source) || isNaN(target)) {
+col.dataType match {
+ case IntegerType | LongType | ShortType | ByteType => Seq.empty
Review comment:
checked with scala
```
scala> Float.NaN == 0
res0: Boolean = false
scala> Float.NaN.toInt == 0
res1: Boolean = true
```
This is also true in Spark. When comparing float and int, we cast int to
float to compare, so `NaN != 0`.
I think it's a bug that we cast the value to the column type and compare. We
shouldn't do any cast and let the type coercion rules to do proper cast for
`CaseKeyWhen`
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