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[WIP][SPARK-25040][SQL] Empty string for double and float types should be nulls in JSON #22019

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[WIP][SPARK-25040][SQL] Empty string for double and float types should be nulls in JSON #22019

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4 changes: 2 additions & 2 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/json/JacksonParser.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -137,7 +137,7 @@ class JacksonParser(
case VALUE_NUMBER_INT | VALUE_NUMBER_FLOAT =>
parser.getFloatValue

case VALUE_STRING =>
case VALUE_STRING if parser.getTextLength >= 1 =>
// Special case handling for NaN and Infinity.
parser.getText match {
case "NaN" => Float.NaN
Expand All @@ -153,7 +153,7 @@ class JacksonParser(
case VALUE_NUMBER_INT | VALUE_NUMBER_FLOAT =>
parser.getDoubleValue

case VALUE_STRING =>
case VALUE_STRING if parser.getTextLength >= 1 =>
// Special case handling for NaN and Infinity.
parser.getText match {
case "NaN" => Double.NaN
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6 changes: 6 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonSuite.scala
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Expand Up @@ -2490,4 +2490,10 @@ class JsonSuite extends QueryTest with SharedSQLContext with TestJsonData {
assert(exception.getMessage.contains("encoding must not be included in the blacklist"))
}
}

test("SPARK-25040: empty strings should be treated as null for double and float") {
val df = spark.read.schema("a DOUBLE, b FLOAT")
.option("mode", "FAILFAST").json(Seq("""{"a":"","b": ""}""", """{"a": 1.1,"b": 1.1}""").toDS)
checkAnswer(df, Row(null, null) :: Row(1.1D, 1.1F) :: Nil)
}
}