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[SPARK-52626][SQL] Allow grouping by the time type #51325

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[SPARK-52626][SQL] Allow grouping by the time type #51325

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6139b19
Testing
bersprockets Jun 30, 2025
3c6e1a3
Update
bersprockets Jul 1, 2025
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3 changes: 2 additions & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/HashMapGenerator.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -160,7 +160,8 @@ abstract class HashMapGenerator(
case BooleanType => hashInt(s"$input ? 1 : 0")
case ByteType | ShortType | IntegerType | DateType | _: YearMonthIntervalType =>
hashInt(input)
case LongType | TimestampType | TimestampNTZType | _: DayTimeIntervalType => hashLong(input)
case LongType | TimestampType | TimestampNTZType | _: DayTimeIntervalType | _: TimeType =>
hashLong(input)
case FloatType => hashInt(s"Float.floatToIntBits($input)")
case DoubleType => hashLong(s"Double.doubleToLongBits($input)")
case d: DecimalType =>
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13 changes: 12 additions & 1 deletion sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@
package org.apache.spark.sql

import java.sql.{Date, Timestamp}
import java.time.{Duration, LocalDateTime, Period}
import java.time.{Duration, LocalDateTime, LocalTime, Period}

import scala.util.Random

Expand Down Expand Up @@ -2902,6 +2902,17 @@ class DataFrameAggregateSuite extends QueryTest
)
assert(badAgg2.checkInputDataTypes().isFailure)
}

test("SPARK-52626: Support group by Time column") {
val ts1 = "15:00:00"
val ts2 = "22:00:00"
val localTime = Seq(ts1, ts1, ts2).map(LocalTime.parse)
val df = localTime.toDF("t").groupBy("t").count().orderBy("t")
val expectedSchema =
new StructType().add(StructField("t", TimeType())).add("count", LongType, false)
assert (df.schema == expectedSchema)
checkAnswer(df, Seq(Row(LocalTime.parse(ts1), 2), Row(LocalTime.parse(ts2), 1)))
}
}

case class B(c: Option[Double])
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