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[SPARK-30671][SQL] emptyDataFrame should use a LocalRelation #27400

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[SPARK-30671][SQL] emptyDataFrame should use a LocalRelation #27400

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4 changes: 1 addition & 3 deletions sql/core/src/main/scala/org/apache/spark/sql/SparkSession.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -274,9 +274,7 @@ class SparkSession private(
* @since 2.0.0
*/
@transient
lazy val emptyDataFrame: DataFrame = {
createDataFrame(sparkContext.emptyRDD[Row].setName("empty"), StructType(Nil))
}
lazy val emptyDataFrame: DataFrame = Dataset.ofRows(self, LocalRelation())
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Suggested change
lazy val emptyDataFrame: DataFrame = Dataset.ofRows(self, LocalRelation())
lazy val emptyDataFrame: DataFrame = emptyDataset(RowEncoder(new StructType()))

?

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Why would that be better? This is basically re-implementing Dataset.ofRows.

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This is arguable for sure. DataFrame is Dataset[Row]. We already have a function which can construct empty Dataset[T], why not just re-use it. emptyDataFrame is some kind of specialization of emptyDataset.

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@HyukjinKwon HyukjinKwon Jan 31, 2020 •
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If we take this suggestion, maybe: emptyDataset(RowEncoder(StructType(Nil))).

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Dataset.ofRows(self, LocalRelation()) looks simpler as I don't need to jump into another method when reading the code.


/**
* Creates a new [[Dataset]] of type T containing zero elements.
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13 changes: 12 additions & 1 deletion sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
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Expand Up @@ -33,7 +33,7 @@ import org.apache.spark.sql.catalyst.TableIdentifier
import org.apache.spark.sql.catalyst.encoders.RowEncoder
import org.apache.spark.sql.catalyst.expressions.Uuid
import org.apache.spark.sql.catalyst.optimizer.ConvertToLocalRelation
import org.apache.spark.sql.catalyst.plans.logical.{OneRowRelation, Union}
import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, OneRowRelation, Union}
import org.apache.spark.sql.execution.{FilterExec, QueryExecution, WholeStageCodegenExec}
import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper
import org.apache.spark.sql.execution.aggregate.HashAggregateExec
Expand Down Expand Up @@ -2287,6 +2287,17 @@ class DataFrameSuite extends QueryTest
}
assert(err.getMessage.contains("cannot resolve '`d`'"))
}

test("emptyDataFrame should be foldable") {
val emptyDf = spark.emptyDataFrame.withColumn("id", lit(1L))
val joined = spark.range(10).join(emptyDf, "id")
joined.queryExecution.optimizedPlan match {
case LocalRelation(Seq(id), Nil, _) =>
assert(id.name == "id")
case _ =>
fail("emptyDataFrame should be foldable")
}
}
}

case class GroupByKey(a: Int, b: Int)