viirya commented on code in PR #100:
URL:
https://github.com/apache/arrow-datafusion-comet/pull/100#discussion_r1505528298
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spark/src/main/scala/org/apache/spark/sql/comet/CometExecUtils.scala:
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@@ -21,15 +21,40 @@ package org.apache.spark.sql.comet
import scala.collection.JavaConverters.asJavaIterableConverter
+import org.apache.spark.{Partition, SparkContext, TaskContext}
+import org.apache.spark.rdd.RDD
import org.apache.spark.sql.catalyst.expressions.{Attribute, NamedExpression,
SortOrder}
import org.apache.spark.sql.execution.SparkPlan
+import org.apache.spark.sql.vectorized.ColumnarBatch
import org.apache.comet.serde.OperatorOuterClass
import org.apache.comet.serde.OperatorOuterClass.Operator
import org.apache.comet.serde.QueryPlanSerde.{exprToProto, serializeDataType}
object CometExecUtils {
+ /**
+ * Create an empty ColumnarBatch RDD with a single partition.
+ */
+ def createEmptyColumnarRDDWithSinglePartition(
+ sparkContext: SparkContext): RDD[ColumnarBatch] = {
+ new EmptyRDDWithPartitions(sparkContext, 1)
+ }
+
+ /**
+ * Transform the given RDD into a new RDD that takes the first `limit`
elements of each
+ * partition. The limit operation is performed on the native side.
+ */
+ def toNativeLimitedPerPartition(
Review Comment:
The method name is not good to me.
Maybe simply `getNativeLimitRDD`.
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