asfgit closed pull request #23262: [SPARK-26312][SQL]Replace
RDDConversions.rowToRowRdd with RowEncoder to improve its conversion performance
URL: https://github.com/apache/spark/pull/23262
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diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala
index e214bfd050410..49fb288fdea6a 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala
@@ -18,54 +18,14 @@
package org.apache.spark.sql.execution
import org.apache.spark.rdd.RDD
-import org.apache.spark.sql.{Encoder, Row, SparkSession}
-import org.apache.spark.sql.catalyst.{CatalystTypeConverters, InternalRow}
+import org.apache.spark.sql.{Encoder, SparkSession}
+import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.analysis.MultiInstanceRelation
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.plans.physical.{Partitioning,
UnknownPartitioning}
import org.apache.spark.sql.catalyst.util.truncatedString
import org.apache.spark.sql.execution.metric.SQLMetrics
-import org.apache.spark.sql.types.DataType
-
-object RDDConversions {
- def productToRowRdd[A <: Product](data: RDD[A], outputTypes: Seq[DataType]):
RDD[InternalRow] = {
- data.mapPartitions { iterator =>
- val numColumns = outputTypes.length
- val mutableRow = new GenericInternalRow(numColumns)
- val converters =
outputTypes.map(CatalystTypeConverters.createToCatalystConverter)
- iterator.map { r =>
- var i = 0
- while (i < numColumns) {
- mutableRow(i) = converters(i)(r.productElement(i))
- i += 1
- }
-
- mutableRow
- }
- }
- }
-
- /**
- * Convert the objects inside Row into the types Catalyst expected.
- */
- def rowToRowRdd(data: RDD[Row], outputTypes: Seq[DataType]):
RDD[InternalRow] = {
- data.mapPartitions { iterator =>
- val numColumns = outputTypes.length
- val mutableRow = new GenericInternalRow(numColumns)
- val converters =
outputTypes.map(CatalystTypeConverters.createToCatalystConverter)
- iterator.map { r =>
- var i = 0
- while (i < numColumns) {
- mutableRow(i) = converters(i)(r(i))
- i += 1
- }
-
- mutableRow
- }
- }
- }
-}
object ExternalRDD {
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
index c6000442fae76..b304e2da6e1cf 100644
---
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
+++
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
@@ -29,11 +29,11 @@ import
org.apache.spark.sql.catalyst.{CatalystTypeConverters, InternalRow, Quali
import org.apache.spark.sql.catalyst.CatalystTypeConverters.convertToScala
import org.apache.spark.sql.catalyst.analysis._
import org.apache.spark.sql.catalyst.catalog._
+import org.apache.spark.sql.catalyst.encoders.RowEncoder
import org.apache.spark.sql.catalyst.expressions
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.planning.PhysicalOperation
import org.apache.spark.sql.catalyst.plans.logical.{InsertIntoDir,
InsertIntoTable, LogicalPlan, Project}
-import org.apache.spark.sql.catalyst.plans.physical.HashPartitioning
import org.apache.spark.sql.catalyst.rules.Rule
import org.apache.spark.sql.execution.{RowDataSourceScanExec, SparkPlan}
import org.apache.spark.sql.execution.command._
@@ -416,7 +416,10 @@ case class DataSourceStrategy(conf: SQLConf) extends
Strategy with Logging with
output: Seq[Attribute],
rdd: RDD[Row]): RDD[InternalRow] = {
if (relation.relation.needConversion) {
- execution.RDDConversions.rowToRowRdd(rdd, output.map(_.dataType))
+ val converters = RowEncoder(StructType.fromAttributes(output))
+ rdd.mapPartitions { iterator =>
+ iterator.map(converters.toRow)
+ }
} else {
rdd.asInstanceOf[RDD[InternalRow]]
}
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