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[SPARK-26312][SQL]Replace RDDConversions.rowToRowRdd with RowEncoder to improve its conversion performance #23262

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eatoncys wants to merge 7 commits into from
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[SPARK-26312][SQL]Replace RDDConversions.rowToRowRdd with RowEncoder to improve its conversion performance #23262

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ddb2528
Converting converters in RDDConversions into arrays to improve their …
eatoncys Dec 8, 2018
89f3191
Using RowEncoder
eatoncys Dec 10, 2018
907d3f3
Using same parameter
eatoncys Dec 10, 2018
56cf4e5
indent
eatoncys Dec 10, 2018
41937f5
Remove RDDConversions
eatoncys Dec 10, 2018
e8817e3
Remove RDDConversions
eatoncys Dec 10, 2018
9758534
Remove RDDConversions
eatoncys Dec 10, 2018
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36 changes: 12 additions & 24 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -17,51 +17,39 @@

package org.apache.spark.sql.execution

import scala.reflect.runtime.universe.TypeTag

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.catalyst.InternalRow
import org.apache.spark.sql.catalyst.analysis.MultiInstanceRelation
import org.apache.spark.sql.catalyst.encoders.{ExpressionEncoder, RowEncoder}
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
import org.apache.spark.sql.types.StructType

object RDDConversions {
def productToRowRdd[A <: Product](data: RDD[A], outputTypes: Seq[DataType]): RDD[InternalRow] = {
def productToRowRdd[A <: Product : TypeTag](data: RDD[A],
outputSchema: StructType): RDD[InternalRow] = {
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@mgaido91 mgaido91 Dec 10, 2018

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nit: indent

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@mgaido91 mgaido91 Dec 10, 2018

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well, seems like this is never used actually... shall we remove it instead if this is the case?

val converters = ExpressionEncoder[A].resolveAndBind(outputSchema.toAttributes)
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
converters.toRow(r)
}
}
}

/**
* Convert the objects inside Row into the types Catalyst expected.
*/
def rowToRowRdd(data: RDD[Row], outputTypes: Seq[DataType]): RDD[InternalRow] = {
def rowToRowRdd(data: RDD[Row], outputSchema: StructType): RDD[InternalRow] = {
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@HyukjinKwon HyukjinKwon Dec 10, 2018

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Let's remove whole object. rowToRowRdd looks only being used at one place and the code here is quite small.

val converters = RowEncoder(outputSchema)
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@HyukjinKwon HyukjinKwon Dec 10, 2018

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I checked each case. Every case looks fine except one case:

spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/CatalystTypeConverters.scala

Line 289 in fa0d4bf

case chr: Char => UTF8String.fromString(chr.toString)

Looks we're going to drop Char as StringType. I think it's trivial and rather a mistake that we supported this. I don't feel strongly about documenting it in migration guide but if anyone feels so, we better do that.

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
converters.toRow(r)
}
}
}
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2 changes: 1 addition & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
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Expand Up @@ -416,7 +416,7 @@ 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))
execution.RDDConversions.rowToRowRdd(rdd, StructType.fromAttributes(output))
} else {
rdd.asInstanceOf[RDD[InternalRow]]
}
Expand Down