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[SPARK-5049][SQL] Fix ordering of partition columns in ParquetTableScan #3990

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[SPARK-5049][SQL] Fix ordering of partition columns in ParquetTableScan #3990

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4 changes: 3 additions & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetRelation.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ import parquet.schema.MessageType

import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.catalyst.analysis.{MultiInstanceRelation, UnresolvedException}
import org.apache.spark.sql.catalyst.expressions.Attribute
import org.apache.spark.sql.catalyst.expressions.{AttributeMap, Attribute}
import org.apache.spark.sql.catalyst.plans.logical.{LeafNode, LogicalPlan, Statistics}

/**
Expand Down Expand Up @@ -67,6 +67,8 @@ private[sql] case class ParquetRelation(
conf,
sqlContext.isParquetBinaryAsString)

lazy val attributeMap = AttributeMap(output.map(o => o -> o))

override def newInstance() = ParquetRelation(path, conf, sqlContext).asInstanceOf[this.type]

// Equals must also take into account the output attributes so that we can distinguish between
Expand Down
43 changes: 26 additions & 17 deletions sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala
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Expand Up @@ -64,18 +64,17 @@ case class ParquetTableScan(
// The resolution of Parquet attributes is case sensitive, so we resolve the original attributes
// by exprId. note: output cannot be transient, see
// https://issues.apache.org/jira/browse/SPARK-1367
val normalOutput =
attributes
.filterNot(a => relation.partitioningAttributes.map(_.exprId).contains(a.exprId))
.flatMap(a => relation.output.find(o => o.exprId == a.exprId))
val output = attributes.map(relation.attributeMap)

val partOutput =
attributes.flatMap(a => relation.partitioningAttributes.find(o => o.exprId == a.exprId))
// A mapping of ordinals partitionRow -> finalOutput.
val requestedPartitionOrdinals = {
val partitionAttributeOrdinals = AttributeMap(relation.partitioningAttributes.zipWithIndex)

def output = partOutput ++ normalOutput

assert(normalOutput.size + partOutput.size == attributes.size,
s"$normalOutput + $partOutput != $attributes, ${relation.output}")
attributes.zipWithIndex.flatMap {
case (attribute, finalOrdinal) =>
partitionAttributeOrdinals.get(attribute).map(_ -> finalOrdinal)
}
}.toArray

override def execute(): RDD[Row] = {
import parquet.filter2.compat.FilterCompat.FilterPredicateCompat
Expand All @@ -97,7 +96,7 @@ case class ParquetTableScan(
// Store both requested and original schema in `Configuration`
conf.set(
RowReadSupport.SPARK_ROW_REQUESTED_SCHEMA,
ParquetTypesConverter.convertToString(normalOutput))
ParquetTypesConverter.convertToString(output))
conf.set(
RowWriteSupport.SPARK_ROW_SCHEMA,
ParquetTypesConverter.convertToString(relation.output))
Expand Down Expand Up @@ -125,7 +124,7 @@ case class ParquetTableScan(
classOf[Row],
conf)

if (partOutput.nonEmpty) {
if (requestedPartitionOrdinals.nonEmpty) {
baseRDD.mapPartitionsWithInputSplit { case (split, iter) =>
val partValue = "([^=]+)=([^=]+)".r
val partValues =
Expand All @@ -138,15 +137,25 @@ case class ParquetTableScan(
case _ => None
}.toMap

// Convert the partitioning attributes into the correct types
val partitionRowValues =
partOutput.map(a => Cast(Literal(partValues(a.name)), a.dataType).eval(EmptyRow))
relation.partitioningAttributes
.map(a => Cast(Literal(partValues(a.name)), a.dataType).eval(EmptyRow))

new Iterator[Row] {
private[this] val joinedRow = new JoinedRow5(Row(partitionRowValues:_*), null)

def hasNext = iter.hasNext

def next() = joinedRow.withRight(iter.next()._2)
def next() = {
val row = iter.next()._2.asInstanceOf[SpecificMutableRow]

// Parquet will leave partitioning columns empty, so we fill them in here.
var i = 0
while (i < requestedPartitionOrdinals.size) {
row(requestedPartitionOrdinals(i)._2) =
partitionRowValues(requestedPartitionOrdinals(i)._1)
i += 1
}
row
}
}
}
} else {
Expand Down
12 changes: 12 additions & 0 deletions sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala
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Expand Up @@ -174,6 +174,18 @@ abstract class ParquetPartitioningTest extends QueryTest with BeforeAndAfterAll
}

Seq("partitioned_parquet", "partitioned_parquet_with_key").foreach { table =>
test(s"ordering of the partitioning columns $table") {
checkAnswer(
sql(s"SELECT p, stringField FROM $table WHERE p = 1"),
Seq.fill(10)((1, "part-1"))
)

checkAnswer(
sql(s"SELECT stringField, p FROM $table WHERE p = 1"),
Seq.fill(10)(("part-1", 1))
)
}

test(s"project the partitioning column $table") {
checkAnswer(
sql(s"SELECT p, count(*) FROM $table group by p"),
Expand Down