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[SPARK-5684][SQL]: Pass in partition name along with location information, as the location can be different (that is may not contain the partition keys) #4469

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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@

package org.apache.spark.sql.catalyst.expressions

import java.net.URLDecoder
import java.sql.{Date, Timestamp}
import java.text.{DateFormat, SimpleDateFormat}

Expand Down Expand Up @@ -158,6 +159,8 @@ case class Cast(child: Expression, dataType: DataType) extends UnaryExpression w
if (periodIdx != -1 && n.length() - periodIdx > 9) {
n = n.substring(0, periodIdx + 10)
}
// Timestamp value in the partition could be in the form: (2015-02-09 00%3A55%3A00)
n = URLDecoder.decode(n, "UTF-8");
try Timestamp.valueOf(n) catch { case _: java.lang.IllegalArgumentException => null }
})
case BooleanType =>
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -434,7 +434,7 @@ case object BooleanType extends BooleanType
* @group dataType
*/
@DeveloperApi
class TimestampType private() extends NativeType {
class TimestampType private() extends NativeType with PrimitiveType {
// The companion object and this class is separated so the companion object also subclasses
// this type. Otherwise, the companion object would be of type "TimestampType$" in byte code.
// Defined with a private constructor so the companion object is the only possible instantiation.
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -49,7 +49,8 @@ private[sql] case class ParquetRelation(
path: String,
@transient conf: Option[Configuration],
@transient sqlContext: SQLContext,
partitioningAttributes: Seq[Attribute] = Nil)
partitioningAttributes: Seq[Attribute] = Nil,
partitionValues: String = "")
extends LeafNode with MultiInstanceRelation {

self: Product =>
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -80,18 +80,34 @@ private[sql] case class ParquetTableScan(
override def execute(): RDD[Row] = {
import parquet.filter2.compat.FilterCompat.FilterPredicateCompat

var partMap = mutable.HashMap[String, String]()
val sc = sqlContext.sparkContext
val job = new Job(sc.hadoopConfiguration)
ParquetInputFormat.setReadSupportClass(job, classOf[RowReadSupport])

val conf: Configuration = ContextUtil.getConfiguration(job)

relation.path.split(",").foreach { curPath =>
val qualifiedPath = {
val path = new Path(curPath)
path.getFileSystem(conf).makeQualified(path)
if (requestedPartitionOrdinals.nonEmpty) {
val partVals = relation.partitionValues.split(",")
var i = 0
relation.path.split(",").foreach { curPath =>
val partition = partVals.apply(i)
i += 1
val qualifiedPath = {
val path = new Path(curPath)
path.getFileSystem(conf).makeQualified(path)
}
partMap += curPath->partition;
NewFileInputFormat.addInputPath(job, qualifiedPath)
}
} else {
relation.path.split(",").foreach { curPath =>
val qualifiedPath = {
val path = new Path(curPath)
path.getFileSystem(conf).makeQualified(path)
}
NewFileInputFormat.addInputPath(job, qualifiedPath)
}
NewFileInputFormat.addInputPath(job, qualifiedPath)
}

// Store both requested and original schema in `Configuration`
Expand Down Expand Up @@ -135,15 +151,18 @@ private[sql] case class ParquetTableScan(

baseRDD.mapPartitionsWithInputSplit { case (split, iter) =>
val partValue = "([^=]+)=([^=]+)".r
val iSplit = split.asInstanceOf[parquet.hadoop.ParquetInputSplit]
.getPath
.toString
val partValues =
split.asInstanceOf[parquet.hadoop.ParquetInputSplit]
.getPath
.toString
.split("/")
.flatMap {
case partValue(key, value) => Some(key -> value)
case _ => None
}.toMap
partMap.get(
iSplit.splitAt(iSplit.lastIndexOf("/"))._1)
.get
.split("/")
.flatMap {
case partValue(key, value) => Some(key -> value)
case _ => None
}.toMap

// Convert the partitioning attributes into the correct types
val partitionRowValues =
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -60,15 +60,16 @@ private[hive] trait HiveStrategies {
implicit class LogicalPlanHacks(s: DataFrame) {
def lowerCase: DataFrame = DataFrame(s.sqlContext, s.logicalPlan)

def addPartitioningAttributes(attrs: Seq[Attribute]): DataFrame = {
def addPartitioningAttributes(attrs: Seq[Attribute], partVals: String): DataFrame = {
// Don't add the partitioning key if its already present in the data.
if (attrs.map(_.name).toSet.subsetOf(s.logicalPlan.output.map(_.name).toSet)) {
s
} else {
DataFrame(
s.sqlContext,
s.logicalPlan transform {
case p: ParquetRelation => p.copy(partitioningAttributes = attrs)
case p: ParquetRelation => p.copy(partitioningAttributes = attrs,
partitionValues = partVals)
})
}
}
Expand Down Expand Up @@ -137,14 +138,15 @@ private[hive] trait HiveStrategies {
pruningCondition(inputData)
}

val partitionLocations = partitions.map(_.getLocation)
val partitionLocations = partitions.map(part => part.getLocation)
val partitionNames = partitions.map(part => part.getName)

if (partitionLocations.isEmpty) {
PhysicalRDD(plan.output, sparkContext.emptyRDD[Row]) :: Nil
} else {
hiveContext
.parquetFile(partitionLocations: _*)
.addPartitioningAttributes(relation.partitionKeys)
.addPartitioningAttributes(relation.partitionKeys, partitionNames.mkString(","))
.lowerCase
.where(unresolvedOtherPredicates)
.select(unresolvedProjection: _*)
Expand Down