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unnecessary serialize/deserialize for cases where no conversion was performed #329

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unnecessary serialize/deserialize for cases where no conversion was performed #329

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0b2a7a2
unnecessary serialize/deserialize for cases where no conversion was p…
chiragaggarwal May 6, 2014
7bfc9e6
unnecessary serialize/deserialize for cases where no conversion was p…
chiragaggarwal May 23, 2014
eea72cd
Incorporated the feedback
chiragaggarwal May 29, 2014
6efb4d0
Since partValues does not change, so moving it out of iter.map
chiragaggarwal May 29, 2014
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43 changes: 25 additions & 18 deletions src/main/scala/shark/execution/HadoopTableReader.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -33,6 +33,7 @@ import org.apache.hadoop.hive.serde2.`lazy`.LazyStruct
import org.apache.hadoop.hive.serde2.objectinspector.{StructObjectInspector, ObjectInspectorConverters}
import org.apache.hadoop.io.Writable
import org.apache.hadoop.mapred.{FileInputFormat, InputFormat, JobConf}
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorConverters.IdentityConverter

import org.apache.spark.broadcast.Broadcast
import org.apache.spark.rdd.{EmptyRDD, HadoopRDD, RDD, UnionRDD}
Expand Down Expand Up @@ -194,30 +195,36 @@ class HadoopTableReader(@transient _tableDesc: TableDesc, @transient _localHConf
partSerDe.getObjectInspector(), tblConvertedOI)
val rowWithPartArr = new Array[Object](2)
// Map each tuple to a row object
iter.map { value =>
val deserializedRow = {

// If partition schema does not match table schema, update the row to match
val convertedRow = partTblObjectInspectorConverter.convert(partSerDe.deserialize(value))

// If conversion was performed, convertedRow will be a standard Object, but if
// conversion wasn't necessary, it will still be lazy. We can't have both across
// partitions, so we serialize and deserialize again to make it lazy.
if (tableSerDe.isInstanceOf[OrcSerde]) {
convertedRow
} else {

if ((tableSerDe.isInstanceOf[OrcSerde]) || (partTblObjectInspectorConverter.isInstanceOf[IdentityConverter])) {
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The result should be correct, however, this is confusing in logic.

iter.map { value =>
val deserializedRow = partTblObjectInspectorConverter.convert(partSerDe.deserialize(value))
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If it's the IdentityConverter, we don't need to call convert method.

rowWithPartArr.update(0, deserializedRow)
rowWithPartArr.update(1, partValues)
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The partValues doesn't change per partition, we can move out of the iter.map, the same for the later one.

rowWithPartArr.asInstanceOf[Object]
}
}
else {
iter.map { value =>
val deserializedRow = {

// If partition schema does not match table schema, update the row to match
val convertedRow = partTblObjectInspectorConverter.convert(partSerDe.deserialize(value))

// If conversion was performed, convertedRow will be a standard Object, but if
// conversion wasn't necessary, it will still be lazy. We can't have both across
// partitions, so we serialize and deserialize again to make it lazy.
convertedRow match {
case _: LazyStruct => convertedRow
case _: HiveColumnarStruct => convertedRow
case _ => tableSerDe.deserialize(
tableSerDe.asInstanceOf[Serializer].serialize(
convertedRow, tblConvertedOI))
case _ =>
tableSerDe.deserialize( tableSerDe.asInstanceOf[Serializer].serialize( convertedRow, tblConvertedOI))
}
}
rowWithPartArr.update(0, deserializedRow)
rowWithPartArr.update(1, partValues)
rowWithPartArr.asInstanceOf[Object]
}
rowWithPartArr.update(0, deserializedRow)
rowWithPartArr.update(1, partValues)
rowWithPartArr.asInstanceOf[Object]
}
}
}.toSeq
Expand Down