Changing option wording per discussion with Andrew

core/src/main/scala/org/apache/spark/Aggregator.scala

@@ -32,7 +32,7 @@ case class Aggregator[K, V, C] (
     mergeCombiners: (C, C) => C) {
 
   private val sparkConf = SparkEnv.get.conf
-  private val externalSorting = sparkConf.getBoolean("spark.shuffle.external", true)
+  private val externalSorting = sparkConf.getBoolean("spark.shuffle.spill", true)
 
   def combineValuesByKey(iter: Iterator[_ <: Product2[K, V]]) : Iterator[(K, C)] = {
     if (!externalSorting) {

core/src/main/scala/org/apache/spark/storage/BlockManager.scala

@@ -81,7 +81,7 @@ private[spark] class BlockManager(
   // Whether to compress RDD partitions that are stored serialized
   val compressRdds = conf.getBoolean("spark.rdd.compress", false)
   // Whether to compress shuffle output temporarily spilled to disk
-  val compressExternalShuffle = conf.getBoolean("spark.shuffle.external.compress", false)
+  val compressShuffleSpill = conf.getBoolean("spark.shuffle.spill.compress", false)
 
   val heartBeatFrequency = BlockManager.getHeartBeatFrequency(conf)
 
@@ -792,7 +792,7 @@ private[spark] class BlockManager(
     case ShuffleBlockId(_, _, _) => compressShuffle
     case BroadcastBlockId(_) => compressBroadcast
     case RDDBlockId(_, _) => compressRdds
-    case TempBlockId(_) => compressExternalShuffle
+    case TempBlockId(_) => compressShuffleSpill
     case _ => false
   }
 

core/src/main/scala/org/apache/spark/util/collection/ExternalAppendOnlyMap.scala

@@ -87,9 +87,9 @@ private[spark] class ExternalAppendOnlyMap[K, V, C](
   // batches, with each batch using its own serialization stream. This cuts down on the size
   // of reference-tracking maps constructed when deserializing a stream.
   //
-  // NOTE: Setting this too low can cause excess copying when serializing, since some serailizers
+  // NOTE: Setting this too low can cause excess copying when serializing, since some serializers
   // grow internal data structures by growing + copying every time the number of objects doubles.
-  private val serializerBatchSize = sparkConf.getLong("spark.shuffle.external.batchSize", 10000)
+  private val serializerBatchSize = sparkConf.getLong("spark.shuffle.spill.batchSize", 10000)
 
   // How many times we have spilled so far
   private var spillCount = 0

docs/configuration.md

@@ -116,7 +116,7 @@ Apart from these, the following properties are also available, and may be useful
   <td>0.3</td>
   <td>
     Fraction of Java heap to use for aggregation and cogroups during shuffles, if
-    <code>spark.shuffle.external</code> is true. At any given time, the collective size of
+    <code>spark.shuffle.spill</code> is true. At any given time, the collective size of
     all in-memory maps used for shuffles is bounded by this limit, beyond which the contents will
     begin to spill to disk. If spills are often, consider increasing this value at the expense of
     <code>spark.storage.memoryFraction</code>.
@@ -155,7 +155,7 @@ Apart from these, the following properties are also available, and may be useful
   </td>
 </tr>
 <tr>
-  <td>spark.shuffle.external.compress</td>
+  <td>spark.shuffle.spill.compress</td>
   <td>false</td>
   <td>
     Whether to compress data spilled during shuffles.
@@ -395,7 +395,7 @@ Apart from these, the following properties are also available, and may be useful
   </td>
 </tr>
 <tr>
-  <td>spark.shuffle.external</td>
+  <td>spark.shuffle.spill</td>
   <td>true</td>
   <td>
     If set to "true", limits the amount of memory used during reduces by spilling data out to disk. This spilling