fix up scaladoc, naming of type parameters

core/src/main/scala/spark/Accumulators.scala

@@ -19,7 +19,7 @@ class Accumulable[T,R] (
 
   /**
    * add more data to this accumulator / accumulable
-   * @param term
+   * @param term the data to add
    */
   def += (term: R) { value_ = param.addAccumulator(value_, term) }
 
@@ -27,7 +27,7 @@ class Accumulable[T,R] (
    * merge two accumulable objects together
    * <p>
    * Normally, a user will not want to use this version, but will instead call `+=`.
-   * @param term
+   * @param term the other Accumulable that will get merged with this
    */
   def ++= (term: T) { value_ = param.addInPlace(value_, term)}
   def value = this.value_
@@ -64,33 +64,33 @@ trait AccumulatorParam[T] extends AccumulableParam[T,T] {
 
 /**
  * A datatype that can be accumulated, ie. has a commutative & associative +.
- * <p>
+ * 
  * You must define how to add data, and how to merge two of these together.  For some datatypes, these might be
  * the same operation (eg., a counter).  In that case, you might want to use [[spark.AccumulatorParam]].  They won't
  * always be the same, though -- eg., imagine you are accumulating a set.  You will add items to the set, and you
  * will union two sets together.
  *
- * @tparam T the full accumulated data
- * @tparam R partial data that can be added in
+ * @tparam R the full accumulated data
+ * @tparam T partial data that can be added in
  */
-trait AccumulableParam[T,R] extends Serializable {
+trait AccumulableParam[R,T] extends Serializable {
   /**
    * Add additional data to the accumulator value.
    * @param t1 the current value of the accumulator
    * @param t2 the data to be added to the accumulator
    * @return the new value of the accumulator
    */
-  def addAccumulator(t1: T, t2: R) : T
+  def addAccumulator(t1: R, t2: T) : R
 
   /**
    * merge two accumulated values together
-   * @param t1
-   * @param t2
-   * @return
+   * @param t1 one set of accumulated data
+   * @param t2 another set of accumulated data
+   * @return both data sets merged together
    */
-  def addInPlace(t1: T, t2: T): T
+  def addInPlace(t1: R, t2: R): R
 
-  def zero(initialValue: T): T
+  def zero(initialValue: R): R
 }
 
 // TODO: The multi-thread support in accumulators is kind of lame; check

core/src/main/scala/spark/SparkContext.scala

@@ -287,11 +287,8 @@ class SparkContext(
 
   /**
    * create an accumulatable shared variable, with a `+=` method
-   * @param initialValue
-   * @param param
    * @tparam T accumulator type
    * @tparam R type that can be added to the accumulator
-   * @return
    */
   def accumulable[T,R](initialValue: T)(implicit param: AccumulableParam[T,R]) =
     new Accumulable(initialValue, param)