fix up scaladoc, naming of type parameters
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@ -19,7 +19,7 @@ class Accumulable[T,R] (
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/**
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/**
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* add more data to this accumulator / accumulable
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* add more data to this accumulator / accumulable
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* @param term
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* @param term the data to add
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*/
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*/
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def += (term: R) { value_ = param.addAccumulator(value_, term) }
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def += (term: R) { value_ = param.addAccumulator(value_, term) }
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@ -27,7 +27,7 @@ class Accumulable[T,R] (
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* merge two accumulable objects together
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* merge two accumulable objects together
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* <p>
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* <p>
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* Normally, a user will not want to use this version, but will instead call `+=`.
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* Normally, a user will not want to use this version, but will instead call `+=`.
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* @param term
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* @param term the other Accumulable that will get merged with this
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*/
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*/
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def ++= (term: T) { value_ = param.addInPlace(value_, term)}
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def ++= (term: T) { value_ = param.addInPlace(value_, term)}
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def value = this.value_
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def value = this.value_
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@ -64,33 +64,33 @@ trait AccumulatorParam[T] extends AccumulableParam[T,T] {
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/**
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/**
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* A datatype that can be accumulated, ie. has a commutative & associative +.
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* A datatype that can be accumulated, ie. has a commutative & associative +.
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* <p>
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*
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* You must define how to add data, and how to merge two of these together. For some datatypes, these might be
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* You must define how to add data, and how to merge two of these together. For some datatypes, these might be
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* the same operation (eg., a counter). In that case, you might want to use [[spark.AccumulatorParam]]. They won't
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* the same operation (eg., a counter). In that case, you might want to use [[spark.AccumulatorParam]]. They won't
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* always be the same, though -- eg., imagine you are accumulating a set. You will add items to the set, and you
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* always be the same, though -- eg., imagine you are accumulating a set. You will add items to the set, and you
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* will union two sets together.
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* will union two sets together.
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*
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*
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* @tparam T the full accumulated data
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* @tparam R the full accumulated data
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* @tparam R partial data that can be added in
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* @tparam T partial data that can be added in
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*/
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*/
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trait AccumulableParam[T,R] extends Serializable {
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trait AccumulableParam[R,T] extends Serializable {
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/**
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/**
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* Add additional data to the accumulator value.
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* Add additional data to the accumulator value.
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* @param t1 the current value of the accumulator
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* @param t1 the current value of the accumulator
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* @param t2 the data to be added to the accumulator
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* @param t2 the data to be added to the accumulator
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* @return the new value of the accumulator
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* @return the new value of the accumulator
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*/
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*/
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def addAccumulator(t1: T, t2: R) : T
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def addAccumulator(t1: R, t2: T) : R
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/**
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/**
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* merge two accumulated values together
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* merge two accumulated values together
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* @param t1
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* @param t1 one set of accumulated data
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* @param t2
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* @param t2 another set of accumulated data
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* @return
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* @return both data sets merged together
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*/
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*/
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def addInPlace(t1: T, t2: T): T
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def addInPlace(t1: R, t2: R): R
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def zero(initialValue: T): T
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def zero(initialValue: R): R
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}
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}
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// TODO: The multi-thread support in accumulators is kind of lame; check
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// TODO: The multi-thread support in accumulators is kind of lame; check
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@ -250,11 +250,8 @@ class SparkContext(
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/**
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/**
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* create an accumulatable shared variable, with a `+=` method
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* create an accumulatable shared variable, with a `+=` method
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* @param initialValue
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* @param param
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* @tparam T accumulator type
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* @tparam T accumulator type
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* @tparam R type that can be added to the accumulator
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* @tparam R type that can be added to the accumulator
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* @return
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*/
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*/
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def accumulable[T,R](initialValue: T)(implicit param: AccumulableParam[T,R]) =
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def accumulable[T,R](initialValue: T)(implicit param: AccumulableParam[T,R]) =
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new Accumulable(initialValue, param)
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new Accumulable(initialValue, param)
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