PS, we were using Breeze's activeIterator originally as you can see in
the old code, but we found there are overhead there, so we implement
our own implementation which results 4x faster. See
https://github.com/apache/spark/pull/3288 for detail.

Sincerely,

DB Tsai
-------------------------------------------------------
Blog: https://www.dbtsai.com
LinkedIn: https://www.linkedin.com/in/dbtsai



On Sun, Jan 25, 2015 at 12:25 PM, Reza Zadeh <r...@databricks.com> wrote:
> The idea is to unify the code path for dense and sparse vector operations,
> which makes the codebase easier to maintain. By handling (index, value)
> tuples, you can let the foreachActive method take care of checking if the
> vector is sparse or dense, and running a foreach over the values.
>
> On Sun, Jan 25, 2015 at 8:18 AM, kundan kumar <iitr.kun...@gmail.com> wrote:
>>
>> Can someone help me to understand the usage of "foreachActive"  function
>> introduced for the Vectors.
>>
>> I am trying to understand its usage in MultivariateOnlineSummarizer class
>> for summary statistics.
>>
>>
>> sample.foreachActive { (index, value) =>
>>       if (value != 0.0) {
>>         if (currMax(index) < value) {
>>           currMax(index) = value
>>         }
>>         if (currMin(index) > value) {
>>           currMin(index) = value
>>         }
>>
>>         val prevMean = currMean(index)
>>         val diff = value - prevMean
>>         currMean(index) = prevMean + diff / (nnz(index) + 1.0)
>>         currM2n(index) += (value - currMean(index)) * diff
>>         currM2(index) += value * value
>>         currL1(index) += math.abs(value)
>>
>>         nnz(index) += 1.0
>>       }
>>     }
>>
>> Regards,
>> Kundan
>>
>>
>

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