accumulator

While exploring Spark accumulators, I tried to understand and showcase the difference between the accumulator and regular variable in Spark. But output does not seem to match my expectation. I mean both the accumulator and counter have the same value at the end of program and am able read accumulator within transformation function (as per docs only driver can read accumulator). Am i doing something wrong? Is my understanding correct? object Accmulators extends App { val spark = SparkSession.builder().appName("Accmulators").master("local[3]").getOrCreate() val cntAccum = spark.sparkContext

I see code like: mov ax, cs mov ds, ax mov es, ax Why can't I just compress this to: mov ds, cs mov es, cs Is the first way faster since its using the accumulator register? But that wouldn't seem intuitive since cs and ds are segment registers . Or is there some restriction that I'm unaware of? I'm using nasm by the way. You can't mov segment register to segment register -- there's no instruction for it. There is only so much room in a processor for the microcode for all its instructions. So one general instruction is often preferred over several special purpose ones for rarely uused

I'm looking for a fast solution to MATLAB's accumarray in numpy. The accumarray accumulates the elements of an array which belong to the same index. An example: a = np.arange(1,11) # array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) accmap = np.array([0,1,0,0,0,1,1,2,2,1]) Result should be array([13, 25, 17]) What I've done so far: I've tried the accum function in the recipe here which works fine but is slow. accmap = np.repeat(np.arange(1000), 20) a = np.random.randn(accmap.size) %timeit accum(accmap, a, np.sum) # 1 loops, best of 3: 293 ms per loop Then I tried to use the solution here which is

I wanted to use boost accumulators to calculate statistics of a variable that is a vector. Is there a simple way to do this. I think it's not possible to use the dumbest thing: using namespace boost::accumulators; //stuff... accumulator_set<vector<double>, stats<tag::mean> > acc; vector<double> some_vetor; //stuff some_vector = doStuff(); acc(some_vector); maybe this is obvious, but I tried anyway. :P What I wanted was to have an accumulator that would calculate a vector which is the mean of the components of many vectors. Is there an easy way out? EDIT: I don't know if I was thoroughly clear.

In Java 8, Stream has a method reduce: T reduce(T identity, BinaryOperator<T> accumulator); Is the accumulator operator allowed to modify either of its arguments? I presume not since the JavaDoc says the accumulator should be NonInterfering, though all examples talk of modifying the collection, rather than modifying the elements of the collection. So, for a concrete example, if we have integers.reduce(0, Integer::sum); and suppose for a moment that Integer was mutable, would sum be allowed to modify its first parameter by adding to it (in place) the value of its second parameter? I presume not