I believe this is because the type for [] is inferred to be never[], which is the type for an array that MUST be empty. You can use a type cast to address this: [‘a’, ‘b’, ‘c’].reduce((accumulator, value) => accumulator.concat(value), [] as string[]); Normally this wouldn’t be much of a problem since TypeScript does a … Read more
Empty RDD It cannot be substituted when RDD is empty: val rdd = sc.emptyRDD[Int] rdd.reduce(_ + _) // java.lang.UnsupportedOperationException: empty collection at // org.apache.spark.rdd.RDD$$anonfun$reduce$1$$anonfun$apply$ … rdd.fold(0)(_ + _) // Int = 0 You can of course combine reduce with condition on isEmpty but it is rather ugly. Mutable buffer Another use case for fold is … Read more
In ES6 you can use spread operator. One string solution: Math.min(…items)
Python 3.x does have reduce, you just have to do a from functools import reduce. It also has “dict comprehensions”, which have exactly the syntax in your example. Python 2.7 and 3.x also have a Counter class which does exactly what you want: from collections import Counter cnt = Counter(“abracadabra”) In Python 2.6 or earlier, … Read more
Taken from here, arr.reduce() will reduce the array to a value, specified by the callback. In your case, it will basically sum the elements of the array. Steps: Call function on 0,1 ( 0 is the initial value passed to .reduce() as the second argument. Return sum od 0 and 1, which is 1. Call … Read more
In general, all 6 fold functions apply a binary operator to each element of a collection. The result of each step is passed on to the next step (as input to one of the binary operator’s two arguments). This way we can cumulate a result. reduceLeft and reduceRight cumulate a single result. foldLeft and foldRight … Read more
Actually, it is quite simple to implement that cleanly with tasks using a recursive divide-and-conquer approach. This is almost textbook code. void operation(int* p1, int* p2, size_t bins) { for (int i = 0; i < bins; i++) p1[i] += p2[i]; } void reduce(int** arrs, size_t bins, int begin, int end) { assert(begin < end); … Read more
Mappers: Number of mappers depends on various factors such as how the data is distributed among nodes, input format, execution engine and configuration params. See also here: https://cwiki.apache.org/confluence/display/TEZ/How+initial+task+parallelism+works MR uses CombineInputFormat, while Tez uses grouped splits. Tez: set tez.grouping.min-size=16777216; — 16 MB min split set tez.grouping.max-size=1073741824; — 1 GB max split MapReduce: set mapreduce.input.fileinputformat.split.minsize=16777216; — … Read more