I think something like this: A.filterNot(a => B.exists(b => a._3.exists(str => str.contains(b)))) or A.filterNot(a => a._3.exists(str => B.exists(b => str.contains(b)))) or shorter, but less readable A.filterNot(_._3 exists (B exists _.contains))
You can use pattern matching to determine which type of Array you’re dealing with. def arrTest[A](a :Array[A]) :Boolean = a match { case sa :Array[String] => sa.length < 2 || sa.sliding(2).forall(x => x(0) < x(1)) case ia :Array[Int] => ia.length > 2 && ia(0) == 1 && ia(1) == 1 && ia.sliding(3).forall(x => x(0) + … Read more
Your solution for C++ is not the best one, because it might cause integer overflow if a or b is big enough. The right solution would be using xor: a = a ^ b; b = b ^ a; a = b ^ a; But this kind of trick makes sense only if variables are … Read more
Assume – for example – that these are coordinates. Are (x,y) and (y,x) the same coordinates? Certainly not! Therefore, mapreduce must not assume that the order of a tuple is irrelevant by default. (That does not say it can’t be done, just that the system must not assume this as default behavior) If you want … Read more
You can start with an Array and build its elements. Array.tabulate(26)(x => (x+’a’).toChar.toString * k) Or you can start with the elements and then transition to an Array. (‘a’ to ‘z’).map(_.toString * k).toArray
Scala generates class files. Scala class files can be run with java, only requiring the scala-library.jar to be on the class path. The entry point on Scala programs appears to Java as a static main method on a class, just like in Java. The difference is that, in a Scala program, that main method is … Read more
You can’t do that. SortedMap sorts by keys, not values. If you want it sorted by value, you gotta use ListMap, and can’t avoid converting to List: ListMap(i.toList.sortBy(-_._2):_*) There isn’t really too much wrong with converting to list, since you are loading the whole thing in memory anyway. This is faster too, than building a … Read more
What (probably) takes the time here is shuffling the data: when you want to group two or more records together, they must reside within the same partition, so Spark has to first shuffle the records so that all records with same key are in a single partition. Now, even if each key has two records … Read more
You can use a List to store the steps necessary to cook a chicken, because Lists support sequential access and you can access the steps in order. You can use a Tuple to store the latitude and longitude of your home, because a tuple always has a predefined number of elements (in this specific example, … Read more
Not super-short: List(1,2,3,4).grouped(2).collect{ case List(k,v) => k -> v }.toMap