Search results
Results From The WOW.Com Content Network
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...
obj.reduce(func, initial) obj.reduce(func) Where func receives as arguments the result of the previous operation (or the initial value on the first iteration); the current item; the current item's index or key; and a reference to the obj: Clojure (reduce func initval list) (reduce func initval (reverse list)) (reduce func list) (reduce func ...
Although std::map is typically implemented using a self-balancing binary search tree, C++11 defines a second map called std::unordered_map, which has the algorithmic characteristics of a hash table. This is a common vendor extension to the Standard Template Library (STL) as well, usually called hash_map , available from such implementations as ...
[2] [3] [4] The reduction of sets of elements is an integral part of programming models such as Map Reduce, where a reduction operator is applied to all elements before they are reduced. Other parallel algorithms use reduction operators as primary operations to solve more complex problems.
Therefore, compilers will attempt to transform the first form into the second; this type of optimization is known as map fusion and is the functional analog of loop fusion. [2] Map functions can be and often are defined in terms of a fold such as foldr, which means one can do a map-fold fusion: foldr f z . map g is equivalent to foldr (f .
Data mapping; Code generation; Code execution; Data review; These steps are often the focus of developers or technical data analysts who may use multiple specialized tools to perform their tasks. The steps can be described as follows: Data discovery is the first step in the data transformation process. Typically the data is profiled using ...
A common example is the iostream library in C++, which uses the << or >> operators for the message passing, sending multiple data to the same object and allowing "manipulators" for other method calls. Other early examples include the Garnet system (from 1988 in Lisp) and the Amulet system (from 1994 in C++) which used this style for object ...
Explicit parallelism is one of the main reasons for the poor performance of Enterprise Java Beans when building data-intensive, non-OLTP applications. [ citation needed ] Where a sequential program can be imagined as a single worker moving between tasks (operations), a dataflow program is more like a series of workers on an assembly line , each ...