Joins are essential for many data analysis tasks, but are not supported directly by the MapReduce paradigm. While there has been progress on equi-joins, implementation of join alg...
MapReduce and stream processing are two emerging, but different, paradigms for analyzing, processing and making sense of large volumes of modern day data. While MapReduce offers t...
Experience has shown that development using shared-memory concurrency, the prevalent parallel programming paradigm today, is hard and synchronization primitives nonintuitive becaus...
MapReduce has emerged as a promising architecture for large scale data analytics on commodity clusters. The rapid adoption of Hive, a SQL-like data processing language on Hadoop (...
MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to ge...