In this paper, we extend the general applicability of MapReduce by allowing the dependence within a set of input key-value pairs but preserving independence ...
Abstract—MapReduce, proposed as a programming model, has been widely adopted in the field of text processing over large datasets with the capability of ...
In this paper, we extend the general applicability of MapReduce by allowing the dependence within a set of input key-value pairs but preserving independence ...
The experiment of background subtraction, a part of video surveillance, proves that the new modeling paradigm broadens the possibilities of MapReduce and ...
TL;DR: The goal of this paper is to discuss how to improve the performance of Change Detection while processing large video data on Hadoop clusters by using two ...
Jul 30, 2020 · ... two phases Map Phase and Reduce Phase. It is designed for processing the data in parallel which is divided on various machines(nodes). The ...
Sep 12, 2023 · MapReduce is a programming model and a way of processing large amounts of data across multiple computers, which are part of a distributed system.
Preference (top-k) queries play a key role in modern data analytics tasks. Top-k techniques rely on ranking functions in order to determine an overall score ...
MapReduce, proposed as a programming model, has been widely adopted in large-scale data processing with the capability of exploiting distributed resources ...
It takes away the complexity of distributed programming by exposing two processing steps that developers implement: 1) Map and 2) Reduce. In the Mapping step, ...
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