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Everything about MapReduce
Parallel programming model
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. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: MapReduceA 5-minute orientation
- Skim a recent paper: Hybrid Intrusion Detection using MapReduce based Black Widow Optimized Convolutional Long Short-Term Memory Neural NetworksInfluential work since 2022
- Pick up a classic book: Big Data with Hadoop MapreduceThe most-reprinted book on the subject
- Read the landmark paper: The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing dataCited 27,140 times
- Go sideways: Data-intensive computingA closely related topic
- Go sideways: Parallelization contractA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
MapReduce
SOAPnuke: a MapReduce acceleration-supported software for integrated quality control and preprocessing of high-throughput sequencing data
MapReduce
CloudBurst: highly sensitive read mapping with MapReduce
Parallel data processing with MapReduce
MapReduce and parallel DBMSs
Graph Twiddling in a MapReduce World
🆕 Influential since 2022
Hybrid Intrusion Detection using MapReduce based Black Widow Optimized Convolutional Long Short-Term Memory Neural Networks
MapReduce based intelligent model for intrusion detection using machine learning technique
A new service composition method in the cloud‐based Internet of things environment using a grey wolf optimization algorithm and MapReduce framework
A Distributed Framework for Large-scale Protein-protein Interaction Data Analysis and Prediction Using MapReduce
Secure and Transparent Mobility in Smart Cities: Revolutionizing AVNs to Predict Traffic Congestion Using MapReduce, Private Blockchain, and XAI
📚 Books worth reading
Big Data with Hadoop MapreduceRathinaraja Jeyaraj, Pugalendhi Ganeshkumar · 2020
Mapreduce Design PatternsAdam Shook · 2012
Big Data for Chimps: A Guide to Massive-Scale Data Processing in PracticePhilip Kromer, Russell Jurney · 2015- 📕Learning Big Data with Amazon Elastic MapReduceAmarkant Singh, Vijay Rayapati · 2014
Hadoop MapReduce CookbookSrinath Perera, Thilina Gunarathne · 2013
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Data-intensive computing Data-intensive computing is a class of parallel computing applications which use a data parallel approach to process large volumes of data typically terabytes…
- Parallelization contract The parallelization contract or PACT programming model is a generalization of the MapReduce programming model and uses second order functions to perform…
- Sector/Sphere Sector/Sphere is an open source software suite for high-performance distributed data storage and processing. It can be broadly compared to Google's GFS…
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- Apache Hadoop Apache Hadoop (/həˈduːp/) is a collection of open-source software utilities for reliable, scalable, distributed computing. It provides a software framework…
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- Data-centric programming language Data-centric programming language defines a category of programming languages where the primary function is the management and manipulation of data. A…
- Apache SystemDS Apache SystemDS (Previously, Apache SystemML) is an open source ML system for the end-to-end data science lifecycle. SystemDS's distinguishing characteristics…