Big Data Analytics Research Paper

f you are looking for some of the most influential research papers that revolutionised the way how we gather, aggregate, analyze and store increasing volumes of data in a short span of 10 years, you are in the right place!

Chukwa is built on top of Hadoop, an open source distributed filesystem and Map Reduce implementation, and inherits Hadoop’s scalability and robustness.In addition, it combines several ingredients, which form the basis of the modern practice of random forests.A Relational Model of Data for Large Shared Data Banks Written by EF Codd in 1970, this paper was a breakthrough in Relational Data Base systems.Pregel: A System for Large-Scale Graph Processing This paper presents a computational model suitable to solve many practical computing problems that concerns large graphs.Spanner: Google’s Globally-Distributed Database It explains about Spanner, Google’s scalable, multi-version, globally-distributed, and synchronously-replicated database.This paper explores the feasibility of building a hybrid system. This paper outlines the S4 architecture in detail, describes various applications, including real-life deployments, to show that the S4 design is surprisingly flexible and lends itself to run in large clusters built with commodity hardware.Dremel: Interactive Analysis of Web-Scale Datasets This paper describes the architecture and implementation of Dremel, a scalable, interactive ad-hoc query system for analysis of read-only nested data, and explains how it complements Map Reduce-based computing.Spark: Cluster Computing with Working Sets This paper focuses on applications that reuse a working set of data across multiple parallel operations and proposes a new framework called Spark that supports these applications while retaining the scalability and fault tolerance of Map Reduce.The Unified Logging Infrastructure for Data Analytics at Twitter This paper presents Twitter’s production logging infrastructure and its evolution from application-specific logging to a unified “client events” log format, where messages are captured in common, well-formatted, flexible Thrift messages.In case we’ve missed out any important paper, please let us know.Map Reduce: Simplified Data Processing on Large Clusters This paper presents Map Reduce, a programming model and its implementation for large-scale distributed clusters.

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