Journal ArticleDOI
Cassandra: a decentralized structured storage system
Avinash Lakshman,Prashant Malik +1 more
TLDR
Cassandra is a distributed storage system for managing very large amounts of structured data spread out across many commodity servers, while providing highly available service with no single point of failure.Abstract:
Cassandra is a distributed storage system for managing very large amounts of structured data spread out across many commodity servers, while providing highly available service with no single point of failure. Cassandra aims to run on top of an infrastructure of hundreds of nodes (possibly spread across different data centers). At this scale, small and large components fail continuously. The way Cassandra manages the persistent state in the face of these failures drives the reliability and scalability of the software systems relying on this service. While in many ways Cassandra resembles a database and shares many design and implementation strategies therewith, Cassandra does not support a full relational data model; instead, it provides clients with a simple data model that supports dynamic control over data layout and format. Cassandra system was designed to run on cheap commodity hardware and handle high write throughput while not sacrificing read efficiency.read more
Citations
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Proceedings ArticleDOI
OptCon: An Adaptable SLA-Aware Consistency Tuning Framework for Quorum-based Stores
TL;DR: OptCon as mentioned in this paper is a machine learning-based predictive framework that can automate the choice of client-centric consistency setting under user-specified latency and staleness thresholds given in the SLA.
Book ChapterDOI
Exploring the Evolution of Big Data Technologies
TL;DR: This chapter explores the rise of “big data” and the computational strategies, both hardware and software, that have evolved to deal with this paradigm along with the upcoming developments in the near future and how this computing paradigm fits into the road to exascale.
Consistency Management in Cloud Storage Systems
TL;DR: This chapter discusses the consistency issue and describes the CAP theorem as well as its limitations and impacts on big data management in large scale systems, and briefly introduces several models of consistency in cloud storage systems.
Proceedings ArticleDOI
NoSQL Undo: Recovering NoSQL databases by undoing operations
David R. Matos,Miguel Correia +1 more
TL;DR: NOSQL UNDO leverages the logging and snapshot mechanisms built-in NoSQL databases, and is able to undo operations as long as they are present in the logs, the first recovery service that offers these capabilities for No SQL databases.
Journal ArticleDOI
Processing large-scale data with Apache Spark
Seyoon Ko,Joong-Ho Won +1 more
TL;DR: The concept and programming model of Spark is introduced as well as some implementations of simple statistical computing applications and the machine learning package MLlib, and the R language interface SparkR are reviewed.
References
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Journal ArticleDOI
MapReduce: simplified data processing on large clusters
Jeffrey Dean,Sanjay Ghemawat +1 more
TL;DR: This paper presents the implementation of MapReduce, a programming model and an associated implementation for processing and generating large data sets that runs on a large cluster of commodity machines and is highly scalable.
Journal ArticleDOI
MapReduce: simplified data processing on large clusters
Jeffrey Dean,Sanjay Ghemawat +1 more
TL;DR: This presentation explains how the underlying runtime system automatically parallelizes the computation across large-scale clusters of machines, handles machine failures, and schedules inter-machine communication to make efficient use of the network and disks.
Proceedings ArticleDOI
Chord: A scalable peer-to-peer lookup service for internet applications
TL;DR: Results from theoretical analysis, simulations, and experiments show that Chord is scalable, with communication cost and the state maintained by each node scaling logarithmically with the number of Chord nodes.
Journal ArticleDOI
The Google file system
TL;DR: This paper presents file system interface extensions designed to support distributed applications, discusses many aspects of the design, and reports measurements from both micro-benchmarks and real world use.
Proceedings Article
Bigtable: A Distributed Storage System for Structured Data (Awarded Best Paper!).
Fay W. Chang,Jeffrey Dean,Sanjay Ghemawat,Wilson C. Hsieh,Deborah A. Wallach,Michael Burrows,Tushar Deepak Chandra,Andrew Fikes,Robert Gruber +8 more
TL;DR: Bigtable as mentioned in this paper is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers, including web indexing, Google Earth and Google Finance.