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Journal ArticleDOI

Cassandra: a decentralized structured storage system

Avinash Lakshman, +1 more
- 14 Apr 2010 - 
- Vol. 44, Iss: 2, pp 35-40
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.

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Citations
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DottedDB: Anti-Entropy without Merkle Trees, Deletes without Tombstones

TL;DR: Results show that causality metadata per object always converges rapidly to only one id-counter pair; distributed deletes are correctly achieved without global coordination and with constant metadata; divergent nodes are synchronized faster, with less memory-footprint and with less communication overhead than using Merkle Trees.
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Adaptive State Consistency for Distributed ONOS Controllers

TL;DR: This paper proposes an adaptive consistency model for the distributed ONOS controllers following the notion of continuous and compulsory (per-controller) eventual consistency, where network application states adapt their eventual consistency level dynamically at runtime based on the observed state inconsistencies under changing network conditions.
Posted Content

Kollaps: Decentralized and Dynamic Topology Emulation.

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Scalable computational geometry in MapReduce

TL;DR: CG_Hadoop is introduced; a suite of scalable and efficient MapReduce algorithms for various fundamental computational geometry operations, namely polygon union, Voronoi diagram, skyline, convex hull, farthest pair, and closest pair, which present a set of key components for other geometric algorithms.
Proceedings ArticleDOI

Semantic Data Querying over NoSQL Databases with Apache Spark

TL;DR: This paper presents techniques for distributed RDF data storage and querying schemes for HBase and Cassandra clusters and presents a compiler that translates SPARQL queries into their Spark SQL equivalent for execution.
References
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Journal ArticleDOI

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Journal ArticleDOI

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Proceedings Article

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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.
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