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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Journal ArticleDOI
BetrFS: Write-Optimization in a Kernel File System
William Jannen,Jun Yuan,Yang Zhan,Amogh Akshintala,John Esmet,Yizheng Jiao,Ankur Mittal,Prashant Pandey,Phaneendra Reddy,Leif Walsh,Michael A. Bender,Martin Farach-Colton,Rob Johnson,Bradley C. Kuszmaul,Donald E. Porter +14 more
TL;DR: The Be-tree File System, or BetrFS (pronounced “better eff ess”), is the first in-kernel file system to use a write-optimized data structure (WODS) and requires additional data-structure tuning to match current general-purpose file systems on some operations, including deletes, directory renames, and large sequential writes.
Proceedings ArticleDOI
Design Principles for Scaling Multi-core OLTP Under High Contention
TL;DR: This paper implements a prototype system, Orthrus, that is motivated by the principles of separation of database component functionality and advanced planning of transactions, and finds that these two principles alone result in significantly improved scalability on high-contention workloads, and an order of magnitude increase in throughput for a non-trivial subset of these contended workloads.
Journal ArticleDOI
uTree: a persistent B+-tree with low tail latency
TL;DR: A B-tree variant named μTree, which incorporates a shadow list-based layer to the leaf nodes of a B- tree to gain benefits from both list and tree data structures, and achieves a 99th percentile latency that is one order of magnitude lower and 2.7 times higher throughput.
Proceedings ArticleDOI
From clarity to efficiency for distributed algorithms
TL;DR: A very high-level language for clear description of distributed algorithms and optimizations necessary for generating efficient implementations of logic quantifications and new optimizations are presented that automatically transform complex synchronization conditions into incremental updates of necessary auxiliary values as messages are sent and received.
Proceedings ArticleDOI
Walnut: a unified cloud object store
Jianjun Chen,Chris Douglas,Michi Mutsuzaki,Patrick Quaid,Raghu Ramakrishnan,Sriram Rao,Russell Sears +6 more
TL;DR: The motivation for unifying different storage clouds is discussed, the requirements of a common storage layer are described, and the Walnut design is presented, which uses a quorum-based replication protocol and one-hop direct client access to the data in most regular operations.
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.