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Linkbench: A database benchmark based on the facebook social graph

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Title: Linkbench: A database benchmark based on the facebook social graph
Authors: Timothy G. Armstrong, Vamsi Ponnekanti, Dhruba Borthakur, Mark Callaghan, Facebook Inc
Contributors: The Pennsylvania State University CiteSeerX Archives
Source: http://people.cs.uchicago.edu/%7Etga/pubs/sigmod-linkbench-2013.pdf.
Collection: CiteSeerX
Subject Terms: Categories and Subject Descriptors H.2 [Information Systems, Database Management General Terms Experimentation, Measurement, Performance Keywords Social networks, database workload analysis, database bench- marks, MySQL, HBase
Description: Database benchmarks are an important tool for database re-searchers and practitioners that ease the process of making informed comparisons between different database hardware, software and configurations. Large scale web services such as social networks are a major and growing database appli-cation area, but currently there are few benchmarks that accurately model web service workloads. In this paper we present a new synthetic benchmark called LinkBench. LinkBench is based on traces from production databases that store “social graph ” data at Facebook, a ma-jor social network. We characterize the data and query workload in many dimensions, and use the insights gained to construct a realistic synthetic benchmark. LinkBench pro-vides a realistic and challenging test for persistent storage of social and web service data, filling a gap in the available tools for researchers, developers and administrators.
Document Type: text
File Description: application/pdf
Language: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.717.8973
Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.717.8973
http://people.cs.uchicago.edu/%7Etga/pubs/sigmod-linkbench-2013.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Accession Number: edsbas.2DE0EEE
Database: BASE
Description
Abstract:Database benchmarks are an important tool for database re-searchers and practitioners that ease the process of making informed comparisons between different database hardware, software and configurations. Large scale web services such as social networks are a major and growing database appli-cation area, but currently there are few benchmarks that accurately model web service workloads. In this paper we present a new synthetic benchmark called LinkBench. LinkBench is based on traces from production databases that store “social graph ” data at Facebook, a ma-jor social network. We characterize the data and query workload in many dimensions, and use the insights gained to construct a realistic synthetic benchmark. LinkBench pro-vides a realistic and challenging test for persistent storage of social and web service data, filling a gap in the available tools for researchers, developers and administrators.