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102 Results

June 18, 2016

Dynamo: Facebook’s Data Center-Wide Power Management System

ISCA 2016

In this paper, we describe Dynamo – a data center-wide power management system that monitors the entire power hierarchy and makes coordinated control decisions to safely and efficiently use provisioned data center power.

By: Qiang Wu, Qingyuan Deng, Lakshmi Ganesh, Chang-Hong Raymond Hsu, Yun Jin, Sanjeev Kumar, Bin Li, Justin Meza, Yee Jiun Song
June 11, 2016

Treadmill: Attributing the Source of Tail Latency through Precise Load Testing and Statistical Inference

International Symposium on Computer Architecture

Managing tail latency of requests has become one of the primary challenges for large-scale Internet services. In this paper, we develop a methodology for statistically rigorous performance evaluation for server workloads.

By: Yunqi Zhang, David Meisner, Jason Mars, Lingjia Tang
May 22, 2016

The Social Ties of Immigrant Communities in the United States


In this paper we study the composition of Facebook social networks of people who have moved from one country to another.

By: Amaç Herdağdelen, Bogdan State, Lada Adamic, Winter Mason
May 21, 2016

Continuous Deployment at Facebook and OANDA

ICSE 2016: 38th IEEE Conference on Software Engineering

This paper describes the continuous deployment practices at two very different firms: Facebook and OANDA, and shows that continuous deployment does not inhibit productivity or quality even in the face of substantial engineering team and code size growth.

By: Tony Savor, Mitchell Douglas, Michael Gentili, Laurie Williams, Kent Beck, Michael Stumm
May 14, 2016

The Shortest Path is not Always a Straight Line. Leveraging Semi-Metricity in Graph Analysis.

VLDB 2016

This paper leverages the concept of the metric backbone to improve the efficiency of large-scale graph analytics.

By: Dionysios Logothetis
March 15, 2016

Social Hash: an Assignment Framework for Optimizing Distributed Systems Operations on Social Networks

USINEX Symposium on Networked Systems Design and Implementation (NSDI 2016)

We describe the social hash framework, which uses graph partitioning techniques to improve the performance of systems within Facebook. We highlight two applications: 1. how routing similar users to the same web cluster improves our cache performance, 2. how co-locating socially similar data on the same host improves the performance of data serving systems.

By: Alon Shalita, Brian Karrer, Igor Kabiljo, Arun Sharma, Aaron Adcock, Alessandro Presta, Herald Kllapi, Michael Stumm
October 4, 2015

Existential Consistency: Measuring and Understanding Consistency at Facebook

The 25th ACM Symposium on Operating Systems Principles

Replicated storage for large Web services faces a trade-off between stronger forms of consistency and higher performance properties. Stronger consistency prevents anomalies, i.e., unexpected behavior visible to users, and reduces programming complexity.

By: Haonan Lu, Kaushik Veeraraghavan, Philippe Ajoux, Jim Hunt, Yee Jiun Song, Wendy Tobagus, Sanjeev Kumar, Wyatt Lloyd
October 4, 2015

Holistic Configuration Management at Facebook

The 25th ACM Symposium on Operating Systems Principles

This paper gives a comprehensive description of the use cases, design, implementation, and usage statistics of a suite of tools that manage Facebook’s configuration end-to-end, including the frontend products, backend systems, and mobile apps.

By: Chunqiang (CQ) Tang, Thawan Kooburat, Pradeep Venkat, Akshay Chander, Zhe Wen, Aravind Narayanan, Patrick Dowell, Robert Karl
August 31, 2015

One Trillion Edges: Graph Processing at Facebook-Scale

The 41st International Conference on Very Large Data Bases

Analyzing large graphs provides valuable insights for social networking and web companies in content ranking and recommendations. While numerous graph processing systems have been developed and evaluated on available benchmark graphs of up to 6.6B edges, they often face significant difficulties in scaling to much larger graphs. Industry graphs can be two orders of magnitude larger hundreds of billions or up to one trillion edges.

By: Avery Ching, Sergey Edunov, Maja Kabiljo, Dionysios Logothetis, Sambavi Muthukrishnan
August 31, 2015

Cubrick: A Scalable Distributed MOLAP Database for Fast Analytics

41st International Conference on Very Large Databases (Ph.D Workshop)

This paper describes the architecture and design of Cubrick, a distributed multidimensional in-memory database that enables real-time data analysis of large dynamic datasets. Cubrick has a strictly multidimensional data model composed of dimensions, dimensional hierarchies and metrics, supporting sub-second MOLAP operations such as slice and dice, roll-up and drill-down over terabytes of data.

By: Pedro Pedreira, Luis Erpen de Bona, Chris Croswhite