Time series classification under more realistic assumptions

Time series classification under more realistic assumptions - Hu et al. ICDM 2013 This paper sheds light on the gap between research results in time series classification, and what you're likely to see if you try to apply the results in the real world. And having identified the gap of course, the authors go on … Continue reading Time series classification under more realistic assumptions

Searching and mining trillions of time series subsequences under Dynamic Time Warping

Searching and mining trillions of time series subsequences under dynamic time warping - Rakthanmanon et al. SIGKDD 2012 What an astonishing paper this is! By 2012, Dynamic Time Warping had been shown to be the time series similarity measure that generally performs the best for matching, but because of its computational complexity researchers and practitioners … Continue reading Searching and mining trillions of time series subsequences under Dynamic Time Warping

Finding surprising patterns in a time series database in linear time and space

Finding Surprising Patterns in a Time Series Database in Linear Time and Space - Keogh et al. SIGKDD 2002 In the Facebook Gorilla paper, the authors mentioned a number of additional time series analysis techniques they'd like to add to the system over time. Today's paper is one of them, and it deals with the … Continue reading Finding surprising patterns in a time series database in linear time and space

NOVA: A Log-Structured File System for Hybrid Volatile/Non-Volatile Main Memories

NOVA: A Log-structured file system for hybrid volatile/non-volatile main memories - Xu & Swanson 2016 Another paper looking at the design implications of mixed DRAM and NVMM systems (it's the future!), this time in the context of file systems. (NVMM = Non-volatile Main Memory). Hybrid DRAM/NVMM storage systems present a host of opportunities and challenges … Continue reading NOVA: A Log-Structured File System for Hybrid Volatile/Non-Volatile Main Memories

Uncovering bugs in Distributed Storage Systems during Testing (not in production!)

Uncovering bugs in Distributed Storage Systems during Testing (not in production!) - Deligiannis et al. 2016 We interviewed technical leaders and senior managers in Microsoft Azure regarding the top problems in distributed system development. The consensus was that one of the most critical problems today is how to improve testing coverage so that bugs can … Continue reading Uncovering bugs in Distributed Storage Systems during Testing (not in production!)

BTrDB: Optimizing Storage System Design for Timeseries Processing

BTrDB: Optimizing Storage System Design for Timeseries Processing - Anderson & Culler 2016 It turns out you can accomplish quite a lot with 4,709 lines of Go code! How about a full time-series database implementation, robust enough to be run in production for a year where it stored 2.1 trillion data points, and supporting 119M … Continue reading BTrDB: Optimizing Storage System Design for Timeseries Processing

Gorilla: A fast, scalable, in-memory time series database

Gorilla: A fast, scalable, in-memory time series database - Pelkonen et al. 2015 Error rates across one of Facebook's sites were spiking. The problem had first shown up through an automated alert triggered by an in-memory time-series database called Gorilla a few minutes after the problem started. One set of engineers mitigated the immediate issue. … Continue reading Gorilla: A fast, scalable, in-memory time series database

Optimizing Distributed Actor Systems for Dynamic Interactive Services

Optimizing Distributed Actor Systems for Dynamic Interactive Services - Newell et al. 2016 I'm sure many of you have heard of the Orleans distributed actor system, that was used to build some of the systems supporting Microsoft's online Halo game. Halo Presence is an interactive application which implements presence services for a multi-player game running … Continue reading Optimizing Distributed Actor Systems for Dynamic Interactive Services