Time Series Databases – New Ways to Store and Acces Data

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A01=Ellen Friedman
A01=Ted Dunning
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Author_Ellen Friedman
Author_Ted Dunning
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time series nosql machine learning data analysis

Product details

  • ISBN 9781491914724
  • Weight: 136g
  • Dimensions: 151 x 228mm
  • Publication Date: 13 Jan 2015
  • Publisher: O'Reilly Media
  • Publication City/Country: US
  • Product Form: Paperback
  • Language: English
Delivery/Collection within 10-20 working days

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Time series data is of growing importance, especially with the rapid expansion of the Internet of Things. This concise guide shows you effective ways to collect, persist, and access large-scale time series data for analysis. You'll explore the theory behind time series databases and learn practical methods for implementing them. Authors Ted Dunning and Ellen Friedman provide a detailed examination of open source tools such as OpenTSDB and new modifications that greatly speed up data ingestion.

You'll learn:

  • A variety of time series use cases
  • The advantages of NoSQL databases for large-scale time series data
  • NoSQL table design for high-performance time series databases
  • The benefits and limitations of OpenTSDB
  • How to access data in OpenTSDB using R, Go, and Ruby
  • How time series databases contribute to practical machine learning projects
  • How to handle the added complexity of geo-temporal data

For advice on analyzing time series data, check out Practical Machine Learning: A New Look at Anomaly Detection, also from Ted Dunning and Ellen Friedman.