Book description
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.
Table of contents
- Preface
- 1. Time Series Data: Why Collect It?
- 2. A New World for Time Series Databases
- 3. Storing and Processing Time Series Data
-
4. Practical Time Series Tools
- Introduction to Open TSDB: Benefits and Limitations
- Architecture of Open TSDB
- Value Added: Direct Blob Loading for High Performance
- A New Twist: Rapid Loading of Historical Data
- Summary of Open Source Extensions to Open TSDB for Direct Blob Loading
- Accessing Data with Open TSDB
- Working on a Higher Level
- Accessing Open TSDB Data Using SQL-on-Hadoop Tools
- Using Apache Spark SQL
- Why Not Apache Hive?
- Adding Grafana or Metrilyx for Nicer Dashboards
- Possible Future Extensions to Open TSDB
- 5. Solving a Problem You Didn’t Know You Had
- 6. Time Series Data in Practical Machine Learning
- 7. Advanced Topics for Time Series Databases
- 8. What’s Next?
- A. Resources
- About the Authors
- Colophon
- Copyright
Product information
- Title: Time Series Databases: New Ways to Store and Access Data
- Author(s):
- Release date: December 2014
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491914724
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