Fast and efficient operational time series storage: The missing link in dynamic software analysis
Lautenschlager F, Kumlehn A, Adersberger J, Philippsen M (2015)
Publication Language: English
Publication Type: Conference contribution, Original article
Publication year: 2015
Conference Proceedings Title: Softwaretechnik-Trends (Band 35, Nr. 3): Proceedings of the Symposium on Software Performance (SSP 2015)
Event location: München
URI: http://pi.informatik.uni-siegen.de/gi/stt/35_3/03_Technische_Beitraege/SSP_2015_paper_10.pdf
Abstract
Distributed applications, cloud systems, the Internet of Things, etc. are generating increasing amounts of operational
data, such as CPU loads, thread states, memory consumptions, method runtimes, or logs. Many tools continuously
collect and analyze such data that is best represented as
time series. Typical analyses try to nd and localize run-time incidents like outliers, leaks, or trend anomalies. However, these analyses need an ecient use of storage and a
fast interactive query execution, that general purpose storage systems do not provide: neither storing operational time
series data in general-purpose databases nor in conventional
time series databases ful lls these requirements.
We present Chronix, a novel time series storage that is
optimized for operational time series and that improves the
link between storage and analysis in a dynamic software
analysis toolchain. With Chronix a toolchain not only stores
data 4{33 times faster and it takes 5-171 times less storage
space than with other time series databases, it also executes
queries in 15-74% and analyses in 25-74% of the time.
Authors with CRIS profile
How to cite
APA:
Lautenschlager, F., Kumlehn, A., Adersberger, J., & Philippsen, M. (2015). Fast and efficient operational time series storage: The missing link in dynamic software analysis. In Softwaretechnik-Trends (Band 35, Nr. 3): Proceedings of the Symposium on Software Performance (SSP 2015). München, DE.
MLA:
Lautenschlager, Florian, et al. "Fast and efficient operational time series storage: The missing link in dynamic software analysis." Proceedings of the Symposium on Software Performance (SSP 2015), München 2015.
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