iSAX 2.0: Indexing and Mining One Billion Time Series; Database Cracking

Опубликовано 17 августа 2016, 3:35

iSAX 2.0: Indexing and Mining One Billion Time Series abstract -------- There is an increasingly pressing need, by several applications in diverse domains, for developing techniques able to index and mine very large collections of time series. Examples of such applications come from astronomy, biology, the web, and other domains. It is not unusual for these applications to involve numbers of time series in the order of hundreds of millions to billions. In this paper, we describe iSAX 2.0, a data structure designed for indexing and mining truly massive collections of time series. We show that the main bottleneck in mining such massive datasets is the time taken to build the index, and we thus introduce a novel bulk loading mechanism, the first of this kind specifically tailored to a time series index. We show how our method allows mining on datasets that would otherwise be completely untenable, including the first published experiments to index one billion time series, and experiments in mining massive data from domains as diverse as entomology, DNA and web-scale image collections. Database Cracking and the Path Towards Auto-tuning Database Kernels ABSTRACT: Database cracking targets dynamic and exploratory environments where there is no sufficient workload knowledge and idle time to invest in physical design preparations and tuning. With DB cracking indexes are built incrementally, adaptively and on demand; each query is seen as an advice on how data should be stored. With each incoming query, data is reorganized on-the-fly as part of the query operators, while future queries exploit and continuously enhance this knowledge. Autonomously, adaptively and without any external human administration, the system quickly adapts to a new workload and reaches optimal performance when the workload stabilizes. We will talk about the basics of DB cracking including selection cracking, partial and sideways cracking and updates. We will also talk about important open and on going research issues such as disk based cracking, concurrency control and integration of cracking with offline and online index analysis.