In this demonstration paper, we present SPATE, an innovative telco big data exploration framework whose objectives are two-fold: (i) minimizing the storage space needed to incrementally retain data over time; and (ii) minimizing the response time for spatiotemporal data exploration queries over stored data. Our framework deploys lossless data compression to ingest streams of telco big data in the most compact manner retaining full resolution for data exploration tasks. We augment our storage structures with decaying principles that lead to the progressive loss of detail as information gets older. Our framework also includes visual and declarative interfaces for a variety of telco-specific data exploration tasks. We demonstrate SPATE in two modes: (i) Visual Mode, where attendees will be able to interactively explore synthetic telco traces we will provide; and (ii) SQL Mode, where attendees can submit custom SQL queries based on a provided schema.
|Original language||English (US)|
|Title of host publication||Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017|
|Publisher||IEEE Computer Society|
|Number of pages||2|
|State||Published - May 16 2017|
|Event||33rd IEEE International Conference on Data Engineering, ICDE 2017 - San Diego, United States|
Duration: Apr 19 2017 → Apr 22 2017
|Name||Proceedings - International Conference on Data Engineering|
|Other||33rd IEEE International Conference on Data Engineering, ICDE 2017|
|Period||4/19/17 → 4/22/17|
Bibliographical noteFunding Information:
This work was supported in part by the University of Cyprus, an industrial sponsorship by MTN Cyprus and EU COST Action IC1304. The third author's research is supported by the Alexander von Humboldt-Foundation, Germany. The last author's research is supported by NSF grants IIS-0952977, IIS-1218168, IIS-1525953, CNS-1512877.
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