Abstract
Nowadays, we can observe increasing interest in processing and exploration of time series. Growing volumes of data and needs of efficient processing pushed research in new directions. GPU devices combined with fast compression and decompression algorithms open new horizons for data intensive systems. In this paper we present improved cascaded compression mechanism for time series databases build on Big Table–like solution. We achieved extremely fast compression methods with good compression ratio.
The project is funded by National Science Centre, decision DEC-2012/07/D/ST6/02483.
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References
Apache HBase (2013), http://hbase.apache.org
ParStream - website (2013), https://www.parstream.com
TempoDB – Hosted time series database service (2013), https://tempo-db.com/
Boncz, P.A., Zukowski, M., Nes, N.: Monetdb/x100: Hyper-pipelining query execution. In: CIDR, pp. 225–237 (2005)
Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Gruber, R.E.: Bigtable: A Distributed Storage System for Structured Data. In: OSDI 2006: Seventh Symposium on Operating System Design and Implementation, Seattle, WA, pp. 205–218 (November 2006)
Cloudkick. 4 months with cassandra, a love story (March 2010), https://www.cloudkick.com/blog/2010/mar/02/4_months_with_cassandra/
Delbru, R., Campinas, S., Samp, K., Tummarello, G.: Adaptive frame of reference for compressing inverted lists. Technical report, DERI – Digital Enterprise Research Institute (December 2010)
Fang, W., He, B., Luo, Q.: Database compression on graphics processors. Proceedings of the VLDB Endowment 3(1-2), 670–680 (2010)
Fink, E., Gandhi, H.S.: Compression of time series by extracting major extrema. J. Exp. Theor. Artif. Intell. 23(2), 255–270 (2011)
Lees, M., Ellen, R., Steffens, M., Brodie, P., Mareels, I., Evans, R.: Information infrastructures for utilities management in the brewing industry. In: Herrero, P., Panetto, H., Meersman, R., Dillon, T. (eds.) OTM 2012 Workshops. LNCS, vol. 7567, pp. 73–77. Springer, Heidelberg (2012)
OpenTSDB. Whats opentsdb (2010-2012), http://opentsdb.net/
Przymus, P., Kaczmarski, K.: Improving efficiency of data intensive applications on GPU using lightweight compression. In: Herrero, P., Panetto, H., Meersman, R., Dillon, T. (eds.) OTM 2012 Workshops. LNCS, vol. 7567, pp. 3–12. Springer, Heidelberg (2012)
Przymus, P., Rykaczewski, K., Wiśniewski, R.: Application of wavelets and kernel methods to detection and extraction of behaviours of freshwater mussels. In: Kim, T.-h., Adeli, H., Slezak, D., Sandnes, F.E., Song, X., Chung, K.-i., Arnett, K.P. (eds.) FGIT 2011. LNCS, vol. 7105, pp. 43–54. Springer, Heidelberg (2011)
Yan, H., Ding, S., Suel, T.: Inverted index compression and query processing with optimized document ordering. In: Proc. of the 18th Intern. Conf. on World Wide Web, pp. 401–410. ACM (2009)
Zukowski, M., Heman, S., Nes, N., Boncz, P.: Super-scalar ram-cpu cache compression. In: ICDE 2006. Proc. of the 22nd Intern. Conf. on Data Engineering, p. 59. IEEE (2006)
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Przymus, P., Kaczmarski, K. (2014). Dynamic Compression Strategy for Time Series Database Using GPU. In: Catania, B., et al. New Trends in Databases and Information Systems. Advances in Intelligent Systems and Computing, vol 241. Springer, Cham. https://doi.org/10.1007/978-3-319-01863-8_26
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DOI: https://doi.org/10.1007/978-3-319-01863-8_26
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01862-1
Online ISBN: 978-3-319-01863-8
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