Abstract
Data analysis is among the main strategies of our time for enterprises to take advantage of the vast amounts of data their systems generate and store everyday. Thus the standard relational database model is challenged everyday to cope with quantitative operations over a traditionally qualitative, relational model.
A novel approach to the semantics of data is based on (typed) linear algebra (LA), rather than relational algebra, bridging the gap between data dimensions and data measures in a unified way. Also, this bears the promise of increased parallelism, as most operations in LA admit a ‘divide & conquer’ implementation.
This paper presents a first experiment in implementing such a typed linear algebra approach and testing its performance on a data distributed system. It presents solutions to some theoretical limitations and evaluates the overall performance.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
OLTP stands for “Online Transaction Processing”.
- 2.
OLAP stands for “Online Analytical Processing”.
- 3.
Cf. 64 base encoding.
- 4.
References
Watson, H.J., Wixom, B.: The current state of business intelligence. IEEE Comput. 40, 96–99 (2007)
Ginsberg, J., Mohebbi, M.H., Patel, R.S., Brammer, L., Smolinski, M.S., Brilliant, L.: Detecting influenza epidemics using search engine query data. Nature 457, 1012–1014 (2009)
Codd, E.F., Codd, S.B., Salley, C.T.: Providing OLAP to user-analysts: an IT mandate. In: Ann ArborMichigan, p. 24 (1993)
Macedo, H., Oliveira, J.N.: A linear algebra approach to OLAP. Formal Aspects Comput., 1–25 (2014)
Silva, M.: Sparse matrix storage revisited, pp. 230–235 (2005)
Coppersmith, D.: Rectangular matrix multiplication revisited. J. Complex. 13, 42–49 (1997)
Hive
Floratou, A., Patel, J.M., Shekita, E.J., Tata, S.: Column-oriented storage techniques for MapReduce. In: PVLDB, pp. 419–429 (2011)
Oliveira, J.: Towards a linear algebra semantics for query languages, June 2016
Bergamaschi, S., Interlandidi, M., Longo, M., Po, L., Vincini, M.: A meta-language for MDX queries in elog business solution. In: 2012 IEEE 28th International Conference on Data Engineering, pp. 1417–1428 (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Pontes, R., Matos, M., Oliveira, J.N., Pereira, J.O. (2017). Implementing a Linear Algebra Approach to Data Processing. In: Cunha, J., Fernandes, J., Lämmel, R., Saraiva, J., Zaytsev, V. (eds) Grand Timely Topics in Software Engineering. GTTSE 2015. Lecture Notes in Computer Science(), vol 10223. Springer, Cham. https://doi.org/10.1007/978-3-319-60074-1_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-60074-1_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-60073-4
Online ISBN: 978-3-319-60074-1
eBook Packages: Computer ScienceComputer Science (R0)