Abstract
Current OLAP servers are typically implemented as either extensions to conventional relational databases or as non-relational array-based storage engines. In the former case, the unique modeling and processing requirements of OLAP systems often make for a relatively awkward fit with RDBM systems. In the latter case, the proprietary nature of the MOLAP implementations has largely prevented the emergence of a standardized query model. In this paper, we discuss an algebra for the specification, optimization, and execution of OLAP-specific queries, including its ability to support a native language query framework. In addition, we ground the conceptual work by incorporating the query optimization and execution facilities into a fully functional OLAP-aware DBMS prototype. Experimental results clearly demonstrate the potential of the new algebra-driven system relative to both the un-optimized prototype and a pair of popular enterprise servers.
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References
JSR 243: Java Data Objects 2.0 - An Extension to the JDO specification (2008), http://java.sun.com/products/jdo/
HaskellDB (2010), http://www.haskell.org/haskellDB/
Berkeleydb (2011), http://www.oracle.com/technetwork/database/berkeleydb/overview/index.html
Fastbit indexing (2011), http://crd.lbl.gov/~kewu/fastbit/index.html
Ruby programming language (2011), http://www.ruby-lang.org/en/
Babcock, B., Chaudhuri, S., Das, G.: Dynamic sample selection for approximate query processing. In: Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, SIGMOD 2003, pp. 539–550. ACM, New York (2003)
Bauer, C., King, G.: Java Persistence with Hibernate. Manning Publications Co., Greenwich (2006)
Bellatreche, L., Giacometti, A., Laurent, D., Marcel, P., Mouloudi, H.: Olap query optimization: A framework forcombining rule-based and cost-based approaches. In: EDA (2005)
Blakeley, J.A., Rao, V., Kunen, I., Prout, A., Henaire, M., Kleinerman, C.: NET database programmability and extensibility in Microsoft SQL Server. In: ACM SIGMOD International conference on Management of Data, pp. 1087–1098. ACM, New York (2008)
Bruno, N., Chaudhuri, S., Gravano, L.: Stholes: a multidimensional workload-aware histogram. In: Proceedings of the 2001 ACM SIGMOD International Conference on Management of Data, SIGMOD 2001, pp. 211–222. ACM, New York (2001)
Chen, Z., Ordonez, C.: Efficient olap with udfs. In: Proceedings of the ACM 11th International Workshop on Data Warehousing and OLAP, DOLAP 2008, pp. 41–48 (2008)
Chmiel, J., Morzy, T., Wrembel, R.: Time-hobi: indexing dimension hierarchies by means of hierarchically organized bitmaps. In: Proceedings of the ACM 13th International Workshop on Data Warehousing and OLAP, DOLAP 2010, pp. 69–76. ACM, New York (2010)
Cook, W.R., Rai, S.: Safe query objects: statically typed objects as remotely executable queries. In: International Conference on Software Engineering (ICSE), pp. 97–106 (2005)
Cunningham, C., Graefe, G., Galindo-Legaria, C.A.: PIVOT and UNPIVOT: Optimization and execution strategies in an RDBMS. In: International Conference on Very Large Data Bases (VLDB), pp. 998–1009 (2004)
Cuzzocrea, A., Furfaro, F., Saccà , D.: Enabling olap in mobile environments via intelligent data cube compression techniques. J. Intell. Inf. Syst. 33(2), 95–143 (2009)
Cuzzocrea, A., Serafino, P.: Lcs-hist: taming massive high-dimensional data cube compression. In: Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT 2009, pp. 768–779. ACM, New York (2009)
Cuzzocrea, A., Wang, W.: Approximate range—sum query answering on data cubes with probabilistic guarantees. J. Intell. Inf. Syst. 28(2), 161–197 (2007)
Eavis, T., Cueva, D.: The lbf r-tree: Efficient multidimensional indexing with graceful degradation. In: Proc. 11th International Database Engineering and Applications Symposium, IDEAS 2007, September 6-8, pp. 241–250 (2007)
Eavis, T., Tabbara, H., Taleb, A.: The NOX Framework: Native Language Queries for Business Intelligence Applications. In: Bach Pedersen, T., Mohania, M.K., Tjoa, A.M. (eds.) DAWAK 2010. LNCS, vol. 6263, pp. 172–189. Springer, Heidelberg (2010)
Eavis, T., Taleb, A.: Mapgraph: efficient methods for complex olap hierarchies. In: Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management, CIKM 2007, pp. 465–474. ACM, New York (2007)
Gray, J., Bosworth, A., Layman, A., Pirahesh, H.: Data Cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-total. In: International Conference on Data Engineering (ICDE), pp. 152–159. IEEE Computer Society, Washington, DC (1996)
Grund, M., Krüger, J., Plattner, H., Zeier, A., Cudre-Mauroux, P., Madden, S.: Hyrise: a main memory hybrid storage engine. Proc. VLDB Endow 4, 105–116 (2010)
Hanusse, N., Maabout, S., Tofan, R.: A view selection algorithm with performance guarantee. In: Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT 2009, pp. 946–957. ACM, New York (2009)
Hose, K., Klan, D., Marx, M., Sattler, K.-U.: When is it time to rethink the aggregate configuration of your olap server? Proc. VLDB Endow 1, 1492–1495 (2008)
Lauer, T., Datta, A., Khadikov, Z., Anselm, C.: Exploring graphics processing units as parallel coprocessors for online aggregation. In: Proceedings of the ACM 13th International Workshop on Data Warehousing and OLAP, DOLAP 2010, pp. 77–84. ACM, New York (2010)
Morfonios, K., Ioannidis, Y.: CURE for cubes: cubing using a ROLAP engine. In: International Conference on Very Large Data Bases (VLDB), pp. 379–390. VLDB Endowment (2006)
Romero, O., Abelló, A.: On the Need of a Reference Algebra for OLAP. In: Song, I.-Y., Eder, J., Nguyen, T.M. (eds.) DaWaK 2007. LNCS, vol. 4654, pp. 99–110. Springer, Heidelberg (2007)
Stonebraker, M., Madden, S., Abadi, D.J., Harizopoulos, S., Hachem, N., Helland, P.: The end of an architectural era (it’s time for a complete rewrite). In: International conference on Very Large Data Bases (VLDB), pp. 1150–1160 (2007)
Taleb, A., Eavis, T., Tabbara, H.: The NOX OLAP Query Model: From Algebra to Execution. In: Cuzzocrea, A., Dayal, U. (eds.) DaWaK 2011. LNCS, vol. 6862, pp. 167–183. Springer, Heidelberg (2011)
Whitehorn, M., Zare, R., Pasumansky, M.: Fast Track to MDX. Springer-Verlag New York, Inc., Secaucus (2005)
Witkowski, A., Bellamkonda, S., Bozkaya, T., Dorman, G., Folkert, N., Gupta, A., Shen, L., Subramanian, S.: Spreadsheets in rdbms for olap. In: Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, SIGMOD 2003, pp. 52–63 (2003)
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Taleb, A., Eavis, T., Tabbara, H. (2013). Query Optimization for the NOX OLAP Algebra. In: Hameurlain, A., Küng, J., Wagner, R., Cuzzocrea, A., Dayal, U. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems VIII. Lecture Notes in Computer Science, vol 7790. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37574-3_3
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DOI: https://doi.org/10.1007/978-3-642-37574-3_3
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