Skip to main content

Query Processing of Pre-partitioned Data Using Sandwich Operators

  • Conference paper
Enabling Real-Time Business Intelligence (BIRTE 2012)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 154))

Abstract

In this paper we present the “Sandwich Operators”, an elegant approach to exploit pre-sorting or pre-grouping from clustered storage schemes in operators such as Aggregation/Grouping, HashJoin, and Sort of a database management system. Thereby, each of these operator types is “sandwiched” by two new operators, namely PartitionSplit and PartitionRestart. PartitionSplit splits the input relation into its smaller independent groups on which the sandwiched operator is executed. After a group is processed, PartitionRestart is used to trigger the execution on the following group. Executing each of these operator types with the help of the Sandwich Operators introduces minimal overhead and does not penalize performance of the sandwiched operator, as its implementation remains unchanged. On the contrary, we show that sandwiched execution of each operator results in lower memory consumption and faster execution time. PartitionSplit and PartitionRestart replace special implementations of partitioned versions of these operators. For many groups Sandwich Operators turn blocking operators into pseudo streaming operators, resulting in faster response time for the first query results.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bhattacharjee, B., Padmanabhan, S., Malkemus, T., Lai, T., Cranston, L., Huras, M.: Efficient query processing for multi-dimensionally clustered tables in DB2. In: VLDB (2003)

    Google Scholar 

  2. Chen, W.-J., Fisher, A., Lalla, A., McLauchlan, A., Agnew, D.: Database Partitioning, Table Partitioning, and MDC for DB2 9. IBM Redbooks (2007)

    Google Scholar 

  3. Graefe, G.: Partitioned b-trees - a user’s guide. In: BTW, pp. 668–671 (2003)

    Google Scholar 

  4. Herodotou, H., Borisov, N., Babu, S.: Query Optimization Techniques for Partitioned Tables. In: SIGMOD (2011)

    Google Scholar 

  5. Inkster, D., Boncz, P., Zukowski, M.: Integration of VectorWise with Ingres. SIGMOD Record 40(3) (2011)

    Google Scholar 

  6. Leslie, H., Jain, R., Birdsall, D., Yaghmai, H.: Efficient Search of Multi-Dimensional B-Trees. In: VLDB (1995)

    Google Scholar 

  7. Manegold, S., Boncz, P., Kersten, M.: Generic Database Cost Models for Hierarchical Memory. In: VLDB (2002)

    Google Scholar 

  8. Markl, V.: MISTRAL: Processing Relational Queries using a Multidimensional Access Technique. Institut für Informatik der TU München (1999)

    Google Scholar 

  9. Morales, T.: Oracle Database VLDB and Partitioning Guide, 11g Release 1 (11.1). Oracle (July 2007)

    Google Scholar 

  10. O’Neil, P., O’Neil, E., Chen, X., Revilak, S.: The star schema benchmark and augmented fact table indexing. In: Nambiar, R., Poess, M. (eds.) TPCTC 2009. LNCS, vol. 5895, pp. 237–252. Springer, Heidelberg (2009)

    Google Scholar 

  11. Padmanabhan, S., Bhattacharjee, B., Malkemus, T., Cranston, L., Huras, M.: Multi-dimensional Clustering: A New Data Layout Scheme in DB2. In: SIGMOD (2003)

    Google Scholar 

  12. Polyzotis, N.: Selectivity-based Partitioning: A Divide-and-Union Paradigm for Effective Query Optimization. In: CIKM (2005)

    Google Scholar 

  13. Selinger, P., Astrahan, M., Chamberlin, D., Lorie, R., Price, T.: Access Path Selection in a Relational Database Management System. In: SIGMOD (1976)

    Google Scholar 

  14. Stonebraker, M., et al.: C-Store: A Column-Oriented DBMS. In: VLDB (2005)

    Google Scholar 

  15. Talmage, R.: Partitioned Table and Index Strategies Using SQL Server 2008. MSDN Library (March 2009)

    Google Scholar 

  16. Wang, X., Cherniack, M.: Avoiding Sorting and Grouping in Processing Queries. In: VLDB (2003)

    Google Scholar 

  17. Zukowski, M., Boncz, P.A., Nes, N.J., Héman, S.: MonetDB/X100 - A DBMS In The CPU Cache. IEEE Data Eng. Bull. 28(2), 17–22 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Baumann, S., Boncz, P., Sattler, KU. (2013). Query Processing of Pre-partitioned Data Using Sandwich Operators. In: Castellanos, M., Dayal, U., Rundensteiner, E.A. (eds) Enabling Real-Time Business Intelligence. BIRTE 2012. Lecture Notes in Business Information Processing, vol 154. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39872-8_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-39872-8_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39871-1

  • Online ISBN: 978-3-642-39872-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics