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International Conference on Database Systems for Advanced Applications

DASFAA 2014: Database Systems for Advanced Applications pp 102–116Cite as

Leveraging Enterprise Application Characteristics to Optimize Incremental Aggregate Maintenance in a Columnar In-Memory Database

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8505))

Abstract

An analysis of database workloads generated by enterprise applications revealed a mixed workload of short-running transactional and long-running analytical queries. With the latter type of queries containing many aggregate operations, we implemented an efficient aggregate caching mechanism. But the incremental materialized view maintenance is very costly for aggregate queries joining multiple tables. To overcome this problem, we analyzed the characteristics of enterprise applications with respect to the creation of business objects and their persistence in the database layer. We evaluated how the detected patterns can be leveraged to reduce the join operations between the main and delta partitions of the involved tables in a columnar in-memory database. The resulting performance improvements are significant and close to using the caching mechanism with a denormalized schema.

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Notes

  1. 1.

    Distributed key value store focusing on scalability and high availability, http://cassandra.apache.org/.

  2. 2.

    Managed NoSQL database focusing on cost efficiency, http://aws.amazon.com/dynamodb/.

  3. 3.

    Core Data Services - Data Definition Language, a DSL to model objects on SAP HANA.

  4. 4.

    Object Relational Mapper, a framework to easy access to relational databases from object oriented programming languages.

  5. 5.

    Core Data Services - Data Manipulation Language.

  6. 6.

    Quick Patch Interconnect, a direct communication system for processor cores that replaces the Front Side Bus (FSB).

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Author information

Authors and Affiliations

  1. Hasso Plattner Institute, University of Potsdam, Potsdam, Germany

    Stephan Müller, Paul Möller & Hasso Plattner

Authors
  1. Stephan Müller
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  2. Paul Möller
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  3. Hasso Plattner
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Corresponding author

Correspondence to Stephan Müller .

Editor information

Editors and Affiliations

  1. Pohang University of Science and Technology (POSTECH), Pohang, Korea, Republic of (South Korea)

    Wook-Shin Han

  2. National University of Singapore, Singapore, Singapore

    Mong Li Lee

  3. Udayana University, Badung, Indonesia

    Agus Muliantara

  4. Udayana University, Badung, Indonesia

    Ngurah Agus Sanjaya

  5. Christian-Albrechts-Universität zu Kiel Institut für Informatik, Kiel, Germany

    Bernhard Thalheim

  6. Fudan University, Shanghai, China

    Shuigeng Zhou

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© 2014 Springer-Verlag Berlin Heidelberg

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Müller, S., Möller, P., Plattner, H. (2014). Leveraging Enterprise Application Characteristics to Optimize Incremental Aggregate Maintenance in a Columnar In-Memory Database. In: Han, WS., Lee, M., Muliantara, A., Sanjaya, N., Thalheim, B., Zhou, S. (eds) Database Systems for Advanced Applications. DASFAA 2014. Lecture Notes in Computer Science(), vol 8505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43984-5_8

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  • DOI: https://doi.org/10.1007/978-3-662-43984-5_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-43983-8

  • Online ISBN: 978-3-662-43984-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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