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A Study of Partitioning and Parallel UDF Execution with the SAP HANA Database

Large-scale data analysis relies on custom code both for preparing the data for analysis as well as for the core analysis algorithms. The map-reduce framework offers a simple model to parallelize custom code, but it does not integrate well with relational databases. Likewise, the literature on optimizing queries in relational databases has largely ignored user-defined functions (UDFs). In this paper, we discuss annotations for user-defined functions that facilitate optimizations that both consider relational operators and UDFs. We believe this to be the superior approach compared to just linking map-reduce evaluation to a relational database because it enables a broader range of optimizations. In this paper we focus on optimizations that enable the parallel execution of relational operators and UDFs for a number of typical patterns. A study on real-world data investigates the opportunities for parallelization of complex data flows containing both relational operators and UDFs.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:28103
Date08 July 2014
CreatorsGroße, Philipp, May, Norman, Lehner, Wolfgang
PublisherTechnische Universität Dresden
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typedoc-type:workingPaper, info:eu-repo/semantics/workingPaper, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess
Relationurn:nbn:de:bsz:14-qucosa-79344, qucosa:24841

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