Efficiently compiling efficient query plans for Modern Hardware

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Abstract

As main memory grows, query performance is more and more determined by the raw CPU costs of query processing itself. The classical iterator style query processing technique is very simple and exible, but shows poor performance on modern CPUs due to lack of locality and frequent instruction mis- predictions. Several techniques like batch oriented processing or vectorized tuple processing have been proposed in the past to improve this situation, but even these techniques are frequently out-performed by hand-written execution plans. In this work we present a novel compilation strategy that translates a query into compact and effcient machine code using the LLVM compiler framework. By aiming at good code and data locality and predictable branch layout the resulting code frequently rivals the performance of hand- written C++ code. We integrated these techniques into the HyPer main memory database system and show that this results in excellent query performance while requiring only modest compilation time.

Original languageEnglish
Pages (from-to)539-550
Number of pages12
JournalProceedings of the VLDB Endowment
Volume4
Issue number9
DOIs
StatePublished - Jun 2011

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