SQL查询中用户定义函数的高效执行

IF 2.6 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Yannis Foufoulas, Alkis Simitsis
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引用次数: 0

摘要

用户定义函数(udf)已被广泛用于克服SQL的表达性限制,并用函数功能补充其声明性。udf在当今涉及复杂数据分析和机器学习算法和逻辑的应用程序中特别有用。然而,UDF在查询处理和优化方面带来了重大的性能挑战,这主要是由于UDF执行和SQL处理环境的不匹配。在本教程中,我们将介绍在SQL查询中高效执行udf的最新方法和系统。我们专注于物理优化和UDF查询编译的底层技术,描述和比较该领域的核心和最新方法,讨论它们的优势和局限性,确定理论和实践中的关键差距,并提出有希望的未来研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Execution of User-Defined Functions in SQL Queries
User-defined functions (UDFs) have been widely used to overcome the expressivity limitations of SQL and complement its declarative nature with functional capabilities. UDFs are particularly useful in today's applications that involve complex data analytics and machine learning algorithms and logic. However, UDFs pose significant performance challenges in query processing and optimization, largely due to the mismatch of the UDF execution and SQL processing environments. In this tutorial, we present state-of-the-art methods and systems towards efficient execution of UDFs in SQL queries. We focus on low-level techniques for physical optimization and compilation of UDF queries, describe and compare the core, recent approaches in the area, discuss their advantages and limitations, identify critical gaps in theory and practice, and propose promising future research directions.
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来源期刊
Proceedings of the Vldb Endowment
Proceedings of the Vldb Endowment Computer Science-General Computer Science
CiteScore
7.70
自引率
0.00%
发文量
95
期刊介绍: The Proceedings of the VLDB (PVLDB) welcomes original research papers on a broad range of research topics related to all aspects of data management, where systems issues play a significant role, such as data management system technology and information management infrastructures, including their very large scale of experimentation, novel architectures, and demanding applications as well as their underpinning theory. The scope of a submission for PVLDB is also described by the subject areas given below. Moreover, the scope of PVLDB is restricted to scientific areas that are covered by the combined expertise on the submission’s topic of the journal’s editorial board. Finally, the submission’s contributions should build on work already published in data management outlets, e.g., PVLDB, VLDBJ, ACM SIGMOD, IEEE ICDE, EDBT, ACM TODS, IEEE TKDE, and go beyond a syntactic citation.
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