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Recursive Computation Over Relational Data (RECORD)

Recursive Computation Over Relational Data (RECORD)
关系数据的递归计算 (RECORD)
批准号:
511062611
负责人:
Professor Dr. Torsten Grust
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:

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中文摘要
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英文摘要
Move your computation close to the data! This age-old mantra of the database community asserts that we can expect a SQL query engine with immediate access to the data to perform significantly better than an external processor to which we have to ship the data first. The lore holds up if the computation is query-like and primarily involves filtering, data (re-)combination, grouping, or aggregation. It is much less clear how complex algorithms that rely on arbitrary iterative control flow or recursion can be efficiently evaluated inside the same SQL engines. With the advent of SQL:1999, contemporary database engines started to support forms of recursion. The associated language constructs, however, exhibit syntactic restrictions, are based on semantics that are tough to grasp for regular developers, or exhibit sobering runtime performance that often render iterative or recursive SQL impractical. Project RECORD explores compilation and implementation techniques that (1) admit the formulation of iterative and recursive algorithms in a readable, concise (even elegant) fashion and (2) use relational database systems as efficient and scalable runtime environments that perform the computation right next to the data. We adopt established techniques originally developed by the (functional) programming language community, then adapt and bend these ideas so that they apply to recursive SQL functions as well as iterative PL/SQL procedures written in an imperative style. Our focus is on non-invasive approaches that do not turn existing database technology on its head: we thus map functions and procedures to the native, plain SQL recursion constructs already built into off-the-shelf database systems. We take the freedom, however, to apply surgical changes to database kernels where we anticipate that the runtime performance or the systems' space usage can benefit. There is no shortage of data-intensive problem domains whose need for such in-database computation only ever goes up. RECORD will study the core data structures and algorithms of these domains to test-drive its results and to prove that recursive computation over relational data can indeed be practical and efficient.
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Fine-grained Data Provenance for Very Expressive Queries
  • 批准号:
    398800066
  • 项目类别:
    Research Grants
  • 资助金额:
    $0.0万
  • 财政年份:
    2018
  • 负责人:
    Professor Dr. Torsten Grust
  • 依托单位:
ALIEN: Abstractions, Languages, and Implementation Techniques That Cross the Program/Query Divide
  • 批准号:
    282458149
  • 项目类别:
    Research Grants
  • 资助金额:
    $0.0万
  • 财政年份:
    2016
  • 负责人:
    Professor Dr. Torsten Grust
  • 依托单位:
DatabaseSupported Program Execution
  • 批准号:
    161858209
  • 项目类别:
    Research Grants
  • 资助金额:
    $0.0万
  • 财政年份:
    2010
  • 负责人:
    Professor Dr. Torsten Grust
  • 依托单位:
Relationale Datenbanksysteme als hocheffiziente XQuery-Prozessoren: Compilationstechniken und Laufzeitsysteme
  • 批准号:
    27645166
  • 项目类别:
    Research Grants
  • 资助金额:
    $0.0万
  • 财政年份:
    2006
  • 负责人:
    Professor Dr. Torsten Grust
  • 依托单位:
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  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
    2022
  • 负责人:
    李嘉琛
  • 依托单位:
基于g-computation控制纵向数据未测混杂因素的因果推断模型构建及应用研究
  • 批准号:
    81903416
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    19.0万元
  • 批准年份:
    2019
  • 负责人:
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