Technical Perspective for: MATLANG: Matrix Operations and Their Expressive Power

Dan Suciu
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Abstract

The main processing paradigm in data management is bulk processing. As introduced by Codd in the early 70's, under this paradigm relations are processed in bulk, one operator at a time. When applied to relations, this paradigm leads to relational algebra, and its variants, relational calculus, and SQL. Over the years, data management was faced with the challenge of extending bulk processing operators to new kinds of data, and/or new kinds of queries: nested relations, semistructured data, recursive queries. Each such extension requires significant systems development, which should be accompanied, in fact preceded, by a careful study of the expressive power of the new language. Is it as expressive, more expressive, or less expressive than relational algebra? The answer to this question has profound implications on the ability of data processing engines to optimize, compute, distribute, reuse queries in that language. For example, extending relational algebra with nested relations does not increase its expressive power, while extending it with fixpoint does, explaining why modern query engines have an easier time supporting JSON than recursion.
MATLANG:矩阵运算及其表达能力的技术视角
数据管理中的主要处理范式是批量处理。正如Codd在70年代早期所介绍的那样,在这种范式下,关系被批量处理,一次处理一个操作符。当应用于关系时,这种范式导致关系代数及其变体、关系演算和SQL。多年来,数据管理面临着将批量处理操作符扩展到新类型数据和/或新类型查询的挑战:嵌套关系、半结构化数据、递归查询。每一个这样的扩展都需要重要的系统开发,这应该伴随着对新语言的表达能力的仔细研究,实际上在此之前。它是和关系代数一样有表现力,更有表现力,还是不如关系代数有表现力?这个问题的答案对数据处理引擎在该语言中优化、计算、分发和重用查询的能力有着深远的影响。例如,用嵌套关系扩展关系代数并不能提高它的表达能力,而用定点扩展却可以,这就解释了为什么现代查询引擎支持JSON比支持递归更容易。
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