\n","children":[{"type":"text","text":""}]},{"type":"p","children":[{"type":"text","text":"Authors: Todd J. Green, Shan Shan Huang, Boon Thau Loo, Wenchao Zhou. 2013."}]},{"type":"p","children":[{"type":"text","text":"In Foundations and Trends in Databases Vol. 5 No. 2.","italic":true}]},{"type":"p","children":[{"type":"text","text":"In recent years, we have witnessed a revival of the use of recursive queries in\na variety of emerging application domains such as data integration and exchange,\ninformation extraction, networking, and program analysis. A popular language\nused for expressing these queries is Datalog. This paper surveys for a general\naudience the Datalog language, recursive query processing, and optimization\ntechniques. This survey differs from prior surveys written in the eighties and\nnineties in its comprehensiveness of topics, its coverage of recent developments\nand applications, and its emphasis on features and techniques beyond “classical”\nDatalog which are vital for practical applications. Specifically, the topics\ncovered include the core Datalog language and various extensions, semantics,\nquery optimizations, magic-sets optimizations, incremental view maintenance,\naggregates, negation, and types. We conclude the paper with a survey of recent\nsystems and applications that use Datalog and recursive queries."}]},{"type":"p","children":[{"type":"text","text":"Read the PDF:\n"},{"type":"a","url":"https://courses.cs.washington.edu/courses/cse544/20wi/papers/datalog-NOW-2013.pdf","title":null,"children":[{"type":"text","text":"Comprehensive survey of recursive query processing and optimization techniques using Datalog"}]}]}],"_content_source":{"queryId":"src/content/resources/comprehensive-survey-of-recursive-query-processing-and-optimization-techniques-using.mdx","path":["resource","body"]}},"_content_source":{"queryId":"src/content/resources/comprehensive-survey-of-recursive-query-processing-and-optimization-techniques-using.mdx","path":["resource"]}}},"errors":null,"query":"\n query resource($relativePath: String!) {\n resource(relativePath: $relativePath) {\n ... on Document {\n _sys {\n filename\n basename\n breadcrumbs\n path\n relativePath\n extension\n }\n id\n }\n 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Comprehensive Survey of Recursive Query Processing and Optimization Techniques using Datalog · RelationalAI
Check out highlights of RelationalAI at Snowflake's Data Cloud Summit 2024!
In Foundations and Trends in Databases Vol. 5 No. 2.
In recent years, we have witnessed a revival of the use of recursive queries in
a variety of emerging application domains such as data integration and exchange,
information extraction, networking, and program analysis. A popular language
used for expressing these queries is Datalog. This paper surveys for a general
audience the Datalog language, recursive query processing, and optimization
techniques. This survey differs from prior surveys written in the eighties and
nineties in its comprehensiveness of topics, its coverage of recent developments
and applications, and its emphasis on features and techniques beyond “classical”
Datalog which are vital for practical applications. Specifically, the topics
covered include the core Datalog language and various extensions, semantics,
query optimizations, magic-sets optimizations, incremental view maintenance,
aggregates, negation, and types. We conclude the paper with a survey of recent
systems and applications that use Datalog and recursive queries.