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    Advances In SQL Execution Techniques Based On Query Compilation[J]. Journal of Computer Research and Development. DOI: 10.7544/issn1000-1239.202330507
    Citation: Advances In SQL Execution Techniques Based On Query Compilation[J]. Journal of Computer Research and Development. DOI: 10.7544/issn1000-1239.202330507

    Advances In SQL Execution Techniques Based On Query Compilation

    • Information systems usually use data management systems to manage data, among which SQL has been the mainstream query language for data management because of its ease of use and flexibility, users can write SQL statements and submit them to the data management system to get query results. The efficiency of the execution model determines whether the system can quickly respond to user queries. The existing execution models mainly adopts interpreted execution and compiled execution. Interpreted execution is used by most systems due to its scalability and maintainability. Unlike interpreted execution, compiled execution generates efficient custom code to speed up queries that should have been processed by interpreted execution, the significant performance gains have attracted a number of database systems to implement the technology. However, generating the corresponding custom code for a query is a complex process that requires a number of considerations, even in some cases, the performance of using compiled execution may not be as good as the traditional volcano model. This paper provides a systematic review of the progress of compiled execution techniques from conceptual and technical perspectives. Firstly, this paper outlines the basic concepts of query compilation and introduces the relevant terminology and background knowledge. Secondly, this paper introduces the relevant techniques from three perspectives: intermediate code generation, intermediate representation, machine code generation and running. Finally, this paper looks at the future development direction of compiled execution technology in the context of current research trends in data management systems and recent research works.
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