AlphaSQL: Open Source Software Tool for Automatic Dependency Resolution, Parallelization and Validation for SQL and Data

Masahiro Matsui, Takuto Sugisaki, Kensaku Okada, N. Koshizuka
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引用次数: 1

Abstract

Improved performance of database systems has enabled faster SQL querying and more complex data processing. However, as the data becomes more complex and larger, SQL data processing becomes more difficult and costly. Typical problems include changing SQL queries and data schema resolution in complex dependencies by hand. In addition, human errors can lead to complex cyclic dependency problems. To mitigate these problems, we developed AlphaSQL: an open-source software tool for SQL data processing. AlphaSQL mainly supports three techniques to automate data preparation by SQL: (1) extracting a directed acyclic graph (DAG) based on dependencies between SQL and data, (2) validating the schema included in the whole DAG, and (3) parallelizing the queries based on the DAG. We applied AlphaSQL to a real-world data analysis and machine learning project where we analyzed 1445 logs obtained from static validation for git commits and 3243 execution logs. Our analysis showed that AlphaSQL detected various errors with high precision and recall, part of which existing tools could not catch (e.g., missing resources and schema mismatches). AlphaSQL would enable more maintainable data management using SQL.
AlphaSQL:用于SQL和数据的自动依赖解析、并行化和验证的开源软件工具
数据库系统性能的改进使SQL查询更快,数据处理更复杂。然而,随着数据变得越来越复杂和庞大,SQL数据处理变得越来越困难和昂贵。典型的问题包括手动更改复杂依赖项中的SQL查询和数据模式解析。此外,人为错误可能导致复杂的循环依赖问题。为了缓解这些问题,我们开发了AlphaSQL:一个用于SQL数据处理的开源软件工具。AlphaSQL主要支持三种SQL自动化数据准备技术:(1)基于SQL和数据之间的依赖关系提取有向无环图(DAG),(2)验证整个DAG中包含的模式,(3)基于DAG并行化查询。我们将AlphaSQL应用到一个真实的数据分析和机器学习项目中,分析了从git提交的静态验证中获得的1445条日志和3243条执行日志。我们的分析表明,AlphaSQL以很高的准确率和召回率检测各种错误,其中一部分是现有工具无法捕获的(例如,缺少资源和模式不匹配)。AlphaSQL将支持使用SQL进行更可维护的数据管理。
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