Build your own SQL-on-Hadoop Query Engine: A Report on a Term Project in a Master-level Database Course

Stefanie Scherzinger
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引用次数: 2

Abstract

This is a report on a course taught at OTH Regensburg in the summer term of 2018. The students in this course built their own SQL-on-Hadoop engine as a term project in just 8 weeks. miniHive is written in Python and compiles SQL queries into MapReduce workflows. These are then executed on Hadoop. miniHive performs generic query optimizations (selection and projection pushdown, or cost-based join reordering), as well as Map- Reduce-specific optimizations. The course was taught in English, using a flipped classroom model. The course material was mainly compiled from third-party teaching videos. This report describes the course setup, the miniHive milestones, and gives a short review of the most successful student projects.
构建自己的SQL-on-Hadoop查询引擎:硕士级数据库课程的学期项目报告
这是一份关于2018年夏季学期在OTH Regensburg教授的课程的报告。本课程的学生在短短8周内构建了自己的SQL-on-Hadoop引擎作为学期项目。miniHive是用Python编写的,它将SQL查询编译成MapReduce工作流。然后在Hadoop上执行这些操作。miniHive执行通用查询优化(选择和投影下推,或基于成本的连接重新排序),以及特定于Map- reduce的优化。该课程以英语授课,采用翻转课堂模式。课程材料主要来自第三方教学视频。本报告描述了课程设置,miniHive里程碑,并给出了最成功的学生项目的简短回顾。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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