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.

中文翻译：

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构建您自己的 SQL-on-Hadoop 查询引擎

这是关于 2018 年夏季学期在 OTH Regensburg 教授的一门课程的报告。本课程中的学生在短短 8 周内将自己的 SQL-on-Hadoop 引擎构建为学期项目。miniHive 是用 Python 编写的，并将 SQL 查询编译到 MapReduce 工作流中。然后这些在 Hadoop 上执行。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 Map-Reduce 特定的优化。该课程采用英语授课，采用翻转课堂模式。课程资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，并简要回顾了最成功的学生项目。