This is the material for a term project part of a database systems 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 (e.g. on Cloudera'QuickStarts VM). miniHive performs generic query optimizations (selection and projection pushdown, or cost-based join reordering), as well as MapReduce-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 repository contains a report on this course, as well as the material made available to the students for implementing miniHive milestones.

For questions on miniHive, contact stefanie.scherzinger@uni-passau.de.

To refer to this material in a publication, please use this BibTeX entry:

@article{miniHive,
  author    = {Stefanie Scherzinger},
  title     = {Build your own SQL-on-Hadoop Query Engine: {A} Report on a Term Project
               in a Master-level Database Course},
  journal   = {{SIGMOD} Rec.},
  volume    = {48},
  number    = {2},
  pages     = {33--38},
  year      = {2019},
  note      = {Supplementary material available at \url{https://github.com/miniHive/assignment}.},
  url       = {https://doi.org/10.1145/3377330.3377336},
  doi       = {10.1145/3377330.3377336},
}

This work is licensed under the Apache 2.0 License.