dbiir / TS-Benchmark

时序基准评测工具
GNU General Public License v3.0
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benchmark iot-device sql-query time-series

TS-Benchmark: A Benchmark for Time Series Databases

Description

This project is the source code of TS-Benchmark. Related work has been published in ICDE 2021. bibTex:

@inproceedings{DBLP:conf/icde/HaoQCLSTZD21,
  author    = {Yuanzhe Hao and
               Xiongpai Qin and
               Yueguo Chen and
               Yaru Li and
               Xiaoguang Sun and
               Yu Tao and
               Xiao Zhang and
               Xiaoyong Du},
  title     = {TS-Benchmark: {A} Benchmark for Time Series Databases},
  booktitle = {37th {IEEE} International Conference on Data Engineering, {ICDE} 2021,
               Chania, Greece, April 19-22, 2021},
  pages     = {588--599},
  publisher = {{IEEE}},
  year      = {2021},
  url       = {https://doi.org/10.1109/ICDE51399.2021.00057},
  doi       = {10.1109/ICDE51399.2021.00057},
  timestamp = {Mon, 28 Jun 2021 10:16:44 +0200},
  biburl    = {https://dblp.org/rec/conf/icde/HaoQCLSTZD21.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Start

The general steps to complete the test are:

  1. Data generation cd data_generation

  2. Train DCGAN model python DCGAN.py Run the encoder_dc.py file to train the encoder, python encoder_dc.py Finally execute the test python test_dc.py

  3. Data Import Since each database have different build-in tools for data import, we have defined some tools related to data import in the tsdb-test/data/load directory

  4. build project cd Tsdb-benchmark/ts-benchmark/ sh build.sh

  5. config parametes of database and run the benchmark cd Tsdb-benchmark/ts-benchmark/ vim run.sh (choose database and test mode) sh run.sh

Params description

The configuration of TSDBs is shown as follows:

More

If you have interests in the directed graph construction and the generation via random walk. you can ref to the random_walk.ipynb Quick Open It!

More information please ref to for detail