Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
-
○Academic publication links
-
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (7.3%) to scientific vocabulary
Last synced: 10 months ago
·
JSON representation
·
Repository
IT3010 V22 - Group 2
Basic Info
- Host: GitHub
- Owner: LarsV123
- Language: Python
- Default Branch: master
- Size: 62.5 KB
Statistics
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 4 years ago
· Last pushed about 4 years ago
Metadata Files
Readme
Citation
README.md
Insertion speed of indexed spatial data
This Github repository holds the code used by group 2 in the course IT3010 in 2022. This was used to generate data for our paper, the full title of which is:
Insertion speed of indexed spatial data: comparing MySQL, PostgreSQL and MongoDB
Contributors
- Lars-Olav Vågene
- Ingvild Løver Thon
- Eirik Schøien
- Christian Axell
- Lukas Tveiten
Setup
Prerequisites:
- Python
- Docker
Steps:
- Make a copy of the
.env-templatefile and rename it.env - Download the dataset from https://www.microsoft.com/en-us/research/publication/geolife-gps-trajectory-dataset-user-guide/ and place the user folders (000-181) in the folder
./data
Experiment
To run the experiments with the CLI:
```bash
Start Docker containers for all DBMSs
docker-compose --compatibility up
Drop and create SQLite tables for storing experimental results
py cli.py prepare
Run experiment with desired iterations and total size
py cli.py run -i 3 -n 5000 ```
The results are stored in a SQLite database, which can be easily accessed with Python or a GUI tool like DB Browser.
Owner
- Login: LarsV123
- Kind: user
- Repositories: 3
- Profile: https://github.com/LarsV123
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: >-
Insertion speed of indexed spatial data: comparing
MySQL, PostgreSQL and MongoDB
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Lars-Olav
family-names: Vågene
email: larsolov@stud.ntnu.no
- given-names: Eirik
family-names: Schøien
email: eirischo@stud.ntnu.no
- given-names: Christian
family-names: Axell
email: cdaxell@stud.ntnu.no
- given-names: Ingvild
family-names: Løver Thon
email: ingvlt@stud.ntnu.no
- given-names: Lukas
family-names: Tveiten
email: lukasnt@stud.ntnu.no
GitHub Events
Total
Last Year
Dependencies
requirements.txt
pypi
- Pygments ==2.11.2
- black ==22.1.0
- cffi ==1.15.0
- click ==8.0.4
- colorama ==0.4.4
- commonmark ==0.9.1
- cryptography ==36.0.1
- mypy-extensions ==0.4.3
- mysql-connector-python ==8.0.28
- pathspec ==0.9.0
- platformdirs ==2.5.1
- protobuf ==3.19.4
- psycopg2-binary ==2.9.3
- pycparser ==2.21
- pymongo ==4.0.2
- python-dotenv ==0.19.2
- rich ==11.2.0
- snakeviz ==2.1.1
- tabulate ==0.8.9
- tomli ==2.0.1
- tornado ==6.1
- tqdm ==4.63.0