https://github.com/sfu-dis/pibench-online
Interactive Benchmarking of Persistent Memory Indexes
https://github.com/sfu-dis/pibench-online
benchmark indexes interactive persistent-memory pibench pm-indexes reproducibility
Last synced: 2 months ago
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Interactive Benchmarking of Persistent Memory Indexes
- Host: GitHub
- URL: https://github.com/sfu-dis/pibench-online
- Owner: sfu-dis
- License: mit
- Created: 2019-12-18T06:17:05.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2023-01-20T22:39:26.000Z (over 2 years ago)
- Last Synced: 2025-03-15T02:45:03.995Z (2 months ago)
- Topics: benchmark, indexes, interactive, persistent-memory, pibench, pm-indexes, reproducibility
- Language: Vue
- Homepage: http://pibench.org
- Size: 30.2 MB
- Stars: 16
- Watchers: 4
- Forks: 0
- Open Issues: 28
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# PiBench Online
[](https://travis-ci.org/sfu-dis/pibench-online)
## What is PiBench Online?
PiBench Online is an interactive system for benchmarking PM indexes in a fair and reproducible manner, it is based on [PiBench](https://github.com/sfu-dis/pibench), the first unified, highly customizable benchmarking framework for PM indexes.
PiBench Online enables push-button evaluation of PM indexes: the user can upload a shared library that implements the index, set parameters to run customized benchmarks, and analyze results interactively, all through an easy-to-use web interface. We hope it can promote fair comparison and reproducibility in future PM index research
Check out a demo video [here](https://www.cs.sfu.ca/~tzwang/pibench-demo-video.webm) and try it out at http://pibench.org. Use the code in this repo to deploy your own.
## Deploy your own instance
Pibench Online allows you to deploy a server instance on your own machine and connect it with the pibench online web interface (http://pibench.org).
You can either clone the code and build from source (see below), or simply use our official [docker image]().
### Docker
```bash
# 1. Pull the pibench-online image from docker hub
# 2. connect the host's port 8000 with container's port 8000
# so users can access the web api from host's 8000 port
docker run -p 127.0.0.1:8000:8000 pibench-online:latest
```
### Bare metal
```bash
cargo run --release
```
## About Us
PiBench Online is built by: [Xiangpeng Hao](https://haoxp.xyz), [Tianzheng Wang](https://www2.cs.sfu.ca/~tzwang/) (Simon Fraser University), [Lucas Lersch](https://llersch.github.io/) (TU Dresden & SAP SE) and Ismail Oukid (Snowflake Computing).
If you use PiBench Online in your work, please cite our VLDB 2020 demo paper:
````
Xiangpeng Hao, Lucas Lersch, Tianzheng Wang, Ismail Oukid:
PiBench Online: Interactive Benchmarking of Persistent Memory Indexes. PVLDB 13 (2020)
````
Our own range index evaluation using PiBench is presented in the following [VLDB 2020 paper](http://www.vldb.org/pvldb/vol13/p574-lersch.pdf):
````
Lucas Lersch, Xiangpeng Hao, Ismail Oukid, Tianzheng Wang, Thomas Willhalm:
Evaluating Persistent Memory Range Indexes. PVLDB 13(4): 574-587 (2019)
````
Request PiBench resources: [email protected]
## Contribution
### Backend
The backend server requires rust nightly, which you can install from [rustup](https://rustup.rs/)
When rust toolchain is properly setup, building pibench online is as simple as:
```bash
cargo build [--release]
```
### Frontend
The PiBench Online frontend requires nodejs and the yarn package manager.
You also need to be familiar with [Vue.js](https://vuejs.org/) and [ElementUI](https://element.eleme.io/#/en-US) as well as [Echarts.js](echartsjs.com/).
#### Project setup
```
yarn install
```
#### Compiles and hot-reloads for development
```
yarn serve
```
#### Compiles and minifies for production
```
yarn build
```