50 lines
1.4 KiB
Markdown
50 lines
1.4 KiB
Markdown
# benchmarks
|
|
|
|
## `rpc-amplification.R`
|
|
|
|
This benchmark tests how RPC between nodes having
|
|
non negligible latency will impact the final S3 request latency.
|
|
|
|
The idea is that multiple communications must be done over the network
|
|
between nodes of the cluster to answer an S3 request, and some of them
|
|
are even sequentials. Depending of the chosen algorithms and implementations,
|
|
the final S3 request latency will vary.
|
|
|
|
You need to install first R, R development headers, python3, pip3, wget, iproute2 and maybe some other dependencies.
|
|
Then run:
|
|
|
|
```
|
|
sudo ./rpc-amplification.R
|
|
```
|
|
|
|
you can test a different topology with:
|
|
|
|
```
|
|
MKNET_DC=./mknet/with-vdsl.yml sudo ./rpc-amplification.R
|
|
```
|
|
|
|
|
|
|
|
*This benchmark should be fully automated.*
|
|
|
|
## `rpc-complexity.R`
|
|
|
|
This benchmark validates that the time to complete RPC for a
|
|
given S3 request is stable when the number of node change.
|
|
This is not always the case: some distributed protocols send a quadratic number
|
|
of messages according to the number of nodes.
|
|
|
|
You need an access to [Grid5000](https://grid5000.fr).
|
|
Then import `jupyter/rpc-complexity.ipynb` in a [Grid5000 Jupyter Notebook](https://intranet.grid5000.fr/).
|
|
|
|
Download all the `.csv` files in this `csv/` folder.
|
|
And finally run:
|
|
|
|
```
|
|
./rpc-complexity.R
|
|
```
|
|
|
|
|
|
|
|
*This benchmark is not fully automated.*
|