README.md

@@ -49,7 +49,6 @@ All scenarios:
  - `./scenarios/garage-s3lat [garage-v0.7|garage-v0.8]` - Run s3lat on Garage
  - `./scenarios/garage-concurrent [garage-v0.7|garage-v0.8]` - Run s3concurrent on Garage
  - `./scenarios/garage-warp [garage-v0.7|garage-v0.8] [default|fast]` - Run warp on Garage. 2 flavors are available: fast and default.
- - `./scenarios/garage-s3billion [garage-v0.7|garage-v0.8]` - Run s3billion on Garage
 
 *Scenarios take optional flavors as input that modulate their behavioir. Passing them is not mandatory,
 a default one will be selected for you.*

artifacts/2022-09-29-s3billion/plot.R

@@ -1,27 +0,0 @@
-library(tidyverse)
-library(ggpmisc)
-library(scales)
-
-
-read_csv("s3billion-dc-gros-32threads-256batchsize-128000batchcount-v0.8-fix-time-30M.csv") %>% mutate(batch_dur_sec = batch_dur_nanoseconds / 1000 / 1000 / 1000) %>% filter(total_objects != 0) -> s
-
-reg <- lm(s$batch_dur_sec~s$total_objects)
-
-f <- y~x
-
-ggplot(s, aes(x=total_objects, y=batch_dur_sec)) +
-  geom_point(shape = "bullet", alpha=0.4) +
-  geom_smooth(method="lm", formula=f, se = FALSE, color="blue") + 
-  scale_x_continuous(expand=c(0,0), breaks = scales::pretty_breaks(n = 10), labels = unit_format(unit = "M", scale = 1e-6)) +
-  scale_y_continuous(expand=c(0,0), breaks = scales::pretty_breaks(n = 10)) +
-  coord_cartesian(ylim=c(0,3)) +
-  labs(
-    y="Time (in sec) spent sending a batch (8192 objects)",
-    x="Total number of objects stored in the cluster",
-    caption="Get the code to reproduce this graph at https://git.deuxfleurs.fr/Deuxfleurs/mknet",
-    title="Storing 30M small objects in Garage!",
-    subtitle="Daemon: Garage v0.8.0-rc1 (+ #398 pull request) with LMDB as db_engine\nBenchmark: 8192 objects/batch. 32 threads/batch. 256 objects/thread. 16-byte/objects.\nEnvironment: mknet on Grid'5000 (gros) https://www.grid5000.fr/w/Nancy:Hardware#gros (SATA SSD).\nDC topo (3 logical nodes, 1Gb/s, 1ms latency).") +
-  theme_classic()
-ggsave("./garage-0.8-gros.png", width=200, height=120, units="mm")
-#ggsave("./garage-regression.png", width=200, height=120, units="mm")
-

prepare.py

@@ -23,7 +23,7 @@ os.chdir(me)
 print("--- install python dependencies ---")
 venv.create(".venv", with_pip=True)
 shared.exec("""
-. .venv/bin/activate
+source .venv/bin/activate
 which python3
 python3 -m pip install .
 python3 -m pip install -r scenarios/requirements.txt
@@ -36,6 +36,6 @@ flavor.download()
 print(f"""done! now, run:
 > sudo -i
 > cd {os.getcwd()}
-> . ./.venv/bin/activate
+> source ./.venv/bin/activate
 > ./mknet scenario ./topo/with-vdsl.yml ./scenarios/garage-s3lat garage-v0.8
 """)