Merge pull request 'Fix venv sourcing' (#2) from baptiste/mknet:misc_fixes into main

Reviewed-on: Deuxfleurs/mknet#2

README.md

@@ -49,6 +49,7 @@ 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

@@ -0,0 +1,27 @@
+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("""
-source .venv/bin/activate
+. .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()}
-> source ./.venv/bin/activate
+> . ./.venv/bin/activate
 > ./mknet scenario ./topo/with-vdsl.yml ./scenarios/garage-s3lat garage-v0.8
 """)