LMDB s3 million objects

3 files changed, 143 insertions, 0 deletions

diff --git a/artifacts/2022-09-14-s3billion/garage-v0.8-beta2-lmdb.csv b/artifacts/2022-09-14-s3billion/garage-v0.8-beta2-lmdb.csv
new file mode 100644
index 0000000..66552f2
--- /dev/null
+++ b/artifacts/2022-09-14-s3billion/garage-v0.8-beta2-lmdb.csv
@@ -0,0 +1,129 @@
+total_objects,batch_dur_nanoseconds
+0,2018191689
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diff --git a/artifacts/2022-09-14-s3billion/plot.R b/artifacts/2022-09-14-s3billion/plot.R
new file mode 100644
index 0000000..6929a6e
--- /dev/null
+++ b/artifacts/2022-09-14-s3billion/plot.R
@@ -0,0 +1,14 @@
+library(tidyverse)
+read_csv("garage-v0.8-beta2-lmdb.csv") %>% mutate(batch_dur_sec = batch_dur_nanoseconds / 1000 / 1000 / 1000 ) -> s
+
+ggplot(s, aes(x=total_objects, y=batch_dur_sec)) +
+  geom_point() +
+  geom_smooth(method = "gam", se = FALSE) + 
+  labs(
+    y="Time 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 1M+ files on Garage! Impact of existing data on cluster interactiveness",
+    subtitle="Daemon: Garage v0.8 beta 2 with LMDB as db_engine\nBenchmark: 128 batch. 192 objects/batch. 32 threads/batch. 256 objects/thread. 16-byte/objects.\nEnvironment: mknet (Ryzen 5 1400, 16GB RAM, SSD). DC topo (3 nodes, 1Gb/s, 1ms latency).") +
+  theme_classic()
+ggsave("./plot.png", width=200, height=120, units="mm")
diff --git a/artifacts/2022-09-14-s3billion/plot.png b/artifacts/2022-09-14-s3billion/plot.png
new file mode 100644
index 0000000..5c55897
--- /dev/null
+++ b/artifacts/2022-09-14-s3billion/plot.png