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| author | Quentin Dufour <quentin@deuxfleurs.fr> | 2022-09-28 14:59:18 +0200 |
|---|---|---|
| committer | Quentin Dufour <quentin@deuxfleurs.fr> | 2022-09-28 14:59:18 +0200 |
| commit | 1ae69c8e2acef38307d6c562efb8b0d659142b42 (patch) | |
| tree | 2c8eebd47716dda13e5525283c40f75882b79937 /artifacts/2022-09-24-s3billion/plot.R | |
| parent | 7011ec431f021a0e1800ad37e738dd43af0b54a6 (diff) | |
| download | mknet-1ae69c8e2acef38307d6c562efb8b0d659142b42.tar.gz mknet-1ae69c8e2acef38307d6c562efb8b0d659142b42.zip | |
To fit or not to fit
Diffstat (limited to 'artifacts/2022-09-24-s3billion/plot.R')
| -rw-r--r-- | artifacts/2022-09-24-s3billion/plot.R | 18 |
1 files changed, 16 insertions, 2 deletions
diff --git a/artifacts/2022-09-24-s3billion/plot.R b/artifacts/2022-09-24-s3billion/plot.R index 2baf70d..bf8b29c 100644 --- a/artifacts/2022-09-24-s3billion/plot.R +++ b/artifacts/2022-09-24-s3billion/plot.R @@ -1,12 +1,25 @@ library(tidyverse) +library(ggpmisc) -read_csv("garage-v0.8-beta2-lmdb.csv") %>% mutate(batch_dur_sec = batch_dur_nanoseconds / 1000 / 1000 / 1000 ) -> s +read_csv("garage-v0.8-beta2-lmdb.csv") %>% mutate(batch_dur_sec = batch_dur_nanoseconds / 1000 / 1000 / 1000) %>% filter(total_objects != 0) -> s + +reg1 <- lm(s$batch_dur_sec~s$total_objects) +reg2 <- lm(s$batch_dur_sec ~ log(s$total_objects)) + +f1 <- y~log(x) +f2 <- y~x + ggplot(s, aes(x=total_objects, y=batch_dur_sec)) + geom_point() + - geom_smooth(method = "gam", se = FALSE) + + #geom_smooth(method="lm",formula=f1, se = FALSE, color="red") + + #geom_smooth(method="lm",formula=f2, se = FALSE, color="blue") + + #stat_poly_eq(formula = f1, label.y = 0.9, color = "red", aes(label=paste(..eq.label..,..rr.label..,..adj.rr.label..,..AIC.label..,..BIC.label.., sep = "~~~"))) + + #stat_poly_eq(formula = f2, label.y = 0.8, color="blue",aes(label=paste(..eq.label..,..rr.label..,..adj.rr.label..,..AIC.label..,..BIC.label.., sep = "~~~"))) + + #geom_smooth(method = "gam", se = FALSE) + scale_x_continuous(expand=c(0,0), breaks = scales::pretty_breaks(n = 10))+ scale_y_continuous(expand=c(0,0), breaks = scales::pretty_breaks(n = 10))+ + coord_cartesian(ylim=c(0,60)) + labs( y="Time (in sec) spent sending a batch (8192 objects)", x="Total number of objects stored in the cluster", @@ -15,6 +28,7 @@ ggplot(s, aes(x=total_objects, y=batch_dur_sec)) + subtitle="Daemon: Garage v0.8 beta 2 with LMDB as db_engine\nBenchmark: 128 batch. 8192 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("./garage.png", width=200, height=120, units="mm") +#ggsave("./garage-regression.png", width=200, height=120, units="mm") |