146 lines
5.2 KiB
R
146 lines
5.2 KiB
R
library(ggplot2)
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library(sqldf)
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library(plyr)
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library(cowplot)
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thunder_ms <- read.csv("thunder_configure_15.csv")
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thunder_ms <- sqldf("select run,ident,jmax,links,latency, CAST(latency as real) / 1000. as lat_ms from thunder_ms")
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thunder_ms$links <- as.factor(thunder_ms$links)
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thunder_ms$jmax <- as.factor(thunder_ms$jmax)
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v1 <- ggplot(data = thunder_ms, aes(x = jmax, y=lat_ms, fill=links)) +
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geom_violin() +
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geom_hline(yintercept=800, color = "red", linetype="dashed") +
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geom_hline(yintercept=400, color = "DarkGreen") +
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annotate("text", x=6, y=550, label= "high", color="DarkGreen") +
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annotate("text", x=5.7, y=1000, label= "acceptable", color="red") +
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coord_cartesian(xlim = c(1, 6)) +
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scale_fill_grey() +
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#scale_y_log10() +
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ylab("latency (ms)") +
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xlab("max allowed jitter") +
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theme_classic()
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#v1 + ggsave("thunder_configure_ms.png", dpi=300, dev='png', height=5, width=15, units="cm")
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thunder_rcv <- sqldf("select run,jmax,links,(9900-COUNT(latency)*1.0)/9900 as dlv from thunder_ms group by jmax,links,run")
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thunder_rcv$jmax <- as.factor(thunder_rcv$jmax)
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thunder_rcv$links <- as.factor(thunder_rcv$links)
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v2 <- ggplot(data = thunder_rcv, aes(x = jmax, y=dlv, fill=links)) +
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geom_boxplot() +
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scale_y_continuous(labels = scales::percent) +
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scale_fill_grey() +
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ylab("dropped packets") +
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xlab("max allowed jitter") +
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theme_classic()
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thunder_bw <- read.csv("thunder_configure_15_bw.csv")
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thunder_bw <- sqldf("select run,jmax,links,udp_sent,udp_rcv,cells_sent,cells_rcv,1.0*cells_sent/udp_sent as sent_ratio,1.0*cells_rcv/udp_rcv as rcv_ratio from thunder_bw where udp_sent > 4000")
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thunder_bw$jmax <- as.factor(thunder_bw$jmax)
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thunder_bw$links <- as.factor(thunder_bw$links)
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v3 <- ggplot(data = thunder_bw, aes(x = jmax, y=sent_ratio, fill=links)) +
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geom_boxplot() +
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#scale_y_log10() +
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#scale_y_log10(labels = scales::percent) +
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scale_fill_grey() +
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ylab("bandwidth ratio") +
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xlab("max allowed jitter") +
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theme_classic()
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t1 <- plot_grid(v1, v2, v3, labels = c('A', 'B', 'C'), ncol=1)
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t1 + ggsave("thunder_configure.png", dpi=300, dev='png', height=15, width=15, units="cm")
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thunder_links <- read.csv("thunder_configure_15_links.csv")
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links_down_at_least_once <- sqldf("select run,xp_time,link_id, COUNT(status) as downcount, SUM(delta) as elapsed from thunder_links where status='down' group by run,link_id,xp_time")
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links_down_at_least_once2 <- sqldf("select row_number () OVER (PARTITION BY run ORDER BY elapsed DESC) sorting,run,link_id,downcount,elapsed,xp_time,1.0*elapsed/xp_time down_ratio from links_down_at_least_once")
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links_down_at_least_once2$sorting <- as.factor(links_down_at_least_once2$sorting)
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v4 <- ggplot(data = links_down_at_least_once2, aes(x = sorting, y=down_ratio)) +
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#geom_violin() +
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#geom_boxplot(width=0.2) +
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#scale_y_log10() +
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#scale_y_log10(labels = scales::percent) +
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geom_bar(stat="summary") +
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#scale_y_log10() +
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scale_y_continuous(labels = scales::percent) +
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scale_fill_grey() +
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ylab("Cumulated downtime") +
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xlab("Sorted links") +
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theme_classic()
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downtime <- sqldf(
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"
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select sorting,1.0*duration/1000 as dur
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from thunder_links as tl
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inner join links_down_at_least_once2 as l2 on
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tl.run = l2.run
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and tl.link_id = l2.link_id
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where will_change='True'
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and status='down'")
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v5 <- ggplot(data = downtime, aes(x=sorting, y=dur)) +
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geom_violin() +
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scale_y_log10() +
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ylab("Downtime (in sec)") +
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xlab("Sorted links") +
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theme_classic()
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gobal_links <- sqldf(
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"
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select ts,run,durations_global,8-COUNT(status) as down_link_count,xp_time
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from thunder_links
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where will_change_global='True' and status='up' and durations_global > 0
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group by ts,run,durations_global
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")
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down_group_ratio <- sqldf(
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"
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select run,1.0 * SUM(durations_global)/xp_time as down_ratio, down_link_count
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from gobal_links
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where down_link_count >= 0
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group by run,down_link_count,xp_time
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")
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down_group_ratio$down_link_count <- as.factor(down_group_ratio$down_link_count)
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v6 <- ggplot(data = down_group_ratio, aes(x=down_link_count, y=down_ratio)) +
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geom_bar(stat="summary") +
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#scale_y_log10() +
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scale_y_continuous(labels = scales::percent) +
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ylab("Cumulated downtime") +
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xlab("Number of links down at once") +
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theme_classic()
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downtime_group <- sqldf(
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"
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select down_link_count, 1.0*durations_global/1000 as dur from gobal_links where down_link_count >= 0
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")
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downtime_group$down_link_count <- as.factor(downtime_group$down_link_count)
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v7 <- ggplot(data = downtime_group, aes(x=down_link_count, y=dur)) +
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geom_violin() +
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scale_y_log10() +
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ylab("Downtime (in sec)") +
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xlab("Number of links down at once") +
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theme_classic()
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t2 <- plot_grid(v4, v5, v6, v7, labels = c('A', 'B', 'C', 'D'), ncol=2)
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t2 + ggsave("thunder_links.png", dpi=300, dev='png', height=12, width=15, units="cm")
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latency_evol <- sqldf(
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"
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select sorting,lat_ms,ident,tm.jmax,tm.links
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from
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thunder_ms as tm,
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(select run,jmax,links,row_number () OVER (ORDER BY links DESC) sorting from thunder_ms group by run,jmax,links ORDER BY links DESC limit 0,1) as sel_run
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where
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tm.run = sel_run.run and tm.jmax = sel_run.jmax and tm.links = sel_run.links
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")
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latency_evol$sorting <- as.factor(latency_evol$sorting)
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ggplot(data=latency_evol, aes(x=ident,y=lat_ms)) +
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geom_line() +
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theme_classic()
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