如何在同一包装上组合条形图

Question

我需要显示每个 Numa 节点在同一包裹上的内存和 CPU 使用情况，因此架构是可见的。像这样的：

这是我的代码：

library(tidyr)
library(ggplot2)

numa.nodes <- tibble (
  numa_name = c("numa_01","numa_01","numa_01","numa_01","numa_01","numa_01","numa_02","numa_02","numa_02","numa_02"),
  counter_name =c("cpu01","cpu02","cpu03","cpu04","memory_used","memory_total","cpu01","cpu02","memory_used","memory_total"),
    value = c(sample(0:100,4), sample(0:32,1), 32, sample(0:100,1), sample(0:100,1), sample(0:128,1), 128)
)

numa.nodes <- numa.nodes %>% add_row(
  numa_name = c("numa_03","numa_03","numa_03","numa_03","numa_03","numa_03","numa_04","numa_04","numa_04","numa_04"),
  counter_name =c("cpu01","cpu02","cpu03","cpu04","memory_used","memory_total","cpu01","cpu02","memory_used","memory_total"),
  value = c(sample(0:100,4), sample(0:32,1), 32, sample(0:100,1), sample(0:100,1), sample(0:128,1), 128)
  )


numa.nodes <- numa.nodes %>% mutate(counter_name=factor(counter_name,levels = unique(counter_name),ordered = T))

print(numa.nodes)


cpu_p <- numa.nodes %>% filter(counter_name != c("memory_used", "memory_total")) %>% 
ggplot() +
  aes(x = counter_name, y = value, label = value) +
  geom_bar(stat = 'identity', fill = "#00AFBB",  color='black') +
  geom_bar(stat = 'identity',aes(y=100),alpha=0.2,fill='white',color='black') +
  facet_wrap(vars(numa_name), strip.position = 'bottom', scales = "free_x")+
  geom_text(size = 3, position = position_stack(vjust = 0.5)) +
  theme_bw()+
  theme(strip.placement = 'outside',
        strip.background = element_blank(),
        legend.position = 'none',
        axis.text = element_text(color='black',face='bold'),
        axis.title = element_text(color='black',face='bold'),
        legend.text = element_text(color='black',face='bold'),
        legend.title = element_text(color='black',face='bold'),
        strip.text = element_text(color='black',face='bold')) +
        labs(x='CPU',y="Usage %") 



mem_p <- numa.nodes %>% filter(counter_name == c("memory_used", "memory_total")) %>%
  pivot_wider(names_from = counter_name,values_from=value) %>%
  ggplot(aes(x=numa_name,y=memory_total)) +
  geom_bar(stat = 'identity',aes(fill='memory_total'),color='black')+
  geom_bar(stat = 'identity',aes(y=memory_used,fill='memory_used'),color='black') +
  facet_wrap(vars(numa_name), strip.position = 'bottom', scales = "free_x")+
  theme_bw()+
  geom_text(aes(y=memory_total,
                label=memory_total),size = 3) +
  geom_text(aes(y=memory_used,label=memory_used),
            position = position_stack(vjust = 0.5),
            size=3)+
  theme(strip.placement = 'outside',
        strip.background = element_blank(),
        legend.position = 'top',
        axis.text = element_text(color='black',face='bold'),
        axis.title = element_text(color='black',face='bold'),
        legend.text = element_text(color='black',face='bold'),
        legend.title = element_text(color='black',face='bold'),
        strip.text = element_text(color='black',face='bold'),
        axis.text.x = element_blank(),
        axis.ticks.x = element_blank()) +
  labs(x='Memory',y="Usage %")+
  labs(fill='Counter')

library("ggpubr")

ggarrange (cpu_p, mem_p)

很遗憾，我的代码有两个问题。

1. 我的结果不是每个节点的 CPU 和内存都在一起。我需要以某种方式将内存+CPU 结合起来。
2. 奇怪的是，我在看起来非常相似的图表上处理又高又宽的数据。

问题是：

• CPU 的数量可能是 1-8，如果我对 CPU 使用旋转，我将有一些 numa 节点的 N/A，
• CPU 的比例为 100%，我使用 y=100 来显示比例，内存的比例是总内存（使用的内存分层在总内存上），
• 我不能使用质押，也不能将计数器从左到右放置 - 内存和 cpu 数据的处理方式似乎不同。

是否可以显示相邻的每个 Numa 节点的 CPU 和内存？还有任何方法可以使用 Tall 或 Wide 数据，而不是两者？

Answer 1

我采用了一种编程方法，使用 ggpubr 包来安排绘图：

library(tidyverse)
library(ggpubr)

plot_numa = function(num){

  df = numa.nodes %>% filter(str_detect(numa_name, num))
  
  cpu_plot = df %>%
    filter(str_detect(counter_name, "cpu")) %>%
    ggplot(aes(x = counter_name)) +
    geom_col(aes(y = 100), fill = "white", color = "black") +
    geom_col(aes(y = value), fill = "black", color = "black") +
    geom_text(aes(y = value, label = paste0(value,"%")), nudge_y = 5, color = "black") +
    theme_bw() +
    labs(x = "CPU", y = "")
  
  memory_plot = df %>%
    filter(str_detect(counter_name, "memory")) %>%
    pivot_wider(names_from = counter_name, values_from = value) %>%
    ggplot(aes(x = "")) +
    geom_col(aes(y = memory_total), fill = "white", color = "black") +
    geom_col(aes(y = memory_used), fill = "black", color = "black") +
    geom_text(aes(label = paste(memory_total, "GB"), y = memory_total), nudge_y = -2, color = "black") +
    geom_text(aes(label = paste(memory_used, "GB"), y = memory_used), nudge_y = -2, color = "white") +
    theme_bw() +
    labs(x = "Memory", y = "")
  
  ggpubr::ggarrange(cpu_plot, memory_plot, ncol = 2) %>% ggpubr::annotate_figure(top = paste("NUMA",num))
  
}

ggpubr::ggarrange(plotlist = map(.x = c("01","02","03","04"), .f = ~plot_numa(num = .x)))

这个输出：

您可以随心所欲地进行改进，但这可以帮助您实现很多目标。