mirror of https://github.com/apache/druid.git
78 lines
2.4 KiB
R
78 lines
2.4 KiB
R
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library(ggplot2)
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library(stringr)
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library(plyr)
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x <-
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"Dimension Cardinality Concise compressed size (bytes)
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Has_mention 2 586,400
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Has_links 2 580,872
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Has_geo 2 144,004
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Is_retweet 2 584,592
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Is_viral 2 358,380
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User_lang 21 1,414,000
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User_time_zone 142 3,876,244
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URL_domain 31,165 1,562,428
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First_hashtag 100,728 1,837,144
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Rt_name 182,704 2,235,288
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Reply_to_name 620,421 5,673,504
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User_location 637,774 9,511,844
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User_mention_name 923,842 9,086,416
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User_name 1,784,369 16,000,028"
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foo <- function(x){
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m <- matrix(unlist(str_split(x, "\t|\n")), ncol = 3, byrow = TRUE)
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df <- data.frame(m[-1, ], stringsAsFactors = FALSE)
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names(df) <- m[1, ]
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df[, 2] <- as.numeric(str_replace_all(df[, 2], ",", ""))
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df[, 3] <- as.numeric(str_replace_all(df[, 3], ",", ""))
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df <- transform(df, ytext = `Concise\ compressed\ size\ (bytes)`)
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names(df) <- c(m[1, ], "ytext")
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df
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}
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df <- foo(x)
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## df$ytext[12] <- 1.05 * df$ytext[12]
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## df$ytext[13] <- .93 * df$ytext[13]
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## df$ytext[1] <- 1.13 * df$ytext[1]
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## df$ytext[4] <- .87 * df$ytext[4]
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## qplot(x = Cardinality, y = `Concise\ compressed\ size\ (bytes)`, data = df, geom = "point") +
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## geom_text(aes(x = Cardinality * 1.2, y = ytext, label = Dimension), hjust = 0, size = 4) +
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## scale_x_log10(limits = c(1, 10^8.5)) +
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## scale_y_log10() +
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## geom_hline(aes(yintercept = 9089180)) +
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## geom_text(aes(x = 1e2, y = 9089180 * 1.1, label = "Integer array size (bytes)"), hjust = 0, size = 4) +
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## ggtitle("The Relationship of Compressed Size to Cardinality")
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y <-
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"Dimension Cardinality Concise compressed size (bytes)
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Has_mention 2 744
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Has_links 2 1,504
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Has_geo 2 2,840
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Is_retweet 2 1,616
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Is_viral 2 1,488
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User_lang 21 38,416
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User_time_zone 142 319,644
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URL_domain 31,165 700,752
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First_hashtag 100,728 1,505,292
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Rt_name 182,704 1,874,180
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Reply_to_name 620,421 5,404,108
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User_location 637,774 9,091,016
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User_mention_name 923,842 8,686,384
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User_name 1,784,369 16,204,900"
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df2 <- foo(y)
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df$sorted <- "unsorted"
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df2$sorted <- "sorted"
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dat <- rbind(df, df2)
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ggplot(data = dat, aes(x = Cardinality, y = `Concise\ compressed\ size\ (bytes)`)) +
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geom_point(aes(color = sorted, shape = sorted), alpha = .9, size = 4) +
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scale_x_log10(limits = c(1, 10^8.5)) +
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scale_y_log10() +
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geom_hline(aes(yintercept = 9089180)) +
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geom_text(aes(x = 1e1, y = 9089180 * 1.4, label = "Integer array size (bytes)"), hjust = 0, size = 5)
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#ggsave("concise_plot.png", width = 10, height = 8)
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ggsave("../figures/concise_plot.pdf", width = 6, height = 4.5)
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