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Install using with:
devtools::install_github("javierluraschi/sparkwarc")The following example loads a very small subset of a WARC file from Common Crawl, a nonprofit 501 organization that crawls the web and freely provides its archives and datasets to the public.
library(sparkwarc)
library(sparklyr)
library(DBI)
library(dplyr)sc <- spark_connect(master = "local")## * Using Spark: 2.1.0spark_read_warc(
sc,
"warc",
system.file("samples/sample.warc.gz", package = "sparkwarc"),
repartition = 8)SELECT count(value)
FROM WARC
WHERE length(regexp_extract(value, '<html', 0)) > 0| count(value) |
|---|
| 6 |
cc_regex <- function(ops) {
ops %>%
filter(regval != "") %>%
group_by(regval) %>%
summarize(count = n()) %>%
arrange(desc(count)) %>%
head(100)
}
cc_stats <- function(regex) {
tbl(sc, "warc") %>%
transmute(regval = regexp_extract(value, regex, 1)) %>%
cc_regex()
}cc_stats("http-equiv=\"Content-Language\" content=\"(.*)\"")## # Source: lazy query [?? x 2]
## # Database: spark_connection
## # Ordered by: desc(count)
## regval count
## <chr> <dbl>
## 1 ru-RU 5cc_stats("<script .*src=\".*/(.+)\".*")## # Source: lazy query [?? x 2]
## # Database: spark_connection
## # Ordered by: desc(count)
## regval count
## <chr> <dbl>
## 1 08.js 5
## 2 ga.js 5
## 3 jquery.formtips.1.2.2.packed.js 5
## 4 jquery-ui-1.7.2.custom.min.js 5
## 5 jquery-1.4.2.min.js 5
## 6 start.js 5
## 7 jquery.equalHeight.js 5
## 8 lytebox.js 5
## 9 plusone.js 5cc_stats("<([a-zA-Z]+)>")## # Source: lazy query [?? x 2]
## # Database: spark_connection
## # Ordered by: desc(count)
## regval count
## <chr> <dbl>
## 1 li 53
## 2 span 26
## 3 th 18
## 4 p 17
## 5 ul 16
## 6 tr 13
## 7 strong 7
## 8 title 6
## 9 body 6
## 10 head 6
## 11 div 6
## 12 noscript 5
## 13 table 3
## 14 td 3
## 15 br 1
## 16 style 1cc_stats(" ([a-zA-Z]{5,10}) ")## # Source: lazy query [?? x 2]
## # Database: spark_connection
## # Ordered by: desc(count)
## regval count
## <chr> <dbl>
## 1 counter 10
## 2 PUBLIC 6
## 3 return 6
## 4 Banners 5
## 5 widget 5
## 6 function 5
## 7 Banner 5
## 8 solid 2
## 9 Nutch 1
## 10 Domain 1
## 11 visit 1
## 12 crawl 1
## 13 Registry 1
## 14 Parked 1
## 15 Format 1
## 16 priceUAH 1
## 17 domain 1cc_stats("<meta .*keywords.*content=\"([^,\"]+).*")## # Source: lazy query [?? x 2]
## # Database: spark_connection
## # Ordered by: desc(count)
## regval count
## <chr> <dbl>
## 1 Лес 1
## 2 Вип Степ 1
## 3 domain names 1
## 4 Регистрация-ликвидация предприятий 1
## 5 Свобода 1
## 6 Foxy 1cc_stats("<script .*src=\".*/([^/]+.js)\".*")## # Source: lazy query [?? x 2]
## # Database: spark_connection
## # Ordered by: desc(count)
## regval count
## <chr> <dbl>
## 1 jquery.formtips.1.2.2.packed.js 5
## 2 08.js 5
## 3 ga.js 5
## 4 jquery.equalHeight.js 5
## 5 lytebox.js 5
## 6 plusone.js 5
## 7 jquery-ui-1.7.2.custom.min.js 5
## 8 jquery-1.4.2.min.js 5
## 9 start.js 5spark_disconnect(sc)warc_big <- normalizePath("~/cc.warc.gz") # Name a 5GB warc file
if (!file.exists(warc_big)) # If the file does not exist
download.file( # download by
gsub("s3n://commoncrawl/", # mapping the S3 bucket url
"https://commoncrawl.s3.amazonaws.com/", # into a adownloadable url
sparkwarc::cc_warc(1)), warc_big) # from the first archive fileconfig <- spark_config()
config[["spark.memory.fraction"]] <- "0.9"
config[["spark.executor.memory"]] <- "10G"
config[["sparklyr.shell.driver-memory"]] <- "10G"
sc <- spark_connect(master = "local", config = config)## * Using Spark: 2.1.0spark_read_warc(
sc,
"warc",
warc_big,
repartition = 8)df <- data.frame(list(a = list(“a,b,c”)))
SELECT count(value)
FROM WARC
WHERE length(regexp_extract(value, '<([a-z]+)>', 0)) > 0| count(value) |
|---|
| 6336761 |
SELECT count(value)
FROM WARC
WHERE length(regexp_extract(value, '<html', 0)) > 0| count(value) |
|---|
| 74519 |
cc_stats("http-equiv=\"Content-Language\" content=\"([^\"]*)\"")## # Source: lazy query [?? x 2]
## # Database: spark_connection
## # Ordered by: desc(count)
## regval count
## <chr> <dbl>
## 1 en 533
## 2 en-us 323
## 3 ru 150
## 4 es 127
## 5 en-US 105
## 6 fr 95
## 7 de 92
## 8 pl 71
## 9 cs 48
## 10 ja 45
## # ... with 90 more rowscc_stats("WARC-Target-URI: http://([^/]+)/.*")## # Source: lazy query [?? x 2]
## # Database: spark_connection
## # Ordered by: desc(count)
## regval count
## <chr> <dbl>
## 1 www.urbandictionary.com 156
## 2 my-shop.ru 69
## 3 hfboards.hockeysfuture.com 69
## 4 www.greatlakes4x4.com 66
## 5 www.opensecrets.org 60
## 6 www.summitpost.org 57
## 7 brainly.com.br 57
## 8 www.mobileread.com 54
## 9 www.genealogy.com 54
## 10 shop.ccs.com 51
## # ... with 90 more rowscc_stats("<([a-zA-Z]+)>")## # Source: lazy query [?? x 2]
## # Database: spark_connection
## # Ordered by: desc(count)
## regval count
## <chr> <dbl>
## 1 li 2492324
## 2 span 506471
## 3 tr 440658
## 4 p 432221
## 5 td 398106
## 6 ul 258962
## 7 div 211937
## 8 script 198504
## 9 br 196993
## 10 strong 152675
## # ... with 90 more rowscc_stats("<meta .*keywords.*content=\"([a-zA-Z0-9]+).*")## # Source: lazy query [?? x 2]
## # Database: spark_connection
## # Ordered by: desc(count)
## regval count
## <chr> <dbl>
## 1 width 285
## 2 http 235
## 3 free 110
## 4 text 110
## 5 The 100
## 6 index 91
## 7 https 85
## 8 SKYPE 59
## 9 1 55
## 10 news 48
## # ... with 90 more rowsspark_disconnect(sc)By running sparklyr in EMR, one can configure an EMR cluster and load about ~5GB of data using:
sc <- spark_connect(master = "yarn-client")
spark_read_warc(sc, "warc", cc_warc(1, 1))
tbl(sc, "warc") %>% summarize(n = n())
spark_disconnect_all()To read the first 200 files, or about ~1TB of data, first scale the cluster, consider maximizing resource allocation with the followin EMR config:
[
{
"Classification": "spark",
"Properties": {
"maximizeResourceAllocation": "true"
}
}
]Followed by loading the [1, 200] file range with:
sc <- spark_connect(master = "yarn-client")
spark_read_warc(sc, "warc", cc_warc(1, 200))
tbl(sc, "warc") %>% summarize(n = n())
spark_disconnect_all()To query ~1PB for the entire crawl, a custom script would be needed to load all the WARC files.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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