假设我有两个data.tables: summary - data.table(period = c("A","B","C","D"), from_date = ymd(c("2017-01-01", "2017-01-03", "2017-02-08", "2017-03-07")), to_date = ymd(c("2017-01-31", "2017-04-01", "2017-03-08", "2017-05-01")))log - da
summary <- data.table(period = c("A","B","C","D"),
from_date = ymd(c("2017-01-01", "2017-01-03", "2017-02-08", "2017-03-07")),
to_date = ymd(c("2017-01-31", "2017-04-01", "2017-03-08", "2017-05-01"))
)
log <- data.table(date = ymd(c("2017-01-03","2017-01-20","2017-02-01","2017-03-03",
"2017-03-15","2017-03-28","2017-04-03","2017-04-23")),
event1 = c(4,8,8,4,3,4,7,3), event2 = c(1,8,7,3,8,4,6,3))
看起来像这样:
> summary
period from_date to_date
1: A 2017-01-01 2017-01-31
2: B 2017-01-03 2017-04-01
3: C 2017-02-08 2017-03-08
4: D 2017-03-07 2017-05-01
> log
date event1 event2
1: 2017-01-03 4 1
2: 2017-01-20 8 8
3: 2017-02-01 8 7
4: 2017-03-03 4 3
5: 2017-03-15 3 8
6: 2017-03-28 4 4
7: 2017-04-03 7 6
8: 2017-04-23 3 3
我想在表摘要中获取每个时间段的event1和event2的总和.
我知道我可以这样做:
summary[, c("event1","event2") := .(sum(log[date>=from_date & date<=to_date, event1]),
sum(log[date>=from_date & date<=to_date, event2]))
, by=period][]
获得所需的结果:
period from_date to_date event1 event2 1: A 2017-01-01 2017-01-31 12 9 2: B 2017-01-03 2017-04-01 31 31 3: C 2017-02-08 2017-03-08 4 3 4: D 2017-03-07 2017-05-01 17 21
现在,在我的现实问题中,我有大约30个要汇总的列,我可能想稍后更改,汇总有~35,000行,日志有~40,000,000行.有没有一种有效的方法来实现这一目标?
注意:这是我在这里的第一篇文章.我希望我的问题清楚而具体,如果我有什么需要改进的话,请提出建议.谢谢!
是的,您可以执行非equi连接.(注意我已将日志和摘要更改为Log和Summary,因为原件已经是R中的函数.)
Log[Summary,
on = c("date>=from_date", "date<=to_date"),
nomatch=0L,
allow.cartesian = TRUE][, .(from_date = date[1],
to_date = date.1[1],
event1 = sum(event1),
event2 = sum(event2)),
keyby = "period"]
要总结列的模式,请使用lapply和.SD:
joined_result <-
Log[Summary,
on = c("date>=from_date", "date<=to_date"),
nomatch = 0L,
allow.cartesian = TRUE]
cols <- grep("event[a-z]?[0-9]", names(joined_result), value = TRUE)
joined_result[, lapply(.SD, sum),
.SDcols = cols,
keyby = .(period,
from_date = date,
to_date = date.1)]
