R 中两个时间戳之间的左连接

我的目标是执行左连接intervals哪里的bike_id比赛和created_at时间戳在records在。。。之间start and end in the intervals table

> class(records)
[1] "data.table" "data.frame"
> class(intervals)
[1] "data.table" "data.frame"

> records
  bike_id          created_at         resolved_at
1   28780 2019-05-03 08:29:18 2019-05-03 08:35:37
2   28780 2019-05-03 21:05:28 2019-05-03 21:07:28
3   28780 2019-05-04 21:13:39 2019-05-04 21:15:40
4   28780 2019-05-07 17:24:20 2019-05-07 17:26:39
5   28780 2019-05-08 11:34:32 2019-05-08 12:16:44
6   28780 2019-05-08 23:38:39 2019-05-08 23:40:36


> intervals
   bike_id               start                 end id
1:   28780 2019-05-03 04:44:45 2019-05-03 16:58:56  1
2:   28780 2019-05-04 07:07:39 2019-05-04 14:48:29  2
3:   28780 2019-05-07 23:28:32 2019-05-08 12:56:24  3
4:   28780 2019-05-10 06:06:21 2019-05-10 13:12:08  4
5:   28780 2019-05-12 05:21:24 2019-05-12 11:35:52  5
6:   28780 2019-05-13 08:44:54 2019-05-13 12:28:31  6

在这种情况下，输出看起来像

> output
  bike_id          created_at         resolved_at   id
1   28780 2019-05-03 08:29:18 2019-05-03 08:35:37    1
2   28780 2019-05-03 21:05:28 2019-05-03 21:07:28  NULL   
3   28780 2019-05-04 21:13:39 2019-05-04 21:15:40  NULL
4   28780 2019-05-07 17:24:20 2019-05-07 17:26:39  NULL
5   28780 2019-05-08 11:34:32 2019-05-08 12:16:44  NULL
6   28780 2019-05-08 23:38:39 2019-05-08 23:40:36  NULL

我尝试过使用该解决方案发布在这里 https://community.rstudio.com/t/tidy-way-to-range-join-tables-on-an-interval-of-dates/7881 using tidyverse但这会导致R耗尽内存（尽管两个表中的记录量都只有100K左右）

fuzzy_left_join(
 records, intervals,
  by = c(
    "bike_id" = "bike_id",
    "created_at" = "start",
    "created_at" = "end"
    ),
  match_fun = list(`==`, `>=`, `<=`)
  ) %>%
  select(id, bike_id = bike_id.x, created_at, start, end)

这会引发错误：Error: vector memory exhausted (limit reached?)

是否有滚动加入的替代方法data.table甚至在基本 R 中使用merge()？通过 id 连接两个数据帧以及连接表中其他两个数据帧之间的时间戳的好方法是什么？

这是数据

dput(intervals)
structure(list(bike_id = c(28780L, 28780L, 28780L, 28780L, 28780L, 
28780L), start = structure(c(1556858685, 1556953659, 1557271712, 
1557468381, 1557638484, 1557737094), class = c("POSIXct", "POSIXt"
), tzone = "UTC"), end = structure(c(1556902736, 1556981309, 
1557320184, 1557493928, 1557660952, 1557750511), class = c("POSIXct", 
"POSIXt"), tzone = "UTC"), id = c(1, 2, 3, 4, 5, 6)), row.names = c(NA, 
-6L), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x1030056e0>)

dput(records)
structure(list(bike_id = c(28780L, 28780L, 28780L, 28780L, 28780L, 
28780L), created_at = structure(c(1556872158.796, 1556917528.845, 
1557004419.928, 1557249860.939, 1557315272.396, 1557358719.333
), class = c("POSIXct", "POSIXt"), tzone = "UTC"), resolved_at = structure(c(1556872537.867, 
1556917648.118, 1557004540.056, 1557249999.892, 1557317804.183, 
1557358836.202), class = c("POSIXct", "POSIXt"), tzone = "UTC")), row.names = c(NA, 
6L), class = "data.frame")

我们可以用data.table不等加入

library(data.table)
setDT(records)[intervals, on = .(bike_id, created_at >= start, created_at <= end)]