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stats %>% group_by(implementation, message.size) %>% summarise(total.size=sum(message.size), begin=min(ts.in), end=max(ts.out), duration=end-begin, message.rate=total.size/as.numeric(duration)/1024/1024) %>% ungroup() %>% select(begin, end, duration, message.rate) ## # A tibble: 6 x 4 ## begin end duration message.rate ## <dttm> <dttm> <time> <dbl> ## 1 2017-07-17 04:27:52 2017-07-17 04:28:13 21.000000 secs 0.4650298 ## 2 2017-07-17 04:30:25 2017-07-17 04:32:02 1.616667 secs 30.2029639 ## 3 2017-07-17 04:32:58 2017-07-17 04:36:17 3.316667 secs 29.4440955 ## 4 2017-07-17 04:18:31 2017-07-17 04:18:54 23.000000 secs 0.4245924 ## 5 2017-07-17 04:19:47 2017-07-17 04:21:29 1.700000 secs 28.7224265 ## 6 2017-07-17 04:23:10 2017-07-17 04:26:28 3.300000 secs 29.5928030
For details please refer to
The text was updated successfully, but these errors were encountered:
If you're working with difftime objects, consider using hms which subclasses difftime but always converts to seconds (and prints nicer, too).
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For details please refer to
The text was updated successfully, but these errors were encountered: