Hello,
I have logging information for multiple machines, which I am trying to
summarize and graph. So far, I process each host individually, but I
would like to summarize the user count across multiple hosts. I want to
answer the question "how many unique users logged in on a certain day
across a group of machines"?
I'm not quite sure how to scale the data frame and analysis to summarize
multiple hosts, though. I'm still getting a feel for using R.
Here is a snippet of data for one host. the user_count column is
generated from the users column using my custom function "usercount()".
the samples are taken roughly once per minute and only unique samples
are recorded. (i.e. use na.locf() to uncompress the data). Samples may
occur twice in the same minute and are rarely aligned on the same time.
Here is the original data before I turn t into a zoo series and run
na.locf() over it so I can aggregate a single host by day. I'm open to a
better way.
> foo
users datetime user_count
1 user1 & user2 2007-03-29 19:16:30 2
2 user1 & user2 2007-03-31 00:04:46 2
3 user1 & user2 2007-04-02 11:49:20 2
4 user1 & user2 2007-04-02 12:02:04 2
5 user1 & user2 2007-04-02 12:44:02 2
6 user1 & user2 & user3 2007-04-02 16:34:05 3
> dput(foo)
structure(list(users = c("user1 & user2", "user1 & user2", "user1 & user2",
"user1 & user2", "user1 & user2", "user1 & user2 & user3"), datetime =
structure(c(1175210190,
1175313886, 1175528960, 1175529724, 1175532242, 1175546045), class =
c("POSIXt",
"POSIXct"), tzone = "US/Eastern"), user_count = c(2, 2, 2, 2,
2, 3)), .Names = c("users", "datetime", "user_count"), row.names = c(NA,
6L), class = "data.frame")
Thanks,
Jason
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