A snapshot of records from given entries

Filters for entries up to a given entry-number or timestamp, then returns the latest entry per key.

Use rr_snapshot() for a snapshot of a whole register (both schema and data).

rr_records(entries, sequence = c("entry-number", "timestamp"),
  maximum = NULL, include_maximum = TRUE)

Arguments

entries	A data frame or tibble with at least the fields key and either entry-number or timestamp, depending on the value of sequence.
sequence	One of "entry-number" (default) or "timestamp". The snapshot is taken at the maximum value of this field of entries.
maximum	An integer if sequence is "entry-number" orPOSIXctifsequenceis"timestamp", giving the time at which to take the snapshot. Only the latest entry up to this value will be kept, perkey`. By default it is the maximum of all entries, to return the most recent state of the register.
include_maximum	Logical, whether to include entries whose entry-number or timestamp equals maximum.

Value

A tibble of records (latest entry per key).

Details

A record is the latest entry for a given key. 'Latest' can be either the maximum entry-number (recommended), or the maximum timestamp. An entry timestamp may be NA, and may not be unique. If the timestamp of any entry of a given key is NA, then no record for that key will be returned. If the timestamp is not unique, then the entry with the maximum entry-number will be chosen.

Examples

country <- rr_register("country")

# There can be more than one entry per key
country$data %>%
  dplyr::filter(key == "CZ") %>%
  dplyr::select(`entry-number`, timestamp, name, `official-name`)
#> # A tibble: 2 x 4
#>   `entry-number` timestamp           name           `official-name`   
#>            <int> <dttm>              <chr>          <chr>             
#> 1             64 2016-04-05 13:23:05 Czech Republic The Czech Republic
#> 2            217 2016-11-11 16:25:07 Czechia        The Czech Republic

# Snapshot by entry number
country$data %>%
  rr_records(maximum = 64) %>%
  dplyr::filter(key == "CZ") %>%
  dplyr::select(`entry-number`, timestamp, name, `official-name`)
#> # A tibble: 1 x 4
#>   `entry-number` timestamp           name           `official-name`   
#>            <int> <dttm>              <chr>          <chr>             
#> 1             64 2016-04-05 13:23:05 Czech Republic The Czech Republic

country$data %>%
  rr_records(maximum = 217, include_maximum = FALSE) %>%
  dplyr::filter(key == "CZ") %>%
  dplyr::select(`entry-number`, timestamp, name, `official-name`)
#> # A tibble: 1 x 4
#>   `entry-number` timestamp           name           `official-name`   
#>            <int> <dttm>              <chr>          <chr>             
#> 1             64 2016-04-05 13:23:05 Czech Republic The Czech Republic

# Snapshot by entry timestamp
country$data %>%
  rr_records(sequence = "timestamp",
             maximum = as.POSIXct("2016-04-05 13:23:05", tz = "UTC")) %>%
  dplyr::filter(key == "CZ") %>%
  dplyr::select(`entry-number`, timestamp, name, `official-name`)
#> # A tibble: 1 x 4
#>   `entry-number` timestamp           name           `official-name`   
#>            <int> <dttm>              <chr>          <chr>             
#> 1             64 2016-04-05 13:23:05 Czech Republic The Czech Republic

# When the timestamp of any entry of a key is missing, no entries are
# returned.
entries <- country$data
entries$timestamp[entries$`entry-number` == 64] <- NA
rr_records(entries, sequence = "timestamp") %>%
  dplyr::filter(key == "CZ")
#> # A tibble: 0 x 11
#> # ... with 11 variables: `entry-number` <int>, type <chr>, key <chr>,
#> #   timestamp <dttm>, hash <chr>, country <chr>, name <chr>,
#> #   `official-name` <chr>, `citizen-names` <chr>, `start-date` <chr>,
#> #   `end-date` <chr>

# Not all entries are data, some are schema
country$schema$custodians %>%
  rr_records(maximum = 11) %>%
  dplyr::select(`entry-number`, timestamp, custodian)
#> # A tibble: 1 x 3
#>   `entry-number` timestamp           custodian  
#>            <int> <dttm>              <chr>      
#> 1              2 2017-07-17 10:59:47 Tony Worron