For a given blocking rule, returns the n blocking-key combinations
that produce the most record pairs. This helps diagnose skew, where a
single dominant key can create a quadratic explosion of pairs.
Usage
il_largest_blocks(
.data,
rule,
n = 5L,
con = NULL,
link_type = c("dedupe", "link")
)Arguments
- .data
A data frame, dbplyr::tbl_lazy, or character table name (first or only dataset).
- rule
A blocking rule created by
block_on().- n
Integer. Number of largest bins to return. Defaults to
5.- con
A DBI connection object from
DBI::dbConnect(). Optional when.datais a dbplyr::tbl_lazy.- link_type
One of
"dedupe"(default) or"link".
Value
A tibble::tibble() with one row per blocking-key combination, sorted by
descending pair count. Columns are the blocking-key values plus
n_records and n_pairs.
Examples
df <- data.frame(
unique_id = 1:20,
first_name = c(
'John', 'Jon', 'Jane', 'Jane', 'Bob',
'Bobby', 'Alice', 'Alicia', 'Tom', 'Thomas',
'John', 'Jon', 'Jane', 'Janet', 'Bob',
'Robert', 'Alice', 'Alison', 'Tom', 'Tomas'
),
surname = c(
'Smith', 'Smith', 'Doe', 'Doe', 'Jones',
'Jones', 'Brown', 'Brown', 'White', 'White',
'Smith', 'Smyth', 'Doe', 'Doe', 'Jones',
'Jones', 'Brown', 'Browne', 'White', 'White'
),
city = c(
'London', 'London', 'Paris', 'Paris', 'Berlin',
'Berlin', 'Rome', 'Rome', 'Madrid', 'Madrid',
'London', 'London', 'Paris', 'Paris', 'Berlin',
'Berlin', 'Rome', 'Rome', 'Madrid', 'Madrid'
)
)
con <- DBI::dbConnect(duckdb::duckdb())
il_largest_blocks(df, block_on(city), n = 3, con = con)
#> # A tibble: 3 × 3
#> city n_records n_pairs
#> <chr> <dbl> <dbl>
#> 1 Paris 4 6
#> 2 Rome 4 6
#> 3 Berlin 4 6
DBI::dbDisconnect(con, shutdown = TRUE)