starschemar (version 1.2.0)

run_query: Run query

Description

Once we have selected the facts, dimensions and defined the conditions on the instances, we can execute the query to obtain the result.

Usage

run_query(dq, unify_by_grain = TRUE)
# S3 method for dimensional_query
run_query(dq, unify_by_grain = TRUE)

Arguments

dq

A dimensional_query object.

unify_by_grain

A boolean, unify facts with the same grain.

Value

A dimensional_query object.

Details

As an option, we can indicate if we do not want to unify the facts in the case of having the same grain.

See Also

Other query functions: dimensional_query(), filter_dimension(), select_dimension(), select_fact()

Examples

# NOT RUN {
library(tidyr)

ms <- dimensional_query(ms_mrs) %>%
  select_dimension(name = "where",
                   attributes = c("city", "state")) %>%
  select_dimension(name = "when",
                   attributes = c("when_happened_year")) %>%
  select_fact(
    name = "mrs_age",
    measures = c("n_deaths"),
    agg_functions = c("MAX")
  ) %>%
  select_fact(
    name = "mrs_cause",
    measures = c("pneumonia_and_influenza_deaths", "other_deaths")
  ) %>%
  filter_dimension(name = "when", when_happened_week <= "03") %>%
  filter_dimension(name = "where", city == "Boston") %>%
  run_query()

# }