From the planned update, it obtains the instances of the update facts that are already included in the star database facts to be updated.
Usage
get_existing_fact_instances(sdbu)
# S3 method for star_database_update
get_existing_fact_instances(sdbu)Details
The most common thing is that refresh operations only include new instances in fact tables, but it may be the case that repeated instances appear: They may have different values in the measures, but the same values in the dimension foreign keys. When the update occurs, we need to determine what happens to these instances.
See also
Other star database refresh functions:
get_lookup_tables(),
get_new_dimension_instances(),
get_star_database(),
get_star_schema(),
get_transformation_code(),
get_transformation_file(),
incremental_refresh(),
update_according_to()
Examples
f1 <-
flat_table('ft_num', ft_cause_rpd[ft_cause_rpd$City != 'Cambridge' &
ft_cause_rpd$WEEK != '4',]) |>
as_star_database(mrs_cause_schema_rpd) |>
role_playing_dimension(rpd = "When",
roles = c("When Available", "When Received"))
f2 <- flat_table('ft_num2', ft_cause_rpd[ft_cause_rpd$City != 'Bridgeport' &
ft_cause_rpd$WEEK != '2',])
f2 <- f2 |>
update_according_to(f1)
fact_instances <- f2 |>
get_existing_fact_instances()