The goal of the {dm} package and the dm class that comes
with it, is to make your life easier when you are dealing with data from
several different tables.
Let’s take a look at the dm class.
Class dm
The dm class consists of a collection of tables and
metadata about the tables, such as
- the names of the tables
- the names of the columns of the tables
- the primary and foreign keys of the tables to link the tables together
- the data (either as data frames or as references to database tables)
All tables in a dm must be obtained from the same data
source; csv files and spreadsheets would need to be imported to data
frames in R.
Examples of dm objects
There are currently three options available for creating a
dm object. The relevant functions for creating
dm objects are:
To illustrate these options, we will now create the same
dm in several different ways. We can use the tables from
the well-known {nycflights13} package.
Pass the tables directly
Create a dm object directly by providing data frames to
dm():
library(nycflights13)
library(dm)
dm(airlines, airports, flights, planes, weather)#> ── Metadata ───────────────────────────────────────────────────────────────
#> Tables: `airlines`, `airports`, `flights`, `planes`, `weather`
#> Columns: 53
#> Primary keys: 0
#> Foreign keys: 0Start with an empty dm
Start with an empty dm object that has been created with
dm() or new_dm(), and add tables to that
object:
library(nycflights13)
library(dm)
empty_dm <- dm()
empty_dm
#> dm()
dm(empty_dm, airlines, airports, flights, planes, weather)#> ── Metadata ───────────────────────────────────────────────────────────────
#> Tables: `airlines`, `airports`, `flights`, `planes`, `weather`
#> Columns: 53
#> Primary keys: 0
#> Foreign keys: 0Coerce a list of tables
Turn a named list of tables into a dm with
as_dm():
as_dm(list(
airlines = airlines,
airports = airports,
flights = flights,
planes = planes,
weather = weather
))#> ── Metadata ───────────────────────────────────────────────────────────────
#> Tables: `airlines`, `airports`, `flights`, `planes`, `weather`
#> Columns: 53
#> Primary keys: 0
#> Foreign keys: 0Turn tables from a src into a dm
Squeeze all (or a subset of) tables belonging to a src
object into a dm using dm_from_con():
sqlite_con <- dbplyr::nycflights13_sqlite()
flights_dm <- dm_from_con(sqlite_con)
flights_dm#> ── Table source ───────────────────────────────────────────────────────────
#> src: sqlite 3.50.1 [/tmp/Rtmpy7g1cu/nycflights13.sqlite]
#> ── Metadata ───────────────────────────────────────────────────────────────
#> Tables: `airlines`, `airports`, `flights`, `planes`, `sqlite_stat1`, … (7 total)
#> Columns: 62
#> Primary keys: 0
#> Foreign keys: 0The function dm_from_con(con, table_names = NULL)
includes all available tables on a source in the dm object.
This means that you can use this, for example, on a postgres database
that you access via DBI::dbConnect(RPostgres::Postgres())
(with the appropriate arguments dbname, host,
port, …), to produce a dm object with all the
tables on the database.
Low-level construction
Another way of creating a dm object is calling
new_dm() on a list of tbl objects:
base_dm <- new_dm(list(
airlines = airlines,
airports = airports,
flights = flights,
planes = planes,
weather = weather
))
base_dm#> ── Metadata ───────────────────────────────────────────────────────────────
#> Tables: `airlines`, `airports`, `flights`, `planes`, `weather`
#> Columns: 53
#> Primary keys: 0
#> Foreign keys: 0This constructor is optimized for speed and does not perform
integrity checks. Use with caution, validate using
dm_validate() if necessary.
dm_validate(base_dm)Access tables
We can get the list of tables with dm_get_tables() and
the src object with dm_get_con().
In order to pull a specific table from a dm, use:
flights_dm[["airports"]]#> # Source: table<`airports`> [?? x 8]
#> # Database: sqlite 3.50.1 [/tmp/Rtmpy7g1cu/nycflights13.sqlite]
#> faa name lat lon alt tz dst tzone
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <chr>
#> 1 04G Lansdowne Airport 41.1 -80.6 1044 -5 A Amer…
#> 2 06A Moton Field Municipal Airport 32.5 -85.7 264 -6 A Amer…
#> 3 06C Schaumburg Regional 42.0 -88.1 801 -6 A Amer…
#> 4 06N Randall Airport 41.4 -74.4 523 -5 A Amer…
#> 5 09J Jekyll Island Airport 31.1 -81.4 11 -5 A Amer…
#> 6 0A9 Elizabethton Municipal Airpo… 36.4 -82.2 1593 -5 A Amer…
#> 7 0G6 Williams County Airport 41.5 -84.5 730 -5 A Amer…
#> 8 0G7 Finger Lakes Regional Airport 42.9 -76.8 492 -5 A Amer…
#> 9 0P2 Shoestring Aviation Airfield 39.8 -76.6 1000 -5 U Amer…
#> 10 0S9 Jefferson County Intl 48.1 -123. 108 -8 A Amer…
#> # ℹ more rowsBut how can we use {dm}-functions to manage the primary keys of the
tables in a dm object?
Primary keys of dm objects
Some useful functions for managing primary key settings are:
If you created a dm object according to the examples in
“Examples of dm objects”, your object
does not yet have any primary keys set. So let’s add one.
We use the nycflights13 tables,
i.e. flights_dm from above.
dm_has_pk(flights_dm, airports)
#> [1] FALSE
flights_dm_with_key <- dm_add_pk(flights_dm, airports, faa)
flights_dm_with_key#> ── Table source ───────────────────────────────────────────────────────────
#> src: sqlite 3.50.1 [/tmp/Rtmpy7g1cu/nycflights13.sqlite]
#> ── Metadata ───────────────────────────────────────────────────────────────
#> Tables: `airlines`, `airports`, `flights`, `planes`, `sqlite_stat1`, … (7 total)
#> Columns: 62
#> Primary keys: 1
#> Foreign keys: 0The dm now has a primary key:
dm_has_pk(flights_dm_with_key, airports)
#> [1] TRUETo get an overview over all tables with primary keys, use
dm_get_all_pks():
dm_get_all_pks(flights_dm_with_key)#> # A tibble: 1 × 3
#> table pk_col autoincrement
#> <chr> <keys> <lgl>
#> 1 airports faa FALSERemove a primary key:
If you still need to get to know your data better, and it is already
available in the form of a dm object, you can use the
dm_enum_pk_candidates() function in order to get
information about which columns of the table are unique keys:
dm_enum_pk_candidates(flights_dm_with_key, airports)#> # A tibble: 8 × 3
#> columns candidate why
#> <keys> <lgl> <chr>
#> 1 faa TRUE ""
#> 2 lon TRUE ""
#> 3 name FALSE "has duplicate values: Municipal Airport (5), All Airp…
#> 4 lat FALSE "has duplicate values: 38.88944 (2), 40.63975 (2)"
#> 5 alt FALSE "has duplicate values: 0 (51), 13 (13), 14 (12), 15 (1…
#> 6 tz FALSE "has duplicate values: -5 (521), -6 (342), -9 (240), -…
#> 7 dst FALSE "has duplicate values: A (1388), U (47), N (23)"
#> 8 tzone FALSE "has duplicate values: America/New_York (519), America…The flights table does not have any one-column primary
key candidates:
dm_enum_pk_candidates(flights_dm_with_key, flights) %>% dplyr::count(candidate)#> # A tibble: 1 × 2
#> candidate n
#> <lgl> <int>
#> 1 FALSE 19dm_add_pk() has a check argument. If set to
TRUE, the function checks if the column of the table given
by the user is unique. For performance reasons, the default is
check = FALSE. See also [dm_examine_constraints()] for
checking all constraints in a dm.
Foreign keys
Useful functions for managing foreign key relations include:
Now it gets (even more) interesting: we want to define relations
between different tables. With the dm_add_fk() function you
can define which column of which table points to another table’s
column.
This is done by choosing a foreign key from one table that will point
to a primary key of another table. The primary key of the referred table
must be set with dm_add_pk(). dm_add_fk() will
find the primary key column of the referenced table by itself and make
the indicated column of the child table point to it.
#> ── Table source ───────────────────────────────────────────────────────────
#> src: sqlite 3.50.1 [/tmp/Rtmpy7g1cu/nycflights13.sqlite]
#> ── Metadata ───────────────────────────────────────────────────────────────
#> Tables: `airlines`, `airports`, `flights`, `planes`, `sqlite_stat1`, … (7 total)
#> Columns: 62
#> Primary keys: 1
#> Foreign keys: 1This will throw an error:
try(
flights_dm %>% dm_add_fk(flights, origin, airports)
)
#> Error in abort_ref_tbl_has_no_pk(ref_table_name) :
#> ref_table `airports` needs a primary key first. Use `dm_enum_pk_candidates()` to find appropriate columns and `dm_add_pk()` to define a primary key.Let’s create a dm object with a foreign key relation to
work with later on:
flights_dm_with_fk <- dm_add_fk(flights_dm_with_key, flights, origin, airports)What if we tried to add another foreign key relation from
flights to airports to the object? Column
dest might work, since it also contains airport codes:
try(
flights_dm_with_fk %>% dm_add_fk(flights, dest, airports, check = TRUE)
)
#> Error in abort_not_subset_of(table_name, col_name, ref_table_name, ref_col_name) :
#> Column (`dest`) of table `flights` contains values (see examples above) that are not present in column (`faa`) of table `airports`.Checks are opt-in and executed only if check = TRUE. You
can still add a foreign key with the default check = FALSE.
See also dm_examine_constraints() for checking all
constraints in a dm.
Get an overview of all foreign key relations
withdm_get_all_fks():
dm_get_all_fks(dm_nycflights13(cycle = TRUE))#> # A tibble: 5 × 5
#> child_table child_fk_cols parent_table parent_key_cols on_delete
#> <chr> <keys> <chr> <keys> <chr>
#> 1 flights carrier airlines carrier no_action
#> 2 flights origin airports faa no_action
#> 3 flights dest airports faa no_action
#> 4 flights tailnum planes tailnum no_action
#> 5 flights origin, time_hour weather origin, time_hour no_actionRemove foreign key relations with dm_rm_fk() (parameter
columns = NULL means that all relations will be removed,
with a message):
try(
flights_dm_with_fk %>%
dm_rm_fk(table = flights, column = dest, ref_table = airports) %>%
dm_get_all_fks(c(flights, airports))
)
#> Error in abort_is_not_fkc() : No foreign keys to remove.
flights_dm_with_fk %>%
dm_rm_fk(flights, origin, airports) %>%
dm_get_all_fks(c(flights, airports))#> # A tibble: 0 × 5
#> # ℹ 5 variables: child_table <chr>, child_fk_cols <keys>,
#> # parent_table <chr>, parent_key_cols <keys>, on_delete <chr>
flights_dm_with_fk %>%
dm_rm_fk(flights, columns = NULL, airports) %>%
dm_get_all_fks(c(flights, airports))
#> Removing foreign keys: %>%
#> dm_rm_fk(flights, origin, airports)#> # A tibble: 0 × 5
#> # ℹ 5 variables: child_table <chr>, child_fk_cols <keys>,
#> # parent_table <chr>, parent_key_cols <keys>, on_delete <chr>Since the primary keys are defined in the dm object, you
do not usually need to provide the referenced column name of
ref_table.
Another function for getting to know your data better
(cf. dm_enum_pk_candidates() in “Primary keys
of dm objects”) is
dm_enum_fk_candidates(). Use it to get an overview over
foreign key candidates that point from one table to another:
dm_enum_fk_candidates(flights_dm_with_key, weather, airports)#> # A tibble: 15 × 3
#> columns candidate why
#> <keys> <lgl> <chr>
#> 1 origin TRUE ""
#> 2 year FALSE "values of `weather$year` not in `airports$faa`: 2…
#> 3 month FALSE "values of `weather$month` not in `airports$faa`: …
#> 4 day FALSE "values of `weather$day` not in `airports$faa`: 3 …
#> 5 hour FALSE "values of `weather$hour` not in `airports$faa`: 1…
#> 6 temp FALSE "values of `weather$temp` not in `airports$faa`: 3…
#> 7 dewp FALSE "values of `weather$dewp` not in `airports$faa`: 2…
#> 8 humid FALSE "values of `weather$humid` not in `airports$faa`: …
#> 9 wind_dir FALSE "values of `weather$wind_dir` not in `airports$faa…
#> 10 wind_speed FALSE "values of `weather$wind_speed` not in `airports$f…
#> 11 wind_gust FALSE "values of `weather$wind_gust` not in `airports$fa…
#> 12 precip FALSE "values of `weather$precip` not in `airports$faa`:…
#> 13 pressure FALSE "values of `weather$pressure` not in `airports$faa…
#> 14 visib FALSE "values of `weather$visib` not in `airports$faa`: …
#> 15 time_hour FALSE "values of `weather$time_hour` not in `airports$fa…