Build a nice description of a table.

Please see https://win-vector.com/2017/05/26/managing-spark-data-handles-in-r/ for details. Note: one usually needs to alter the keys column which is just populated with all columns.

describe_tables(db, tablenames, ..., keyInspector = key_inspector_all_cols)

Arguments

db	database handle
tablenames	character, names of tables to describe.
...	force later arguments to bind by name.
keyInspector	function that determines preferred primary key set for tables.

Value

table describing the data.

Details

Please see vignette('DependencySorting', package = 'rquery') and vignette('joinController', package= 'rquery') for more details.

See also

build_join_plan, graph_join_plan, actualize_join_plan

Examples

if (requireNamespace("DBI", quietly = TRUE) && requireNamespace("RSQLite", quietly = TRUE)) {
  my_db <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
  ex <- example_employee_date(my_db)
  print(describe_tables(my_db, ex$tableName,
                         keyInspector = key_inspector_sqlite))
  DBI::dbDisconnect(my_db)
}
#>         tableName isEmpty               indicatorColumn
#> 1 employeeanddate   FALSE table_employeeanddate_present
#> 2         revenue   FALSE         table_revenue_present
#> 3        activity   FALSE        table_activity_present
#> 4        orgtable   FALSE        table_orgtable_present
#>                      columns       keys
#> 1                   id, date           
#> 2            date, dept, rev date, dept
#> 3 eid, date, hours, location  eid, date
#> 4  eid, date, dept, location  eid, date
#>                                   colClass
#> 1                       character, integer
#> 2              integer, character, integer
#> 3   character, integer, integer, character
#> 4 character, integer, character, character