Database management system Updated +Created
A software that implements some database system, e.g. PostgreSQL or MySQL are two (widely extended) SQL implementations.
Download all Wikipedia categories Updated +Created
Let's observe them in MySQL:
mysql enwiki -e "select page_id, page_namespace, page_title, page_is_redirect from page where page_namespace in (0, 14) and page_title in ('Computer_storage_devices', 'Computer_data_storage')"
outputs:
+----------+----------------+--------------------------+------------------+
| page_id  | page_namespace | page_title               | page_is_redirect |
+----------+----------------+--------------------------+------------------+
|     5300 |              0 | Computer_data_storage    |                0 |
| 42371130 |              0 | Computer_storage_devices |                1 |
|   711721 |             14 | Computer_data_storage    |                0 |
|   895945 |             14 | Computer_storage_devices |                0 |
+----------+----------------+--------------------------+------------------+
mysql enwiki -e "select cl_from, cl_to from categorylinks where cl_from in (5300, 711721, 895945, 42371130)"
gives:
+----------+-----------------------------------------------------------------------+
| cl_from  | cl_to                                                                 |
+----------+-----------------------------------------------------------------------+
|     5300 | All_articles_containing_potentially_dated_statements                  |
|     5300 | Articles_containing_potentially_dated_statements_from_2009            |
|     5300 | Articles_containing_potentially_dated_statements_from_2011            |
|     5300 | Articles_with_GND_identifiers                                         |
|     5300 | Articles_with_NKC_identifiers                                         |
|     5300 | Articles_with_short_description                                       |
|     5300 | Computer_architecture                                                 |
|     5300 | Computer_data_storage                                                 |
|     5300 | Short_description_matches_Wikidata                                    |
|     5300 | Use_dmy_dates_from_June_2020                                          |
|     5300 | Wikipedia_articles_incorporating_text_from_the_Federal_Standard_1037C |
|   711721 | Computer_architecture                                                 |
|   711721 | Computer_data                                                         |
|   711721 | Computer_hardware_by_type                                             |
|   711721 | Data_storage                                                          |
|   895945 | Computer_data_storage                                                 |
|   895945 | Computer_peripherals                                                  |
|   895945 | Recording_devices                                                     |
| 42371130 | Redirects_from_alternative_names                                      |
+----------+-----------------------------------------------------------------------+
So we see that cl_from encodes the parent categories:
So to find all articls and categories under a given category title, say en.wikipedia.org/wiki/Category:Mathematics we can run:
mariadb enwiki -e "select cl_from, cl_to, page_namespace, page_title from categorylinks inner join page on page_namespace in (0, 14) and cl_from = page_id and cl_to = 'Mathematics'"
PostgreSQL Updated +Created
Had a look at the source tree, and also felt good.
If Oracle is the Microsoft of database, Postgres is the Linux, and MySQL (or more precisely MariaDB) is the FreeBSD (i.e. the one that got delayed by legal issues). Except that their software licenses were accidentally swapped.
The only problem with Postgres is its name. PostgreSQL is so unpronounceable and so untypeable that you should just call it "Postgres" like everyone else.
SQL histogram Updated +Created
Let's try it on SQLite 3.40.1, Ubuntu 23.04. Data setup:
sqlite3 tmp.sqlite 'create table t(x integer)'
sqlite3 tmp.sqlite <<EOF
insert into t values (
  0,
  2,
  2,
  3,

  5,
  6,
  6,
  8,
  9,

  17,
)
EOF
sqlite3 tmp.sqlite 'create index tx on t(x)'
For a bin size of 5 ignoring empty ranges we can:
sqlite3 tmp.sqlite <<EOF
select floor(x/5)*5 as x,
       count(*) as cnt
from t
group by 1
order by 1
EOF
which produces the desired:
0|4
5|5
15|1
And to consider empty ranges we can use SQL genenerate_series + as per stackoverflow.com/questions/72367652/populating-empty-bins-in-a-histogram-generated-using-sql:
sqlite3 tmp.sqlite <<EOF
select x, sum(cnt) from (
  select floor(x/5)*5 as x,
         count(*) as cnt
    from t
    group by 1
  union
  select *, 0 as cnt from generate_series(0, 15, 5)
)
group by x
EOF
which outputs the desired:
0|4
5|5
10|0
15|1
SQL tree traversal Updated +Created