datafy
, nav
, and the :schema
optionClojure 1.10 introduced a new namespace, clojure.datafy
, and two new protocols (Datafiable
and Navigable
) that allow for generalized, lazy navigation around data structures. Cognitect also released REBL -- a graphical, interactive tool for browsing Clojure data structures, based on the new datafy
and nav
functions.
Shortly after REBL's release, I added experimental support to clojure.java.jdbc
for datafy
and nav
that supported lazy navigation through result sets into foreign key relationships and connected rows and tables. next.jdbc
bakes that support into result sets produced by execute!
and execute-one!
.
datafy
/nav
LifecycleHere's how the process works:
execute!
and execute-one!
produce result sets containing rows that are Datafiable
,datafy
on result sets to render them as "pure data" (which they already are, but this makes them also Navigable
),nav
,nav
will fetch the related row(s),datafy
'd and nav
'd to continue drilling down through connected data in the database.By default, next.jdbc
assumes that a column named <something>id
or <something>_id
is a foreign key into a table called <something>
with a primary key called id
. As an example, if you have a table address
which has columns id
(the primary key), name
, email
, etc, and a table contact
which has various columns including addressid
, then if you retrieve a result set based on contact
, call datafy
on it and then "drill down" into the columns, when (nav row :contact/addressid v)
is called (where v
is the value of that column in that row) next.jdbc
's implementation of nav
will fetch a single row from the address
table, identified by id
matching v
.
You can override this default behavior for any column in any table by providing a :schema
option that is a hash map whose keys are column names (usually the table-qualified keywords that next.jdbc
produces by default) and whose values are tuples containing the name of the table to which that column is a foreign key and the name of the key column within that table. These tuples can optionally include a third value which indicates the cardinality of the foreign key relationship: :one
or :many
. The default is :one
and indicates a one-to-one or many-to-one relationship -- nav
igation will produce a single row. :many
indicates a one-to-many or many-to-many relationship -- nav
igation will produce a result set.
The default behavior in the example above is equivalent to this :schema
value:
{:contact/addressid [:address :id :one]} ; :one is the default and could be omitted
If you had a table to track the current valid/bouncing status of email addresses, where email
is the primary key, you could provide automatic navigation into that using:
{:contact/addressid [:address :id :one]
:address/email [:deliverability :email]}
If you use foreign key constraints in your database, you could probably generate this :schema
data structure automatically from the metadata in your database.
Making rows datafiable is implemented by adding metadata to each row with a key of clojure.core.protocols/datafy
and a function as the value. That function closes over the connectable and options passed in to the execute!
or execute-one!
call that produced the result set containing those rows.
When called (datafy
on a row), it adds metadata to the row with a key of clojure.core.protocols/nav
and another function as the value. That function also closes over the connectable and options passed in.
When that is called (nav
on a row, column name, and column value), if a :schema
entry exists for that column or it matches the default convention described above, then it will fetch row(s) using next.jdbc
's Executable
functions -execute-one
or -execute-all
, passing in the connectable and options closed over.
The protocol next.jdbc.result-set/DatafiableRow
has a default implementation of datafiable-row
for clojure.lang.IObj
that just adds the metadata to support datafy
. There is also an implementation baked into the result set handling behind reducible!
so that you can call datafiable-row
directly during reduction and get a fully-realized row that can be datafy
'd (and then nav
igated).
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