Friendly SQL Functions

In Getting Started, we used execute! and execute-one! for all our SQL operations, except when we were reducing a result set. These functions (and plan) all expect a "connectable" and a vector containing a SQL string followed by any parameter values required.

A "connectable" can be a javax.sql.DataSource, a java.sql.Connection, or something that can produce a datasource (when get-datasource is called on it). It can also be a java.sql.PreparedStatement but we'll cover that a bit later...

Because string-building isn't always much fun, next.jdbc.sql also provides some "friendly" functions for basic CRUD operations:

• insert! and insert-multi! -- for inserting one or more rows into a table -- "Create",
• query -- an alias for execute! when using a vector of SQL and parameters -- "Read",
• update! -- for updating one or more rows in a table -- "Update",
• delete! -- for deleting one or more rows in a table -- "Delete".

as well as these more specific "read" operations:

• find-by-keys -- a query on one or more column values, specified as a hash map or WHERE clause,
• get-by-id -- a query to return a single row, based on a single column value, usually the primary key.

These functions are described in more detail below. They are deliberately simple and intended to cover only the most common, basic SQL operations. The primary API (plan, execute!, execute-one!) is the recommended approach for everything beyond that. If you need more expressiveness, consider one of the following libraries to build SQL/parameter vectors, or run queries:

• HoneySQL -- a composable DSL for creating SQL/parameter vectors from Clojure data structures
• seql -- a simplified EQL-inspired query language, built on next.jdbc (as of release 0.1.6)
• SQLingvo -- a composable DSL for creating SQL/parameter vectors
• Walkable -- full EQL query language support for creating SQL/parameter vectors

If you prefer to write your SQL separately from your code, take a look at HugSQL -- HugSQL documentation -- which has a next.jdbc adapter, as of version 0.5.1. See below for a "quick start" for using HugSQL with next.jdbc.

As of 1.3.925, aggregate-by-keys exists as a wrapper around find-by-keys that accepts the same options as find-by-keys and an aggregate SQL expression and it returns a single value (the aggregate). aggregate-by-keys accepts the same options as find-by-keys except that :columns may not be specified (since it is used to add the aggregate to the query).

insert!

Given a table name (as a keyword) and a hash map of column names and values, this performs a single row insertion into the database:

(sql/insert! ds :address {:name "A. Person" :email "albert@person.org"})
;; equivalent to
(jdbc/execute-one! ds ["INSERT INTO address (name,email) VALUES (?,?)"
                       "A.Person" "albert@person.org"] {:return-keys true})
;; some databases may require this instead
(jdbc/execute-one! ds ["INSERT INTO address (name,email) VALUES (?,?) RETURNING *"
                       "A.Person" "albert@person.org"])
;; which you can achieve with the :suffix option
(sql/insert! ds :address {:name "A. Person" :email "albert@person.org"}
             {:suffix "RETURNING *"})

If you have multiple rows (hash maps) to insert and they all have the same set of keys, you can use insert-multi! instead (see below), which will perform a single multi-row insertion, which will generally be faster.

insert-multi!

Given a table name (as a keyword), a vector of column names, and a vector of row value vectors, this performs a single multi-row insertion into the database:

(sql/insert-multi! ds :address
  [:name :email]
  [["Stella" "stella@artois.beer"]
   ["Waldo" "waldo@lagunitas.beer"]
   ["Aunt Sally" "sour@lagunitas.beer"]])
;; equivalent to
(jdbc/execute! ds ["INSERT INTO address (name,email) VALUES (?,?), (?,?), (?,?)"
                   "Stella" "stella@artois.beer"
                   "Waldo" "waldo@lagunitas.beer"
                   "Aunt Sally" "sour@lagunitas.beer"] {:return-keys true})

All the row vectors must be the same length, and must match the number of columns specified.

Given a table name (as a keyword) and a vector of hash maps, this performs a single multi-row insertion into the database:

(sql/insert-multi! ds :address
  [{:name "Stella", :email "stella@artois.beer"}
   {:name "Waldo", :email "waldo@lagunitas.beer"}
   {:name "Aunt Sally", :email "sour@lagunitas.beer"}])
;; equivalent to
(jdbc/execute! ds ["INSERT INTO address (name,email) VALUES (?,?), (?,?), (?,?)"
                   "Stella" "stella@artois.beer"
                   "Waldo" "waldo@lagunitas.beer"
                   "Aunt Sally" "sour@lagunitas.beer"] {:return-keys true})

All the hash maps must have the same set of keys, so that the vector of hash maps can be converted to a vector of columns names and a vector of row value vectors, as above, so a single multi-row insertion can be performed.

If you wish to insert multiple hash maps that do not have identical keys, you need to iterate over insert! and insert one row at a time, which will generally be much slower.

Note: both of these expand to a single SQL statement with placeholders for every value being inserted -- for large sets of rows, this may exceed the limits on SQL string size and/or number of parameters for your JDBC driver or your database. Several databases have a limit of 1,000 parameter placeholders. Oracle does not support this form of multi-row insert, requiring a different syntax altogether.

Batch Insertion

As of release 1.2.790, you can specify :batch true in the options, which will use execute-batch! under the hood, instead of execute!, as follows:

(sql/insert-multi! ds :address
  [:name :email]
  [["Stella" "stella@artois.beer"]
   ["Waldo" "waldo@lagunitas.beer"]
   ["Aunt Sally" "sour@lagunitas.beer"]]
  {:batch true})
;; equivalent to
(jdbc/execute-batch! ds
                     ["INSERT INTO address (name,email) VALUES (?,?)"
                      ["Stella" "stella@artois.beer"]
                      ["Waldo" "waldo@lagunitas.beer"]
                      ["Aunt Sally" "sour@lagunitas.beer"]]
                     {:return-keys true :return-generated-keys true})
;; and
(sql/insert-multi! ds :address
  [:name :email]
  [{:name "Stella", :email "stella@artois.beer"}
   {:name "Waldo", :email "waldo@lagunitas.beer"}
   {:name "Aunt Sally", :email "sour@lagunitas.beer"}]
  {:batch true})
;; equivalent to
(jdbc/execute-batch! ds
                     ["INSERT INTO address (name,email) VALUES (?,?)"
                      ["Stella" "stella@artois.beer"]
                      ["Waldo" "waldo@lagunitas.beer"]
                      ["Aunt Sally" "sour@lagunitas.beer"]]
                     {:return-keys true :return-generated-keys true})

Note: not all databases or drivers support returning generated keys like this -- see Batched Parameters for caveats and possible database-specific behaviors. You may need RETURNING * in your SQL instead.

query

Given a vector of SQL and parameters, execute it:

(sql/query ds ["select * from address where name = ?" "Stella"])
;; equivalent to
(jdbc/execute! ds ["SELECT * FROM address WHERE name = ?" "Stella"])

Note that the single argument form of execute!, taking just a PreparedStatement, is not supported by query.

update!

Given a table name (as a keyword), a hash map of columns names and values to set, and either a hash map of column names and values to match on or a vector containing a partial WHERE clause and parameters, perform an update operation on the database:

(sql/update! ds :address {:name "Somebody New"} {:id 2})
;; equivalent to
(sql/update! ds :address {:name "Somebody New"} ["id = ?" 2])
;; equivalent to
(jdbc/execute-one! ds ["UPDATE address SET name = ? WHERE id = ?"
                       "Somebody New" 2])

delete!

Given a table name (as a keyword) and either a hash map of column names and values to match on or a vector containing a partial WHERE clause and parameters, perform a delete operation on the database:

(sql/delete! ds :address {:id 8})
;; equivalent to
(sql/delete! ds :address ["id = ?" 8])
;; equivalent to
(jdbc/execute-one! ds ["DELETE FROM address WHERE id = ?" 8])

find-by-keys

Given a table name (as a keyword) and either a hash map of column names and values to match on or a vector containing a partial WHERE clause and parameters, execute a query on the database:

(sql/find-by-keys ds :address {:name "Stella" :email "stella@artois.beer"})
;; equivalent to
(sql/find-by-keys ds :address ["name = ? AND email = ?"
                               "Stella" "stella@artois.beer"])
;; equivalent to
(jdbc/execute! ds ["SELECT * FROM address WHERE name = ? AND email = ?"
                   "Stella" "stella@artois.beer"])

While the hash map approach -- "query by example" -- is great for equality comparisons, sometimes you need other types of comparisons. For example, you might want to find all the rows where the email address ends in .beer:

(sql/find-by-keys ds :address ["email LIKE ?" "%.beer"])
;; equivalent to
(jdbc/execute! ds ["SELECT * FROM address WHERE email LIKE ?" "%.beer"])

Or you may want to find all the rows where the name is one of a specific set of values:

(sql/find-by-keys ds :address ["name IN (?,?)" "Stella" "Waldo"])
;; equivalent to
(jdbc/execute! ds ["SELECT * FROM address WHERE name IN (?,?)" "Stella" "Waldo"])

The default behavior is to return all the columns in each row. You can specify a subset of columns to return using the :columns option. It takes a vector and each element of the vector can be:

• a simple keyword representing the column name (:column-fn will be applied, if provided),
• a pair of keywords representing the column name and an alias (:column-fn will be applied to both, if provided),
• a pair consisting of a string and a keyword, representing a SQL expression and an alias (:column-fn will be applied to the alias, if provided).

(sql/find-by-keys ds :address {:name "Stella"} {:columns [[:email :address]]})
;; equivalent to
(jdbc/execute! ds ["SELECT email AS address FROM address WHERE name = ?"
                   "Stella"])

(sql/find-by-keys ds :address {:name "Stella"} {:columns [["count(*)" :n]]})
;; equivalent to
(jdbc/execute! ds ["SELECT count(*) AS n FROM address WHERE name = ?"
                   "Stella"])

Note: the SQL string provided for a column is copied exactly as-is into the generated SQL -- you are responsible for ensuring it is legal SQL!

find-by-keys supports an :order-by option which can specify a vector of column names to sort the results by. Elements may be column names or pairs of a column name and the direction to sort: :asc or :desc:

(sql/find-by-keys ds :address
                  {:name "Stella" :email "stella@artois.beer"}
                  {:order-by [[:id :desc]]})
;; equivalent to
(jdbc/execute! ds ["SELECT * FROM address WHERE name = ? AND email = ? ORDER BY id DESC"
                   "Stella" "stella@artois.beer"])

find-by-keys also supports basic pagination with :offset and :fetch options which both accept numeric values and adds OFFSET ? ROWS FETCH NEXT ? ROWS ONLY to the generated query. To support MySQL and SQLite, you can specify :limit instead :fetch which adds LIMIT ? OFFSET ? to the generated query instead.

If you want to match all rows in a table -- perhaps with the pagination options in effect -- you can pass the keyword :all instead of either a hash map of column names and values or a vector containing a partial WHERE clause and parameters.

(sql/find-by-keys ds :address :all {:order-by [:id] :offset 5 :fetch 10})
;; equivalent to
(jdbc/execute! ds ["SELECT * FROM address ORDER BY id OFFSET ? ROWS FETCH NEXT ? ROWS ONLY" 5 10])

If no rows match, find-by-keys returns [], just like execute!.

aggregate-by-keys

Added in 1.3.925, this is a wrapper around find-by-keys that makes it easier to perform aggregate queries::

(sql/aggregate-by-keys ds :address "count(*)" {:name "Stella"
                                               :email "stella@artois.beer"})
;; is roughly equivalent to
(-> (sql/find-by-keys ds :address {:name "Stella" :email "stella@artois.beer"}
                      {:columns [["count(*)" :next_jdbc_aggregate_123]]})
    (first)
    (get :next_jdbc_aggregate_123))

(where :next_jdbc_aggregate_123 is a unique alias generated by next.jdbc, derived from the aggregate expression string).

Note: the SQL string provided for the aggregate is copied exactly as-is into the generated SQL -- you are responsible for ensuring it is legal SQL!

get-by-id

Given a table name (as a keyword) and a primary key value, with an optional primary key column name, execute a query on the database:

(sql/get-by-id ds :address 2)
;; equivalent to
(sql/get-by-id ds :address 2 {}) ; empty options map
;; equivalent to
(sql/get-by-id ds :address 2 :id {}) ; empty options map
;; equivalent to
(jdbc/execute-one! ds ["SELECT * FROM address WHERE id = ?" 2])

Note that in order to override the default primary key column name (of :id), you need to specify both the column name and an options hash map.

If no rows match, get-by-id returns nil, just like execute-one!.

Table & Column Entity Names

By default, next.jdbc.sql functions construct SQL strings with the entity names exactly matching the (unqualified) keywords provided. If you are trying to use a table name or column name that is a reserved name in SQL for your database, you will need to tell those functions to quote those names.

The namespace next.jdbc.quoted provides five functions that cover the most common types of entity quoting, and a modifier function for quoting dot-separated names (e.g., that include schemas):

• ansi -- wraps entity names in double quotes,

• mysql -- wraps entity names in back ticks,

• sql-server -- wraps entity names in square brackets,

• oracle -- an alias for ansi,

• postgres -- an alias for ansi.

• schema -- wraps a quoting function to support dbo.table style entity names.

These quoting functions can be provided to any of the friendly SQL functions above using the :table-fn and :column-fn options, in a hash map provided as the (optional) last argument in any call. If you want to provide your own entity naming function, you can do that:

(defn snake-case [s] (str/replace s #"-" "_"))

(sql/insert! ds :my-table {:some "data"} {:table-fn snake-case})

next.jdbc provides snake-kebab-opts and unqualified-snake-kebab-opts which are hash maps containing :column-fn and :table-fn that use the ->snake_case function from the camel-snake-kebab library which performs a more sophisticated transformation:

;; transforms :my-table to my_table as above but will also transform
;; column names; in addition, it will perform the reverse transformation
;; on any results, e.g., turning MySQL's :GENERATED_KEY into :generated-key
(sql/insert! ds :my-table {:some "data"} jdbc/snake-kebab-opts)

Note: The entity naming function is passed a string, the result of calling name on the keyword passed in. Also note that the default quoting functions do not handle schema-qualified names, such as dbo.table_name -- sql-server would produce [dbo.table_name] from that. Use the schema function to wrap the quoting function if you need that behavior, e.g,. {:table-fn (schema sql-server)} which would produce [dbo].[table_name].

HugSQL Quick Start

Here's how to get up and running quickly with next.jdbc and HugSQL. For more detail, consult the HugSQL documentation. Add the following dependencies to your project (in addition to com.github.seancorfield/next.jdbc and whichever JDBC drivers you need):

        com.layerware/hugsql-core {:mvn/version "0.5.3"}
        com.layerware/hugsql-adapter-next-jdbc {:mvn/version "0.5.3"}

Check the HugSQL documentation for the latest versions to use!

Write your SQL in .sql files that are on the classpath (somewhere under src or resources). For our purposes, assume a SQL file db/example.sql containing your first set of definitions. In your namespace, add these requires:

            [hugsql.core :as hugsql]
            [hugsql.adapter.next-jdbc :as adapter]
            [next.jdbc :as jdbc]

At program startup you'll need to call these functions (either at the top-level of your namespace on inside your initialization function):

;; regular SQL functions
(hugsql/def-db-fns "db/example.sql"
                   {:adapter (adapter/hugsql-adapter-next-jdbc)})

;; development/advanced usage functions that produce a vector containing
;; SQL and parameters that could be passed to jdbc/execute! etc
(hugsql/def-sqlvec-fns "db/example.sql"
                       {:adapter (adapter/hugsql-adapter-next-jdbc)})

Those calls will add function definitions to that namespace based on what is in the .sql files. Now set up your db-spec and datasource as usual with next.jdbc:

(def db-spec {:dbtype "h2:mem" :dbname "example"}) ; assumes H2 driver in deps.edn

(def ds (jdbc/get-datasource db-spec))

Borrowing from Princess Bride examples from the HugSQL documentation, you can now do things like this:

(create-characters-table ds)
;;=> [#:next.jdbc{:update-count 0}]
(insert-character ds {:name "Westley", :specialty "love"})
;;=> 1

By default, for compatibility with their default adapter (clojure.java.jdbc), the next.jdbc adapter uses the next.jdbc.result-set/as-unqualified-lower-maps builder function. You can specify a different builder function when you pass in the adapter:

;; add require next.jdbc.result-set :as rs to your ns

(hugsql/def-db-fns "db/example.sql"
                   {:adapter (adapter/hugsql-adapter-next-jdbc
                              {:builder-fn rs/as-maps})})

;; now you'll get qualified as-is hash maps back:
(character-by-id ds {:id 1})
;;=> #:CHARACTERS{:ID 1, :NAME "Westley", :SPECIALTY "love", :CREATED_AT #inst "2019-09-27T18:52:54.413000000-00:00"}