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next-jdbc/doc/getting-started.md
Sean Corfield 79236b45e5 Improve plan/reduce documentation 
Also rolls H2 version back so examples work properly. 1.4.200 doesn't 
like one of the data types the examples use.
2020-03-08 17:05:13 -07:00

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# Getting Started with next.jdbc
The `next.jdbc` library provides a simpler, faster alternative to the [`clojure.java.jdbc`](https://github.com/clojure/java.jdbc) Contrib library and is the next step in the evolution of that library.
It is designed to work with Clojure 1.10 or later, supports `datafy`/`nav`, and by default produces hash maps with automatically qualified keywords, indicating source tables and column names (labels), if your database supports that.
## Installation
You can add `next.jdbc` to your project with either:
```clojure
{seancorfield/next.jdbc {:mvn/version "1.0.395"}}
```
for `deps.edn` or:
```clojure
[seancorfield/next.jdbc "1.0.395"]
```
for `project.clj` or `build.boot`.
In addition, you will need to add dependencies for the JDBC drivers you wish to use for whatever databases you are using. You can see the drivers and versions that `next.jdbc` is tested against in [the project's `deps.edn` file](https://github.com/seancorfield/next-jdbc/blob/master/deps.edn#L11-L24), but many other JDBC drivers for other databases should also work (e.g., Oracle, Red Shift).
## An Example REPL Session
To start using `next.jdbc`, you need to create a datasource (an instance of `javax.sql.DataSource`). You can use `next.jdbc/get-datasource` with either a "db-spec" -- a hash map describing the database you wish to connect to -- or a JDBC URI string. Or you can construct a datasource from one of the connection pooling libraries out there, such as [HikariCP](https://brettwooldridge.github.io/HikariCP/) or [c3p0](https://www.mchange.com/projects/c3p0/) -- see [Connection Pooling](#connection-pooling) below.
For the examples in this documentation, we will use a local H2 database on disk, and we'll use the [Clojure CLI tools](https://clojure.org/guides/deps_and_cli) and `deps.edn`:
```clojure
;; deps.edn
{:deps {org.clojure/clojure {:mvn/version "1.10.1"}
seancorfield/next.jdbc {:mvn/version "1.0.395"}
com.h2database/h2 {:mvn/version "1.4.199"}}}
```
### Create & Populate a Database
In this REPL session, we'll define an H2 datasource, create a database with a simple table, and then add some data and query it:
```clojure
> clj
Clojure 1.10.1
user=> (require '[next.jdbc :as jdbc])
nil
user=> (def db {:dbtype "h2" :dbname "example"})
#'user/db
user=> (def ds (jdbc/get-datasource db))
#'user/ds
user=> (jdbc/execute! ds ["
create table address (
id int auto_increment primary key,
name varchar(32),
email varchar(255)
)"])
[#:next.jdbc{:update-count 0}]
user=> (jdbc/execute! ds ["
insert into address(name,email)
values('Sean Corfield','sean@corfield.org')"])
[#:next.jdbc{:update-count 1}]
user=> (jdbc/execute! ds ["select * from address"])
[#:ADDRESS{:ID 1, :NAME "Sean Corfield", :EMAIL "sean@corfield.org"}]
user=>
```
### The "db-spec" hash map
We described the database with just `:dbtype` and `:dbname` because it is created as a local file and needs no authentication. For most databases, you would need `:user` and `:password` for authentication, and if the database is running on a remote machine you would need `:host` and possibly `:port` (`next.jdbc` tries to guess the correct port based on the `:dbtype`).
> Note: You can see the full list of `:dbtype` values supported in [next.jdbc/get-datasource](https://cljdoc.org/d/seancorfield/next.jdbc/CURRENT/api/next.jdbc#get-datasource)'s docstring. If you need this programmatically, you can get it from the [next.jdbc.connection/dbtypes](https://cljdoc.org/d/seancorfield/next.jdbc/CURRENT/api/next.jdbc.connection#dbtypes) hash map. If those lists differ, the hash map is the definitive list (and I'll need to fix the docstring!). The docstring of that Var explains how to tell `next.jdbc` about additional databases.
If you already have a JDBC URL (string), you can use that as-is instead of the db-spec hash map. If you have a JDBC URL and still need additional options passed into the JDBC driver, you can use a hash map with the `:jdbcUrl` key specifying the string and whatever additional options you need.
### `execute!` & `execute-one!`
We used `execute!` to create the `address` table, to insert a new row into it, and to query it. In all three cases, `execute!` returns a vector of hash maps with namespace-qualified keys, representing the result set from the operation, if available.
If the result set contains no rows, `execute!` returns an empty vector `[]`.
When no result set is produced, `next.jdbc` returns a "result set" containing the "update count" from the operation (which is usually the number of rows affected; note that `:builder-fn` does not affect this fake "result set"). By default, H2 uses uppercase names and `next.jdbc` returns these as-is.
If you only want a single row back -- the first row of any result set, generated keys, or update counts -- you can use `execute-one!` instead. Continuing the REPL session, we'll insert another address and ask for the generated keys to be returned, and then we'll query for a single row:
```clojure
user=> (jdbc/execute-one! ds ["
insert into address(name,email)
values('Someone Else','some@elsewhere.com')
"] {:return-keys true})
#:ADDRESS{:ID 2}
user=> (jdbc/execute-one! ds ["select * from address where id = ?" 2])
#:ADDRESS{:ID 2, :NAME "Someone Else", :EMAIL "some@elsewhere.com"}
user=>
```
Since we used `execute-one!`, we get just one row back (a hash map). This also shows how you provide parameters to SQL statements -- with `?` in the SQL and then the corresponding parameter values in the vector after the SQL string.
If the result set contains no rows, `execute-one!` returns `nil`.
When no result is produced, and `next.jdbc` returns a fake "result set" containing the "update count", `execute-one!` returns just a single hash map with the key `next.jdbc/update-count` and the number of rows updated.
> Note: In general, you should use `execute-one!` for DDL operations since you will only get back an update count. If you have a SQL statement that you know will only return an update count, `execute-one!` is the right choice. If you have a SQL statement that you know will only return a single row in the result set, you probably want to use `execute-one!`. If you use `execute-one!` for a SQL statement that would return multiple rows in a result set, even though you will only get the first row back (as a hash map), the full result set will still be retrieved from the database -- it does not limit the SQL in any way.
### Options & Result Set Builders
All functions in `next.jdbc` (except `get-datasource`) can accept, as the optional last argument, a hash map containing a [variety of options](/doc/all-the-options.md) that control the behavior of the `next.jdbc` functions.
We saw `:return-keys` provided as an option to the `execute-one!` function above and mentioned the `:builder-fn` option just above that. As noted, the default behavior it to return rows as hash maps with namespace-qualified keywords identifying the column names with the table name as the qualifier. There's a whole chapter on [result set builders](/doc/result-set-builders.md) but here's a quick example showing how to get unqualified, lower case keywords instead:
```clojure
user=> (require '[next.jdbc.result-set :as rs])
nil
user=> (jdbc/execute-one! ds ["
insert into address(name,email)
values('Someone Else','some@elsewhere.com')
"] {:return-keys true :builder-fn rs/as-unqualified-lower-maps})
{:id 2}
user=> (jdbc/execute-one! ds ["select * from address where id = ?" 2]
{:builder-fn rs/as-unqualified-lower-maps})
{:id 2, :name "Someone Else", :email "some@elsewhere.com"}
user=>
```
Relying on the default result set builder -- and table-qualified column names -- is the recommended approach to take, if possible, with a few caveats:
* MS SQL Server produces unqualified column names by default (see [**Tips & Tricks**](/doc/tips-and-tricks.md) for how to get table names back from MS SQL Server),
* Oracle's JDBC driver doesn't support `.getTableName()` so it will only produce unqualified column names (also mentioned in **Tips & Tricks**),
* If your SQL query joins tables in a way that produces duplicate column names, and you use unqualified column names, then those duplicated column names will conflict and you will get only one of them in your result -- use aliases in SQL (`as`) to make the column names distinct,
* If your SQL query joins a table to itself under different aliases, the _qualified_ column names will conflict because they are based on the underlying table name provided by the JDBC driver rather the alias you used in your query -- again, use aliases in SQL to make those column names distinct.
### `plan` & Reducing Result Sets
While the `execute!` and `execute-one!` functions are fine for retrieving result sets as data, most of the time you want to process that data efficiently without necessarily converting the entire result set into a Clojure data structure, so `next.jdbc` provides a SQL execution function that works with `reduce` and with transducers to consume the result set without the intermediate overhead of creating Clojure data structures for every row.
We're going to create a new table that contains invoice items so we can see how to use `plan` without producing data structures:
```clojure
user=> (jdbc/execute-one! ds ["
create table invoice (
id int auto_increment primary key,
product varchar(32),
unit_price decimal(10,2),
unit_count int unsigned,
customer_id int unsigned
)"])
#:next.jdbc{:update-count 0}
user=> (jdbc/execute-one! ds ["
insert into invoice (product, unit_price, unit_count, customer_id)
values ('apple', 0.99, 6, 100),
('banana', 1.25, 3, 100),
('cucumber', 2.49, 2, 100)
"])
#:next.jdbc{:update-count 3}
user=> (reduce
(fn [cost row]
(+ cost (* (:unit_price row)
(:unit_count row))))
0
(jdbc/plan ds ["select * from invoice where customer_id = ?" 100]))
14.67M
```
The call to `jdbc/plan` returns an `IReduceInit` object but does not actually run the SQL. Only when the returned object is reduced is the connection obtained from the data source, the SQL executed, and the computation performed. The connection is closed automatically when the reduction is complete. The `row` in the reduction is an abstraction over the underlying (mutable) `ResultSet` object -- it is not a Clojure data structure. Because of that, you can simply access the columns via their SQL labels as shown -- you do not need to use the column-qualified name, and you do not need to worry about the database returning uppercase column names (SQL labels are not case sensitive).
Here's the same computation rewritten using `transduce`:
```clojure
user=> (transduce
(map #(* (:unit_price %) (:unit_count %)))
+
0
(jdbc/plan ds ["select * from invoice where customer_id = ?" 100]))
14.67M
```
or composing the transforms:
```clojure
user=> (transduce
(comp (map (juxt :unit_price :unit_count))
(map #(apply * %)))
+
0
(jdbc/plan ds ["select * from invoice where customer_id = ?" 100]))
14.67M
```
If you just wanted the total item count:
```clojure
user=> (transduce
(map :unit_count)
+
0
(jdbc/plan ds ["select * from invoice where customer_id = ?" 100]))
11
```
You can use other functions that perform reductions to process the result of `plan`, such as obtaining a set of unique products from an invoice:
```clojure
user=> (into #{}
(map :product)
(jdbc/plan ds ["select * from invoice where customer_id = ?" 100]))
#{"apple" "banana" "cucumber"}
```
Any operation that can perform key-based lookup can be used here without creating hash maps from the rows: `get`, `contains?`, `find` (returns a `MapEntry` of whatever key you requested and the corresponding column value), or direct keyword access as shown above. Any operation that would require a Clojure hash map, such as `assoc` or anything that invokes `seq` (`keys`, `vals`), will cause the full row to be expanded into a hash map, such as produced by `execute!` or `execute-one!`, which implements `Datafiable` and `Navigable` and supports lazy navigation via foreign keys, explained in [`datafy`, `nav`, and the `:schema` option](/doc/datafy-nav-and-schema.md).
This means that `select-keys` can be used to create regular Clojure hash map from (a subset of) columns in the row, without realizing the row, and it will not implement `Datafiable` or `Navigable`.
If you wish to create a Clojure hash map that supports that lazy navigation, you can call `next.jdbc.result-set/datafiable-row`, passing in the current row, a `connectable`, and an options hash map, just as you passed into `plan`. Compare the difference in output between these three expressions:
```clojure
user=> (into []
(map #(select-keys % [:id :product :unit_price :unit_cost :customer_id]))
(jdbc/plan ds ["select * from invoice where customer_id = ?" 100]))
user=> (into []
(map #(select-keys % [:invoice/id :invoice/product
:invoice/unit_price :invoice/unit_cost
:invoice/customer_id]))
(jdbc/plan ds ["select * from invoice where customer_id = ?" 100]))
user=> (into []
(map #(rs/datafiable-row % ds {}))
(jdbc/plan ds ["select * from invoice where customer_id = ?" 100]))
```
The latter produces a vector of hash maps, just like the result of `execute!`, where each "row" follows the case conventions of the database, the keys are qualified by the table name, and the hash map is datafiable and navigable.
> Note: since `plan` expects you to process the result set via reduction, you should not use it for DDL or for SQL statements that only produce update counts.
## Datasources, Connections & Transactions
In the examples above, we created a datasource and then passed it into each function call. When `next.jdbc` is given a datasource, it creates a `java.sql.Connection` from it, uses it for the SQL operation (by creating and populating a `java.sql.PreparedStatement` from the connection and the SQL string and parameters passed in), and then closes it. If you're not using a connection pooling datasource (see below), that can be quite an overhead: setting up database connections to remote servers is not cheap!
If you want to run multiple SQL operations without that overhead each time, you can create the connection yourself and reuse it across several operations using `with-open` and `next.jdbc/get-connection`:
```clojure
(with-open [con (jdbc/get-connection ds)]
(jdbc/execute! con ...)
(jdbc/execute! con ...)
(into [] (map :column) (jdbc/plan con ...)))
```
If any of these operations throws an exception, the connection will still be closed but operations prior to the exception will have already been committed to the database. If you want to reuse a connection across multiple operations but have them all rollback if an exception occurs, you can use `next.jdbc/with-transaction`:
```clojure
(jdbc/with-transaction [tx ds]
(jdbc/execute! tx ...)
(jdbc/execute! tx ...)
(into [] (map :column) (jdbc/plan tx ...)))
```
If `with-transaction` is given a datasource, it will create and close the connection for you. If you pass in an existing connection, `with-transaction` will set up a transaction on that connection and, after either committing or rolling back the transaction, will restore the state of the connection and leave it open:
```clojure
(with-open [con (jdbc/get-connection ds)]
(jdbc/execute! con ...) ; committed
(jdbc/with-transaction [tx con] ; will commit or rollback this group:
(jdbc/execute! tx ...)
(jdbc/execute! tx ...)
(into [] (map :column) (jdbc/plan tx ...)))
(jdbc/execute! con ...)) ; committed
```
You can read more about [working with transactions](/doc/transactions.md) further on in the documentation.
### Prepared Statement Caveat
Not all databases support using a `PreparedStatement` for every type of SQL operation. You might have to create a `java.sql.Statement` instead, directly from a `java.sql.Connection` and use that, without parameters, in `plan`, `execute!`, or `execute-one!`. See the following example:
```clojure
(require '[next.jdbc.prepare :as prep])
(with-open [con (jdbc/get-connection ds)]
(jdbc/execute! (prep/statement con) ["...just a SQL string..."])
(jdbc/execute! con ["...some SQL..." "and" "parameters"]) ; uses PreparedStatement
(into [] (map :column) (jdbc/plan (prep/statement con) ["..."])))
```
## Connection Pooling
`next.jdbc` makes it easy to use either HikariCP or c3p0 for connection pooling.
First, you need to add the connection pooling library as a dependency, e.g.,
```clojure
com.zaxxer/HikariCP {:mvn/version "3.3.1"}
;; or:
com.mchange/c3p0 {:mvn/version "0.9.5.4"}
```
_Check those libraries' documentation for the latest version to use!_
Then import the appropriate classes into your code:
```clojure
(ns my.main
(:require [next.jdbc :as jdbc]
[next.jdbc.connection :as connection])
(:import (com.zaxxer.hikari HikariDataSource)
;; or:
(com.mchange.v2.c3p0 ComboPooledDataSource PooledDataSource)))
```
Finally, create the connection pooled datasource. `db-spec` here contains the regular `next.jdbc` options (`:dbtype`, `:dbname`, and maybe `:host`, `:port`, `:classname` etc -- or the `:jdbcUrl` format mentioned above). Those are used to construct the JDBC URL that is passed into the datasource object (by calling `.setJdbcUrl` on it). You can also specify any of the connection pooling library's options, as mixed case keywords corresponding to any simple setter methods on the class being passed in, e.g., `:connectionTestQuery`, `:maximumPoolSize` (HikariCP), `:maxPoolSize`, `:preferredTestQuery` (c3p0).
Some important notes regarding HikariCP:
* Authentication credentials must use `:username` (if you are using c3p0 or regular, non-pooled, connections, then the db-spec hash map must contain `:user`).
* When using `:dbtype "jtds"`, you must specify `:connectionTestQuery "SELECT 1"` (or some other query to verify the health of a connection) because the jTDS JDBC driver does not implement `.isValid()` so HikariCP requires a specific test query instead (c3p0 does not rely on this method so it works with jTDS without needing `:preferredTestQuery`).
* When using PostgreSQL, and trying to set a default `:schema` via HikariCP, you will need to specify `:connectionInitSql "COMMIT;"` until [this HikariCP issue](https://github.com/brettwooldridge/HikariCP/issues/1369) is addressed.
You will generally want to create the connection pooled datasource at the start of your program (and close it before you exit, although that's not really important since it'll be cleaned up when the JVM shuts down):
```clojure
(defn -main [& args]
(with-open [^HikariDataSource ds (connection/->pool HikariDataSource db-spec)]
(jdbc/execute! ds ...)
(jdbc/execute! ds ...)
(do-other-stuff ds args)
(into [] (map :column) (jdbc/plan ds ...))))
;; or:
(defn -main [& args]
(with-open [^PooledDataSource ds (connection/->pool ComboPooledDataSource db-spec)]
(jdbc/execute! ds ...)
(jdbc/execute! ds ...)
(do-other-stuff ds args)
(into [] (map :column) (jdbc/plan ds ...))))
```
You only need the type hints on `ds` if you plan to call methods on it via Java interop, such as `.close` (or using `with-open` to auto-close it) and you want to avoid reflection.
If you are using [Component](https://github.com/stuartsierra/component), a connection pooled datasource is a good candidate since it has a `start`/`stop` lifecycle:
```clojure
(ns ...
(:require [com.stuartsierra.component :as component]
...))
(defrecord Database [db-spec ^HikariDataSource datasource]
component/Lifecycle
(start [this]
(if datasource
this ; already started
(assoc this :datasource (connection/->pool HikariDataSource db-spec))))
(stop [this]
(if datasource
(do
(.close datasource)
(assoc this :datasource nil))
this))) ; already stopped
(defn -main [& args]
(let [db (component/start (map->Database {:db-spec db-spec}))]
(try
(jdbc/execute! (:datasource db) ...)
(jdbc/execute! (:datasource db) ...)
(do-other-stuff db args)
(into [] (map :column) (jdbc/plan (:datasource db) ...)))
(catch Throwable t)
(component/stop db)))
```
## Working with Additional Data Types
By default, `next.jdbc` relies on the JDBC driver to handle all data type conversions when reading from a result set (to produce Clojure values from SQL values) or setting parameters (to produce SQL values from Clojure values). Sometimes that means that you will get back a database-specific Java object that would need to be manually converted to a Clojure data structure, or that certain database column types require you to manually construct the appropriate database-specific Java object to pass into a SQL operation. You can usually automate those conversions using either the [`ReadableColumn` protocol](/doc/result-set-builders.md#readablecolumn) (for converting database-specific types to Clojure values) or the [`SettableParameter` protocol](/doc/prepared-statements.md#prepared-statement-parameters) (for converting Clojure values to database-specific types).
In particular, PostgreSQL does not seem to perform a conversion from `java.util.Date` to a SQL data type automatically. You must `require` the [`next.jdbc.date-time` namespace](https://cljdoc.org/d/seancorfield/next.jdbc/CURRENT/api/next.jdbc.date-time) to enable that conversion.
If you are working with Java Time, some JDBC drivers will automatically convert `java.time.Instant` (and `java.time.LocalDate` and `java.time.LocalDateTime`) to a SQL data type automatically, but others will not. Requiring `next.jdbc.date-time` will enable those automatic conversions for all databases.
> Note: `next.jdbc.date-time` does **not** provide automatic conversion of SQL data types to Clojure data types when reading result sets. If you want specific conversions to happen automatically, consider extending the `ReadableColumn` protocol, mentioned above.
## Support from Specs
As you are developing with `next.jdbc`, it can be useful to have assistance from `clojure.spec` in checking calls to `next.jdbc`'s functions, to provide explicit argument checking and/or better error messages for some common mistakes, e.g., trying to pass a plain SQL string where a vector (containing a SQL string, and no parameters) is expected.
You can enable argument checking for functions in `next.jdbc`, `next.jdbc.connection`, `next.jdbc.prepare`, and `next.jdbc.sql` by requiring the `next.jdbc.specs` namespace and instrumenting the functions. A convenience function is provided:
```clojure
(require '[next.jdbc.specs :as specs])
(specs/instrument) ; instruments all next.jdbc API functions
(jdbc/execute! ds "SELECT * FROM fruit")
Call to #'next.jdbc/execute! did not conform to spec.
```
In the `:problems` output, you'll see the `:path [:sql :sql-params]` and `:pred vector?` for the `:val "SELECT * FROM fruit"`. Without the specs' assistance, this mistake would produce a more cryptic error, a `ClassCastException`, that a `Character` cannot be cast to a `String`, from inside `next.jdbc.prepare`.
A convenience function also exists to revert that instrumentation:
```clojure
(specs/unstrument) ; undoes the instrumentation of all next.jdbc API functions
```
[Friendly SQL Functions :>](/doc/friendly-sql-functions.md)
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