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Data Access with R2DBC
R2DBC ("Reactive Relational Database Connectivity") is a community-driven specification effort to standardize access to SQL databases using reactive patterns.
Package Hierarchy
The Spring Framework’s R2DBC abstraction framework consists of two different packages:
-
core
: Theorg.springframework.r2dbc.core
package contains theDatabaseClient
class plus a variety of related classes. See Using the R2DBC Core Classes to Control Basic R2DBC Processing and Error Handling. -
connection
: Theorg.springframework.r2dbc.connection
package contains a utility class for easyConnectionFactory
access and various simpleConnectionFactory
implementations that you can use for testing and running unmodified R2DBC. See Controlling Database Connections.
Using the R2DBC Core Classes to Control Basic R2DBC Processing and Error Handling
This section covers how to use the R2DBC core classes to control basic R2DBC processing, including error handling. It includes the following topics:
Using DatabaseClient
DatabaseClient
is the central class in the R2DBC core package. It handles the
creation and release of resources, which helps to avoid common errors, such as
forgetting to close the connection. It performs the basic tasks of the core R2DBC
workflow (such as statement creation and execution), leaving application code to provide
SQL and extract results. The DatabaseClient
class:
-
Runs SQL queries
-
Update statements and stored procedure calls
-
Performs iteration over
Result
instances -
Catches R2DBC exceptions and translates them to the generic, more informative, exception hierarchy defined in the
org.springframework.dao
package. (See Consistent Exception Hierarchy.)
The client has a functional, fluent API using reactive types for declarative composition.
When you use the DatabaseClient
for your code, you need only to implement
java.util.function
interfaces, giving them a clearly defined contract.
Given a Connection
provided by the DatabaseClient
class, a Function
callback creates a Publisher
. The same is true for mapping functions that
extract a Row
result.
You can use DatabaseClient
within a DAO implementation through direct instantiation
with a ConnectionFactory
reference, or you can configure it in a Spring IoC container
and give it to DAOs as a bean reference.
The simplest way to create a DatabaseClient
object is through a static factory method, as follows:
-
Java
-
Kotlin
DatabaseClient client = DatabaseClient.create(connectionFactory);
val client = DatabaseClient.create(connectionFactory)
The ConnectionFactory should always be configured as a bean in the Spring IoC
container.
|
The preceding method creates a DatabaseClient
with default settings.
You can also obtain a Builder
instance from DatabaseClient.builder()
.
You can customize the client by calling the following methods:
-
….bindMarkers(…)
: Supply a specificBindMarkersFactory
to configure named parameter to database bind marker translation. -
….executeFunction(…)
: Set theExecuteFunction
howStatement
objects get run. -
….namedParameters(false)
: Disable named parameter expansion. Enabled by default.
Dialects are resolved by BindMarkersFactoryResolver
from a ConnectionFactory , typically by inspecting ConnectionFactoryMetadata .
You can let Spring auto-discover your BindMarkersFactory by registering a
class that implements org.springframework.r2dbc.core.binding.BindMarkersFactoryResolver$BindMarkerFactoryProvider
through META-INF/spring.factories .
BindMarkersFactoryResolver discovers bind marker provider implementations from
the class path using Spring’s SpringFactoriesLoader .
|
Currently supported databases are:
-
H2
-
MariaDB
-
Microsoft SQL Server
-
MySQL
-
Postgres
All SQL issued by this class is logged at the DEBUG
level under the category
corresponding to the fully qualified class name of the client instance (typically
DefaultDatabaseClient
). Additionally, each execution registers a checkpoint in
the reactive sequence to aid debugging.
The following sections provide some examples of DatabaseClient
usage. These examples
are not an exhaustive list of all of the functionality exposed by the DatabaseClient
.
See the attendant javadoc for that.
Executing Statements
DatabaseClient
provides the basic functionality of running a statement.
The following example shows what you need to include for minimal but fully functional
code that creates a new table:
-
Java
-
Kotlin
Mono<Void> completion = client.sql("CREATE TABLE person (id VARCHAR(255) PRIMARY KEY, name VARCHAR(255), age INTEGER);")
.then();
client.sql("CREATE TABLE person (id VARCHAR(255) PRIMARY KEY, name VARCHAR(255), age INTEGER);")
.await()
DatabaseClient
is designed for convenient, fluent usage.
It exposes intermediate, continuation, and terminal methods at each stage of the
execution specification. The preceding example above uses then()
to return a completion
Publisher
that completes as soon as the query (or queries, if the SQL query contains
multiple statements) completes.
execute(…) accepts either the SQL query string or a query Supplier<String>
to defer the actual query creation until execution.
|
Querying (SELECT
)
SQL queries can return values through Row
objects or the number of affected rows.
DatabaseClient
can return the number of updated rows or the rows themselves,
depending on the issued query.
The following query gets the id
and name
columns from a table:
-
Java
-
Kotlin
Mono<Map<String, Object>> first = client.sql("SELECT id, name FROM person")
.fetch().first();
val first = client.sql("SELECT id, name FROM person")
.fetch().awaitSingle()
The following query uses a bind variable:
-
Java
-
Kotlin
Mono<Map<String, Object>> first = client.sql("SELECT id, name FROM person WHERE first_name = :fn")
.bind("fn", "Joe")
.fetch().first();
val first = client.sql("SELECT id, name FROM person WHERE first_name = :fn")
.bind("fn", "Joe")
.fetch().awaitSingle()
You might have noticed the use of fetch()
in the example above. fetch()
is a
continuation operator that lets you specify how much data you want to consume.
Calling first()
returns the first row from the result and discards remaining rows.
You can consume data with the following operators:
-
first()
return the first row of the entire result. Its Kotlin Coroutine variant is namedawaitSingle()
for non-nullable return values andawaitSingleOrNull()
if the value is optional. -
one()
returns exactly one result and fails if the result contains more rows. Using Kotlin Coroutines,awaitOne()
for exactly one value orawaitOneOrNull()
if the value may benull
. -
all()
returns all rows of the result. When using Kotlin Coroutines, useflow()
. -
rowsUpdated()
returns the number of affected rows (INSERT
/UPDATE
/DELETE
count). Its Kotlin Coroutine variant is namedawaitRowsUpdated()
.
Without specifying further mapping details, queries return tabular results
as Map
whose keys are case-insensitive column names that map to their column value.
You can take control over result mapping by supplying a Function<Row, T>
that gets
called for each Row
so it can return arbitrary values (singular values,
collections and maps, and objects).
The following example extracts the name
column and emits its value:
-
Java
-
Kotlin
Flux<String> names = client.sql("SELECT name FROM person")
.map(row -> row.get("name", String.class))
.all();
val names = client.sql("SELECT name FROM person")
.map{ row: Row -> row.get("name", String.class) }
.flow()
Updating (INSERT
, UPDATE
, and DELETE
) with DatabaseClient
The only difference of modifying statements is that these statements typically
do not return tabular data so you use rowsUpdated()
to consume results.
The following example shows an UPDATE
statement that returns the number
of updated rows:
-
Java
-
Kotlin
Mono<Integer> affectedRows = client.sql("UPDATE person SET first_name = :fn")
.bind("fn", "Joe")
.fetch().rowsUpdated();
val affectedRows = client.sql("UPDATE person SET first_name = :fn")
.bind("fn", "Joe")
.fetch().awaitRowsUpdated()
Binding Values to Queries
A typical application requires parameterized SQL statements to select or
update rows according to some input. These are typically SELECT
statements
constrained by a WHERE
clause or INSERT
and UPDATE
statements that accept
input parameters. Parameterized statements bear the risk of SQL injection if
parameters are not escaped properly. DatabaseClient
leverages R2DBC’s
bind
API to eliminate the risk of SQL injection for query parameters.
You can provide a parameterized SQL statement with the execute(…)
operator
and bind parameters to the actual Statement
. Your R2DBC driver then runs
the statement by using prepared statements and parameter substitution.
Parameter binding supports two binding strategies:
-
By Index, using zero-based parameter indexes.
-
By Name, using the placeholder name.
The following example shows parameter binding for a query:
db.sql("INSERT INTO person (id, name, age) VALUES(:id, :name, :age)")
.bind("id", "joe")
.bind("name", "Joe")
.bind("age", 34);
The query-preprocessor unrolls named Collection
parameters into a series of bind
markers to remove the need of dynamic query creation based on the number of arguments.
Nested object arrays are expanded to allow usage of (for example) select lists.
Consider the following query:
SELECT id, name, state FROM table WHERE (name, age) IN (('John', 35), ('Ann', 50))
The preceding query can be parameterized and run as follows:
-
Java
-
Kotlin
List<Object[]> tuples = new ArrayList<>();
tuples.add(new Object[] {"John", 35});
tuples.add(new Object[] {"Ann", 50});
client.sql("SELECT id, name, state FROM table WHERE (name, age) IN (:tuples)")
.bind("tuples", tuples);
val tuples: MutableList<Array<Any>> = ArrayList()
tuples.add(arrayOf("John", 35))
tuples.add(arrayOf("Ann", 50))
client.sql("SELECT id, name, state FROM table WHERE (name, age) IN (:tuples)")
.bind("tuples", tuples)
Usage of select lists is vendor-dependent. |
The following example shows a simpler variant using IN
predicates:
-
Java
-
Kotlin
client.sql("SELECT id, name, state FROM table WHERE age IN (:ages)")
.bind("ages", Arrays.asList(35, 50));
val tuples: MutableList<Array<Any>> = ArrayList()
tuples.add(arrayOf("John", 35))
tuples.add(arrayOf("Ann", 50))
client.sql("SELECT id, name, state FROM table WHERE age IN (:ages)")
.bind("tuples", arrayOf(35, 50))
R2DBC itself does not support Collection-like values. Nevertheless,
expanding a given List in the example above works for named parameters
in Spring’s R2DBC support, e.g. for use in IN clauses as shown above.
However, inserting or updating array-typed columns (e.g. in Postgres)
requires an array type that is supported by the underlying R2DBC driver:
typically a Java array, e.g. String[] to update a text[] column.
Do not pass Collection<String> or the like as an array parameter.
|
Statement Filters
Sometimes you need to fine-tune options on the actual Statement
before it gets run. To do so, register a Statement
filter
(StatementFilterFunction
) with the DatabaseClient
to intercept and
modify statements in their execution, as the following example shows:
-
Java
-
Kotlin
client.sql("INSERT INTO table (name, state) VALUES(:name, :state)")
.filter((s, next) -> next.execute(s.returnGeneratedValues("id")))
.bind("name", …)
.bind("state", …);
client.sql("INSERT INTO table (name, state) VALUES(:name, :state)")
.filter { s: Statement, next: ExecuteFunction -> next.execute(s.returnGeneratedValues("id")) }
.bind("name", …)
.bind("state", …)
DatabaseClient
also exposes a simplified filter(…)
overload that accepts
a Function<Statement, Statement>
:
-
Java
-
Kotlin
client.sql("INSERT INTO table (name, state) VALUES(:name, :state)")
.filter(statement -> s.returnGeneratedValues("id"));
client.sql("SELECT id, name, state FROM table")
.filter(statement -> s.fetchSize(25));
client.sql("INSERT INTO table (name, state) VALUES(:name, :state)")
.filter { statement -> s.returnGeneratedValues("id") }
client.sql("SELECT id, name, state FROM table")
.filter { statement -> s.fetchSize(25) }
StatementFilterFunction
implementations allow filtering of the
Statement
and filtering of Result
objects.
DatabaseClient
Best Practices
Instances of the DatabaseClient
class are thread-safe, once configured. This is
important because it means that you can configure a single instance of a DatabaseClient
and then safely inject this shared reference into multiple DAOs (or repositories).
The DatabaseClient
is stateful, in that it maintains a reference to a ConnectionFactory
,
but this state is not conversational state.
A common practice when using the DatabaseClient
class is to configure a ConnectionFactory
in your Spring configuration file and then dependency-inject
that shared ConnectionFactory
bean into your DAO classes. The DatabaseClient
is created in
the setter for the ConnectionFactory
. This leads to DAOs that resemble the following:
-
Java
-
Kotlin
public class R2dbcCorporateEventDao implements CorporateEventDao {
private DatabaseClient databaseClient;
public void setConnectionFactory(ConnectionFactory connectionFactory) {
this.databaseClient = DatabaseClient.create(connectionFactory);
}
// R2DBC-backed implementations of the methods on the CorporateEventDao follow...
}
class R2dbcCorporateEventDao(connectionFactory: ConnectionFactory) : CorporateEventDao {
private val databaseClient = DatabaseClient.create(connectionFactory)
// R2DBC-backed implementations of the methods on the CorporateEventDao follow...
}
An alternative to explicit configuration is to use component-scanning and annotation
support for dependency injection. In this case, you can annotate the class with @Component
(which makes it a candidate for component-scanning) and annotate the ConnectionFactory
setter
method with @Autowired
. The following example shows how to do so:
-
Java
-
Kotlin
@Component (1)
public class R2dbcCorporateEventDao implements CorporateEventDao {
private DatabaseClient databaseClient;
@Autowired (2)
public void setConnectionFactory(ConnectionFactory connectionFactory) {
this.databaseClient = DatabaseClient.create(connectionFactory); (3)
}
// R2DBC-backed implementations of the methods on the CorporateEventDao follow...
}
1 | Annotate the class with @Component . |
2 | Annotate the ConnectionFactory setter method with @Autowired . |
3 | Create a new DatabaseClient with the ConnectionFactory . |
@Component (1)
class R2dbcCorporateEventDao(connectionFactory: ConnectionFactory) : CorporateEventDao { (2)
private val databaseClient = DatabaseClient(connectionFactory) (3)
// R2DBC-backed implementations of the methods on the CorporateEventDao follow...
}
1 | Annotate the class with @Component . |
2 | Constructor injection of the ConnectionFactory . |
3 | Create a new DatabaseClient with the ConnectionFactory . |
Regardless of which of the above template initialization styles you choose to use (or
not), it is seldom necessary to create a new instance of a DatabaseClient
class each
time you want to run SQL. Once configured, a DatabaseClient
instance is thread-safe.
If your application accesses multiple
databases, you may want multiple DatabaseClient
instances, which requires multiple
ConnectionFactory
and, subsequently, multiple differently configured DatabaseClient
instances.
Retrieving Auto-generated Keys
INSERT
statements may generate keys when inserting rows into a table
that defines an auto-increment or identity column. To get full control over
the column name to generate, simply register a StatementFilterFunction
that
requests the generated key for the desired column.
-
Java
-
Kotlin
Mono<Integer> generatedId = client.sql("INSERT INTO table (name, state) VALUES(:name, :state)")
.filter(statement -> s.returnGeneratedValues("id"))
.map(row -> row.get("id", Integer.class))
.first();
// generatedId emits the generated key once the INSERT statement has finished
val generatedId = client.sql("INSERT INTO table (name, state) VALUES(:name, :state)")
.filter { statement -> s.returnGeneratedValues("id") }
.map { row -> row.get("id", Integer.class) }
.awaitOne()
// generatedId emits the generated key once the INSERT statement has finished
Controlling Database Connections
This section covers:
Using ConnectionFactory
Spring obtains an R2DBC connection to the database through a ConnectionFactory
.
A ConnectionFactory
is part of the R2DBC specification and is a common entry-point
for drivers. It lets a container or a framework hide connection pooling
and transaction management issues from the application code. As a developer,
you need not know details about how to connect to the database. That is the
responsibility of the administrator who sets up the ConnectionFactory
. You
most likely fill both roles as you develop and test code, but you do not
necessarily have to know how the production data source is configured.
When you use Spring’s R2DBC layer, you can configure your own with a
connection pool implementation provided by a third party. A popular
implementation is R2DBC Pool (r2dbc-pool
). Implementations in the Spring
distribution are meant only for testing purposes and do not provide pooling.
To configure a ConnectionFactory
:
-
Obtain a connection with
ConnectionFactory
as you typically obtain an R2DBCConnectionFactory
. -
Provide an R2DBC URL (See the documentation for your driver for the correct value).
The following example shows how to configure a ConnectionFactory
:
-
Java
-
Kotlin
ConnectionFactory factory = ConnectionFactories.get("r2dbc:h2:mem:///test?options=DB_CLOSE_DELAY=-1;DB_CLOSE_ON_EXIT=FALSE");
val factory = ConnectionFactories.get("r2dbc:h2:mem:///test?options=DB_CLOSE_DELAY=-1;DB_CLOSE_ON_EXIT=FALSE");
Using ConnectionFactoryUtils
The ConnectionFactoryUtils
class is a convenient and powerful helper class
that provides static
methods to obtain connections from ConnectionFactory
and close connections (if necessary).
It supports subscriber Context
-bound connections with, for example
R2dbcTransactionManager
.
Using SingleConnectionFactory
The SingleConnectionFactory
class is an implementation of DelegatingConnectionFactory
interface that wraps a single Connection
that is not closed after each use.
If any client code calls close
on the assumption of a pooled connection (as when using
persistence tools), you should set the suppressClose
property to true
. This setting
returns a close-suppressing proxy that wraps the physical connection. Note that you can
no longer cast this to a native Connection
or a similar object.
SingleConnectionFactory
is primarily a test class and may be used for specific requirements
such as pipelining if your R2DBC driver permits for such use.
In contrast to a pooled ConnectionFactory
, it reuses the same connection all the time, avoiding
excessive creation of physical connections.
Using TransactionAwareConnectionFactoryProxy
TransactionAwareConnectionFactoryProxy
is a proxy for a target ConnectionFactory
.
The proxy wraps that target ConnectionFactory
to add awareness of Spring-managed transactions.
Using this class is required if you use a R2DBC client that is not integrated otherwise
with Spring’s R2DBC support. In this case, you can still use this client and, at
the same time, have this client participating in Spring managed transactions. It is generally
preferable to integrate a R2DBC client with proper access to ConnectionFactoryUtils
for resource management.
|
See the TransactionAwareConnectionFactoryProxy
javadoc for more details.
Using R2dbcTransactionManager
The R2dbcTransactionManager
class is a ReactiveTransactionManager
implementation for
a single R2DBC ConnectionFactory
. It binds an R2DBC Connection
from the specified
ConnectionFactory
to the subscriber Context
, potentially allowing for one subscriber
Connection
for each ConnectionFactory
.
Application code is required to retrieve the R2DBC Connection
through
ConnectionFactoryUtils.getConnection(ConnectionFactory)
, instead of R2DBC’s standard
ConnectionFactory.create()
. All framework classes (such as DatabaseClient
) use this
strategy implicitly. If not used with a transaction manager, the lookup strategy behaves
exactly like ConnectionFactory.create()
and can therefore be used in any case.