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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:

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 specific BindMarkersFactory to configure named parameter to database bind marker translation.

  • ….executeFunction(…): Set the ExecuteFunction how Statement 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 named awaitSingle() for non-nullable return values and awaitSingleOrNull() 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 or awaitOneOrNull() if the value may be null.

  • all() returns all rows of the result. When using Kotlin Coroutines, use flow().

  • rowsUpdated() returns the number of affected rows (INSERT/UPDATE/DELETE count). Its Kotlin Coroutine variant is named awaitRowsUpdated().

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()

Alternatively, there is a shortcut for mapping to a single value:

	Flux<String> names = client.sql("SELECT name FROM person")
			.mapValue(String.class)
			.all();

Or you may map to a result object with bean properties or record components:

	// assuming a name property on Person
	Flux<Person> persons = client.sql("SELECT name FROM person")
			.mapProperties(Person.class)
			.all();
What about null?

Relational database results can contain null values. The Reactive Streams specification forbids the emission of null values. That requirement mandates proper null handling in the extractor function. While you can obtain null values from a Row, you must not emit a null value. You must wrap any null values in an object (for example, Optional for singular values) to make sure a null value is never returned directly by your extractor function.

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);

Alternatively, you may pass in a map of names and values:

	Map<String, Object> params = new LinkedHashMap<>();
	params.put("id", "joe");
	params.put("name", "Joe");
	params.put("age", 34);
	db.sql("INSERT INTO person (id, name, age) VALUES(:id, :name, :age)")
			.bindValues(params);

Or you may pass in a parameter object with bean properties or record components:

	// assuming id, name, age properties on Person
	db.sql("INSERT INTO person (id, name, age) VALUES(:id, :name, :age)")
			.bindProperties(new Person("joe", "Joe", 34);

Alternatively, you can use positional parameters for binding values to statements. Indices are zero based.

    db.sql("INSERT INTO person (id, name, age) VALUES(:id, :name, :age)")
	    	.bind(0, "joe")
	    	.bind(1, "Joe")
			.bind(2, 34);

In case your application is binding to many parameters, the same can be achieved with a single call:

    List<?> values = List.of("joe", "Joe", 34);
    db.sql("INSERT INTO person (id, name, age) VALUES(:id, :name, :age)")
	    	.bindValues(values);
R2DBC Native Bind Markers

R2DBC uses database-native bind markers that depend on the actual database vendor. As an example, Postgres uses indexed markers, such as $1, $2, $n. Another example is SQL Server, which uses named bind markers prefixed with @.

This is different from JDBC which requires ? as bind markers. In JDBC, the actual drivers translate ? bind markers to database-native markers as part of their statement execution.

Spring Framework’s R2DBC support lets you use native bind markers or named bind markers with the :name syntax.

Named parameter support leverages a BindMarkersFactory instance to expand named parameters to native bind markers at the time of query execution, which gives you a certain degree of query portability across various database vendors.

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));
client.sql("SELECT id, name, state FROM table WHERE age IN (:ages)")
	    .bind("ages", 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, for example, for use in IN clauses as shown above. However, inserting or updating array-typed columns (for example, in Postgres) requires an array type that is supported by the underlying R2DBC driver: typically a Java array, for example, 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:

  1. Obtain a connection with ConnectionFactory as you typically obtain an R2DBC ConnectionFactory.

  2. 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.