As NoSQL solutions are getting more and more popular for many kind of problems, more often the modern projects consider to use some (or several) of NoSQLs instead (or side-by-side) of traditional RDBMS. I have already covered my experience with MongoDB in this, this and this posts. In this post I would like to switch gears a bit towards Redis, an advanced key-value store.
Aside from very rich key-value semantics, Redis also supports pub-sub messaging and transactions. In this post I am going just to touch the surface and demonstrate how simple it is to integrate Redis into your Spring application. As always, we will start with Maven POM file for our project:
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemalocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelversion>4.0.0</modelversion>
<groupid>com.example.spring</groupid>
<artifactid>redis</artifactid>
<version>0.0.1-SNAPSHOT</version>
<packaging>jar</packaging>
<properties>
<project.build.sourceencoding>UTF-8</project.build.sourceencoding>
<spring.version>3.1.0.RELEASE</spring.version>
</properties>
<dependencies>
<dependency>
<groupid>org.springframework.data</groupid>
<artifactid>spring-data-redis</artifactid>
<version>1.0.0.RELEASE</version>
</dependency>
<dependency>
<groupid>cglib</groupid>
<artifactid>cglib-nodep</artifactid>
<version>2.2</version>
</dependency>
<dependency>
<groupid>log4j</groupid>
<artifactid>log4j</artifactid>
<version>1.2.16</version>
</dependency>
<dependency>
<groupid>redis.clients</groupid>
<artifactid>jedis</artifactid>
<version>2.0.0</version>
<type>jar</type>
</dependency>
<dependency>
<groupid>org.springframework</groupid>
<artifactid>spring-core</artifactid>
<version>${spring.version}</version>
</dependency>
<dependency>
<groupid>org.springframework</groupid>
<artifactid>spring-context</artifactid>
<version>${spring.version}</version>
</dependency>
</dependencies>
</project>
Spring Data Redis is the another project under Spring Data umbrella which provides seamless injection of Redis into your application. The are several Redis clients for Java and I have chosen the Jedis as it is stable and recommended by Redis team at the moment of writing this post.
We will start with simple configuration and introduce the necessary components first. Then as we move forward, the configuration will be extended a bit to demonstrated pub-sub capabilities. Thanks to Java config support, we will create the configuration class and have all our dependencies strongly typed, no XML anymore:
package com.example.redis.config;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.connection.jedis.JedisConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.serializer.GenericToStringSerializer;
import org.springframework.data.redis.serializer.StringRedisSerializer;
@Configuration
public class AppConfig {
@Bean
JedisConnectionFactory jedisConnectionFactory() {
return new JedisConnectionFactory();
}
@Bean
RedisTemplate< String, Object > redisTemplate() {
final RedisTemplate< String, Object > template = new RedisTemplate< String, Object >();
template.setConnectionFactory( jedisConnectionFactory() );
template.setKeySerializer( new StringRedisSerializer() );
template.setHashValueSerializer( new GenericToStringSerializer< Object >( Object.class ) );
template.setValueSerializer( new GenericToStringSerializer< Object >( Object.class ) );
return template;
}
}
That’s basically everything we need assuming we have single Redis server up and running on localhost with default configuration. Let’s consider several common uses cases: setting a key to some value, storing the object and, finally, pub-sub implementation. Storing and retrieving a key/value pair is very simple:
@Autowired private RedisTemplate< String, Object > template;
public Object getValue( final String key ) {
return template.opsForValue().get( key );
}
public void setValue( final String key, final String value ) {
template.opsForValue().set( key, value );
}
Optionally, the key could be set to expire (yet another useful feature of Redis), f.e. let our keys expire in 1 second:
public void setValue( final String key, final String value ) {
template.opsForValue().set( key, value );
template.expire( key, 1, TimeUnit.SECONDS );
}
Arbitrary objects could be saved into Redis as hashes (maps), f.e. let save instance of some class User
public class User {
private final Long id;
private String name;
private String email;
// Setters and getters are omitted for simplicity
}
into Redis using key pattern “user:<id>”:
public void setUser( final User user ) {
final String key = String.format( "user:%s", user.getId() );
final Map< String, Object > properties = new HashMap< String, Object >();
properties.put( "id", user.getId() );
properties.put( "name", user.getName() );
properties.put( "email", user.getEmail() );
template.opsForHash().putAll( key, properties);
}
Respectively, object could easily be inspected and retrieved using the id.
public User getUser( final Long id ) {
final String key = String.format( "user:%s", id );
final String name = ( String )template.opsForHash().get( key, "name" );
final String email = ( String )template.opsForHash().get( key, "email" );
return new User( id, name, email );
}
There are much, much more which could be done using Redis, I highly encourage to take a look on it. It surely is not a silver bullet but could solve many challenging problems very easy. Finally, let me show how to use a pub-sub messaging with Redis. Let’s add a bit more configuration here (as part of AppConfig class):
@Bean
MessageListenerAdapter messageListener() {
return new MessageListenerAdapter( new RedisMessageListener() );
}
@Bean
RedisMessageListenerContainer redisContainer() {
final RedisMessageListenerContainer container = new RedisMessageListenerContainer();
container.setConnectionFactory( jedisConnectionFactory() );
container.addMessageListener( messageListener(), new ChannelTopic( "my-queue" ) );
return container;
}
The style of message listener definition should look very familiar to Spring users: generally, the same approach we follow to define JMS message listeners. The missed piece is our RedisMessageListener class definition:
package com.example.redis.impl;
import org.springframework.data.redis.connection.Message;
import org.springframework.data.redis.connection.MessageListener;
public class RedisMessageListener implements MessageListener {
@Override
public void onMessage(Message message, byte[] paramArrayOfByte) {
System.out.println( "Received by RedisMessageListener: " + message.toString() );
}
}
Now, when we have our message listener, let see how we could push some messages into the queue using Redis. As always, it’s pretty simple:
@Autowired private RedisTemplate< String, Object > template;
public void publish( final String message ) {
template.execute(
new RedisCallback< Long >() {
@SuppressWarnings( "unchecked" )
@Override
public Long doInRedis( RedisConnection connection ) throws DataAccessException {
return connection.publish(
( ( RedisSerializer< String > )template.getKeySerializer() ).serialize( "queue" ),
( ( RedisSerializer< Object > )template.getValueSerializer() ).serialize( message ) );
}
}
);
}
That’s basically it for very quick introduction but definitely enough to fall in love with Redis.
Reference: Using Redis with Spring from our JCG partner Andrey Redko at the Andriy Redko {devmind} blog.
