© 2011-2016 The original authors.
Copies of this document may be made for your own use and for distribution to others, provided that you do not charge any fee for such copies and further provided that each copy contains this Copyright Notice, whether distributed in print or electronically. |
- Preface
- Introduction
- Reference Documentation
- 5. Redis support
- 5.1. Redis Requirements
- 5.2. Redis Support High Level View
- 5.3. Connecting to Redis
- 5.4. Redis Sentinel Support
- 5.5. Working with Objects through RedisTemplate
- 5.6. String-focused convenience classes
- 5.7. Serializers
- 5.8. Hash mapping
- 5.9. Redis Messaging/PubSub
- 5.10. Redis Transactions
- 5.11. Pipelining
- 5.12. Redis Scripting
- 5.13. Support Classes
- 6. Reactive Redis support
- 7. Redis Cluster
- 8. Redis Repositories
- 5. Redis support
- Appendixes
Preface
1. New Features
New and noteworthy in the latest releases.
1.1. New in Spring Data Redis 2.0
-
Upgrade to Java 8.
-
Upgrade to Lettuce 5.0.
-
Removed support for SRP and JRedis drivers.
-
Introduce Redis feature-specific interfaces for
RedisConnection
. -
Improved
RedisConnectionFactory
configuration viaJedisClientConfiguration
andLettuceClientConfiguration
. -
Revised
RedisCache
implementation. -
Add
SPOP
with count command for Redis 3.2.
1.2. New in Spring Data Redis 1.8
-
Upgrade to Jedis 2.9.
-
Upgrade to
Lettuce
4.2 (Note: Lettuce 4.2 requires Java 8). -
Support for Redis GEO commands.
-
Support for Geospatial Indexes using Spring Data Repository abstractions (see Geospatial Index).
-
MappingRedisConverter
basedHashMapper
implementation (see Hash mapping). -
Support for
PartialUpdate
in repository support (see Persisting Partial Updates). -
SSL support for connections to Redis cluster.
-
Support for
client name
viaConnectionFactory
when using Jedis.
1.3. New in Spring Data Redis 1.7
-
Support for RedisCluster.
-
Support for Spring Data Repository abstractions (see Redis Repositories).
1.4. New in Spring Data Redis 1.6
-
The
Lettuce
Redis driver switched from wg/lettuce to mp911de/lettuce. -
Support for
ZRANGEBYLEX
. -
Enhanced range operations for
ZSET
s including+inf
/-inf
. -
Performance improvements in
RedisCache
now releasing connections earlier. -
Generic Jackson2
RedisSerializer
making use of Jackson’s polymorphic deserialization.
1.5. New in Spring Data Redis 1.5
-
Add support for Redis HyperLogLog commands
PFADD
,PFCOUNT
andPFMERGE
. -
Configurable
JavaType
lookup for Jackson basedRedisSerializers
. -
PropertySource
based configuration for connecting to Redis Sentinel (see: Redis Sentinel Support).
Introduction
This document is the reference guide for Spring Data Redis (SDR) Support. It explains Key Value module concepts and semantics and the syntax for various stores namespaces.
For an introduction to key value stores or Spring, or Spring Data examples, please refer to Getting Started - this documentation refers only to Spring Data Redis Support and assumes the user is familiar with the key value storages and Spring concepts.
2. Why Spring Data Redis?
The Spring Framework is the leading full-stack Java/JEE application framework. It provides a lightweight container and a non-invasive programming model enabled by the use of dependency injection, AOP, and portable service abstractions.
NoSQL storages provide an alternative to classical RDBMS for horizontal scalability and speed. In terms of implementation, Key Value stores represent one of the largest (and oldest) members in the NoSQL space.
The Spring Data Redis (or SDR) framework makes it easy to write Spring applications that use the Redis key value store by eliminating the redundant tasks and boiler plate code required for interacting with the store through Spring’s excellent infrastructure support.
3. Requirements
Spring Data Redis 1.x binaries requires JDK level 6.0 and above, and Spring Framework 5.0.2.RELEASE and above.
In terms of key value stores, Redis 2.6.x or higher is required. Spring Data Redis is currently tested against the latest 3.2 release.
4. Getting Started
Learning a new framework is not always straight forward. In this section, we (the Spring Data team) tried to provide, what we think is, an easy to follow guide for starting with the Spring Data Redis module. Of course, feel free to create your own learning 'path' as you see fit and, if possible, please report back any improvements to the documentation that can help others.
4.1. First Steps
As explained in Why Spring Data Redis?, Spring Data Redis (SDR) provides integration between Spring framework and the Redis key value store. Thus, it is important to become acquainted with both of these frameworks (storages or environments depending on how you want to name them). Throughout the SDR documentation, each section provides links to resources relevant however, it is best to become familiar with these topics beforehand.
4.1.1. Knowing Spring
Spring Data uses heavily Spring framework’s core functionality, such as the IoC container, resource abstract or AOP infrastructure. While it is not important to know the Spring APIs, understanding the concepts behind them is. At a minimum, the idea behind IoC should be familiar. That being said, the more knowledge one has about the Spring, the faster she will pick up Spring Data Redis. Besides the very comprehensive (and sometimes disarming) documentation that explains in detail the Spring Framework, there are a lot of articles, blog entries and books on the matter - take a look at the Spring Guides home page for more information. In general, this should be the starting point for developers wanting to try Spring DR.
4.1.2. Knowing NoSQL and Key Value stores
NoSQL stores have taken the storage world by storm. It is a vast domain with a plethora of solutions, terms and patterns (to make things worse even the term itself has multiple meanings). While some of the principles are common, it is crucial that the user is familiar to some degree with the stores supported by SDR. The best way to get acquainted with these solutions is to read their documentation and follow their examples - it usually doesn’t take more then 5-10 minutes to go through them and if you are coming from an RDMBS-only background many times these exercises can be an eye opener.
4.1.3. Trying Out The Samples
One can find various samples for key value stores in the dedicated example repo, at http://github.com/spring-projects/spring-data-keyvalue-examples. For Spring Data Redis, of interest is the retwisj
sample, a Twitter-clone built on top of Redis which can be run locally or be deployed into the cloud. See its documentation, the following blog entry or the live instance for more information.
4.2. Need Help?
If you encounter issues or you are just looking for advice, feel free to use one of the links below:
4.2.1. Community Support
The Spring Data tag on Stackoverflow is a message board for all Spring Data (not just Redis) users to share information and help each other. Note that registration is needed only for posting.
4.2.2. Professional Support
Professional, from-the-source support, with guaranteed response time, is available from Pivotal Software, Inc., the company behind Spring Data and Spring.
4.3. Following Development
For information on the Spring Data source code repository, nightly builds and snapshot artifacts please see the Spring Data home page.
You can help make Spring Data best serve the needs of the Spring community by interacting with developers on Stackoverflow at either spring-data or spring-data-redis.
If you encounter a bug or want to suggest an improvement, please create a ticket on the Spring Data issue tracker.
To stay up to date with the latest news and announcements in the Spring eco system, subscribe to the Spring Community Portal.
Lastly, you can follow the Spring blog or the project team (@SpringData) on Twitter.
Reference Documentation
Document structure
This part of the reference documentation explains the core functionality offered by Spring Data Redis.
Redis support introduces the Redis module feature set.
5. Redis support
One of the key value stores supported by Spring Data is Redis. To quote the project home page:
Redis is an advanced key-value store. It is similar to memcached but the dataset is not volatile, and values can be strings, exactly like in memcached, but also lists, sets, and ordered sets. All this data types can be manipulated with atomic operations to push/pop elements, add/remove elements, perform server side union, intersection, difference between sets, and so forth. Redis supports different kind of sorting abilities.
Spring Data Redis provides easy configuration and access to Redis from Spring applications. It offers both low-level and high-level abstractions for interacting with the store, freeing the user from infrastructural concerns.
5.2. Redis Support High Level View
The Redis support provides several components (in order of dependencies):
For most tasks, the high-level abstractions and support services are the best choice. Note that at any point, one can move between layers - for example, it’s very easy to get a hold of the low level connection (or even the native library) to communicate directly with Redis.
5.3. Connecting to Redis
One of the first tasks when using Redis and Spring is to connect to the store through the IoC container. To do that, a Java connector (or binding) is required. No matter the library one chooses, there is only one set of Spring Data Redis API that one needs to use that behaves consistently across all connectors, namely the org.springframework.data.redis.connection
package and its RedisConnection
and RedisConnectionFactory
interfaces for working with and retrieving active connections
to Redis.
5.3.1. RedisConnection and RedisConnectionFactory
RedisConnection
provides the building block for Redis communication as it handles the communication with the Redis back-end. It also automatically translates the underlying connecting library exceptions to Spring’s consistent DAO exception hierarchy so one can switch the connectors without any code changes as the operation semantics remain the same.
For the corner cases where the native library API is required, RedisConnection provides a dedicated method getNativeConnection which returns the raw, underlying object used for communication.
|
Active RedisConnection
s are created through RedisConnectionFactory
. In addition, the factories act as PersistenceExceptionTranslator
s, meaning once declared, they allow one to do transparent exception translation. For example, exception translation through the use of the @Repository
annotation and AOP. For more information see the dedicated section in Spring Framework documentation.
Depending on the underlying configuration, the factory can return a new connection or an existing connection (in case a pool or shared native connection is used). |
The easiest way to work with a RedisConnectionFactory
is to configure the appropriate connector through the IoC container and inject it into the using class.
Unfortunately, currently, not all connectors support all Redis features. When invoking a method on the Connection API that is unsupported by the underlying library, an UnsupportedOperationException is thrown.
This situation is likely to be fixed in the future, as the various connectors mature.
|
5.3.2. Configuring Jedis connector
Jedis is one of the connectors supported by the Spring Data Redis module through the org.springframework.data.redis.connection.jedis
package. In its simplest form, the Jedis configuration looks as follow:
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd">
<!-- Jedis ConnectionFactory -->
<bean id="jedisConnectionFactory" class="org.springframework.data.redis.connection.jedis.JedisConnectionFactory"/>
</beans>
For production use however, one might want to tweak the settings such as the host or password:
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:p="http://www.springframework.org/schema/p"
xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd">
<bean id="jedisConnectionFactory" class="org.springframework.data.redis.connection.jedis.JedisConnectionFactory" p:host-name="server" p:port="6379" />
</beans>
5.3.3. Configuring Lettuce connector
Lettuce is a netty-based open-source connector supported by Spring Data Redis through the org.springframework.data.redis.connection.lettuce
package.
Its configuration is probably easy to guess:
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:p="http://www.springframework.org/schema/p"
xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd">
<bean id="lettuceConnectionFactory" class="org.springframework.data.redis.connection.lettuce.LettuceConnectionFactory" p:host-name="server" p:port="6379"/>
</beans>
There are also a few Lettuce-specific connection parameters that can be tweaked. By default, all LettuceConnection
s created by the LettuceConnectionFactory
share the same thread-safe native connection for all non-blocking and non-transactional operations. Set shareNativeConnection
to false to use a dedicated connection each time. LettuceConnectionFactory
can also be configured with a LettucePool
to use for pooling blocking and transactional connections, or all connections if shareNativeConnection
is set to false.
5.4. Redis Sentinel Support
For dealing with high available Redis there is support for Redis Sentinel using RedisSentinelConfiguration
.
/**
* jedis
*/
@Bean
public RedisConnectionFactory jedisConnectionFactory() {
RedisSentinelConfiguration sentinelConfig = new RedisSentinelConfiguration()
.master("mymaster")
.sentinel("127.0.0.1", 26379)
.sentinel("127.0.0.1", 26380);
return new JedisConnectionFactory(sentinelConfig);
}
/**
* Lettuce
*/
@Bean
public RedisConnectionFactory lettuceConnectionFactory() {
RedisSentinelConfiguration sentinelConfig = new RedisSentinelConfiguration()
.master("mymaster")
.sentinel("127.0.0.1", 26379)
.sentinel("127.0.0.1", 26380);
return new LettuceConnectionFactory(sentinelConfig);
}
Configuration Properties
|
Sometimes direct interaction with the one of the Sentinels is required. Using RedisConnectionFactory.getSentinelConnection()
or RedisConnection.getSentinelCommands()
gives you access to the first active Sentinel configured.
5.5. Working with Objects through RedisTemplate
Most users are likely to use RedisTemplate
and its corresponding package org.springframework.data.redis.core
- the template is in fact the central class of the Redis module due to its rich feature set. The template offers a high-level abstraction for Redis interactions. While RedisConnection
offers low level methods that accept and return binary values (byte
arrays), the template takes care of serialization and connection management, freeing the user from dealing with such details.
Moreover, the template provides operations views (following the grouping from Redis command reference) that offer rich, generified interfaces for working against a certain type or certain key (through the KeyBound
interfaces) as described below:
Interface | Description |
---|---|
Key Type Operations |
|
GeoOperations |
Redis geospatial operations like |
HashOperations |
Redis hash operations |
HyperLogLogOperations |
Redis HyperLogLog operations like ( |
ListOperations |
Redis list operations |
SetOperations |
Redis set operations |
ValueOperations |
Redis string (or value) operations |
ZSetOperations |
Redis zset (or sorted set) operations |
Key Bound Operations |
|
BoundGeoOperations |
Redis key bound geospatial operations. |
BoundHashOperations |
Redis hash key bound operations |
BoundKeyOperations |
Redis key bound operations |
BoundListOperations |
Redis list key bound operations |
BoundSetOperations |
Redis set key bound operations |
BoundValueOperations |
Redis string (or value) key bound operations |
BoundZSetOperations |
Redis zset (or sorted set) key bound operations |
Once configured, the template is thread-safe and can be reused across multiple instances.
Out of the box, RedisTemplate
uses a Java-based serializer for most of its operations. This means that any object written or read by the template will be serialized/deserialized through Java. The serialization mechanism can be easily changed on the template, and the Redis module offers several implementations available in the org.springframework.data.redis.serializer
package - see Serializers for more information. You can also set any of the serializers to null and use RedisTemplate with raw byte
arrays by setting the enableDefaultSerializer
property to false. Note that the template requires all keys to be non-null - values can be null as long as the underlying serializer accepts them; read the javadoc of each serializer for more information.
For cases where a certain template view is needed, declare the view as a dependency and inject the template: the container will automatically perform the conversion eliminating the opsFor[X]
calls:
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:p="http://www.springframework.org/schema/p"
xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd">
<bean id="jedisConnectionFactory" class="org.springframework.data.redis.connection.jedis.JedisConnectionFactory" p:use-pool="true"/>
<!-- redis template definition -->
<bean id="redisTemplate" class="org.springframework.data.redis.core.RedisTemplate" p:connection-factory-ref="jedisConnectionFactory"/>
...
</beans>
public class Example {
// inject the actual template
@Autowired
private RedisTemplate<String, String> template;
// inject the template as ListOperations
@Resource(name="redisTemplate")
private ListOperations<String, String> listOps;
public void addLink(String userId, URL url) {
listOps.leftPush(userId, url.toExternalForm());
}
}
5.6. String-focused convenience classes
Since it’s quite common for the keys and values stored in Redis to be java.lang.String
, the Redis modules provides two extensions to RedisConnection
and RedisTemplate
, respectively the StringRedisConnection
(and its DefaultStringRedisConnection
implementation) and StringRedisTemplate
as a convenient one-stop solution for intensive String operations. In addition to being bound to String
keys, the template and the connection use the StringRedisSerializer
underneath which means the stored keys and values are human readable (assuming the same encoding is used both in Redis and your code). For example:
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:p="http://www.springframework.org/schema/p"
xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd">
<bean id="jedisConnectionFactory" class="org.springframework.data.redis.connection.jedis.JedisConnectionFactory" p:use-pool="true"/>
<bean id="stringRedisTemplate" class="org.springframework.data.redis.core.StringRedisTemplate" p:connection-factory-ref="jedisConnectionFactory"/>
...
</beans>
public class Example {
@Autowired
private StringRedisTemplate redisTemplate;
public void addLink(String userId, URL url) {
redisTemplate.opsForList().leftPush(userId, url.toExternalForm());
}
}
As with the other Spring templates, RedisTemplate
and StringRedisTemplate
allow the developer to talk directly to Redis through the RedisCallback
interface. This gives complete control to the developer as it talks directly to the RedisConnection
. Note that the callback receives an instance of StringRedisConnection
when a StringRedisTemplate
is used.
public void useCallback() {
redisTemplate.execute(new RedisCallback<Object>() {
public Object doInRedis(RedisConnection connection) throws DataAccessException {
Long size = connection.dbSize();
// Can cast to StringRedisConnection if using a StringRedisTemplate
((StringRedisConnection)connection).set("key", "value");
}
});
}
5.7. Serializers
From the framework perspective, the data stored in Redis is just bytes. While Redis itself supports various types, for the most part these refer to the way the data is stored rather than what it represents. It is up to the user to decide whether the information gets translated into Strings or any other objects.
The conversion between the user (custom) types and raw data (and vice-versa) is handled in Spring Data Redis in the org.springframework.data.redis.serializer
package.
This package contains two types of serializers which as the name implies, takes care of the serialization process:
-
Two-way serializers based on`RedisSerializer`.
-
Element readers and writers using
RedisElementReader
andRedisElementWriter
.
The main difference between these variants is that RedisSerializer
primarily serializes to byte[]
while readers and writers use ByteBuffer
.
Multiple implementations are available out of the box, two of which have been already mentioned before in this documentation:
-
the
StringRedisSerializer
-
JdkSerializationRedisSerializer
However one can use OxmSerializer
for Object/XML mapping through Spring OXM support or either Jackson2JsonRedisSerializer
or GenericJackson2JsonRedisSerializer
for storing data in JSON format.
Do note that the storage format is not limited only to values - it can be used for keys, values or hashes without any restrictions.
5.8. Hash mapping
Data can be stored using various data structures within Redis. You already learned about Jackson2JsonRedisSerializer
which can convert objects
in JSON format. JSON can be ideally stored as value using plain keys. A more sophisticated mapping of structured objects
can be achieved using Redis Hashes. Spring Data Redis offers various strategies for mapping data to hashes depending on the use case.
-
Direct mapping using
HashOperations
and a serializer -
Using Redis Repositories
-
Using
HashMapper
andHashOperations
5.8.1. Hash mappers
Hash mappers are converters to map objects to a Map<K, V>
and back. HashMapper
is intended for using with Redis Hashes.
Multiple implementations are available out of the box:
-
BeanUtilsHashMapper
using Spring’s BeanUtils. -
ObjectHashMapper
using Object to Hash Mapping.
public class Person {
String firstname;
String lastname;
// …
}
public class HashMapping {
@Autowired
HashOperations<String, byte[], byte[]> hashOperations;
HashMapper<Object, byte[], byte[]> mapper = new ObjectHashMapper();
public void writeHash(String key, Person person) {
Map<byte[], byte[]> mappedHash = mapper.toHash(person);
hashOperations.putAll(key, mappedHash);
}
public Person loadHash(String key) {
Map<byte[], byte[]> loadedHash = hashOperations.entries("key");
return (Person) mapper.fromHash(loadedHash);
}
}
5.8.2. Jackson2HashMapper
Jackson2HashMapper
provides Redis Hash mapping for domain objects using FasterXML Jackson.
Jackson2HashMapper
can map data map top-level properties as Hash field names and optionally flatten the structure.
Simple types map to simple values. Complex types (nested objects, collections, maps) are represented as nested JSON.
Flattening creates individual hash entries for all nested properties and resolves complex types into simple types, as far as possible.
public class Person {
String firstname;
String lastname;
Address address;
}
public class Address {
String city;
String country;
}
Hash Field | Value |
---|---|
firstname |
|
lastname |
|
address |
|
Hash Field | Value |
---|---|
firstname |
|
lastname |
|
address.city |
|
address.country |
|
Flattening requires all property names to not interfere with the JSON path. Using dots or brackets in map keys or as property names is not supported using flattening. The resulting hash cannot be mapped back into an Object. |
5.9. Redis Messaging/PubSub
Spring Data provides dedicated messaging integration for Redis, very similar in functionality and naming to the JMS integration in Spring Framework; in fact, users familiar with the JMS support in Spring should feel right at home.
Redis messaging can be roughly divided into two areas of functionality, namely the production or publication and consumption or subscription of messages, hence the shortcut pubsub (Publish/Subscribe). The RedisTemplate
class is used for message production. For asynchronous reception similar to Java EE’s message-driven bean style, Spring Data provides a dedicated message listener container that is used to create Message-Driven POJOs (MDPs) and for synchronous reception, the RedisConnection
contract.
The package org.springframework.data.redis.connection
and org.springframework.data.redis.listener
provide the core functionality for using Redis messaging.
5.9.1. Sending/Publishing messages
To publish a message, one can use, as with the other operations, either the low-level RedisConnection
or the high-level RedisTemplate
. Both entities offer the publish
method that accepts as an argument the message that needs to be sent as well as the destination channel. While RedisConnection
requires raw-data (array of bytes), the RedisTemplate
allow arbitrary objects to be passed in as messages:
// send message through connection RedisConnection con = ...
byte[] msg = ...
byte[] channel = ...
con.publish(msg, channel); // send message through RedisTemplate
RedisTemplate template = ...
template.convertAndSend("hello!", "world");
5.9.2. Receiving/Subscribing for messages
On the receiving side, one can subscribe to one or multiple channels either by naming them directly or by using pattern matching. The latter approach is quite useful as it not only allows multiple subscriptions to be created with one command but to also listen on channels not yet created at subscription time (as long as they match the pattern).
At the low-level, RedisConnection
offers subscribe
and pSubscribe
methods that map the Redis commands for subscribing by channel respectively by pattern. Note that multiple channels or patterns can be used as arguments. To change the subscription of a connection or simply query whether it is listening or not, RedisConnection
provides getSubscription
and isSubscribed
method.
Subscription commands in Spring Data Redis are blocking. That is, calling subscribe on a connection will cause the current thread to block as it will start waiting for messages - the thread will be released only if the subscription is canceled, that is an additional thread invokes unsubscribe or pUnsubscribe on the same connection. See message listener container below for a solution to this problem.
|
As mentioned above, once subscribed a connection starts waiting for messages. No other commands can be invoked on it except for adding new subscriptions or modifying/canceling the existing ones. That is, invoking anything other then subscribe
, pSubscribe
, unsubscribe
, or pUnsubscribe
is illegal and will throw an exception.
In order to subscribe for messages, one needs to implement the MessageListener
callback: each time a new message arrives, the callback gets invoked and the user code executed through onMessage
method. The interface gives access not only to the actual message but to the channel it has been received through and the pattern (if any) used by the subscription to match the channel. This information allows the callee to differentiate between various messages not just by content but also through data.
Message Listener Containers
Due to its blocking nature, low-level subscription is not attractive as it requires connection and thread management for every single listener. To alleviate this problem, Spring Data offers RedisMessageListenerContainer
which does all the heavy lifting on behalf of the user - users familiar with EJB and JMS should find the concepts familiar as it is designed as close as possible to the support in Spring Framework and its message-driven POJOs (MDPs)
RedisMessageListenerContainer
acts as a message listener container; it is used to receive messages from a Redis channel and drive the MessageListener
s that are injected into it. The listener container is responsible for all threading of message reception and dispatches into the listener for processing. A message listener container is the intermediary between an MDP and a messaging provider, and takes care of registering to receive messages, resource acquisition and release, exception conversion and the like. This allows you as an application developer to write the (possibly complex) business logic associated with receiving a message (and reacting to it), and delegates boilerplate Redis infrastructure concerns to the framework.
Furthermore, to minimize the application footprint, RedisMessageListenerContainer
allows one connection and one thread to be shared by multiple listeners even though they do not share a subscription. Thus no matter how many listeners or channels an application tracks, the runtime cost will remain the same through out its lifetime. Moreover, the container allows runtime configuration changes so one can add or remove listeners while an application is running without the need for restart. Additionally, the container uses a lazy subscription approach, using a RedisConnection
only when needed - if all the listeners are unsubscribed, cleanup is automatically performed and the used thread released.
To help with the asynch manner of messages, the container requires a java.util.concurrent.Executor
( or Spring’s TaskExecutor
) for dispatching the messages. Depending on the load, the number of listeners or the runtime environment, one should change or tweak the executor to better serve her needs - in particular in managed environments (such as app servers), it is highly recommended to pick a a proper TaskExecutor
to take advantage of its runtime.
The MessageListenerAdapter
The MessageListenerAdapter
class is the final component in Spring’s asynchronous messaging support: in a nutshell, it allows you to expose almost any class as a MDP (there are of course some constraints).
Consider the following interface definition. Notice that although the interface doesn’t extend the MessageListener
interface, it can still be used as a MDP via the use of the MessageListenerAdapter
class. Notice also how the various message handling methods are strongly typed according to the contents of the various Message
types that they can receive and handle. In addition, the channel or pattern to which a message is sent can be passed in to the method as the second argument of type String:
public interface MessageDelegate {
void handleMessage(String message);
void handleMessage(Map message); void handleMessage(byte[] message);
void handleMessage(Serializable message);
// pass the channel/pattern as well
void handleMessage(Serializable message, String channel);
}
public class DefaultMessageDelegate implements MessageDelegate {
// implementation elided for clarity...
}
In particular, note how the above implementation of the MessageDelegate
interface (the above DefaultMessageDelegate
class) has no Redis dependencies at all. It truly is a POJO that we will make into an MDP via the following configuration.
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:redis="http://www.springframework.org/schema/redis"
xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd
http://www.springframework.org/schema/redis http://www.springframework.org/schema/redis/spring-redis.xsd">
<!-- the default ConnectionFactory -->
<redis:listener-container>
<!-- the method attribute can be skipped as the default method name is "handleMessage" -->
<redis:listener ref="listener" method="handleMessage" topic="chatroom" />
</redis:listener-container>
<bean id="listener" class="redisexample.DefaultMessageDelegate"/>
...
<beans>
The listener topic can be either a channel (e.g. topic="chatroom" ) or a pattern (e.g. topic="*room" )
|
The example above uses the Redis namespace to declare the message listener container and automatically register the POJOs as listeners. The full blown, beans definition is displayed below:
<bean id="messageListener" class="org.springframework.data.redis.listener.adapter.MessageListenerAdapter">
<constructor-arg>
<bean class="redisexample.DefaultMessageDelegate"/>
</constructor-arg>
</bean>
<bean id="redisContainer" class="org.springframework.data.redis.listener.RedisMessageListenerContainer">
<property name="connectionFactory" ref="connectionFactory"/>
<property name="messageListeners">
<map>
<entry key-ref="messageListener">
<bean class="org.springframework.data.redis.listener.ChannelTopic">
<constructor-arg value="chatroom">
</bean>
</entry>
</map>
</property>
</bean>
Each time a message is received, the adapter automatically performs translation (using the configured RedisSerializer
) between the low-level format and the required object type transparently. Any exception caused by the method invocation is caught and handled by the container (by default, being logged).
5.10. Redis Transactions
Redis provides support for transactions through the multi
, exec
, and discard
commands. These operations are available on RedisTemplate
, however RedisTemplate
is not guaranteed to execute all operations in the transaction using the same connection.
Spring Data Redis provides the SessionCallback
interface for use when multiple operations need to be performed with the same connection
, as when using Redis transactions. For example:
//execute a transaction
List<Object> txResults = redisTemplate.execute(new SessionCallback<List<Object>>() {
public List<Object> execute(RedisOperations operations) throws DataAccessException {
operations.multi();
operations.opsForSet().add("key", "value1");
// This will contain the results of all ops in the transaction
return operations.exec();
}
});
System.out.println("Number of items added to set: " + txResults.get(0));
RedisTemplate
will use its value, hash key, and hash value serializers to deserialize all results of exec
before returning. There is an additional exec
method that allows you to pass a custom serializer for transaction results.
An important change has been made to the exec methods of RedisConnection and RedisTemplate in version 1.1. Previously these methods returned the results of transactions directly from the connectors. This means that the data types often differed from those returned from the methods of RedisConnection . For example, zAdd returns a boolean indicating that the element has been added to the sorted set. Most connectors return this value as a long and Spring Data Redis performs the conversion. Another common difference is that most connectors return a status reply (usually the String "OK") for operations like set . These replies are typically discarded by Spring Data Redis. Prior to 1.1, these conversions were not performed on the results of exec . Also, results were not deserialized in RedisTemplate , so they often included raw byte arrays. If this change breaks your application, you can set convertPipelineAndTxResults to false on your RedisConnectionFactory to disable this behavior.
|
5.10.1. @Transactional Support
Transaction Support is disabled by default and has to be explicitly enabled for each RedisTemplate
in use by setting setEnableTransactionSupport(true)
. This will force binding the RedisConnection
in use to the current Thread
triggering MULTI
. If the transaction finishes without errors, EXEC
is called, otherwise DISCARD
. Once in MULTI
, RedisConnection
would queue write operations, all readonly
operations, such as KEYS
are piped to a fresh (non thread bound) RedisConnection
.
/** Sample Configuration **/
@Configuration
public class RedisTxContextConfiguration {
@Bean
public StringRedisTemplate redisTemplate() {
StringRedisTemplate template = new StringRedisTemplate(redisConnectionFactory());
// explicitly enable transaction support
template.setEnableTransactionSupport(true);
return template;
}
@Bean
public PlatformTransactionManager transactionManager() throws SQLException {
return new DataSourceTransactionManager(dataSource());
}
@Bean
public RedisConnectionFactory redisConnectionFactory( // jedis || lettuce);
@Bean
public DataSource dataSource() throws SQLException { // ... }
}
/** Usage Constrainsts **/
// executed on thread bound connection
template.opsForValue().set("foo", "bar");
// read operation executed on a free (not tx-aware)
connection template.keys("*");
// returns null as values set within transaction are not visible
template.opsForValue().get("foo");
5.11. Pipelining
Redis provides support for pipelining, which involves sending multiple commands to the server without waiting for the replies and then reading the replies in a single step. Pipelining can improve performance when you need to send several commands in a row, such as adding many elements to the same List.
Spring Data Redis provides several RedisTemplate
methods for executing commands in a pipeline. If you don’t care about the results of the pipelined operations, you can use the standard execute
method, passing true
for the pipeline
argument. The executePipelined
methods will execute the provided RedisCallback
or SessionCallback
in a pipeline and return the results. For example:
//pop a specified number of items from a queue
List<Object> results = stringRedisTemplate.executePipelined(
new RedisCallback<Object>() {
public Object doInRedis(RedisConnection connection) throws DataAccessException {
StringRedisConnection stringRedisConn = (StringRedisConnection)connection;
for(int i=0; i< batchSize; i++) {
stringRedisConn.rPop("myqueue");
}
return null;
}
});
The example above executes a bulk right pop of items from a queue in a pipeline. The results
List contains all of the popped items. RedisTemplate
uses its value, hash key, and hash value serializers to deserialize all results before returning, so the returned items in the above example will be Strings. There are additional executePipelined
methods that allow you to pass a custom serializer for pipelined results.
Note that the value returned from the RedisCallback
is required to be null, as this value is discarded in favor of returning the results of the pipelined commands.
An important change has been made to the closePipeline method of RedisConnection in version 1.1. Previously this method returned the results of pipelined operations directly from the connectors. This means that the data types often differed from those returned by the methods of RedisConnection . For example, zAdd returns a boolean indicating that the element has been added to the sorted set. Most connectors return this value as a long and Spring Data Redis performs the conversion. Another common difference is that most connectors return a status reply (usually the String "OK") for operations like set . These replies are typically discarded by Spring Data Redis. Prior to 1.1, these conversions were not performed on the results of closePipeline . If this change breaks your application, you can set convertPipelineAndTxResults to false on your RedisConnectionFactory to disable this behavior.
|
5.12. Redis Scripting
Redis versions 2.6 and higher provide support for execution of Lua scripts through the eval and evalsha commands. Spring Data Redis provides a high-level abstraction for script execution that handles serialization and automatically makes use of the Redis script cache.
Scripts can be run through the execute
methods of RedisTemplate
and ReactiveRedisTemplate
. Both use a configurable ScriptExecutor
/ ReactiveScriptExecutor
to run the provided script. By default, the ScriptExecutor
takes care of serializing the provided keys and arguments and deserializing the script result. This is done via the key and value serializers of the template. There is an additional overload that allows you to pass custom serializers for the script arguments and result.
The default ScriptExecutor
optimizes performance by retrieving the SHA1 of the script and attempting first to run evalsha
, falling back to eval
if the script is not yet present in the Redis script cache.
Here’s an example that executes a common "check-and-set" scenario using a Lua script. This is an ideal use case for a Redis script, as it requires that we execute a set of commands atomically and the behavior of one command is influenced by the result of another.
@Bean
public RedisScript<Boolean> script() {
ScriptSource scriptSource = new ResourceScriptSource(new ClassPathResource("META-INF/scripts/checkandset.lua");
return RedisScript.of(scriptSource, Boolean.class);
}
public class Example {
@Autowired
RedisScript<Boolean> script;
public boolean checkAndSet(String expectedValue, String newValue) {
return redisTemplate.execute(script, singletonList("key"), asList(expectedValue, newValue));
}
}
-- checkandset.lua local
current = redis.call('GET', KEYS[1])
if current == ARGV[1]
then redis.call('SET', KEYS[1], ARGV[2])
return true
end
return false
The code above configures a RedisScript
pointing to a file called checkandset.lua
, which is expected to return a boolean value. The script resultType
should be one of Long
, Boolean
, List
, or deserialized value type. It can also be null
if the script returns a throw-away status (i.e "OK"). It is ideal to configure a single instance of DefaultRedisScript
in your application context to avoid re-calculation of the script’s SHA1 on every script execution.
The checkAndSet method above then executes th
Scripts can be executed within a SessionCallback
as part of a transaction or pipeline. See Redis Transactions and Pipelining for more information.
The scripting support provided by Spring Data Redis also allows you to schedule Redis scripts for periodic execution using the Spring Task and Scheduler abstractions. See the Spring Framework
documentation for more details.
5.13. Support Classes
Package org.springframework.data.redis.support
offers various reusable components that rely on Redis as a backing store. Currently the package contains various JDK-based
interface implementations on top of Redis such as atomic counters and JDK
Collections.
The atomic counters make it easy to wrap Redis key incrementation while the collections allow easy management of Redis keys with minimal storage exposure or API
leakage: in particular the RedisSet
and RedisZSet
interfaces offer easy access to the set operations supported by Redis such as intersection
and union
while RedisList
implements the List
, Queue
and Deque
contracts (and their equivalent blocking siblings) on top of Redis, exposing the storage as a
FIFO (First-In-First-Out), LIFO (Last-In-First-Out) or capped collection with minimal configuration:
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:p="http://www.springframework.org/schema/p" xsi:schemaLocation="
http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd">
<bean id="queue" class="org.springframework.data.redis.support.collections.DefaultRedisList">
<constructor-arg ref="redisTemplate"/>
<constructor-arg value="queue-key"/>
</bean>
</beans>
public class AnotherExample {
// injected
private Deque<String> queue;
public void addTag(String tag) {
queue.push(tag);
}
}
As shown in the example above, the consuming code is decoupled from the actual storage implementation - in fact there is no indication that Redis is used underneath. This makes moving from development to production environments transparent and highly increases testability (the Redis implementation can just as well be replaced with an in-memory one).
5.13.1. Support for Spring Cache Abstraction
Changed in 2.0 |
Spring Redis provides an implementation for Spring cache abstraction through the org.springframework.data.redis.cache
package. To use Redis as a backing implementation, simply add RedisCacheManager
to your configuration:
@Bean
public RedisCacheManager cacheManager(RedisConnectionFactory connectionFactory) {
return RedisCacheManager.create(connectionFactory);
}
RedisCacheManager
behavior can be configured via RedisCacheManagerBuilder
allowing to set the default RedisCacheConfiguration
, transaction behaviour and predefined caches.
RedisCacheManager cm = RedisCacheManager.builder(connectionFactory)
.cacheDefaults(defaultCacheConfig())
.initialCacheConfigurations(singletonMap("predefined", defaultCacheConfig().disableCachingNullValues()))
.transactionAware()
.build();
Behavior of RedisCache
created via RedisCacheManager
is defined via RedisCacheConfiguration
. The configuration allows to set key expiration times, prefixes and RedisSerializer
s for converting to and from the binary storage format.
As shown above RedisCacheManager
allows definition of configurations on a per cache base.
RedisCacheConfiguration config = RedisCacheConfiguration.defaultCacheConfig()
.entryTtl(Duration.ofSeconds(1))
.disableCachingNullValues();
RedisCacheManager
defaults to a lock-free RedisCacheWriter
for reading & writing binary values. Lock-free caching improves throughput. The lack of entry locking can lead to overlapping, non atomic commands, for putIfAbsent
and clean
methods as those require multiple commands sent to Redis.
The locking counterpart prevents command overlap by setting an explicit lock key and checking against presence of this key, which leads to additional requests and potential command wait times.
It is possible to opt in to the locking behavior as follows:
RedisCacheManager cm = RedisCacheManager.build(RedisCacheWriter.lockingRedisCacheWriter())
.cacheDefaults(defaultCacheConfig())
...
Setting | Value |
---|---|
Cache Writer |
non locking |
Cache Configuration |
|
Initial Caches |
none |
Trasaction Aware |
no |
Key Expiration | none |
---|---|
Cache |
yes |
Prefix Keys |
yes |
Default Prefix |
the actual cache name |
Key Serializer |
|
Value Serializer |
|
Conversion Service |
|
6. Reactive Redis support
This section covers reactive Redis support and how to get started. You will find certain overlaps with the imperative Redis support.
6.1. Redis Requirements
Spring Data Redis requires Redis 2.6 or above and Java SE 8.0 or above. In terms of language bindings (or connectors), Spring Data Redis currently integrates with Lettuce as the only reactive Java connector. Project Reactor is used as reactive composition library.
6.2. Connecting to Redis using a reactive driver
One of the first tasks when using Redis and Spring is to connect to the store through the IoC container. To do that, a Java connector (or binding) is required. No matter the library one chooses, there is only one set of Spring Data Redis API that one needs to use that behaves consistently across all connectors, namely the org.springframework.data.redis.connection
package and its ReactiveRedisConnection
and ReactiveRedisConnectionFactory
interfaces for working with and retrieving active connections
to Redis.
6.2.1. Redis Operation Modes
Redis can be run as standalone server, with Redis Sentinel or in Redis Cluster mode. Lettuce supports all above mentioned connection types.
6.2.2. ReactiveRedisConnection and ReactiveRedisConnectionFactory
ReactiveRedisConnection
provides the building block for Redis communication as it handles the communication with the Redis back-end. It also automatically translates the underlying driver exceptions to Spring’s consistent DAO exception hierarchy so one can switch the connectors without any code changes as the operation semantics remain the same.
Active ReactiveRedisConnection
s are created through ReactiveRedisConnectionFactory
. In addition, the factories act as PersistenceExceptionTranslator
s, meaning once declared, they allow one to do transparent exception translation. For example, exception translation through the use of the @Repository
annotation and AOP. For more information see the dedicated section in Spring Framework documentation.
Depending on the underlying configuration, the factory can return a new connection or an existing connection (in case a pool or shared native connection is used). |
The easiest way to work with a ReactiveRedisConnectionFactory
is to configure the appropriate connector through the IoC container and inject it into the using class.
6.2.3. Configuring Lettuce connector
Lettuce is supported by Spring Data Redis through the org.springframework.data.redis.connection.lettuce
package.
Setting up ReactiveRedisConnectionFactory
for Lettuce can be done as follows:
@Bean
public ReactiveRedisConnectionFactory connectionFactory() {
return new LettuceConnectionFactory("localhost", 6379);
}
A more sophisticated configuration, including SSL and timeouts, using LettuceClientConfigurationBuilder
might look like below:
@Bean
public ReactiveRedisConnectionFactory lettuceConnectionFactory() {
LettuceClientConfiguration clientConfig = LettuceClientConfiguration.builder()
.useSsl().and()
.commandTimeout(Duration.ofSeconds(2))
.shutdownTimeout(Duration.ZERO)
.build();
return new LettuceConnectionFactory(new RedisStandaloneConfiguration("localhost", 6379), clientConfig);
}
For more detailed client configuration tweaks have a look at LettuceClientConfiguration
.
6.3. Working with Objects through ReactiveRedisTemplate
Most users are likely to use ReactiveRedisTemplate
and its corresponding package org.springframework.data.redis.core
- the template is in fact the central class of the Redis module due to its rich feature set. The template offers a high-level abstraction for Redis interactions. While ReactiveRedisConnection
offers low level methods that accept and return binary values (ByteBuffer
), the template takes care of serialization and connection management, freeing the user from dealing with such details.
Moreover, the template provides operation views (following the grouping from Redis command reference) that offer rich, generified interfaces for working against a certain type as described below:
Interface | Description |
---|---|
Key Type Operations |
|
ReactiveGeoOperations |
Redis geospatial operations like |
ReactiveHashOperations |
Redis hash operations |
ReactiveHyperLogLogOperations |
Redis HyperLogLog operations like ( |
ReactiveListOperations |
Redis list operations |
ReactiveSetOperations |
Redis set operations |
ReactiveValueOperations |
Redis string (or value) operations |
ReactiveZSetOperations |
Redis zset (or sorted set) operations |
Once configured, the template is thread-safe and can be reused across multiple instances.
Out of the box, ReactiveRedisTemplate
uses a Java-based serializer for most of its operations. This means that any object written or read by the template will be serialized/deserialized through RedisElementWriter
respective RedisElementReader
. The serialization context is passed to the template upon construction, and the Redis module offers several implementations available in the org.springframework.data.redis.serializer
package - see Serializers for more information.
@Configuration
class RedisConfiguration {
@Bean
ReactiveRedisTemplate<String, String> reactiveRedisTemplate(ReactiveRedisConnectionFactory factory) {
return new ReactiveRedisTemplate<>(connectionFactory, RedisSerializationContext.string());
}
}
public class Example {
@Autowired
private ReactiveRedisTemplate<String, String> template;
public Mono<Long> addLink(String userId, URL url) {
return template.opsForList().leftPush(userId, url.toExternalForm());
}
}
6.4. Reactive Scripting
Executing Redis scripts via the reactive infrastructure can be done using the ReactiveScriptExecutor
accessed best via ReactiveRedisTemplate
.
public class Example {
@Autowired
private ReactiveRedisTemplate<String, String> template;
public Flux<Long> theAnswerToLife() {
DefaultRedisScript<Long> script = new DefaultRedisScript<>();
script.setLocation(new ClassPathResource("META-INF/scripts/42.lua"));
script.setResultType(Long.class);
return reactiveTemplate.execute(script);
}
}
Please refer to the scripting section for more details on scripting commands.
7. Redis Cluster
Working with Redis Cluster requires a Redis Server version 3.0+ and provides a very own set of features and capabilities. Please refer to the Cluster Tutorial for more information.
7.1. Enabling Redis Cluster
Cluster support is based on the very same building blocks as non clustered communication. RedisClusterConnection
an extension to RedisConnection
handles the communication with the Redis Cluster and translates errors into the Spring DAO exception hierarchy.
RedisClusterConnection
's are created via the RedisConnectionFactory
which has to be set up with the according RedisClusterConfiguration
.
@Component
@ConfigurationProperties(prefix = "spring.redis.cluster")
public class ClusterConfigurationProperties {
/*
* spring.redis.cluster.nodes[0] = 127.0.0.1:7379
* spring.redis.cluster.nodes[1] = 127.0.0.1:7380
* ...
*/
List<String> nodes;
/**
* Get initial collection of known cluster nodes in format {@code host:port}.
*
* @return
*/
public List<String> getNodes() {
return nodes;
}
public void setNodes(List<String> nodes) {
this.nodes = nodes;
}
}
@Configuration
public class AppConfig {
/**
* Type safe representation of application.properties
*/
@Autowired ClusterConfigurationProperties clusterProperties;
public @Bean RedisConnectionFactory connectionFactory() {
return new JedisConnectionFactory(
new RedisClusterConfiguration(clusterProperties.getNodes()));
}
}
Configuration Properties
|
The initial configuration points driver libraries to an initial set of cluster nodes. Changes resulting from live cluster reconfiguration will only be kept in the native driver and not be written back to the configuration. |
7.2. Working With Redis Cluster Connection
As mentioned above Redis Cluster behaves different from single node Redis or even a Sentinel monitored master slave environment. This is reasoned by the automatic sharding that maps a key to one of 16384 slots which are distributed across the nodes. Therefore commands that involve more than one key must assert that all keys map to the exact same slot in order to avoid cross slot execution errors.
Further on, hence a single cluster node, only serves a dedicated set of keys, commands issued against one particular server only return results for those keys served by the server. As a very simple example take the KEYS
command. When issued to a server in cluster environment it only returns the keys served by the node the request is sent to and not necessarily all keys within the cluster. So to get all keys in cluster environment it is necessary to read the keys from at least all known master nodes.
While redirects for to a specific keys to the corresponding slot serving node are handled by the driver libraries, higher level functions like collecting information across nodes, or sending commands to all nodes in the cluster that are covered by RedisClusterConnection
. Picking up the keys example from just before, this means, that the keys(pattern)
method picks up every master node in cluster and simultaneously executes the KEYS
command on every single one, while picking up the results and returning the cumulated set of keys. To just request the keys of a single node RedisClusterConnection
provides overloads for those (like keys(node, pattern)
).
A RedisClusterNode
can be obtained from RedisClusterConnection.clusterGetNodes
or it can be constructed using either host and port or the node Id.
[email protected]:7379 > cluster nodes
6b38bb... 127.0.0.1:7379 master - 0 0 25 connected 0-5460 (1)
7bb78c... 127.0.0.1:7380 master - 0 1449730618304 2 connected 5461-10922 (2)
164888... 127.0.0.1:7381 master - 0 1449730618304 3 connected 10923-16383 (3)
b8b5ee... 127.0.0.1:7382 slave 6b38bb... 0 1449730618304 25 connected (4)
RedisClusterConnection connection = connectionFactory.getClusterConnnection();
connection.set("foo", value); (5)
connection.set("bar", value); (6)
connection.keys("*"); (7)
connection.keys(NODE_7379, "*"); (8)
connection.keys(NODE_7380, "*"); (9)
connection.keys(NODE_7381, "*"); (10)
connection.keys(NODE_7382, "*"); (11)
1 | Master node serving slots 0 to 5460 replicated to slave at 7382 |
2 | Master node serving slots 5461 to 10922 |
3 | Master node serving slots 10923 to 16383 |
4 | Slave node holding replicates of master at 7379 |
5 | Request routed to node at 7381 serving slot 12182 |
6 | Request routed to node at 7379 serving slot 5061 |
7 | Request routed to nodes at 7379, 7380, 7381 → [foo, bar] |
8 | Request routed to node at 7379 → [bar] |
9 | Request routed to node at 7380 → [] |
10 | Request routed to node at 7381 → [foo] |
11 | Request routed to node at 7382 → [bar] |
Cross slot requests such as MGET
are automatically served by the native driver library when all keys map to the same slot. However once this is not the case RedisClusterConnection
executes multiple parallel GET
commands against the slot serving nodes and again returns a cumulated result. Obviously this is less performing than the single slot execution and therefore should be used with care. In doubt please consider pinning keys to the same slot by providing a prefix in curly brackets like {my-prefix}.foo
and {my-prefix}.bar
which will both map to the same slot number.
[email protected]:7379 > cluster nodes
6b38bb... 127.0.0.1:7379 master - 0 0 25 connected 0-5460 (1)
7bb...
RedisClusterConnection connection = connectionFactory.getClusterConnnection();
connection.set("foo", value); // slot: 12182
connection.set("{foo}.bar", value); // slot: 12182
connection.set("bar", value); // slot: 5461
connection.mGet("foo", "{foo}.bar"); (2)
connection.mGet("foo", "bar"); (3)
1 | Same Configuration as in the sample before. |
2 | Keys map to same slot → 127.0.0.1:7381 MGET foo {foo}.bar |
3 | Keys map to different slots and get split up into single slot ones routed to the according nodes → 127.0.0.1:7379 GET bar → 127.0.0.1:7381 GET foo |
The above provided simple examples to demonstrate the general strategy followed by Spring Data Redis. Be aware that some operations might require loading huge amounts of data into memory in order to compute the desired command. Additionally not all cross slot requests can safely be ported to multiple single slot requests and will error if misused (eg. PFCOUNT ).
|
7.3. Working With RedisTemplate and ClusterOperations
Please refer to the section Working with Objects through RedisTemplate to read about general purpose, configuration and usage of RedisTemplate
.
Please be careful when setting up RedisTemplate#keySerializer using any of the JSON RedisSerializers as changing json structure has immediate influence on hash slot calculation.
|
RedisTemplate
provides access to cluster specific operations via the ClusterOperations
interface that can be obtained via RedisTemplate.opsForCluster()
. This allows to execute commands explicitly on a single node within the cluster while retaining de-/serialization features configured for the template and provides administrative commands such as CLUSTER MEET
or more high level operations for eg. resharding.
ClusterOperations clusterOps = redisTemplate.opsForCluster();
clusterOps.shutdown(NODE_7379); (1)
1 | Shut down node at 7379 and cross fingers there is a slave in place that can take over. |
8. Redis Repositories
Working with Redis Repositories allows to seamlessly convert and store domain objects in Redis Hashes, apply custom mapping strategies and make use of secondary indexes.
Redis Repositories requires at least Redis Server version 2.8.0. |
8.1. Usage
To access domain entities stored in a Redis you can leverage repository support that eases implementing those quite significantly.
@RedisHash("persons")
public class Person {
@Id String id;
String firstname;
String lastname;
Address address;
}
We have a pretty simple domain object here. Note that it has a property named id
annotated with org.springframework.data.annotation.Id
and a @RedisHash
annotation on its type.
Those two are responsible for creating the actual key used to persist the hash.
Properties annotated with @Id as well as those named id are considered as the identifier properties. Those with the annotation are favored over others.
|
To now actually have a component responsible for storage and retrieval we need to define a repository interface.
public interface PersonRepository extends CrudRepository<Person, String> {
}
As our repository extends CrudRepository
it provides basic CRUD and finder operations. The thing we need in between to glue things together is the according Spring configuration.
@Configuration
@EnableRedisRepositories
public class ApplicationConfig {
@Bean
public RedisConnectionFactory connectionFactory() {
return new JedisConnectionFactory();
}
@Bean
public RedisTemplate<?, ?> redisTemplate() {
RedisTemplate<byte[], byte[]> template = new RedisTemplate<byte[], byte[]>();
return template;
}
}
Given the setup above we can go on and inject PersonRepository
into our components.
@Autowired PersonRepository repo;
public void basicCrudOperations() {
Person rand = new Person("rand", "al'thor");
rand.setAddress(new Address("emond's field", "andor"));
repo.save(rand); (1)
repo.findOne(rand.getId()); (2)
repo.count(); (3)
repo.delete(rand); (4)
}
1 | Generates a new id if current value is null or reuses an already set id value and stores properties of type Person inside the Redis Hash with key with pattern keyspace:id in this case eg. persons:5d67b7e1-8640-4475-beeb-c666fab4c0e5 . |
2 | Uses the provided id to retrieve the object stored at keyspace:id . |
3 | Counts the total number of entities available within the keyspace persons defined by @RedisHash on Person . |
4 | Removes the key for the given object from Redis. |
8.2. Object to Hash Mapping
The Redis Repository support persists Objects in Hashes. This requires an Object to Hash conversion which is done by a RedisConverter
. The default implementation uses Converter
for mapping property values to and from Redis native byte[]
.
Given the Person
type from the previous sections the default mapping looks like the following:
_class = org.example.Person (1)
id = e2c7dcee-b8cd-4424-883e-736ce564363e
firstname = rand (2)
lastname = al’thor
address.city = emond's field (3)
address.country = andor
1 | The _class attribute is included on root level as well as on any nested interface or abstract types. |
2 | Simple property values are mapped by path. |
3 | Properties of complex types are mapped by their dot path. |
Type | Sample | Mapped Value |
---|---|---|
Simple Type |
String firstname = "rand"; |
firstname = "rand" |
Complex Type |
Address adress = new Address("emond’s field"); |
address.city = "emond’s field" |
List |
List<String> nicknames = asList("dragon reborn", "lews therin"); |
nicknames.[0] = "dragon reborn", |
Map |
Map<String, String> atts = asMap({"eye-color", "grey"}, {"… |
atts.[eye-color] = "grey", |
List |
List<Address> addresses = asList(new Address("em… |
addresses.[0].city = "emond’s field", |
Map |
Map<String, Address> addresses = asMap({"home", new Address("em… |
addresses.[home].city = "emond’s field", |
Mapping behavior can be customized by registering the according Converter
in RedisCustomConversions
. Those converters can take care of converting from/to a single byte[]
as well as Map<String,byte[]>
whereas the first one is suitable for eg. converting one complex type to eg. a binary JSON representation that still uses the default mappings hash structure. The second option offers full control over the resulting hash. Writing objects to a Redis hash will delete the content from the hash and re-create the whole hash, so not mapped data will be lost.
@WritingConverter
public class AddressToBytesConverter implements Converter<Address, byte[]> {
private final Jackson2JsonRedisSerializer<Address> serializer;
public AddressToBytesConverter() {
serializer = new Jackson2JsonRedisSerializer<Address>(Address.class);
serializer.setObjectMapper(new ObjectMapper());
}
@Override
public byte[] convert(Address value) {
return serializer.serialize(value);
}
}
@ReadingConverter
public class BytesToAddressConverter implements Converter<byte[], Address> {
private final Jackson2JsonRedisSerializer<Address> serializer;
public BytesToAddressConverter() {
serializer = new Jackson2JsonRedisSerializer<Address>(Address.class);
serializer.setObjectMapper(new ObjectMapper());
}
@Override
public Address convert(byte[] value) {
return serializer.deserialize(value);
}
}
Using the above byte[] Converter
produces eg.
_class = org.example.Person
id = e2c7dcee-b8cd-4424-883e-736ce564363e
firstname = rand
lastname = al’thor
address = { city : "emond's field", country : "andor" }
@WritingConverter
public class AddressToMapConverter implements Converter<Address, Map<String,byte[]>> {
@Override
public Map<String,byte[]> convert(Address source) {
return singletonMap("ciudad", source.getCity().getBytes());
}
}
@ReadingConverter
public class MapToAddressConverter implements Converter<Address, Map<String, byte[]>> {
@Override
public Address convert(Map<String,byte[]> source) {
return new Address(new String(source.get("ciudad")));
}
}
Using the above Map Converter
produces eg.
_class = org.example.Person
id = e2c7dcee-b8cd-4424-883e-736ce564363e
firstname = rand
lastname = al’thor
ciudad = "emond's field"
Custom conversions have no effect on index resolution. Secondary Indexes will still be created even for custom converted types. |
8.3. Keyspaces
Keyspaces define prefixes used to create the actual key for the Redis Hash.
By default the prefix is set to getClass().getName()
. This default can be altered via @RedisHash
on aggregate root level or by setting up a programmatic configuration. However, the annotated keyspace supersedes any other configuration.
@Configuration
@EnableRedisRepositories(keyspaceConfiguration = MyKeyspaceConfiguration.class)
public class ApplicationConfig {
//... RedisConnectionFactory and RedisTemplate Bean definitions omitted
public static class MyKeyspaceConfiguration extends KeyspaceConfiguration {
@Override
protected Iterable<KeyspaceSettings> initialConfiguration() {
return Collections.singleton(new KeyspaceSettings(Person.class, "persons"));
}
}
}
@Configuration
@EnableRedisRepositories
public class ApplicationConfig {
//... RedisConnectionFactory and RedisTemplate Bean definitions omitted
@Bean
public RedisMappingContext keyValueMappingContext() {
return new RedisMappingContext(
new MappingConfiguration(
new MyKeyspaceConfiguration(), new IndexConfiguration()));
}
public static class MyKeyspaceConfiguration extends KeyspaceConfiguration {
@Override
protected Iterable<KeyspaceSettings> initialConfiguration() {
return Collections.singleton(new KeyspaceSettings(Person.class, "persons"));
}
}
}
8.4. Secondary Indexes
Secondary indexes are used to enable lookup operations based on native Redis structures. Values are written to the according indexes on every save and are removed when objects are deleted or expire.
8.4.1. Simple Property Index
Given the sample Person
entity we can create an index for firstname by annotating the property with @Indexed
.
@RedisHash("persons")
public class Person {
@Id String id;
@Indexed String firstname;
String lastname;
Address address;
}
Indexes are built up for actual property values. Saving two Persons eg. "rand" and "aviendha" results in setting up indexes like below.
SADD persons:firstname:rand e2c7dcee-b8cd-4424-883e-736ce564363e
SADD persons:firstname:aviendha a9d4b3a0-50d3-4538-a2fc-f7fc2581ee56
It is also possible to have indexes on nested elements. Assume Address
has a city property that is annotated with @Indexed
. In that case, once person.address.city
is not null
, we have Sets for each city.
SADD persons:address.city:tear e2c7dcee-b8cd-4424-883e-736ce564363e
Further more the programmatic setup allows to define indexes on map keys and list properties.
@RedisHash("persons")
public class Person {
// ... other properties omitted
Map<String,String> attributes; (1)
Map<String Person> relatives; (2)
List<Address> addresses; (3)
}
1 | SADD persons:attributes.map-key:map-value e2c7dcee-b8cd-4424-883e-736ce564363e |
2 | SADD persons:relatives.map-key.firstname:tam e2c7dcee-b8cd-4424-883e-736ce564363e |
3 | SADD persons:addresses.city:tear e2c7dcee-b8cd-4424-883e-736ce564363e |
Indexes will not be resolved on References. |
Same as with keyspaces it is possible to configure indexes without the need of annotating the actual domain type.
@Configuration
@EnableRedisRepositories(indexConfiguration = MyIndexConfiguration.class)
public class ApplicationConfig {
//... RedisConnectionFactory and RedisTemplate Bean definitions omitted
public static class MyIndexConfiguration extends IndexConfiguration {
@Override
protected Iterable<IndexDefinition> initialConfiguration() {
return Collections.singleton(new SimpleIndexDefinition("persons", "firstname"));
}
}
}
@Configuration
@EnableRedisRepositories
public class ApplicationConfig {
//... RedisConnectionFactory and RedisTemplate Bean definitions omitted
@Bean
public RedisMappingContext keyValueMappingContext() {
return new RedisMappingContext(
new MappingConfiguration(
new KeyspaceConfiguration(), new MyIndexConfiguration()));
}
public static class MyIndexConfiguration extends IndexConfiguration {
@Override
protected Iterable<IndexDefinition> initialConfiguration() {
return Collections.singleton(new SimpleIndexDefinition("persons", "firstname"));
}
}
}
8.4.2. Geospatial Index
Assume the Address
type contains a property location
of type Point
that holds the geo coordinates of the particular address. By annotating the property with @GeoIndexed
those values will be added using Redis GEO
commands.
@RedisHash("persons")
public class Person {
Address address;
// ... other properties omitted
}
public class Address {
@GeoIndexed Point location;
// ... other properties omitted
}
public interface PersonRepository extends CrudRepository<Person, String> {
List<Person> findByAddressLocationNear(Point point, Distance distance); (1)
List<Person> findByAddressLocationWithin(Circle circle); (2)
}
Person rand = new Person("rand", "al'thor");
rand.setAddress(new Address(new Point(13.361389D, 38.115556D)));
repository.save(rand); (3)
repository.findByAddressLocationNear(new Point(15D, 37D), new Distance(200)); (4)
1 | Query method declaration on nested property using Point and Distance. |
2 | Query method declaration on nested property using Circle to search within. |
3 | GEOADD persons:address:location 13.361389 38.115556 e2c7dcee-b8cd-4424-883e-736ce564363e |
4 | GEORADIUS persons:address:location 15.0 37.0 200.0 km |
In the above example the lon/lat values are stored using GEOADD
using the objects id
as the member’s name. The finder methods allow usage of Circle
or Point, Distance
combinations for querying those values.
It is not possible to combine near /within with other criteria.
|
8.5. Time To Live
Objects stored in Redis may only be valid for a certain amount of time. This is especially useful for persisting short lived objects in Redis without having to remove them manually when they reached their end of life.
The expiration time in seconds can be set via @RedisHash(timeToLive=…)
as well as via KeyspaceSettings
(see Keyspaces).
More flexible expiration times can be set by using the @TimeToLive
annotation on either a numeric property or method. However do not apply @TimeToLive
on both a method and a property within the same class.
public class TimeToLiveOnProperty {
@Id
private String id;
@TimeToLive
private Long expiration;
}
public class TimeToLiveOnMethod {
@Id
private String id;
@TimeToLive
public long getTimeToLive() {
return new Random().nextLong();
}
}
Annotating a property explicitly with @TimeToLive will read back the actual TTL or PTTL value from Redis. -1 indicates that the object has no expire associated.
|
The repository implementation ensures subscription to Redis keyspace notifications via RedisMessageListenerContainer
.
When the expiration is set to a positive value the according EXPIRE
command is executed.
Additionally to persisting the original, a phantom copy is persisted in Redis and set to expire 5 minutes after the original one. This is done to enable the Repository support to publish RedisKeyExpiredEvent
holding the expired value via Springs ApplicationEventPublisher
whenever a key expires even though the original values have already been gone. Expiry events
will be received on all connected applications using Spring Data Redis repositories.
By default, the key expiry listener is disabled when initializing the application. The startup mode can be adjusted in @EnableRedisRepositories
or RedisKeyValueAdapter
to start the listener with the application or upon the first insert of an entity with a TTL. See EnableKeyspaceEvents
for possible values.
The RedisKeyExpiredEvent
will hold a copy of the actually expired domain object as well as the key.
Delaying or disabling the expiry event listener startup impacts RedisKeyExpiredEvent publishing.
A disabled event listener will not publish expiry events. A delayed startup can cause loss of events because the delayed
listener initialization.
|
The keyspace notification message listener will alter notify-keyspace-events settings in Redis if those are not already set. Existing settings will not be overridden, so it is left to the user to set those up correctly when not leaving them empty. Please note that CONFIG is disabled on AWS ElastiCache and enabling the listener leads to an error.
|
Redis Pub/Sub messages are not persistent. If a key expires while the application is down the expiry event will not be processed which may lead to secondary indexes containing still references to the expired object. |
8.6. Persisting References
Marking properties with @Reference
allows storing a simple key reference instead of copying values into the hash itself.
On loading from Redis, references are resolved automatically and mapped back into the object.
_class = org.example.Person
id = e2c7dcee-b8cd-4424-883e-736ce564363e
firstname = rand
lastname = al’thor
mother = persons:a9d4b3a0-50d3-4538-a2fc-f7fc2581ee56 (1)
1 | Reference stores the whole key (keyspace:id ) of the referenced object. |
Referenced Objects are not subject of persisting changes when saving the referencing object. Please make sure to persist changes on referenced objects separately, since only the reference will be stored. Indexes set on properties of referenced types will not be resolved. |
8.7. Persisting Partial Updates
In some cases it is not necessary to load and rewrite the entire entity just to set a new value within it. A session timestamp for last active time might be such a scenario where you just want to alter one property.
PartialUpdate
allows to define set
and delete
actions on existing objects while taking care of updating potential expiration times of the entity itself as well as index structures.
PartialUpdate<Person> update = new PartialUpdate<Person>("e2c7dcee", Person.class)
.set("firstname", "mat") (1)
.set("address.city", "emond's field") (2)
.del("age"); (3)
template.update(update);
update = new PartialUpdate<Person>("e2c7dcee", Person.class)
.set("address", new Address("caemlyn", "andor")) (4)
.set("attributes", singletonMap("eye-color", "grey")); (5)
template.update(update);
update = new PartialUpdate<Person>("e2c7dcee", Person.class)
.refreshTtl(true); (6)
.set("expiration", 1000);
template.update(update);
1 | Set the simple property firstname to mat. |
2 | Set the simple property address.city to emond’s field without having to pass in the entire object. This does not work when a custom conversion is registered. |
3 | Remove the property age. |
4 | Set complex property address. |
5 | Set a map/collection of values removes the previously existing map/collection and replaces the values with the given ones. |
6 | Automatically update the server expiration time when altering Time To Live. |
Updating complex objects as well as map/collection structures requires further interaction with Redis to determine existing values which means that it might turn out that rewriting the entire entity might be faster. |
8.8. Queries and Query Methods
Query methods allow automatic derivation of simple finder queries from the method name.
public interface PersonRepository extends CrudRepository<Person, String> {
List<Person> findByFirstname(String firstname);
}
Please make sure properties used in finder methods are set up for indexing. |
Query methods for Redis repositories support only queries for entities and collections of entities with paging. |
Using derived query methods might not always be sufficient to model the queries to execute. RedisCallback
offers more control over the actual matching of index structures or even custom added ones. All it takes is providing a RedisCallback
that returns a single or Iterable
set of id values.
String user = //...
List<RedisSession> sessionsByUser = template.find(new RedisCallback<Set<byte[]>>() {
public Set<byte[]> doInRedis(RedisConnection connection) throws DataAccessException {
return connection
.sMembers("sessions:securityContext.authentication.principal.username:" + user);
}}, RedisSession.class);
Here’s an overview of the keywords supported for Redis and what a method containing that keyword essentially translates to.
Keyword | Sample | Redis snippet |
---|---|---|
|
|
|
|
|
|
|
|
|
|
|
8.9. Redis Repositories running on Cluster
Using the Redis repository support in a clustered Redis environment is fine. Please see the Redis Cluster section for ConnectionFactory
configuration details.
Still some considerations have to be done as the default key distribution will spread entities and secondary indexes through out the whole cluster and its slots.
key | type | slot | node |
---|---|---|---|
persons:e2c7dcee-b8cd-4424-883e-736ce564363e |
id for hash |
15171 |
127.0.0.1:7381 |
persons:a9d4b3a0-50d3-4538-a2fc-f7fc2581ee56 |
id for hash |
7373 |
127.0.0.1:7380 |
persons:firstname:rand |
index |
1700 |
127.0.0.1:7379 |
Some commands like SINTER
and SUNION
can only be processed on the Server side when all involved keys map to the same slot. Otherwise computation has to be done on client side.
Therefore it be useful to pin keyspaces to a single slot which allows to make use of Redis serverside computation right away.
key | type | slot | node |
---|---|---|---|
{persons}:e2c7dcee-b8cd-4424-883e-736ce564363e |
id for hash |
2399 |
127.0.0.1:7379 |
{persons}:a9d4b3a0-50d3-4538-a2fc-f7fc2581ee56 |
id for hash |
2399 |
127.0.0.1:7379 |
{persons}:firstname:rand |
index |
2399 |
127.0.0.1:7379 |
Define and pin keyspaces via `@RedisHash("{yourkeyspace}") to specific slots when using Redis cluster. |
8.10. CDI integration
Instances of the repository interfaces are usually created by a container, which Spring is the most natural choice when working with Spring Data. There’s sophisticated support to easily set up Spring to create bean instances. Spring Data Redis ships with a custom CDI extension that allows using the repository abstraction in CDI environments. The extension is part of the JAR so all you need to do to activate it is dropping the Spring Data Redis JAR into your classpath.
You can now set up the infrastructure by implementing a CDI Producer for the RedisConnectionFactory
and RedisOperations
:
class RedisOperationsProducer {
@Produces
RedisConnectionFactory redisConnectionFactory() {
JedisConnectionFactory jedisConnectionFactory = new JedisConnectionFactory(new RedisStandaloneConfiguration());
jedisConnectionFactory.afterPropertiesSet();
return jedisConnectionFactory;
}
void disposeRedisConnectionFactory(@Disposes RedisConnectionFactory redisConnectionFactory) throws Exception {
if (redisConnectionFactory instanceof DisposableBean) {
((DisposableBean) redisConnectionFactory).destroy();
}
}
@Produces
@ApplicationScoped
RedisOperations<byte[], byte[]> redisOperationsProducer(RedisConnectionFactory redisConnectionFactory) {
RedisTemplate<byte[], byte[]> template = new RedisTemplate<byte[], byte[]>();
template.setConnectionFactory(redisConnectionFactory);
template.afterPropertiesSet();
return template;
}
}
The necessary setup can vary depending on the JavaEE environment you run in.
The Spring Data Redis CDI extension will pick up all Repositories available as CDI beans and create a proxy for a Spring Data repository whenever a bean of a repository type is requested by the container. Thus obtaining an instance of a Spring Data repository is a matter of declaring an @Injected
property:
class RepositoryClient {
@Inject
PersonRepository repository;
public void businessMethod() {
List<Person> people = repository.findAll();
}
}
A Redis Repository requires RedisKeyValueAdapter
and RedisKeyValueTemplate
instances. These beans are created and managed by the Spring Data CDI extension if no provided beans are found. You can however supply your own beans to configure the specific properties of RedisKeyValueAdapter
and RedisKeyValueTemplate
.
Appendixes
Appendix Document structure
Various appendixes outside the reference documentation.
Schema defines the schemas provided by Spring Data Redis.
Appendix A: Schema
Core schema
<?xml version="1.0" encoding="UTF-8"?>
<xsd:schema xmlns="http://www.springframework.org/schema/redis"
xmlns:xsd="http://www.w3.org/2001/XMLSchema"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:tool="http://www.springframework.org/schema/tool"
targetNamespace="http://www.springframework.org/schema/redis"
elementFormDefault="qualified"
attributeFormDefault="unqualified">
<xsd:import namespace="http://www.springframework.org/schema/tool" schemaLocation="http://www.springframework.org/schema/tool/spring-tool.xsd"/>
<xsd:annotation>
<xsd:documentation><![CDATA[
Defines the configuration elements for the Spring Data Redis support.
Allows for configuring Redis listener containers in XML 'shortcut' style.
]]></xsd:documentation>
</xsd:annotation>
<xsd:element name="listener-container">
<xsd:annotation>
<xsd:documentation><![CDATA[
Container of Redis listeners. All listeners will be hosted by the same container.
]]></xsd:documentation>
<xsd:appinfo>
<tool:annotation>
<tool:exports type="org.springframework.data.redis.listener.RedisMessageListenerContainer"/>
</tool:annotation>
</xsd:appinfo>
</xsd:annotation>
<xsd:complexType>
<xsd:sequence>
<xsd:element name="listener" type="listenerType" minOccurs="0" maxOccurs="unbounded"/>
</xsd:sequence>
<xsd:attribute name="connection-factory" type="xsd:string" default="redisConnectionFactory">
<xsd:annotation>
<xsd:documentation><![CDATA[
A reference to the Redis ConnectionFactory bean.
Default is "redisConnectionFactory".
]]></xsd:documentation>
<xsd:appinfo>
<tool:annotation kind="ref">
<tool:expected-type type="org.springframework.data.redis.connection.ConnectionFactory"/>
</tool:annotation>
</xsd:appinfo>
</xsd:annotation>
</xsd:attribute>
<xsd:attribute name="task-executor" type="xsd:string">
<xsd:annotation>
<xsd:documentation><![CDATA[
A reference to a Spring TaskExecutor (or standard JDK 1.5 Executor) for executing
Redis listener invokers. Default is a SimpleAsyncTaskExecutor.
]]></xsd:documentation>
<xsd:appinfo>
<tool:annotation kind="ref">
<tool:expected-type type="java.util.concurrent.Executor"/>
</tool:annotation>
</xsd:appinfo>
</xsd:annotation>
</xsd:attribute>
<xsd:attribute name="subscription-task-executor" type="xsd:string">
<xsd:annotation>
<xsd:documentation><![CDATA[
A reference to a Spring TaskExecutor (or standard JDK 1.5 Executor) for listening
to Redis messages. By default reuses the 'task-executor' value.
]]></xsd:documentation>
<xsd:appinfo>
<tool:annotation kind="ref">
<tool:expected-type type="java.util.concurrent.Executor"/>
</tool:annotation>
</xsd:appinfo>
</xsd:annotation>
</xsd:attribute>
<xsd:attribute name="topic-serializer" type="xsd:string">
<xsd:annotation>
<xsd:documentation><![CDATA[
A reference to the RedisSerializer strategy for converting Redis channels/patterns to
serialized format. Default is a StringRedisSerializer.
]]></xsd:documentation>
<xsd:appinfo>
<tool:annotation kind="ref">
<tool:expected-type type="org.springframework.data.redis.serializer.RedisSerializer"/>
</tool:annotation>
</xsd:appinfo>
</xsd:annotation>
</xsd:attribute>
<xsd:attribute name="phase" type="xsd:string">
<xsd:annotation>
<xsd:documentation><![CDATA[
The lifecycle phase within which this container should start and stop. The lower
the value the earlier this container will start and the later it will stop. The
default is Integer.MAX_VALUE meaning the container will start as late as possible
and stop as soon as possible.
]]></xsd:documentation>
</xsd:annotation>
</xsd:attribute>
</xsd:complexType>
</xsd:element>
<xsd:complexType name="listenerType">
<xsd:attribute name="ref" type="xsd:string" use="required">
<xsd:annotation>
<xsd:documentation><![CDATA[
The bean name of the listener object, implementing
the MessageListener interface or defining the specified listener method.
Required.
]]></xsd:documentation>
<xsd:appinfo>
<tool:annotation kind="ref"/>
</xsd:appinfo>
</xsd:annotation>
</xsd:attribute>
<xsd:attribute name="topic" type="xsd:string">
<xsd:annotation>
<xsd:documentation><![CDATA[
The topics(s) to which the listener is subscribed. Can be (in Redis terminology) a
channel or/and a pattern. Multiple values can be specified by separating them with
spaces. Patterns can be specified by using the '*' character.
]]></xsd:documentation>
</xsd:annotation>
</xsd:attribute>
<xsd:attribute name="method" type="xsd:string">
<xsd:annotation>
<xsd:documentation><![CDATA[
The name of the listener method to invoke. If not specified,
the target bean is supposed to implement the MessageListener
interface or provide a method named 'handleMessage'.
]]></xsd:documentation>
</xsd:annotation>
</xsd:attribute>
<xsd:attribute name="serializer" type="xsd:string">
<xsd:annotation>
<xsd:documentation><![CDATA[
A reference to the RedisSerializer strategy for converting Redis Messages to
listener method arguments. Default is a StringRedisSerializer.
]]></xsd:documentation>
<xsd:appinfo>
<tool:annotation kind="ref">
<tool:expected-type type="org.springframework.data.redis.serializer.RedisSerializer"/>
</tool:annotation>
</xsd:appinfo>
</xsd:annotation>
</xsd:attribute>
</xsd:complexType>
<xsd:element name="collection">
<xsd:annotation>
<xsd:documentation><![CDATA[
Factory creating collections on top of Redis keys.
]]></xsd:documentation>
<xsd:appinfo>
<tool:annotation>
<tool:exports type="org.springframework.data.redis.support.collections.RedisCollectionFactoryBean"/>
</tool:annotation>
</xsd:appinfo>
</xsd:annotation>
<xsd:complexType>
<xsd:attribute name="id" type="xsd:ID">
<xsd:annotation>
<xsd:documentation><![CDATA[
The name of the Redis collection.]]></xsd:documentation>
</xsd:annotation>
</xsd:attribute>
<xsd:attribute name="key" type="xsd:string" use="optional">
<xsd:annotation>
<xsd:documentation><![CDATA[
Redis key of the created collection. Defaults to bean id.
]]></xsd:documentation>
</xsd:annotation>
</xsd:attribute>
<xsd:attribute name="template" type="xsd:string" default="redisTemplate">
<xsd:annotation>
<xsd:documentation><![CDATA[
A reference to a RedisTemplate bean.Default is "redisTemplate".
]]></xsd:documentation>
<xsd:appinfo>
<tool:annotation kind="ref">
<tool:expected-type type="org.springframework.data.redis.core.RedisTemplate"/>
</tool:annotation>
</xsd:appinfo>
</xsd:annotation>
</xsd:attribute>
<xsd:attribute name="type" default="LIST" use="optional">
<xsd:annotation>
<xsd:documentation><![CDATA[
The collection type (default is list).
If the key exists, its type takes priority. The type is used to disambiguate the collection type (map vs properties) or
specify one in case the key is missing.]]></xsd:documentation>
</xsd:annotation>
<xsd:simpleType>
<xsd:restriction base="xsd:string">
<xsd:enumeration value="LIST"/>
<xsd:enumeration value="SET"/>
<xsd:enumeration value="ZSET"/>
<xsd:enumeration value="MAP"/>
<xsd:enumeration value="PROPERTIES"/>
</xsd:restriction>
</xsd:simpleType>
</xsd:attribute>
</xsd:complexType>
</xsd:element>
</xsd:schema>
Appendix B: Command Reference
Supported commands
Command | Template Support |
---|---|
APPEND |
X |
AUTH |
X |
BGREWRITEAOF |
X |
BGSAVE |
X |
BITCOUNT |
X |
BITOP |
X |
BLPOP |
X |
BRPOP |
X |
BRPOPLPUSH |
X |
CLIENT KILL |
X |
CLIENT GETNAME |
X |
CLIENT LIST |
X |
CLIENT SETNAME |
X |
CLUSTER SLOTS |
- |
COMMAND |
- |
COMMAND COUNT |
- |
COMMAND GETKEYS |
- |
COMMAND INFO |
- |
CONFIG GET |
X |
CONFIG RESETSTAT |
X |
CONFIG REWRITE |
- |
CONFIG SET |
X |
DBSIZE |
X |
DEBUG OBJECT |
- |
DEBUG SEGFAULT |
- |
DECR |
X |
DECRBY |
X |
DEL |
X |
DISCARD |
X |
DUMP |
X |
ECHO |
X |
EVAL |
X |
EVALSHA |
X |
EXEC |
X |
EXISTS |
X |
EXPIRE |
X |
EXPIREAT |
X |
FLUSHALL |
X |
FLUSHDB |
X |
GET |
X |
GETBIT |
X |
GETRANGE |
X |
GETSET |
X |
HDEL |
X |
HEXISTS |
X |
HGET |
X |
HGETALL |
X |
HINCRBY |
X |
HINCRBYFLOAT |
X |
HKEYS |
X |
HLEN |
X |
HMGET |
X |
HMSET |
X |
HSCAN |
X |
HSET |
X |
HSETNX |
X |
HVALS |
X |
INCR |
X |
INCRBY |
X |
INCRBYFLOAT |
X |
INFO |
X |
KEYS |
X |
LASTSAVE |
X |
LINDEX |
X |
LINSERT |
X |
LLEN |
X |
LPOP |
X |
LPUSH |
X |
LPUSHX |
X |
LRANGE |
X |
LREM |
X |
LSET |
X |
LTRIM |
X |
MGET |
X |
MIGRATE |
- |
MONITOR |
- |
MOVE |
X |
MSET |
X |
MSETNX |
X |
MULTI |
X |
OBJECT |
- |
PERSIST |
X |
PEXIPRE |
X |
PEXPIREAT |
X |
PFADD |
X |
PFCOUNT |
X |
PFMERGE |
X |
PING |
X |
PSETEX |
X |
PSUBSCRIBE |
X |
PTTL |
X |
PUBLISH |
X |
PUBSUB |
- |
PUBSUBSCRIBE |
- |
QUIT |
X |
RANDOMKEY |
X |
RENAME |
X |
RENAMENX |
X |
RESTORE |
X |
ROLE |
- |
RPOP |
X |
RPOPLPUSH |
X |
RPUSH |
X |
RPUSHX |
X |
SADD |
X |
SAVE |
X |
SCAN |
X |
SCARD |
X |
SCRIPT EXITS |
X |
SCRIPT FLUSH |
X |
SCRIPT KILL |
X |
SCRIPT LOAD |
X |
SDIFF |
X |
SDIFFSTORE |
X |
SELECT |
X |
SENTINEL FAILOVER |
X |
SENTINEL GET-MASTER-ADD-BY-NAME |
- |
SENTINEL MASTER |
- |
SENTINEL MASTERS |
X |
SENTINEL MONITOR |
X |
SENTINEL REMOVE |
X |
SENTINEL RESET |
- |
SENTINEL SET |
- |
SENTINEL SLAVES |
X |
SET |
X |
SETBIT |
X |
SETEX |
X |
SETNX |
X |
SETRANGE |
X |
SHUTDOWN |
X |
SINTER |
X |
SINTERSTORE |
X |
SISMEMBER |
X |
SLAVEOF |
X |
SLOWLOG |
- |
SMEMBERS |
X |
SMOVE |
X |
SORT |
X |
SPOP |
X |
SRANDMEMBER |
X |
SREM |
X |
SSCAN |
X |
STRLEN |
X |
SUBSCRIBE |
X |
SUNION |
X |
SUNIONSTORE |
X |
SYNC |
- |
TIME |
X |
TTL |
X |
TYPE |
X |
UNSUBSCRIBE |
X |
UNWATCH |
X |
WATCH |
X |
ZADD |
X |
ZCARD |
X |
ZCOUNT |
X |
ZINCRBY |
X |
ZINTERSTORE |
X |
ZLEXCOUNT |
- |
ZRANGE |
X |
ZRANGEBYLEX |
- |
ZREVRANGEBYLEX |
- |
ZRANGEBYSCORE |
X |
ZRANK |
X |
ZREM |
X |
ZREMRANGEBYLEX |
- |
ZREMRANGEBYRANK |
X |
ZREVRANGE |
X |
ZREVRANGEBYSCORE |
X |
ZREVRANK |
X |
ZSCAN |
X |
ZSCORE |
X |
ZUNINONSTORE |
X |