springboot redis 使用 CrudRepository 类似jpa一样的效果

xiaoxiao2021-02-28  5

新建springboot项目 maven引入redis依赖

<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-data-redis</artifactId> </dependency>

配置文件application.yml

spring: redis: database: 0 host: 127.0.0.1 port: 6379

Spring Data Redis - Repository Examples

This project contains examples for Spring Data specific repository abstraction on top of Redis.

Repository Suport

Redis Repository support allows to convert, store, retrieve and index entities within Redis native data structures. To do, besides the HASH containing the actual properties several Secondary Index structures are set up and maintained.

@RedisHash("persons") class Person { @Id String id; @Indexed String firstname; @Indexed String lastname; Gender gender; Address address; @Reference List<Person> children; }

The above entity would for example then be stored in a Redis HASH with key persons:9b0ed8ee-14be-46ec-b5fa-79570aadb91d.

_class=example.springdata.redis.domain.Person <1> id=9b0ed8ee-14be-46ec-b5fa-79570aadb91d firstname=eddard <2> lastname=stark gender=MALE address.city=winterfell <3> address.country=the north children.[0]=persons:41436096-aabe-42fa-bd5a-9a517fbf0260 <4> children.[1]=persons:1973d8e7-fbd4-4f93-abab-a2e3a00b3f53 children.[2]=persons:440b24c6-ede2-495a-b765-2d8b8d6e3995 <1> The _class attribute is used to store the actual type and is required for object/hash conversion. <2> Values are also included in Secondary Index when annotated with @Indexed. <3> Complex types are flattened out and embedded into the HASH as long as there is no explicit Converter registered or a @Reference annotation present. <4> Using @Reference stores only the key of a referenced object without embedding values like in <3>.

Additionally indexes are created for firstname, lastname and address.city containing the id of the actual entity.

redis/src $ ./redis-cli keys * 1) "persons" <1> 2) "persons:9b0ed8ee-14be-46ec-b5fa-79570aadb91d" <2> 3) "persons:9b0ed8ee-14be-46ec-b5fa-79570aadb91d:idx" <3> 4) "persons:41436096-aabe-42fa-bd5a-9a517fbf0260" 5) "persons:41436096-aabe-42fa-bd5a-9a517fbf0260:idx" 6) "persons:1973d8e7-fbd4-4f93-abab-a2e3a00b3f53" 7) "persons:1973d8e7-fbd4-4f93-abab-a2e3a00b3f53:idx" 8) "persons:440b24c6-ede2-495a-b765-2d8b8d6e3995" 9) "persons:440b24c6-ede2-495a-b765-2d8b8d6e3995:idx" 10) "persons:firstname:eddard" <4> 11) "persons:firstname:robb" 12) "persons:firstname:sansa" 13) "persons:firstname:arya" 14) "persons:lastname:stark" <5> 15) "persons:address.city:winterfell" <6> <1> SET holding all ids known in the keyspace "persons". <2> HASH holding property values for id "9b0ed8ee-14be-46ec-b5fa-79570aadb91d" in keyspace "persons". <3> SET holding index information for CRUD operations. <4> SET used for indexing entities with "firstname" equal to "eddard" within keyspace "persons". <5> SET used for indexing entities with "lastname" equal to "stark" within keyspace "persons". <6> SET used for indexing entities with "address.city" equal to "winterfell" within keyspace "persons".

Configuration

The below configuration uses Lettuce to connect to Redis on its default port. Please note the usage of @EnableRedisRepositories to create Repository instances.

@Configuration @EnableRedisRepositories class AppConfig { @Bean RedisConnectionFactory connectionFactory() { return new LettuceConnectionFactory(); } @Bean RedisTemplate<?, ?> redisTemplate(RedisConnectionFactory connectionFactory) { RedisTemplate<byte[], byte[]> template = new RedisTemplate<>(); template.setConnectionFactory(connectionFactory); return template; } }

Having the infrastructure in place you can go on declaring and using the Repository interface.

interface PersonRepository extends CrudRepository<Person, String> { List<Person> findByLastname(String lastname); Page<Person> findByLastname(String lastname, Pageable page); List<Person> findByFirstnameAndLastname(String firstname, String lastname); List<Person> findByFirstnameOrLastname(String firstname, String lastname); List<Person> findByAddress_City(String city); }

One Word of Caution

Maintaining complex types and index structures stands and falls with its usage. Please consider the following:

Nested document structures increase object <> hash conversion overhead.Consider having only those indexes you really need instead of indexing each and every property.Pagination is a costly operation since the total number of elements is calculated before returning just a slice of data.Pagination gives no guarantee on information as elements might be added, moved or removed.

注意@Indexed注解的使用例子中

@Indexed String firstname;

@Indexed String lastname;

如果不加注解 List<Person> findByLastname(String lastname); 是查询不到数据的

详细参考:https://github.com/spring-projects/spring-data-examples/tree/master/redis/repositories

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