Redis OM Spring provides powerful repository and custom object-mapping abstractions built on top of the powerful Spring Data Redis (SDR) framework. This app is a simple started application using Redis OM Spring to map, manipulate and query some simple Spring Data models backed by RedisJSON documents.
Check out our workshop video for this project on YouTube.
The app provides a simple model Person:
id: An autogeneratedStringusing ULIDsfirstName: AStringrepresenting their first or given name.lastName: AStringrepresenting theirlast or surname.age: AnIntegerrepresenting their age in years.personalStatement: AStringrepresenting a text personal statement containing facts or other biographical information.homeLoc: Aorg.springframework.data.geo.Pointrepresenting the geo coordinates.address: An entity of typeAddressrepresenting the Person's postal address.skills: ASet<String>, representing a collection of Strings representing skills the person has.
The Person model is annotated with @Document, this enables the models to be saved as RedisJSON documents.
The individuals fields that will be used to create the entity search index are annotated with @Indexed or
@Searchable (for full-text search capable text fields).
@Document
class Person(
@Id
@Indexed
var id: String? = null,
// Indexed for exact text matching
@Indexed
var firstName: String,
@Indexed
var lastName: String,
//Indexed for numeric matches
@Indexed
var age: Int,
//Indexed for Full Text matches
@Searchable
var personalStatement: String,
//Indexed for Geo Filtering
@Indexed var homeLoc: Point,
// Nest indexed object
@Indexed
var address: Address,
@Indexed
var skills: Set<String>
)For example, saving the above object using a repository (see below) you'll get a JSON document under the Redis key com.redis.om.skeleton.models.Person:01FXD97WTHNYFQEA56YQ27BNQ6:
{
"id": "01FXD97WTHNYFQEA56YQ27BNQ6",
"firstName": "Elizabeth",
"lastName": "Olsen",
"age": 32,
"personalStatement": "You Guys Know I Can Move Things With My Mind, Right?",
"homeLoc": "40.6976701,-74.2598641",
"address": {
"houseNumber": "20",
"street": "W 34th St",
"city": "New York",
"state": "NY",
"postalCode": "10001",
"country": "US"
},
"skills": [
"loyalty",
"magic"
]
}The resulting JSON has a generated value for the id field using a ULIDs. Note that
the homeLoc field is mapped to the lon-lat format expected by Redis, and the set of skills is mapped into a JSON array.
Use the @EnableRedisDocumentRepositories annotation to scan for @Document annotated Spring models,
Inject repositories beans implementing RedisDocumentRepository which you can use for CRUD operations and custom queries (all by declaring Spring Data Query Interfaces):
@SpringBootApplication
@EnableRedisDocumentRepositories("com.redis.om.skeleton.*")
class OmKotlinDemoApplication(val repo: PeopleRepository) {
}Redis OM Spring data repository's goal, like other Spring Data repositories, is to significantly reduce the amount of boilerplate code required to implement data access. Simply create a Java interface
that extends RedisDocumentRepository that takes the domain class to manage as well as the ID type of the domain class as type arguments. RedisDocumentRepository extends Spring Data's PagingAndSortingRepository.
Declare query methods on the interface. You can both, expose CRUD methods or create declarations for complex queries that Redis OM Spring will fullfil at runtime:
interface PeopleRepository : RedisDocumentRepository<Person, String> {
// Find people by age range
fun findByAgeBetween(minAge: Int, maxAge: Int): Iterable<Person>
// Draws a circular geo-filter around a spot and returns all people in that radius
fun findByHomeLoc(point: Point, distance: Distance): Iterable<Person>
// Find people by their first and last name
fun findByFirstNameAndLastName(firstName: String, lastName: String): Iterable<Person>
// Performs full text search on a person's personal Statement
fun searchByPersonalStatement(text: String): Iterable<Person>
// Performing a tag search on city
fun findByAddress_City(city: String): Iterable<Person>
// Performing a full-search on street
fun findByAddress_CityAndAddress_State(city: String, state: String): Iterable<Person>
// Search Persons that have one of multiple skills (OR condition)
fun findBySkills(skills: Set<String>): Iterable<Person>
// Search Persons that have all the skills (AND condition):
fun findBySkillsContainingAll(skills: Set<String>): Iterable<Person>
// Performing a text search on all text fields:
fun search(text: String?): Iterable<Person>
}The repository proxy has two ways to derive a store-specific query from the method name:
- By deriving the query from the method name directly.
- By using a manually defined query using the
@Queryor@Aggregationannotations.
You can inject a Repository and perform the basic CRUD operations as well as any custom queries you've defined:
@RestController
@RequestMapping("/api/v1/people")
class PeopleControllerV1(val repo: PeopleRepository) {
@PostMapping("new")
fun create(@RequestBody newPerson: Person): Person {
return repo.save(newPerson)
}
}Redis OM Spring Entity Streams provides a Java 8 Streams interface to Query Redis JSON documents using RediSearch. Entity Streams allow you to process data in a typesafe declarative way similar to SQL statements. Streams can be used to express a query as a chain of operations.
Entity Streams in Redis OM Spring provide the same semantics as Java 8 streams. Streams can be made of Redis Mapped entities (@Document) or one or more properties of an Entity. Entity Streams progressively build the query until a terminal operation is invoked (such as collect). Whenever a Terminal operation is applied to a Stream, the Stream cannot accept additional operations to its pipeline and it also means that the Stream is started.
Let's start with a simple example, a Spring @Service which includes EntityStream to query for instances of the mapped class Person:
package com.redis.om.skeleton.services
import com.redis.om.skeleton.models.Person
import com.redis.om.skeleton.models.`Person$`
import com.redis.om.spring.search.stream.EntityStream
import org.springframework.stereotype.Service
import redis.clients.jedis.search.aggr.SortedField
import java.util.stream.Collectors
@Service
class PeopleService(val entityStream: EntityStream) {
// Find people by age range
fun findByAgeBetween(minAge: Int, maxAge: Int): Iterable<Person> {
return entityStream //
.of(Person::class.java) //
.filter(`Person$`.AGE.between(minAge, maxAge)) //
.sorted(`Person$`.AGE, SortedField.SortOrder.ASC) //
.collect(Collectors.toList())
}
}The EntityStream is injected into the PeopleService using @Autowired. We can then get a stream for Person objects by using entityStream.of(Person.class). At this point the stream represents the equivalent of a SELECT * FROM Person on a relational database. The call to collect will then execute the underlying query and return a collection of all Person objects in Redis.
To produce more elaborate queries, you're provided with a generated meta-model, which is a class with the same name as your model but ending with a dollar sign. In the
example below, our entity model is Person therefore we get a meta-model named Person$. With the meta-model you have access to the operations related to the
underlying search engine field. For example, in the example we have an age property which is an integer. Therefore our metamodel has an AGE property which has
numeric operations we can use with the stream's filter method such as between.
// Find people by age range
fun findByAgeBetween(minAge: Int, maxAge: Int): Iterable<Person> {
return entityStream //
.of(Person::class.java) //
.filter(`Person$`.AGE.between(minAge, maxAge)) //
.sorted(`Person$`.AGE, SortedField.SortOrder.ASC) //
.collect(Collectors.toList())
}In this example we also make use of the Streams sorted method to declare that our stream will be sorted by the Person$.AGE in ASCending order.
Clone the repository from GitHub:
$ git clone https://github.com/redis-developer/redis-om-spring-kotlin-skeleton-app
$ cd redis-om-spring-skeleton-appRedis OM Spring relies on the power of the [RediSearch][redisearch-url] and [RedisJSON][redis-json-url] modules. We have provided a docker compose YAML file for you to quickly get started. To launch the docker compose application, on the command line (or via Docker Desktop), clone this repository and run (from the root folder):
docker compose upThis launches Redis Stack; Redis Stack Server on port 6379, and Redis Insight 8001.
If you're using Redis Enterprise Cloud, you'll need the hostname, port number, and password for your database. Use these to set the application.properties configuration like this:
spring.data.redis.host=<host>
spring.data.redis.port=<port>
spring.data.redis.password=<password>
spring.data.redis.username=<username>For example if your Redis Enterprise Cloud database is at port 9139 on host enterprise.redis.com and your password is 5uper53cret then you'd set REDIS_OM_URL as follows:
spring.data.redis.host=enterprise.redis.com
spring.data.redis.port=9139
spring.data.redis.password=5uper53cret
spring.data.redis.username=default- Java 17 or higher
- Spring Boot 3.0.5 (included by Redis OM Spring)
- A Redis database with the RediSearch module version TODO or higher installed. We've provided a
docker-compose.ymlwith Redis Stack for this. You can also sign up for a free 30Mb database with Redis Enterprise Cloud - be sure to check the box to configure a Redis Stack instance, follow this guide. - curl, or Postman - to send HTTP requests to the application. We'll provide examples using curl in this document.
- Optional: RedisInsight, a free data visualization and database management tool for Redis. When downloading RedisInsight, be sure to select version 2.x.
./mvnw spring-boot:runYou can interact with the API directly with CURL or through the Swagger interface.
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