This version is still in development and is not considered stable yet. For the latest stable version, please use Spring Data Redis 3.4.0!spring-doc.cn

Redis Repositories Anatomy

Redis as a store itself offers a very narrow low-level API leaving higher level functions, such as secondary indexes and query operations, up to the user.spring-doc.cn

This section provides a more detailed view of commands issued by the repository abstraction for a better understanding of potential performance implications.spring-doc.cn

Consider the following entity class as the starting point for all operations:spring-doc.cn

Example 1. Example entity

@RedisHash("people")
public class Person {

  @Id String id;
  @Indexed String firstname;
  String lastname;
  Address hometown;
}

public class Address {

  @GeoIndexed Point location;
}

Insert new

repository.save(new Person("rand", "al'thor"));

HMSET "people:19315449-cda2-4f5c-b696-9cb8018fa1f9" "_class" "Person" "id" "19315449-cda2-4f5c-b696-9cb8018fa1f9" "firstname" "rand" "lastname" "al'thor" (1)
SADD  "people" "19315449-cda2-4f5c-b696-9cb8018fa1f9"                           (2)
SADD  "people:firstname:rand" "19315449-cda2-4f5c-b696-9cb8018fa1f9"            (3)
SADD  "people:19315449-cda2-4f5c-b696-9cb8018fa1f9:idx" "people:firstname:rand" (4)

1	Save the flattened entry as hash.
2	Add the key of the hash written in <1> to the helper index of entities in the same keyspace.
3	Add the key of the hash written in <2> to the secondary index of firstnames with the properties value.
4	Add the index of <3> to the set of helper structures for entry to keep track of indexes to clean on delete/update.

Replace existing

repository.save(new Person("e82908cf-e7d3-47c2-9eec-b4e0967ad0c9", "Dragon Reborn", "al'thor"));

DEL       "people:e82908cf-e7d3-47c2-9eec-b4e0967ad0c9"                           (1)
HMSET     "people:e82908cf-e7d3-47c2-9eec-b4e0967ad0c9" "_class" "Person" "id" "e82908cf-e7d3-47c2-9eec-b4e0967ad0c9" "firstname" "Dragon Reborn" "lastname" "al'thor" (2)
SADD      "people" "e82908cf-e7d3-47c2-9eec-b4e0967ad0c9"                         (3)
SMEMBERS  "people:e82908cf-e7d3-47c2-9eec-b4e0967ad0c9:idx"                       (4)
TYPE      "people:firstname:rand"                                                 (5)
SREM      "people:firstname:rand" "e82908cf-e7d3-47c2-9eec-b4e0967ad0c9"          (6)
DEL       "people:e82908cf-e7d3-47c2-9eec-b4e0967ad0c9:idx"                       (7)
SADD      "people:firstname:Dragon Reborn" "e82908cf-e7d3-47c2-9eec-b4e0967ad0c9" (8)
SADD      "people:e82908cf-e7d3-47c2-9eec-b4e0967ad0c9:idx" "people:firstname:Dragon Reborn" (9)

1	Remove the existing hash to avoid leftovers of hash keys potentially no longer present.
2	Save the flattened entry as hash.
3	Add the key of the hash written in <1> to the helper index of entities in the same keyspace.
4	Get existing index structures that might need to be updated.
5	Check if the index exists and what type it is (text, geo, …).
6	Remove a potentially existing key from the index.
7	Remove the helper holding index information.
8	Add the key of the hash added in <2> to the secondary index of firstnames with the properties value.
9	Add the index of <6> to the set of helper structures for entry to keep track of indexes to clean on delete/update.

Save Geo Data

Geo indexes follow the same rules as normal text based ones but use geo structure to store values. Saving an entity that uses a Geo-indexed property results in the following commands:spring-doc.cn

GEOADD "people:hometown:location" "13.361389" "38.115556" "76900e94-b057-44bc-abcf-8126d51a621b"  (1)
SADD   "people:76900e94-b057-44bc-abcf-8126d51a621b:idx" "people:hometown:location"               (2)

1	Add the key of the saved entry to the the geo index.
2	Keep track of the index structure.

Find using simple index

repository.findByFirstname("egwene");

SINTER  "people:firstname:egwene"                     (1)
HGETALL "people:d70091b5-0b9a-4c0a-9551-519e61bc9ef3" (2)
HGETALL ...

1	Fetch keys contained in the secondary index.
2	Fetch each key returned by <1> individually.

Find using Geo Index

repository.findByHometownLocationNear(new Point(15, 37), new Distance(200, KILOMETERS));

GEORADIUS "people:hometown:location" "15.0" "37.0" "200.0" "km" (1)
HGETALL   "people:76900e94-b057-44bc-abcf-8126d51a621b"         (2)
HGETALL   ...

1	Fetch keys contained in the secondary index.
2	Fetch each key returned by <1> individually.