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This approach is the same as browsing by subjectscontributors, but with a few extensions.

ProsCons

Easy to implement by reusing existing code baseRequires only Elasticsearch and Kafka

Requires additional space to store the dedicated index with all linked instance ids

Requires integration with kafka to prevent race conditions and get rid of optimistic locks on Elasticsearch documents

Requires additional code to manage update and delete events

Approach is contains a several steps to implement:

  1. Send contributor events from instance to the search.instance-contributor topic (message key = sha1 hash of concatenatination - tenantId + contributorType + key)
  2. Implement a new Kafka Listener to listen contributor only events (Kafka will arrange contributors with the same key in the same partition, allowing event processing without optimistic locking)
  3. Implement a new InstanceContributor repository with following upsert request for events

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  1. groups
  2. Implement a query which allows to find contributor exact by name and type (it can be CQL with double equal sign, but it looks like that John and John. are thread as same value (ES standard tokenizer))

Upsert query example:

No Format
{
  "script": {
    "source": "def set=new LinkedHashSet(ctx._source.instances);set.addAll(params.ins);params.del.forEach(set::remove);ctx._source.instances=set",
    "lang": "painless",
    "params": {
      "ins": [ "instanceId#1|type#1", "instanceId#2|type#1", "instanceId#3|type#1" ],
	  "del": [ "instanceId#4|type#1"]
    }
  },
  "upsert": {
    "id": "abshc",
    "name": "Antoniou, Grigoris",
    "contributorTypeId": "type#1",
    "instances": [ "instanceId#1|type#1", "instanceId#2|type#1", "instanceId#3|type#1" ]
  }
}

#2 Browsing by Contributors using PostgreSQL table

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Code Block
languagesql
titleDatabase schema
create table instance_subjectscontributor
(
    subject    contributor text not null,
    instance_id text not null,
    constraint instance_subjectcontributors_pk
        primary key (subjectcontributor, instance_id)
);

create index instance_subjectscontributors_subjectcontributor
    on diku_mod_search.instance_subjectscontributors (lower(subjectcontributor));

Insertions can be done in batch, which can be done configuring Spring Data Jpa:

Code Block
languagesql
titleInsert script
insert into instance_subjectscontributor(instance_id, subjectcontributor) values (?,?) on conflict do nothing;

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Code Block
languagejava
titleJava Entities
@Data
@Entity
@NoArgsConstructor
@Table(name = "instance_subjectscontributors")
@AllArgsConstructor(staticName = "of")
@SQLInsert(sql = "insert into instance_subjectscontributors(instance_id, subjectcontributor) values (?, ?) on conflict do nothing")
public class InstanceSubjectEntityInstanceContributorEntity implements Persistable<InstanceSubjectEntityId>Persistable<InstanceContributorEntityId> {

  @EmbeddedId
  private InstanceSubjectEntityIdInstanceContributorEntityId id;

  @Override
  public boolean isNew() {
    return true;
  }
}

@Data
@Embeddable
@NoArgsConstructor
@AllArgsConstructor(staticName = "of")
public class InstanceSubjectEntityIdInstancecontributorEntityId implements Serializable {

  private String subjectcontributor;
  private String instanceId;
}

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Code Block
languagesql
titlePreceding Query
select subjectcontributor, count(*)
from instance_subjectscontributors
where subjectcontributor in (
  select distinct on (lower(subjectcontributor)) subjectcontributor
  from instance_subjectscontributors
  where lower(subjectcontributor) < :anchor
  order by lower(subjectcontributor) desc
  limit :limit
)
group by subjectcontributor
order by lower(subjectcontributor);


Code Block
languagesql
titleSucceeding Query
select subjectcontributor, count(*)
from instance_subjectscontributors
where subjectcontributor in (
  select distinct on (lower(subjectcontributor)) subjectcontributor
  from instance_subjectscontributors
  where lower(subjectcontributor) >= :anchor
  order by lower(subjectcontributor)
  limit :limit
)
group by subjectcontributor
order by lower(subjectcontributor);


ProsCons

Fast to query (faster than other options)

Requires additional space to store the dedicated index (~1Gb per million resources)
Easy to manage update and delete events

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