投稿
  1. 首页
  2. 随笔

Elasticsearch与Spring的集成

比思论坛网站 • 2022-12-16 • 随笔 • 阅读 35

Elasticsearch与Spring的集成,第1张

Elasticsearch与Spring的集成

目前常见的Elasticsearch Java API有四类client连接方式：

  • TransportClient（不推荐）：Elasticsearch原生的api，TransportClient可以支持2.x，5.x版本，TransportClient将会在 Elasticsearch7.0弃用并在8.0中完成删除。
  • RestClient：ES官方推荐使用。
  • Jest（不推荐）：是Java社区开发的，是Elasticsearch的Java Http Rest客户端。
  • Spring Data Elasticsearch：与Spring生态对接，可以在web系统中整合到Spring中使用，与SpringBoot、SpringData 版本容易冲突，而且往往很难跟上Elasticsearch版本的更新，比如SpringBoot目前的2.3.1.RELEASE，所支持Elasticsearch7.6.2。

从使用上来说，Spring Data的使命是给各种数据访问提供统一的编程接口，不管是关系型数据库（如 MySQL），还是非关系数据库（如Redis），或者类似Elasticsearch这样的索引数据库。从而简化开发人员的代码，提高开发效率，也就是说，Spring Data想要把对任何数据的访问都抽象为类似接口，这就导致了Spring Data Elasticsearch在基本查询上没问题，但是复杂查询（模糊、通配符、match查询、聚集查询等）就显得力不从心了，此时，我们还是只能使用原生查询。

所以我们把精力放在REST Client上，Java REST Client有Low Level和High Level两种：

  • Java Low Level REST Client：使用该客户端需要将HTTP请求的body手动拼成JSON格式，HTTP响应也必须将返回的JSON数据手动封装成对象，使用上更为原始。
  • Java High Level REST Client：该客户端基于Low Level客户端实现，提供API解决Low Level客户端需要手动转换数据格式的问题。

ES的官网已经提供了非常详尽的API参考手册，参见
https://www.elastic.co/guide/en/elasticsearch/client/java-rest/current/index.html

Java Low Level REST Client的使用

pom.xml中引入依赖，注意依赖的版本与Elasticsearch保持一致：


    org.elasticsearch.client
    elasticsearch-rest-client
    7.7.0

演示代码：

package com.morris.es.low;

import org.apache.http.HttpEntity;
import org.apache.http.HttpHost;
import org.apache.http.entity.ContentType;
import org.apache.http.nio.entity.NStringEntity;
import org.elasticsearch.client.Request;
import org.elasticsearch.client.Response;
import org.elasticsearch.client.RestClient;

import java.io.IOException;

public class LowDemo {

    public static void main(String[] args) throws IOException {

        RestClient restClient = RestClient.builder(
                new HttpHost("10.0.44.5", 9200, "http")
        ).build();

        String indexName = "low_test";
        String docId = "1";

        createIndex(restClient, indexName);

        addDoc(restClient, indexName, docId);

        queryDoc(restClient, indexName, docId);

        restClient.close();
    }

    private static void createIndex(RestClient restClient, String indexName) throws IOException {
        Request request = new Request("PUT", indexName);
        Response response = restClient.performRequest(request);
        System.out.println(response);
    }

    private static void addDoc(RestClient restClient, String indexName, String docId) throws IOException {
        String jsonString = "{" +
                ""msg":"Java Low Level REST Client"" +
                "}";
        HttpEntity entity = new NStringEntity(jsonString, ContentType.APPLICATION_JSON);
        Request request = new Request("PUT", indexName + "/_doc/" + docId);
        request.setEntity(entity);
        Response response = restClient.performRequest(request);
        System.out.println(response);
    }

    private static void queryDoc(RestClient restClient, String indexName, String docId) throws IOException {
        Request request = new Request("get", indexName + "/_doc/" + docId);
        Response response = restClient.performRequest(request);
        System.out.println(response.getEntity());
    }

}
Java High Level REST Client

pom.xml中引入依赖，注意依赖的版本与Elasticsearch保持一致：


    org.elasticsearch.client
    elasticsearch-rest-high-level-client
    7.4.0

获得连接：

RestClientBuilder restClientBuilder =
        RestClient.builder(
                new HttpHost("10.0.73.146", 9200, "http")
        );
restHighLevelClient = new RestHighLevelClient(restClientBuilder);
索引的管理 创建索引

DSL：

put high_test/_mappings
{
    "properties": {
      "age": {
        "type": "integer"
      },
      "content": {
        "type": "text"
      },
      "firstName": {
        "type": "keyword"
      },
      "secondName": {
        "type": "keyword"
      }
    } 
}

代码如下：

XContentBuilder xContentBuilder = XContentFactory.jsonBuilder()
        .startObject()
        .field("properties").startObject()
        .field("firstName").startObject()
        .field("type", "keyword")
        .endObject()
        .field("secondName").startObject()
        .field("type", "keyword")
        .endObject()
        .field("age").startObject()
        .field("type", "integer")
        .endObject()
        .field("content").startObject()
        .field("type", "text")
        .endObject()
        .endObject()
        .endObject();

CreateIndexRequest createIndexRequest = new CreateIndexRequest(indexName);
createIndexRequest.mapping(xContentBuilder);

CreateIndexResponse createIndexResponse
        = restHighLevelClient.indices().create(createIndexRequest,
        RequestOptions.DEFAULT);
System.out.println(createIndexResponse.index());
System.out.println(createIndexResponse.isAcknowledged());
索引是否存在

DSL：

HEAD high_test

代码如下：

GetIndexRequest createIndexRequest = new GetIndexRequest(indexName);
boolean exists = restHighLevelClient.indices().exists(createIndexRequest, RequestOptions.DEFAULT);
System.out.println(exists);
删除索引

DSL：

DELETe high_test

代码如下：

DeleteIndexRequest createIndexRequest = new DeleteIndexRequest(indexName);
AcknowledgedResponse acknowledgedResponse = restHighLevelClient.indices().delete(createIndexRequest, RequestOptions.DEFAULT);
System.out.println(acknowledgedResponse.isAcknowledged());
文档的管理 创建文档

DSL：

put high_test/_doc/777
{
  "age": 18,
  "content": "hello world",
  "firstName": "morris",
  "id": 666,
  "secondName": "chen"
}

代码如下：

User user = new User();
user.setId(666L);
user.setFirstName("morris");
user.setSecondName("chen");
user.setAge(18);
user.setContent("hello world");

IndexRequest indexRequest = new IndexRequest(indexName);
indexRequest.id(String.valueOf(user.getId()));
indexRequest.source(JSON.toJSONString(user), XContentType.JSON);
IndexResponse indexResponse =
        restHighLevelClient.index(indexRequest, RequestOptions.DEFAULT);
if (indexResponse != null) {
    String id = indexResponse.getId();
    String index = indexResponse.getIndex();
    System.out.println(id);
    System.out.println(index);
    if (indexResponse.getResult() == DocWriteResponse.Result.CREATED) {
        System.out.println("新增文档成功");
    } else if (indexResponse.getResult() == DocWriteResponse.Result.UPDATED) {
        System.out.println("覆盖文档成功");
    }
}
查询文档

DSL：

get high_test/_doc/666

代码如下：

GetRequest getRequest = new GetRequest(indexName, "666");
GetResponse getResponse = restHighLevelClient.get(getRequest, RequestOptions.DEFAULT);
System.out.println(getResponse.getSource());
修改文档

DSL：

post high_test/_update/666
{
  "doc": {
    "name": "morris131"
  },
  "doc_as_upsert": true
}

代码如下：

XContentBuilder xContentBuilder = XContentFactory.jsonBuilder();
xContentBuilder.startObject();
{
    xContentBuilder.field("name", "morris131");
}
xContentBuilder.endObject();
UpdateRequest request =
        new UpdateRequest(indexName, "666").doc(xContentBuilder);
request.docAsUpsert(true);
request.fetchSource(true);
UpdateResponse updateResponse =
        restHighLevelClient.update(request, RequestOptions.DEFAULT);
GetResult getResult = updateResponse.getGetResult();
if (getResult.isExists()) {
    String sourceAsString = getResult.sourceAsString();
    System.out.println(sourceAsString);
} else {
    System.out.println("更新失败");
}
删除文档

DSL：

DELETE high_test/_doc/777

代码如下：

DeleteRequest deleteRequest = new DeleteRequest(indexName, "666");
DeleteResponse deleteResponse =
        restHighLevelClient.delete(deleteRequest, RequestOptions.DEFAULT);
if (deleteResponse.getResult() == DocWriteResponse.Result.NOT_FOUND) {
    System.out.println("文档不存在");
} else {
    System.out.println("删除成功");
}
普通搜索

DSL：

post kibana_sample_data_flights/_search
{
  "query": {
    "match_all": {}
  },
  "_source": {
    "includes": [
      "Origin*",
      "*Weather"
    ]
  },
  "sort": {
    "DistanceKilometers": "asc",
    "FlightNum": "desc"
  },
  "from": 0,
  "size": 5
}

代码如下：

SearchRequest searchRequest = new SearchRequest();
searchRequest.indices(indexName);
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.from(0);
searchSourceBuilder.size(5);
searchSourceBuilder.query(QueryBuilders.matchAllQuery());
String[] includeFields = new String[]{"Origin*","*Weather"};
searchSourceBuilder.fetchSource(includeFields,null);
searchSourceBuilder.sort(new FieldSortBuilder("DistanceKilometers")
        .order(SortOrder.ASC)

);
searchSourceBuilder.sort(new FieldSortBuilder("FlightNum")
        .order(SortOrder.DESC)

);
searchRequest.source(searchSourceBuilder);
SearchResponse search = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
SearchHits hits = search.getHits();
for(SearchHit hit:hits){
    String src = hit.getSourceAsString();
    System.out.println(src);
}
聚合搜索

DSL：

post kibana_sample_data_flights/_search?filter_path=aggregations
{
  "query": {
    "term": {
      "OriginCountry": "CN"
    }
  },
  "aggs": {
    "month_price_histogram": {
      "date_histogram": {
        "field": "timestamp",
        "fixed_interval": "30d"
      },
      "aggs": {
        "avg_delay": {
          "avg": {
            "field": "FlightDelayMin"
          }
        }
      }
    }
  }
}

代码如下：

SearchRequest searchRequest = new SearchRequest();
        searchRequest.indices(indexName);

        
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        searchSourceBuilder.query(
                QueryBuilders.termQuery("OriginCountry", "CN"));
        
        
DateHistogramAggregationBuilder date_price_histogram
        = AggregationBuilders.dateHistogram("month_price_histogram");
date_price_histogram.field("timestamp")
        .fixedInterval(DateHistogramInterval.days(30));
date_price_histogram.subAggregation(
        AggregationBuilders.avg("avg_delay").field("FlightDelayMin")
);
searchSourceBuilder.aggregation(date_price_histogram);
searchRequest.source(searchSourceBuilder);

JSONArray jsonArray = new JSONArray();

SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);

Aggregations aggregations = searchResponse.getAggregations();
for (Aggregation aggregation : aggregations) {
    String aggString = JSON.toJSONString(aggregation);
    jsonArray.add(JSON.parseObject(aggString));
    List buckets
            = ((Histogram) aggregation).getBuckets();
    for (Histogram.Bucket bucket : buckets) {
        System.out.println("--------------------------------------");
        System.out.println(bucket.getKeyAsString());
        System.out.println(bucket.getDocCount());
        ParsedAvg parsedAvg
                = (ParsedAvg) bucket.getAggregations().getAsMap().get("avg_delay");
        System.out.println(parsedAvg.getValueAsString());
    }
}
Spring Data Elasticsearch

引入依赖：


    org.springframework.boot
    spring-boot-starter-data-elasticsearch
    2.6.1



    org.elasticsearch.client
    elasticsearch-rest-high-level-client
    7.15.2

配置文件中指定Elasticsearch的host：

spring.elasticsearch.uris=http://10.0.73.146:9200

搜索代码如下：

@Resource
private ElasticsearchOperations elasticsearchOperations;

@GetMapping("search")
public String search() {
    Criteria criteria = new Criteria("agent").matches("firefox");
    Query query = new CriteriaQuery(criteria);
    query.setPageable(Pageable.ofSize(5).withPage(1));
    query.addSort(Sort.by("timestamp").descending());
    IndexCoordinates indexCoordinates = IndexCoordinates.of("kibana_sample_data_logs");
    SearchHits searchHits = elasticsearchOperations.search(query, Log.class, indexCoordinates);
    for (SearchHit searchHit : searchHits.getSearchHits()) {
        System.out.println(searchHit.getContent());
    }
    return "OK";
}

欢迎分享，转载请注明来源：内存溢出

原文地址: http://outofmemory.cn/zaji/5654739.html

赞 (0)
打赏 微信扫一扫 微信扫一扫 支付宝扫一扫 支付宝扫一扫
比思论坛网站 比思论坛网站 一级用户组
0 0
上一篇 2022-12-16
下一篇 2022-12-16

发表评论

登录后才能评论

评论列表（0条）

保存