1、elasticsearch官方文档的使用与介绍

1.1、Rest客户端初始化官方文档链接：

https://www.elastic.co/guide/en/elasticsearch/client/java-rest/current/java-rest-high-getting-started-initialization.html#java-rest-high-getting-started-initialization

RestHighLevelClient client = new RestHighLevelClient(
RestClient.builder(
new HttpHost("localhost", 9200, "http"),
new HttpHost("localhost", 9201, "http")));

1.2、RequestOptions官方文档链接：

https://www.elastic.co/guide/en/elasticsearch/client/java-rest/current/java-rest-low-usage-requests.html#java-rest-low-usage-request-options

这 RequestOptions类包含应共享的部分请求在同一应用程序中的多个请求之间。通过RequestOptions对请求进行统一设置

private static final RequestOptions COMMON_OPTIONS;
static {
RequestOptions.Builder builder = RequestOptions.DEFAULT.toBuilder();
builder.addHeader("Authorization", "Bearer " + TOKEN);
builder.setHttpAsyncResponseConsumerFactory(
new HttpAsyncResponseConsumerFactory
.HeapBufferedResponseConsumerFactory(30 * 1024 * 1024 * 1024));
COMMON_OPTIONS = builder.build();
}

1.3、对数据进行保存，创建Index索引官方文档：

https://www.elastic.co/guide/en/elasticsearch/client/java-rest/current/java-rest-high-document-index.html#java-rest-high-document-index

选择在哪个索引中存储数据，并且设置“键”-“存储的值”：

IndexRequest indexRequest = new IndexRequest("posts").id("1").source(要存储的JSON数据)；

 执行存储：

IndexResponse indexResponse = client.index(request, RequestOptions.DEFAULT);

 1.4、对数据进行查询官方文档：

https://www.elastic.co/guide/en/elasticsearch/client/java-rest/current/java-rest-high-search.html

所有的根操作都可以根据SearchSourceBuilder进行实现：

SearchRequest searchRequest = new SearchRequest();
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.query(QueryBuilders.matchAllQuery());
searchSourceBuilder.size()；
searchSourceBuilder.from();
searchRequest.source(searchSourceBuilder);

使用同步方式进行查询执行

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

要获取筛选后的数据，我们首先需要获取响应中包含的 SearchHits：

SearchHits hits = searchResponse.getHits();

SearchHits 提供有关所有命中的全局信息，例如命中总数或最高分数：

TotalHits totalHits = hits.getTotalHits();
//总命中数，必须在totalHits.relation的上下文中解释
long numHits = totalHits.value;
//命中数是准确的 (EQUAL_TO) 还是总数的下限 (GREATER_THAN_OR_EQUAL_TO)
TotalHits.Relation relation = totalHits.relation;
float maxScore = hits.getMaxScore();

嵌套在 SearchHits 中的是可以迭代的划分开的具体搜索结果：

SearchHit[] searchHits = hits.getHits();
for (SearchHit hit : searchHits) {
// do something with the SearchHit
}

2、实际案例中整合例子：

2.1、创建elasticsearch存储结构：

PUT imooc_news
{
"mappings": {
"properties": {
"id":{
"type": "keyword"
},
"title":{
"type": "text"
},
"categoryId":{
"type": "integer"
},
" articleType":{
"type": "integer"
},
"articleCover":{
"type": "keyword"
},
"isAppoint":{
"type": "keyword"
},
"articleStatus":{
"type": "integer"
},
"publishUserId":{
"type": "keyword"
},
"publishTime":{
"type": "date"
},
"readCounts":{
"type": "integer"
},
"commentCounts":{
"type": "integer"
},
"mongoFileId":{
"type": "keyword"
},
"isDelete":{
"type": "integer"
},
"createTime":{
"type": "date"
},
"updateTime":{
"type": "date"
},
"content":{
"type": "text"
}
}
}
}

2.2、配置方法

@Configuration
public class ElasticSearchConfig {
public static final RequestOptions COMMON_OPTIONS;
static {
RequestOptions.Builder builder = RequestOptions.DEFAULT.toBuilder();
/*        builder.addHeader("Authorization", "Bearer " + TOKEN);
builder.setHttpAsyncResponseConsumerFactory(
new HttpAsyncResponseConsumerFactory
.HeapBufferedResponseConsumerFactory(30 * 1024 * 1024 * 1024));*/
COMMON_OPTIONS = builder.build();
}

@Bean
public RestHighLevelClient restHighLevelClient() {
RestHighLevelClient client = new RestHighLevelClient(RestClient.builder(
new HttpHost("192.168.111.131", 9200, "http")));
return client;
}
}

2.3、进行相关数据存储：

public void updateArticleStatus(String articleId, Integer status) throws IOException {
Article article = new Article();
article.setId(articleId);
article.setArticleStatus(status);
articleMapper.updateByPrimaryKeySelective(article);
Article articleOne = articleMapper.selectByPrimaryKey(articleId);

//ES官方推荐的一次bulk size介于5-15MB之间，请求个数是1000-5000个
//BulkRequest bulkRequest = new BulkRequest();
IndexRequest indexRequest = new IndexRequest(EsContant.PRODUCT_INDEX);
indexRequest.id(articleOne.getId());
String s = JSON.toJSONString(articleOne);
　　//传入Json类型数据时必须设置XContentType.JSON
indexRequest.source(s, XContentType.JSON);
//bulkRequest.add(indexRequest);
IndexResponse index = restHighLevelClient.index(indexRequest, ElasticSearchConfig.COMMON_OPTIONS);
}

 2.4、对数据进行查询：

@Override
public PagedGridResult queryArticlePortalString(String keyword, Integer category, Integer page, Integer pageSize) throws IOException {
//SearchSourceBuilder用于构建查询语句，所有跟操作都可以直接使用 SearchSourceBuilder的方法进
//在本例中：{"query":{"bool":{"filter":[{"term":{"categoryId":{"value":11,"boost":1.0}}}],"adjust_pure_negative":true,"boost":1.0}}}
//所以跟操作时query
//总指elasticsearch查询核心在于对捋清楚条件的嵌套逻辑
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
BoolQueryBuilder boolQuery = QueryBuilders.boolQuery();
//进行模糊查询，由于要对title进行模糊查询，所以title的类型应该设置成text而不是keyword
if (!StringUtils.isEmpty(keyword)) {
boolQuery.must(QueryBuilders.matchQuery("title", keyword));
}
//根据category进行查找筛选
if (!StringUtils.isEmpty(category)) {
boolQuery.filter(QueryBuilders.termQuery("categoryId", category));
}
sourceBuilder.query(boolQuery);

String s = sourceBuilder.toString();

System.out.println("构建DSL" + s);

　　　　　/** SearchRequest searchRequest = new SearchRequest(); 
　　　　　　* searchRequest.indices("posts"); 
　　　　　　* searchRequest.source(sourceBuilder);
　　　　　　* 以下的方法相当于以上方法的结合体
　　　　　**/
SearchRequest searchRequest = new SearchRequest(new String[]{EsContant.PRODUCT_INDEX}, sourceBuilder);

/**
* {
*   "took" : 3,
*   "timed_out" : false,
*   "_shards" : {
*     "total" : 1,
*     "successful" : 1,
*     "skipped" : 0,
*     "failed" : 0
*   },
*   "hits" : {
*     "total" : {
*       "value" : 1,
*       "relation" : "eq"
*     },
*     "max_score" : 0.9105468,
*     "hits" : [
*       {
*         "_index" : "imooc_news_dev",
*         "_type" : "_doc",
*         "_id" : "210510BTG8GFT8BC",
*         "_score" : 0.9105468,
*         "_source" : {
*           "articleCover" : "",
*           "articleStatus" : 4,
*           "articleType" : 2,
*           "categoryId" : 11,
*           "commentCounts" : 0,
*           "content" : ".......文章内容.......",
*           "createTime" : 1620635728000,
*           "id" : "210510BTG8GFT8BC",
*           "isAppoint" : 0,
*           "isDelete" : 0,
*           "publishTime" : 1620635728000,
*           "publishUserId" : "210509HK5HYTHZR4",
*           "readCounts" : 0,
*           "title" : "字节、腾讯、金山wps、跟谁学、百度 go工程师面试题集锦",
*           "updateTime" : 1620635728000
*         }
*       }
*     ]
*   }
* }
*/
// 2、执行检索
SearchResponse response = client.search(searchRequest, ElasticSearchConfig.COMMON_OPTIONS);

SearchHits hits = response.getHits();
SearchHit[] newsHits = hits.getHits();
List<Article> articles = new ArrayList<>();
if (newsHits != null && newsHits.length > 0) {
for (SearchHit newsHit : newsHits) {
String sourceAsString = newsHit.getSourceAsString();
Article article = JSON.parseObject(sourceAsString, Article.class);
articles.add(article);
}
}
// PageHelper.startPage(page,pageSize);
return setterPagedGrid(articles, page);
}