Elasticsearch使用

es数据的基础功能使用为了配合7.1.1版本es使用一、客户端配置ElasticsearchConfig使用 Spring Data ES 的RestClients创建RestHighLevelClientConfigurationpublic class ElasticsearchConfig extends AbstractElasticsearchConfiguration {Beanpublic RestHighLevelClient elasticsearchClient() {return RestClients.create(ClientConfiguration.builder().connectedTo(uris) // host:port.withConnectTimeout(Duration.ofSeconds(connectTimeout)).withSocketTimeout(Duration.ofSeconds(socketTimeout)).withBasicAuth(username, password).build()).rest();}}二、构建查询SearchRequest/** 构建索引查询请求 */SearchRequest searchRequest new SearchRequest(searchFieldVo.getIndexName());/**用来构建搜索请求体的核心工具类‌它帮你把查询条件、分页、排序等参数组装 */SearchSourceBuilderSearchSourceBuilder searchSourceBuilder new SearchSourceBuilder();‌创建实例‌SearchSourceBuilder sourceBuilder new SearchSourceBuilder();‌设置查询条件‌用sourceBuilder.query(QueryBuilders.matchQuery(字段, 值))或sourceBuilder.query(QueryBuilders.matchAllQuery())来指定查什么。‌分页控制‌sourceBuilder.from(起始位置)和sourceBuilder.size(每页条数)from默认0size默认10。‌排序‌sourceBuilder.sort(字段名, SortOrder.ASC)可添加多个sort实现多级排序。‌返回字段筛选‌sourceBuilder.fetchSource(new String{字段1, 字段2}, null)只返回指定字段。‌‌‌BoolQueryBuilder/** 用于构建复杂布尔逻辑查询的核心类通过组合must、should、must_not、filter子句实现多条件精准检索 */BoolQueryBuilder boolQuery QueryBuilders.boolQuery();核心机制与子句语义‌must‌逻辑“与”AND所有子句必须匹配‌参与相关性评分‌。‌should‌逻辑“或”OR倾向默认非强制若与must共存则提升得分若单独使用需配合minimumShouldMatch生效‌参与评分‌。‌must_not‌逻辑“非”NOT匹配该条件的文档被排除‌不参与评分‌。‌filter‌逻辑“与”AND强制过滤且‌零评分开销‌支持缓存适用于精确匹配或范围过滤 。‌‌功能支持 nested 嵌套数组字段查询如 JSON 数组内的字段支持 term 精确匹配、fuzzy 模糊匹配、exists 存在、range 区间使用 from/size 分页适用于前 10000 条支持的查询条件boolQuery├── must: nestedQuery(queryField → secField secFieldValue) ← 嵌套字段匹配├── must: termQuery(queryMapVoList[] 每个元素) ← 多字段精确 AND├── must: fuzzyQuery(fuzzyField, fuzzyFieldValue) ← 模糊匹配├── must: existsQuery(existField) ← 存在判断├── must: rangeQuery(rangeField, filedValueStart, filedValueEnd) ← 区间└── from/size 分页 sortField 排序三、案例例searchFieldVo为请求参数用不同字段来组建复杂的查询条件/** 设置区间查询 */ if (!StringUtils.isEmpty(searchFieldVo.getRangeField())) { boolQuery.must(addRangeQuery(searchFieldVo)); }addRangeQuery方法RangeQueryBuilder rangeQuery QueryBuilders.rangeQuery(rangeField); if (valueStart ! null) rangeQuery.gte(valueStart); if (valueEnd ! null) rangeQuery.lte(valueEnd);/** 集合内字段查询[{A:B},{A:C}]比如查询集合内A的值 */ if (!StringUtils.isEmpty(searchFieldVo.getQueryField())) { NestedQueryBuilder nestedQuery QueryBuilders.nestedQuery( searchFieldVo.getQueryField(), QueryBuilders.matchQuery(searchFieldVo.getSecField(), searchFieldVo.getSecFieldValue()), ScoreMode.None ); boolQuery.must(nestedQuery); }/** 不存在某值(not in) */if (StrUtil.isNotBlank(searchFieldVo.getNotField()) searchFieldVo.getNotValues() ! null) { boolQuery.mustNot(QueryBuilders.termsQuery(searchFieldVo.getNotField(), searchFieldVo.getNotValues())); } if (CollectionUtil.isNotEmpty(searchFieldVo.getQueryMapVoList())) { for (QueryMapVo queryMapVo : searchFieldVo.getQueryMapVoList()) { if (queryMapVo.getField() ! null) { boolQuery.must(QueryBuilders.termQuery(queryMapVo.getField(),queryMapVo.getFiledValue())); } } }/** 存在某值(in) */if (StrUtil.isNotBlank(searchFieldVo.getShouldField()) searchFieldVo.getShouldValues() ! null) { boolQuery.should(QueryBuilders.termsQuery(searchFieldVo.getShouldField(), searchFieldVo.getShouldValues())); boolQuery.minimumShouldMatch(1); }/** 将查询层层设置到searchRequest中 */searchSourceBuilder.query(boolQuery); searchRequest.source(searchSourceBuilder);/** 用客户端执行查询 */ SearchResponse searchResponse client.search(searchRequest, RequestOptions.DEFAULT);四、其他新建索引/** * 新建索引 * param index * param id * param jsonSource * return */ public boolean indexDocument(String index, String id, String jsonSource) { boolean ackFlag false; IndexRequest request new IndexRequest(index) .id(id) .source(jsonSource, XContentType.JSON); try { IndexResponse response client.index(request, RequestOptions.DEFAULT); ackFlag response.status() RestStatus.CREATED || response.status() RestStatus.OK; } catch (IOException e) { e.printStackTrace(); } return ackFlag; }删除索引/** * 删除索引 */ public boolean deleteIndex(String indexName) throws IOException { if (!indexExists(indexName)) { return false; } DeleteIndexRequest request new DeleteIndexRequest(indexName); AcknowledgedResponse response client.indices().delete(request, RequestOptions.DEFAULT); return response.isAcknowledged(); }添加文档/** * 添加文档使用默认_doc类型 */ public boolean addDocumentJson(String indexName, String id, String document) throws IOException { IndexRequest request new IndexRequest(indexName); request.id(id); request.source(document, XContentType.JSON); client.index(request, RequestOptions.DEFAULT); return true; }删除文档/** * 删除文档 */ public boolean deleteDocument(String indexName, String id) throws IOException { DeleteRequest request new DeleteRequest(indexName, id); client.delete(request, RequestOptions.DEFAULT); return true; }更新文档/** * 更新文档 */ public boolean updateDocument(String index, String id, String jsonSource) { boolean ackFLag false; UpdateRequest request new UpdateRequest(index, id) .doc(jsonSource, XContentType.JSON); try { UpdateResponse response client.update(request, RequestOptions.DEFAULT); ackFLag response.status() RestStatus.CREATED || response.status() RestStatus.OK; } catch (IOException e) { e.printStackTrace(); } return ackFLag; }根据id获取文档/** * 根据ID获取文档 */ public MapString, Object getDocumentById(String indexName, String id) throws IOException { GetRequest request new GetRequest(indexName, id); GetResponse response client.get(request, RequestOptions.DEFAULT); if (response.isExists()) { return response.getSourceAsMap(); } return null; }解析搜索结果/** * 解析搜索结果 * param response 响应信息 * return 查询数据 */ private ListMapString, Object parseSearchResponse(SearchResponse response) { ListMapString, Object resultList new ArrayList(); log.info(查询到的数据总数量{}, response.getHits().getTotalHits()); for (SearchHit hit : response.getHits().getHits()) { resultList.add(hit.getSourceAsMap()); } return resultList; }