遥遥领先

MD

https://github.com/DW-Zhou/ES-6.5.4open in new window 地址

sojson.com/analyzeropen in new window ik分词器

Skip to contentopen in new windowPull requestsIssuesMarketplace****Explore

•  Watch 2 •  Star****20 •  Fork****23 • Code • Issuesopen in new window • Pull requestsopen in new window3 • Actionsopen in new window • Projectsopen in new window • Wikiopen in new window • Securityopen in new window • Insightsopen in new window master  ES-6.5.4**/ElasticSearch知识点.mdGo to filedengzhou** ES增加复合查询部分open in new windowLatest commit 05d54aaopen in new window on 23 Jul 2020 History 0 contributors1159 lines (949 sloc)  31.6 KBRaw****Blame   ElaticSearch 1.索引基本操作 1.1 创建一个索引 #创建一个索引


PUT /person
{
  "settings": {
    "number_of_shards": 5,
    "number_of_replicas": 1
  }
}

1.2 查看索引信息 #查看索引


GET /person

1.3 删除索引 #删除索引


DELETE /person

1.4 ES中Field可以指定的类型 #String: text：一般用于全文检索。将当前的field进行分词 # keyword: 当前的Field不可被分词 # # # # 1.5 创建索引并指定数据结构 ——以创建小说为例子


PUT /book
{
  "settings": {
      #备份数
    "number_of_replicas": 1,
      #分片数
       "number_of_shards": 5
  },
    #指定数据结构
  "mappings": {
    #指定类型 Type
    "novel": {
    # 文件存储的Field属性名
      "properties": {
        "name": {
          "type": "text",
          "analyzer": "ik_max_word",
    #   指定当前的Field可以作为查询的条件
          "index": true
        },
        "authoor": {
          "type": "keyword"
        },
        "onsale": {
          "type": "date",
          "format": "yyyy-MM-dd"
        }
      }
    }
  }
}

1.6 文档的操作 • 文档在ES服务中的唯一标志，_index, _type, _id 三个内容为组合，来锁定一个文档，操作抑或是修改 1.6.1 新建文档 • 自动生成id PUT /book/novel { "name": "西游记", "authoor": "刘明", "onsale": "2020-12-11" } • 手动指定ID（更推荐） PUT /book/novel/1 { "name": "三国演义", "authoor": "小明", "onsale": "2020-12-11" } 1.6.2 修改文档 • 覆盖式修改 POST /book/novel/1 { "name": "三国演义", "authoor": "小明", "onsale": "2020-12-11" } • doc修改方式（更推荐） POST /book/novel/1/_update { "doc": { "name": "极品家丁" } } #先锁定文档，_update 修改需要的字段即可 1.6.3 删除文档 • 删库跑路 DELETE /book/novel/1 2. java操作ElaticSearch 2.1 Java链接ES 1、创建Maven工程 导入依赖 # 4个依赖 1、1 elasticsearch <!-- https://mvnrepository.com/artifact/org.elasticsearch/elasticsearch --> <dependency> <groupId>org.elasticsearch</groupId> <artifactId>elasticsearch</artifactId> <version>6.5.4</version> </dependency> 1、2 elasticsearch的高级API <!-- https://mvnrepository.com/artifact/org.elasticsearch.client/elasticsearch-rest-high-level-client --> <dependency> <groupId>org.elasticsearch.client</groupId> <artifactId>elasticsearch-rest-high-level-client</artifactId> <version>6.5.4</version> </dependency> 1、3 junit <!-- https://mvnrepository.com/artifact/junit/junit --> <dependency> <groupId>junit</groupId> <artifactId>junit</artifactId> <version>4.12</version> <scope>test</scope> </dependency> 1、4 lombok <!-- https://mvnrepository.com/artifact/org.projectlombok/lombok --> <dependency> <groupId>org.projectlombok</groupId> <artifactId>lombok</artifactId> <version>1.18.12</version> <scope>provided</scope> </dependency> 2.1.2 创建测试类，连接ES // 先创建连接，工具类 public class ESClient { public static RestHighLevelClient getClient(){ // 创建HttpHost对象 HttpHost httpHost = new HttpHost("127.0.0.1",9200); // 创建RestClientBuilder RestClientBuilder builder = RestClient.builder(httpHost); // 创建RestHighLevelClien对象 RestHighLevelClient client = new RestHighLevelClient(builder); return client; } } 2.2 java创建索引 import com.dengzhou.utils.ESClient; import org.elasticsearch.action.admin.indices.create.CreateIndexRequest; import org.elasticsearch.action.admin.indices.create.CreateIndexResponse; import org.elasticsearch.client.RequestOptions; import org.elasticsearch.client.RestHighLevelClient; import org.elasticsearch.common.settings.Settings; import org.elasticsearch.common.xcontent.XContentBuilder; import org.elasticsearch.common.xcontent.json.JsonXContent; import org.junit.jupiter.api.Test; import java.io.IOException; public class Create_ES_Index { String index = "person"; String type = "man"; @Test public void createIndex() throws IOException { //1、 准备关于索引的settings Settings.Builder settings = Settings.builder() .put("number_of_shards", 3) .put("number_of_replicas", 1); //2、 准备关于索引的结构mappings XContentBuilder mappings = JsonXContent.contentBuilder() .startObject() .startObject("properties") .startObject("name") .field("type","text") .endObject() .startObject("age") .field("type","integer") .endObject() .startObject("birthday") .field("type","date") .field("format","yyyy-MM-dd") .endObject() .endObject() .endObject(); //2 将settings 和 mappings封装成一个request对象 CreateIndexRequest request = new CreateIndexRequest(index) .settings(settings) .mapping(type,mappings); //3 通过client对象去链接es并执行创建索引 RestHighLevelClient client = ESClient.getClient(); CreateIndexResponse response = client.indices().create(request, RequestOptions.DEFAULT); //测试 System.out.println("response"+response.toString()); } 2.3 检查索引是否存在，删除索引 //检查索引是否存在 @Test public void exists() throws IOException { //1 准备request对象 GetIndexRequest request = new GetIndexRequest(); request.indices(index); // 2 通过client去检查 RestHighLevelClient client = ESClient.getClient(); boolean exists = client.indices().exists(request, RequestOptions.DEFAULT); System.out.println(exists); } 2.4 修改文档 • 添加文档操作 @Test public void createDoc() throws IOException { ObjectMapper mapper = new ObjectMapper(); // 1. 准备json数据 Person person = new Person(1, "张三", 23, new Date()); String json = mapper.writeValueAsString(person); System.out.println(json); // 2. 准备一个request对象(手动指定id创建) IndexRequest indexRequest = new IndexRequest(index,type,person.getId().toString()); indexRequest.source(json, XContentType.JSON); // 3、通过client对象执行添加操作 RestHighLevelClient client = ESClient.getClient(); IndexResponse resp = client.index(indexRequest, RequestOptions.DEFAULT); // 4、 输出返回 System.out.println(resp.getResult().toString()); } • 修改文档 // 修改文档，通过doc方式 @Test public void updateDoc() throws IOException { // 创建map,指定需要修改的内容 Map<String,Object> map = new HashMap<String, Object>(); map.put("name","李四"); String docId = "1"; // 创建一个request对象，封装数据 UpdateRequest updateRequest = new UpdateRequest(index,type,docId); updateRequest.doc(map); // 通过client对象执行 RestHighLevelClient client = ESClient.getClient(); UpdateResponse update = client.update(updateRequest, RequestOptions.DEFAULT); // 返回输出结果 System.out.println(update.getResult().toString()); } 2.5 删除文档 2.6 java批量操作文档 ◦ 3.ElasticSearch练习 • 索引 ： sms-logs-index • 类型：sms-logs-type字段名称备注createDate创建时间StringsendDate发送时间 datelongCode发送长号码 如 16092389287811 stringMobile如 13000000000corpName发送公司名称，需要分词检索smsContent下发短信内容，需要分词检索State短信下发状态 0 成功 1 失败 integerOperatorid运营商编号1移动2联通3电信 integerProvince省份ipAddr下发服务器IP地址replyTotal短信状态报告返回时长 integerFee扣费 integer • 创建实例代码 //先定义索引名和类型名 String index = "sms_logs_index"; String type = "sms_logs_type"; public void create_index() throws IOException { Settings.Builder settings = Settings.builder() .put("number_of_shards", 3) .put("number_of_replicas", 1); XContentBuilder mappings = JsonXContent.contentBuilder() .startObject() .startObject("properties") .startObject("createDate") .field("type", "text") .endObject() .startObject("sendDate") .field("type", "date") .field("format", "yyyy-MM-dd") .endObject() .startObject("longCode") .field("type", "text") .endObject() .startObject("mobile") .field("type", "text") .endObject() .startObject("corpName") .field("type", "text") .field("analyzer", "ik_max_word") .endObject() .startObject("smsContent") .field("type", "text") .field("analyzer", "ik_max_word") .endObject() .startObject("state") .field("type", "integer") .endObject() .startObject("operatorid") .field("type", "integer") .endObject() .startObject("province") .field("type", "text") .endObject() .startObject("ipAddr") .field("type", "text") .endObject() .startObject("replyTotal") .field("type", "integer") .endObject() .startObject("fee") .field("type", "integer") .endObject() .endObject() .endObject(); CreateIndexRequest request = new CreateIndexRequest(index) .settings(settings) .mapping(type,mappings); RestHighLevelClient client = ESClient.getClient(); CreateIndexResponse response = client.indices().create(request, RequestOptions.DEFAULT); System.out.println(response.toString()); } ◦ 数据导入部分 PUT /sms_logs_index/sms_logs_type/1 { "corpName": "途虎养车", "createDate": "2020-1-22", "fee": 3, "ipAddr": "10.123.98.0", "longCode": 106900000009, "mobile": "1738989222222", "operatorid": 1, "province": "河北", "relyTotal": 10, "sendDate": "2020-2-22", "smsContext": "【途虎养车】亲爱的灯先生，您的爱车已经购买", "state": 0 } 4. ES的各种查询 4.1 term&terms查询 4.1.1 term查询 • term的查询是代表完全匹配，搜索之前不会对你的关键字进行分词 **

#term匹配查询(完整匹配):

** POST /sms_logs_index/sms_logs_type/_search { "from": 0, #limit from,size "size": 5, "query": { "term": { "province": { "value": "河北" } } } }

##不会对term中所匹配的值进行分词查询 // java代码实现方式 @Test public void testQuery() throws IOException { // 1 创建Request对象 SearchRequest request = new SearchRequest(index); request.types(type); // 2 指定查询条件 SearchSourceBuilder builder = new SearchSourceBuilder(); builder.from(0); builder.size(5); builder.query(QueryBuilders.termQuery("province", "河北")); request.source(builder); // 3 执行查询 RestHighLevelClient client = ESClient.getClient(); SearchResponse response = client.search(request, RequestOptions.DEFAULT); // 4 获取到_source中的数据 for (SearchHit hit : response.getHits().getHits()) { Map<String, Object> result = hit.getSourceAsMap(); System.out.println(result); } } • terms是针对一个字段包含多个值得运用 ◦ terms: where province = 河北 or province = ? or province = ? #terms 匹配查询 POST /sms_logs_index/sms_logs_type/_search { "from": 0, "size": 5, "query": { "terms": { "province": [ "河北", "河南" ] } } } // java代码 terms 查询 @Test public void test_terms() throws IOException { SearchRequest request = new SearchRequest(index); request.types(type); SearchSourceBuilder builder = new SearchSourceBuilder(); builder.query(QueryBuilders.termsQuery("province","河北","河南")); request.source(builder); RestHighLevelClient client = ESClient.getClient(); SearchResponse resp = client.search(request, RequestOptions.DEFAULT); for (SearchHit hit : resp.getHits().getHits()){ System.out.println(hit); } } 4.2 match查询 match查询属于高层查询，它会根据你查询字段类型不一样，采用不同的查询方式 match查询，实际底层就是多个term查询，将多个term查询的结果进行了封装 • 查询的如果是日期或者是数值的话，它会根据你的字符串查询内容转换为日期或者是数值对等 • 如果查询的内容是一个不可被分的内容（keyword），match查询不会对你的查询的关键字进行分词 • 如果查询的内容是一个可被分的内容（text）,match则会根据指定的查询内容按照一定的分词规则去分词进行查询 4.2.1 match_all查询 查询全部内容，不指定任何查询条件 POST /sms_logs_index/sms_logs_type/_search { "query": { "match_all": {} } } @Test public void test_match_all() throws IOException { // 创建Request ,放入索引和类型 SearchRequest request = new SearchRequest(index); request.types(type); builder.size(20); //es默认查询结果只展示10条，这里可以指定展示的条数 //指定查询条件 SearchSourceBuilder builder = new SearchSourceBuilder(); builder.query(QueryBuilders.matchAllQuery()); request.source(builder); // 执行查询 RestHighLevelClient client = ESClient.getClient(); SearchResponse response = client.search(request, RequestOptions.DEFAULT); // 获取查询结果，遍历显示 for (SearchHit hit : response.getHits().getHits()){ System.out.println(hit); } } 4.2.2 match查询 根据某个Field POST /sms_logs_index/sms_logs_type/_search { "query": { "match": { "smsContent": "打车" } } } @Test public void test_match_field() throws IOException { SearchRequest request = new SearchRequest(index); request.types(type); SearchSourceBuilder builder = new SearchSourceBuilder(); builder.query(QueryBuilders.matchQuery("smsContext","打车")); request.source(builder); RestHighLevelClient client = ESClient.getClient(); SearchResponse response = client.search(request, RequestOptions.DEFAULT); for (SearchHit hit : response.getHits().getHits()){ System.out.println(hit); } } 4.2.3 布尔match查询 基于一个Filed匹配的内容，采用and或者or的方式进行连接 # 布尔match查询 POST /sms_logs_index/sms_logs_type/_search { "query": { "match": { "smsContext": { "query": "打车 女士", "operator": "and" #or } } } } @Test public void test_match_boolean() throws IOException { SearchRequest request = new SearchRequest(index); request.types(type); SearchSourceBuilder builder = new SearchSourceBuilder(); builder.query(QueryBuilders.matchQuery("smsContext","打车 女士").operator(Operator.AND)); request.source(builder); RestHighLevelClient client = ESClient.getClient(); SearchResponse response = client.search(request, RequestOptions.DEFAULT); for (SearchHit hit : response.getHits().getHits()){ System.out.println(hit); } 4.2.4 multi_match查询 match针对一个field做检索，multi_match针对多个field进行检索，多个key对应一个text POST /sms_logs_index/sms_logs_type/_search { "query": { "multi_match": { "query": "河北", #指定text "fields": ["province","smsContext"] #指定field } } } // java 实现 @Test public void test_multi_match() throws IOException { SearchRequest request = new SearchRequest(index); request.types(type); SearchSourceBuilder builder = new SearchSourceBuilder(); // 查询的文本内容 字段1 字段2 字段3 。。。。。 builder.query(QueryBuilders.multiMatchQuery("河北", "province", "smsContext")); request.source(builder); RestHighLevelClient client = ESClient.getClient(); SearchResponse response = client.search(request, RequestOptions.DEFAULT); for (SearchHit hit : response.getHits().getHits()) { System.out.println(hit); } } 4.3 ES 的其他查询 4.3.1 ID 查询 # id查询 GET /sms_logs_index/sms_logs_type/1 GET /索引名/type类型/id public void test_multi_match() throws IOException { GetRequest request = new GetRequest(index,type,"1"); RestHighLevelClient client = ESClient.getClient(); GetResponse resp = client.get(request, RequestOptions.DEFAULT); System.out.println(resp.getSourceAsMap()); } 4.3.2 ids查询 根据多个id进行查询，类似MySql中的where Id in (id1,id2,id3….) POST /sms_logs_index/sms_logs_type/_search { "query": { "ids": { "values": [1,2,3] #id值 } } } //java代码 @Test public void test_query_ids() throws IOException { SearchRequest request = new SearchRequest(index); request.types(type); SearchSourceBuilder builder = new SearchSourceBuilder(); builder.query(QueryBuilders.idsQuery().addIds("1","2","3")); request.source(builder); RestHighLevelClient client = ESClient.getClient(); SearchResponse response = client.search(request, RequestOptions.DEFAULT); for (SearchHit hit : response.getHits().getHits()){ System.out.println(hit.getSourceAsMap()); } } 4.3.3 prefix查询 前缀查询，可以通过一个关键字去指定一个Field的前缀，从而查询到指定的文档 POST /sms_logs_index/sms_logs_type/_search { "query": { "prefix": { "smsContext": { "value": "河" } } } } #与 match查询的不同在于，prefix类似mysql中的模糊查询。而match的查询类似于严格匹配查询 # 针对不可分割词 @Test public void test_query_prefix() throws IOException { SearchRequest request = new SearchRequest(index); request.types(type); SearchSourceBuilder builder = new SearchSourceBuilder(); builder.query(QueryBuilders.prefixQuery("smsContext","河")); request.source(builder); RestHighLevelClient client = ESClient.getClient(); SearchResponse response = client.search(request, RequestOptions.DEFAULT); for (SearchHit hit : response.getHits().getHits()){ System.out.println(hit.getSourceAsMap()); } } 4.3.4 fuzzy查询 fuzzy查询：模糊查询，我们可以输入一个字符的大概，ES就可以根据输入的内容大概去匹配一下结果，eg.你可以存在一些错别字 #fuzzy查询 #fuzzy查询 POST /sms_logs_index/sms_logs_type/_search { "query": { "fuzzy": { "corpName": { "value": "盒马生鲜", "prefix_length": 2 # 指定前几个字符要严格匹配 } } } } #不稳定，查询字段差太多也可能查不到 // java 实现 @Test public void test_query_fuzzy() throws IOException { SearchRequest request = new SearchRequest(index); request.types(type); SearchSourceBuilder builder = new SearchSourceBuilder(); builder.query(QueryBuilders.fuzzyQuery("corpName","盒马生鲜").prefixLength(2)); request.source(builder); RestHighLevelClient client = ESClient.getClient(); SearchResponse response = client.search(request, RequestOptions.DEFAULT); for (SearchHit hit : response.getHits().getHits()){ System.out.println(hit.getSourceAsMap()); } } .prefixLength() :指定前几个字符严格匹配 4.3.5 wildcard查询 通配查询，与mysql中的like查询是一样的，可以在查询时，在字符串中指定通配符*和占位符？ #wildcard查询 POST /sms_logs_index/sms_logs_type/_search { "query": { "wildcard": { "corpName": { "value": "*车" # 可以使用*和？指定通配符和占位符 } } } } ?代表一个占位符 ??代表两个占位符 // java代码 @Test public void test_query_wildcard() throws IOException { SearchRequest request = new SearchRequest(index); request.types(type); SearchSourceBuilder builder = new SearchSourceBuilder(); builder.query(QueryBuilders.wildcardQuery("corpName","*车")); request.source(builder); RestHighLevelClient client = ESClient.getClient(); SearchResponse response = client.search(request, RequestOptions.DEFAULT); for (SearchHit hit : response.getHits().getHits()){ System.out.println(hit.getSourceAsMap()); } } 4.3.6 range查询 范围查询，只针对数值类型，对某一个Field进行大于或者小于的范围指定 POST /sms_logs_index/sms_logs_type/_search { "query": { "range": { "relyTotal": { "gte": 0, "lte": 3 } } } } 查询范围:[gte,lte] 查询范围：(gt,lt) //java代码 @Test public void test_query_range() throws IOException { SearchRequest request = new SearchRequest(index); request.types(type); SearchSourceBuilder builder = new SearchSourceBuilder(); builder.query(QueryBuilders.rangeQuery("fee").lt(5).gt(2)); request.source(builder); RestHighLevelClient client = ESClient.getClient(); SearchResponse response = client.search(request, RequestOptions.DEFAULT); for (SearchHit hit : response.getHits().getHits()){ System.out.println(hit.getSourceAsMap()); } } 4.3.7 regexp查询 正则查询，通过你编写的正则表达式去匹配内容 PS: prefix,fuzzy,wildcar和regexp查询效率相对比较低,在对效率要求比较高时，避免去使用 POST /sms_logs_index/sms_logs_type/_search { "query": { "regexp": { "moible": "109[0-8]{7}" # 匹配的正则规则 } } } //java 代码 @Test public void test_query_regexp() throws IOException { SearchRequest request = new SearchRequest(index); request.types(type); SearchSourceBuilder builder = new SearchSourceBuilder(); builder.query(QueryBuilders.regexpQuery("moible","106[0-9]{8}")); request.source(builder); RestHighLevelClient client = ESClient.getClient(); SearchResponse response = client.search(request, RequestOptions.DEFAULT); for (SearchHit hit : response.getHits().getHits()){ System.out.println(hit.getSourceAsMap()); } } 4.4 深分页Scroll ES对from+size有限制，from和size两者之和不能超过1w 原理： from+size ES查询数据的方式： 1 先将用户指定的关键词进行分词处理 2 将分词去词库中进行检索，得到多个文档的id 3 去各个分片中拉去指定的数据 耗时 4 根据数据的得分进行排序 耗时 5 根据from的值，将查询到的数据舍弃一部分， 6 返回查询结果 Scroll+size 在ES中查询方式 1 先将用户指定的关键词进行分词处理 2 将分词去词库中进行检索，得到多个文档的id 3 将文档的id存放在一个ES的上下文中，ES内存 4 根据你指定给的size的个数去ES中检索指定个数的数据，拿完数据的文档id,会从上下文中移除 5 如果需要下一页的数据，直接去ES的上下文中，找后续内容 6 循环进行4.5操作 缺点，Scroll是从内存中去拿去数据的，不适合做实时的查询，拿到的数据不是最新的 # 执行scroll查询，返回第一页数据，并且将文档id信息存放在ES的上下文中，指定生存时间 POST /sms_logs_index/sms_logs_type/_search?scroll=1m { "query": { "match_all": {} }, "size": 2, "sort": [ { "fee": { "order": "desc" } } ] } #查询下一页的数据 POST /_search/scroll { "scroll_id": "DnF1ZXJ5VGhlbkZldGNoAwAAAAAAACSPFnJjV1pHbENVVGZHMmlQbHVZX1JGdmcAAAAAAAAkkBZyY1daR2xDVVRmRzJpUGx1WV9SRnZnAAAAAAAAJJEWcmNXWkdsQ1VUZkcyaVBsdVlfUkZ2Zw==", "scoll" :"1m" #scorll信息的生存时间 } #删除scroll在ES中上下文的数据 DELETE /_search/scroll/scrill_id //java代码 @Test public void test_query_scroll() throws IOException { // 1 创建SearchRequest SearchRequest request = new SearchRequest(index); request.types(type); // 2 指定scroll信息,生存时间 request.scroll(TimeValue.timeValueMinutes(1L)); // 3 指定查询条件 SearchSourceBuilder builder = new SearchSourceBuilder(); builder.size(2); builder.sort("fee",SortOrder.DESC); builder.query(QueryBuilders.matchAllQuery()); // 4 获取返回结果scrollid ,source request.source(builder); RestHighLevelClient client = ESClient.getClient(); SearchResponse response = client.search(request,RequestOptions.DEFAULT); String scrollId = response.getScrollId(); System.out.println(scrollId); while(true){ // 5 循环创建SearchScrollRequest SearchScrollRequest scrollRequest = new SearchScrollRequest(scrollId); // 6 指定scrollid生存时间 scrollRequest.scroll(TimeValue.timeValueMinutes(1L)); // 7 执行查询获取返回结果 SearchResponse scrollResp = client.scroll(scrollRequest, RequestOptions.DEFAULT); // 8.判断是否得到数据，输出 if (scrollResp.getHits().getHits() != null && scrollResp.getHits().getHits().length > 0){ System.out.println("=======下一页的数据========"); for (SearchHit hit : scrollResp.getHits().getHits()){ System.out.println(hit.getSourceAsMap()); } }else{ // 9。判断没有查询到数据-退出循环 System.out.println("没得"); break; } } // 10 创建clearScrollRequest ClearScrollRequest clearScrollRequest = new ClearScrollRequest(); // 11 指定scrollid clearScrollRequest.addScrollId(scrollId); // 12 删除 client.clearScroll(clearScrollRequest,RequestOptions.DEFAULT); } 4.5 delete-by-query 根据term，match等查询方式去删除大量的文档 如果你需要删除的内容，是index下的大部分数据，不建议使用，建议逆向操作，创建新的索引，添加需要保留的数据内容 POST /sms_logs_index/sms_logs_type/_delete_by_query { "query": { "range": { "relyTotal": { "gte": 2, "lte": 3 } } } } ##中间跟你的查询条件，查到什么，删什么t public class test_sms_search2 { String index = "sms_logs_index"; String type = "sms_logs_type"; @Test public void test_query_fuzzy() throws IOException { DeleteByQueryRequest request = new DeleteByQueryRequest(index); request.types(type); request.setQuery(QueryBuilders.rangeQuery("relyTotal").gt("2").lt("3")); RestHighLevelClient client = ESClient.getClient(); BulkByScrollResponse response = client.deleteByQuery(request, RequestOptions.DEFAULT); System.out.println(response.toString()); } } 4.6 复合查询 4.6. 1 bool查询 复合过滤器，可以将多个查询条件以一定的逻辑组合在一起，and or • must : 所有的条件，用must组合在一起，表示AND • must_not:将must_not中的条件，全部不能匹配，表示not的意思，不能匹配该查询条件 • should: 所有条件，用should组合在一起，表示or的意思，文档必须匹配一个或者多个查询条件 • filter: 过滤器，文档必须匹配该过滤条件，跟must子句的唯一区别是，filter不影响查询的score #查询省份为河北或者河南的 #并且公司名不是河马生鲜的 #并且smsContext中包含软件两个字 POST /sms_logs_index/sms_logs_type/_search { "query": { "bool": { "should": [ { "term": { "province": { "value": "河北" } } }, { "term": { "province": { "value": "河南" } } ], "must_not": [ { "term": { "corpName": { "value": "河马生鲜" } } } ], "must": [ { "match": { "smsContext": "软件" } } ] } } }

Loading complete

boosting查询

image

image

这里如果又匹配上了 negative 匹配上后分数会乘以0.5

filter 过滤器查询

image

image

ES高亮查询

image

image

ES聚合查询

image

去重计数查询

image

范围统计

image

image

from带等于 to不带等于

时间范围统计

image

ip方式统计

image

统计聚合查询

image

image

image

$searchParams = [
            'index' => $indexArr,
            'size' => 0,
            'body' => [
                'query' => [
                    'bool' => [
                        'must' => [
                            ['term' => ['app_id' => $option['app_id']]],
                            ['terms' => ['function_id' => $function->pluck('id')->toArray()]],
                        ]
                    ]
                ],
                'aggs' => [
                    'func_total' => [
                        'terms' => [
                            'size' => 8000,
                            'field' => 'function_id',
                            'order' => ['func_users_num.value' => 'desc']
                        ],
                        'aggs' => [
                            'sys_customer_num' => ['sum' => ['field' => 'sys_customer_num']],   //系统访客数
                            'func_customer_num' => ['sum' => ['field' => 'func_customer_num']],  //功能访客数
                            'sys_view_num' => ['sum' => ['field' => 'sys_view_num']],   //系统访问量
                            'func_view_num' => ['sum' => ['field' => 'func_view_num']],  //功能访问量
                            'sys_use_num' => ['sum' => ['field' => 'sys_use_num']],  //系统使用量
                            'func_use_num' => ['sum' => ['field' => 'func_use_num']],  //功能使用量
                            'sys_hit_num' => ['sum' => ['field' => 'sys_hit_num']], //系统点击量
                            'func_hit_num' => ['sum' => ['field' => 'func_hit_num']],  //功能点击量
                            'total_time_on_page' => ['sum' => ['field' => 'total_time_on_page']],  //总页面停留时间
                            'func_users_num' => ['sum' => ['field' => 'func_users_num']],  //用户数（计算平均访问深度）
                            'func_session_num' => ['sum' => ['field' => 'func_session_num']],  //会话数
                            'avg_session_duration' => ['avg' => ['field' => 'avg_session_duration']],  //平均会话时长
                            'total_page_load_time' => ['sum' => ['field' => 'total_page_load_time']],  //总网页加载时间
                            'page_load_sample' => ['sum' => ['field' => 'page_load_sample']],  //网页加载样本
                        ]
                    ]
                ]
            ]
        ];

地图经纬度

image

image

基于api

image

image

https://www.cnblogs.com/yfb918/p/11023581.html#:~:text=elastics,10条数据返回。open in new window

分页方案

search_after 的方式

track_total_hits

Last Updated:
Contributors: 刘荣杰