留神这些所以的货色版本都要一样

ElasticSearch装置

jdk至多1.8 ElasticSearch客户端，界面工具

留神

jdk必须与cpu的位数是一样的否则会报JNA谬误

下载地址

https://www.elastic.co/cn/ shearch和kibabn

https://github.com/medcl/elas... ik分词器

https://github.com/mobz/elast... head插件下载

这些都是解压可用

Elasticearch 启动

点击 bin\下的elasticsearch.bat

如果电脑内存不够大启动前记得去 config\jvm.options 批改

-Xms256m

   -Xmx256m

拜访 http://127.0.0.1:9200/

head插件

必须要有 nodejs 因为他是前端写的

cnpm install 装置依赖
cnpm run start

留神如果9100端口被占用

netstat -ano | findstr "9100"

而后去工作管理器详细信息里去关

启动胜利拜访 http://localhost:9100/

9200 和 9100 是跨域的

须要在elasticearch.yaml中配置跨域

http.cors.enabled: truehttp.cors.allow-origin: "*"

而后重启es服务

head就相当于navicat

kibana

这也是一个规范的前端化工程

bin\kibana.bat

http://localhost:5601

找到开发工具

汉化！！！！

改配置kibana.yaml

i18n.locale: "zh-CN"

IK分词器(中文) elasticsreach默认的不是中文的

放在elasticsreach中的plugins中

有两种算法

ik_smart 默认分词器他所能了解不反复的单词或者字

ik_max_word 最细粒度穷进词库可能

GET _analyze{  "analyzer": "ik_smart",  "text": "我超级喜爱多帅哦"}GET _analyze{  "analyzer": "ik_max_word",  "text": "我超级喜爱多帅哦"}

你本人须要的词，须要本人加到字典中

IKAnalyzer.cfg.xml编写本人的kb.dic而后在配置文件中增加<entry key="ext_dict">kb.dic</entry>重启es

Rest格调

1、创立一个索引随到在申请体中插入数据

PUT /索引名/类型名(可无)/文档id{    json申请体}

增加

创立一个索引，指定字段类型然而没有插入信息

PUT /test2{  "mappings": {    "properties": {      "name":{        "type": "text"      },      "age": {        "type": "long"      },      "birthday":{        "type": "date"      }    }  }}

取得信息

GET test2

如果不写就是默认类型 _doc keyword是不可分割的

PUT /test3/_doc/1{  "name": "多帅哦",  "age": 18,  "birthday": "1999-10-20"}

GET _cat/health   数据库状态GET _cat/indices?v     数据库信息

批改

1、间接暴力PUT

PUT /test3/_doc/1{  "name": "多帅哦123",  "age": 18,  "birthday": "1999-10-20"}然而索引信息会扭转   版本啊  状态啊

2、POST

POST /test3/_doc/1/_update{  "doc":{    "name":"shuaikb"  }}

3、删除索引

DELETE test1 依据你的申请是删除什么 索引或者文档

条件查问

GET /test3/_search?q=name:多帅哦/"_score" : 0.5753642,这个_score是匹配度   匹配度越高分数越高

简单搜寻

GET /test3/_search{  "query": {    "match": {      "name": "多帅"    }  }}name里蕴含 多帅 的都会进去"hits"外面蕴含了 索引的信息 和查问的后果GET /test3/_search{  "query": {    "match": {      "name": "多帅"    }  },  "_source": ["name","age"]}查问数据中只显示 name和age当前在java中操作es  所有的办法都是这里的key排序"sort": [    {      "age": {        "order": "desc"      }    }  ]通过什么字段进行排序   desc降序  asc升序分页"from": 0,  第几个数据开始"size": 1   返回多少条

布尔值查问

GET /test3/_search{  "query": {    "bool": {      "must": [        {          "match": {            "name": "多帅"          }        },        {          "match":{          "age": 18          }        }      ]    }  }}准确匹配  多条件查问   must   相当于 and  should 想当于 ornot    相当于  !=GET /test3/_search{  "query": {    "bool": {      "must": [        {          "match": {            "name": "多帅"          }        }      ],      "filter": [        {          "range": {            "age": {              "gte": 10,              "lte": 17            }          }        }      ]    }  }}filter 能够进行数据过滤 gt> gte>=    lt< lte<=  eq

GET /test3/_search{  "query": {    "match": {      "tag": "男 技术"    }  }}tag查问的多个属性 用空格隔开term，查问时通过倒排是索引进行准确查问match，会应用分词器解析 (先剖析文档，而后通过剖析文档进行查问！)

两个类型

text 能被分词器解析
keyword 不能被分词器解析

GET _analyze{  "analyzer": "standard",  "text": "多帅哦Shuaikb name1"}只有分词器不是keyword就不会被拆分GET testdb/_search{  "query": {    "term": {      "desc": {        "value": "多帅哦Shuaikb desc"      }    }  }}准确匹配         keyword类型的字段不会被分词器解析你会发现  多帅哦Shuaikb desc2不会被查问进去

多个值匹配的准确查问

GET testdb/_search{  "query": {    "bool": {      "should": [        {          "term": {            "t1": {              "value": "22"            }          }        },        {          "term": {            "t1": {              "value": "33"            }          }        }      ]    }  }}

高亮查问

GET testdb/_search{ "query": {   "match": {     "name": "帅"   } }, "highlight": {   "fields": {     "name": {}   } }}"多<em>帅</em>哦Shuaikb name2"这个<em>就是高亮的html自定义搜寻高亮条件GET testdb/_search{ "query": {   "match": {     "name": "帅"   } }, "highlight": {   "pre_tags": "<p class='key' style='color:red'>",   "post_tags": "</p>",    "fields": {     "name": {}   } }}

Spirngboot集成es

原生依赖<repositories>    <repository>        <id>es-snapshots</id>        <name>elasticsearch snapshot repo</name>        <url>https://snapshots.elastic.co/maven/</url>    </repository></repositories>理论咱们导入的依赖<dependency>            <groupId>org.springframework.boot</groupId>            <artifactId>spring-boot-starter-data-elasticsearch</artifactId></dependency>留神依赖的版本必须要和本人的本地的es版本统一所以须要自定义版本依赖初始化RestHighLevelClient client = new RestHighLevelClient(        RestClient.builder(                new HttpHost("localhost", 9200, "http"),                new HttpHost("localhost", 9201, "http")));用完记得关client.close();@Bean    public RestHighLevelClient restHighLevelClient(){        RestHighLevelClient client =new RestHighLevelClient(                RestClient.builder(                        new HttpHost("localhost", 9200, "http"),                        new HttpHost("localhost", 9201, "http")));        return client;    }

API

索引操作

 @Test    public void CreateIndex() throws IOException {        //创立索引        CreateIndexRequest requst = new CreateIndexRequest("shuaikb_index");        //执行申请 取得响应        CreateIndexResponse createIndexResponse =                client.indices().create(requst, RequestOptions.DEFAULT);        System.out.println(createIndexResponse);    }    @Test    void testExisIndex() throws IOException {        //判断存在        GetIndexRequest request =new GetIndexRequest("shuaikb_index");        boolean exists = client.indices().exists(request, RequestOptions.DEFAULT);        System.out.println(exists);    }    @Test    void testDeleteIndex() throws IOException {        //删除索引        DeleteIndexRequest request =new DeleteIndexRequest("shuaikb_index");        AcknowledgedResponse delete = client.indices().delete(request, RequestOptions.DEFAULT);        System.out.println(delete);    }

文档操作

@Test    void testAddDocument() throws IOException {        //增加文档        Dog dog = new Dog();        dog.setName("多帅哦");        dog.setAge(12);        IndexRequest requst = new IndexRequest("shuaikb_index");        //规定 PUT /shuaikb_index/_doc/1        requst.id("1");        requst.timeout(TimeValue.timeValueSeconds(1));        requst.timeout("1s");        //将咱们的数据放入申请 json        requst.source(JSON.toJSONString(dog), XContentType.JSON);        //客户端发送申请        IndexResponse indexResponse = client.index(requst, RequestOptions.DEFAULT);        System.out.println(indexResponse.toString());        System.out.println(indexResponse.status());    }    @Test    void testExisDocument() throws IOException {        //判断文档存在        GetRequest getRequest = new GetRequest("shuaikb_index","1");        //不获取返回的_source的上下文        getRequest.fetchSourceContext(new FetchSourceContext(false));        getRequest.storedFields("_noe_");        boolean exists = client.exists(getRequest, RequestOptions.DEFAULT);        System.out.println(exists);    }    @Test    void testGetDocument() throws IOException {        //获取文档信息        GetRequest getRequest = new GetRequest("shuaikb_index","1");        GetResponse documentFields = client.get(getRequest, RequestOptions.DEFAULT);        System.out.println(documentFields.getSourceAsString());        System.out.println(documentFields);    }    @Test    void testUpdateDocument() throws IOException {        //更新文档信息        UpdateRequest updateRequest = new UpdateRequest("shuaikb_index","1");        updateRequest.timeout("1s");        Dog dog = new Dog("你怎么说",20);        updateRequest.doc(JSON.toJSONString(dog),XContentType.JSON);        client.update(updateRequest,RequestOptions.DEFAULT);    }    @Test    void testDeleteDocument() throws IOException {        //删除文档信息        DeleteRequest deleteRequest = new DeleteRequest("shuaikb_index","1");        deleteRequest.timeout("1s");        DeleteResponse delete = client.delete(deleteRequest, RequestOptions.DEFAULT);        System.out.println(delete);    }

大量数据操作

//大量数据操作    @Test    void testBulkRequest() throws IOException {        BulkRequest bulkRequest = new BulkRequest();        bulkRequest.timeout("10s");        ArrayList<Dog> dogArrayList = new ArrayList<Dog>();        dogArrayList.add(new Dog("test1",1));        dogArrayList.add(new Dog("test2",1));        dogArrayList.add(new Dog("test3",1));        dogArrayList.add(new Dog("test4",1));        dogArrayList.add(new Dog("shuaikb1",1));        dogArrayList.add(new Dog("shuaikb2",1));        dogArrayList.add(new Dog("shuaikb3",1));        dogArrayList.add(new Dog("shuaikb4",1));        for (int i = 0; i <dogArrayList.size() ; i++) {            bulkRequest.add(new IndexRequest("shuaikb_index")                    .id(""+(i+1))//不指定id就会随机生成一个简单id                    .source(JSON.toJSONString(dogArrayList.get(i)),XContentType.JSON));        }        BulkResponse bulk = client.bulk(bulkRequest, RequestOptions.DEFAULT);        System.out.println(bulk.hasFailures());//返回false代表胜利    }    //查问    //searchRequest  搜寻申请    //searchSourceBuilder  条件结构    // HighlightBuilder  结构高亮    //MatchAllQueryBuilders  全副查问    //TermQueryBuilder   准确查问    @Test    void testSearch() throws IOException {        SearchRequest searchRequest = new SearchRequest("shuaikb_index");        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();        //准确        TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("name", "test1");        //全副        //MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();        searchSourceBuilder.query(termQueryBuilder);        searchSourceBuilder.from();        searchSourceBuilder.size();        searchSourceBuilder.timeout(new TimeValue(60, TimeUnit.SECONDS));        searchRequest.source(searchSourceBuilder);        SearchResponse search = client.search(searchRequest, RequestOptions.DEFAULT);        System.out.println(JSON.toJSONString(search));        for (SearchHit hit : search.getHits().getHits()) {            System.out.println(hit.getSourceAsMap());        }    }

留神 这些所以的货色版本都要一样