在docker里安装elasticsearch和Kibana

1  安装elasticsearch和Kibana

1.1.下载镜像

docker search elasticsearch
docker pull elasticsearch:7.14.2

1.2.创建挂载的目录　　

mkdir -p /mydata/elasticsearch/config
mkdir -p /mydata/elasticsearch/data
chmod -R 777
echo "http.host: 0.0.0.0" >> /mydata/elasticsearch/config/elasticsearch.yml 
chmod -R 777

1.3.创建容器并启动

docker run --name elasticsearch -p 9200:9200 -p 9300:9300  -e "discovery.type=single-node" -e ES_JAVA_OPTS="-Xms64m -Xmx128m" -v /mydata/elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml -v /mydata/elasticsearch/data:/usr/share/elasticsearch/data -v /mydata/elasticsearch/plugins:/usr/share/elasticsearch/plugins -d elasticsearch:7.14.2

其中elasticsearch.yml是挂载的配置文件，data是挂载的数据，plugins是es的插件，如ik，而数据挂载需要权限，需要设置data文件的权限为可读可写,需要下边的指令。
chmod -R 777 要修改的路径

-e "discovery.type=single-node" 设置为单节点
特别注意：
-e ES_JAVA_OPTS="-Xms256m -Xmx256m" \ 测试环境下，设置ES的初始内存和最大内存，否则导致过大启动不了ES

1.4..Kibana启动　　

　　

mkdir -p /data/elk7/kibana/config/
vi /data/elk7/kibana/config/kibana.yml


#
# ** THIS IS AN AUTO-GENERATED FILE **
#

# Default Kibana configuration for docker target
server.name: kibana
server.host: "0"
elasticsearch.hosts: [ "http://192.168.31.190:9200" ]
xpack.monitoring.ui.container.elasticsearch.enabled: true

docker pull kibana:7.14.2

docker run -d \
--name=kibana \
--restart=always \
-p 5601:5601 \
-v /data/elk7/kibana/config/kibana.yml:/usr/share/kibana/config/kibana.yml \
kibana:7.14.2

查看日志

docker logs -f kibana

{"type":"log","@timestamp":"2020-08-27T03:00:28Z","tags":["listening","info"],"pid":6,"message":"Server running at http://0:5601"}

{"type":"log","@timestamp":"2020-08-27T03:00:28Z","tags":["info","http","server","Kibana"],"pid":6,"message":"http server running at http://0:5601"}

然后访问页面
http://自己的IP地址:5601
http://自己的IP地址:5601/app/kibana

docker pull kibana:7.14.2

docker run --name kibana -e ELASTICSEARCH_HOSTS=http://自己的IP地址:9200 -p 5601:5601 -d kibana:7.14.2
//docker run --name kibana -e ELASTICSEARCH_URL=http://自己的IP地址:9200 -p 5601:5601 -d kibana:7.14.2

进入容器修改相应内容
server.port: 5601
server.host: 0.0.0.0
elasticsearch.hosts: [ "http://自己的IP地址:9200" ]
i18n.locale: "Zh-CN"

然后访问页面
http://自己的IP地址:5601/app/kibana

2. kibana操作ElasticSearch

2.1._cat

GET /_cat/node 查看所有节点
GET /_cat/health 查看es健康状况
GET /_cat/master 查看主节点
GET /_cat/indices 查看所有索引

2.2 保存文档

保存一个数据，保存在那个索引的那个类型下，指定用唯一的标识，customer为索引,external为类型,1为标识。其中PUT和POST都可以，POST新增。如果不指定ID，会自动生成ID，指定ID就会修改这个数据，并新增版本号。PUT可以新增可以修改，PUT必须指定ID，一般都用来修改操作，不指定ID会报错。

PUT customer/external/1
{
  "name":"张三"
}

返回结果
{
  "_index" : "customer",
  "_type" : "external",
  "_id" : "1",
  "_version" : 3,
  "result" : "updated",
  "_shards" : {
    "total" : 2,
    "successful" : 1,
    "failed" : 0
  },
  "_seq_no" : 1001,
  "_primary_term" : 2
}

2.3 查询文档

GET customer/external/1
    
结果:
{
  "_index" : "customer", //在那个索引
  "_type" : "external", //在那个类型
  "_id" : "1", //记录ID
  "_version" : 1, //版本号
  "_seq_no" : 0, //并发控制字段，每次更新就+1，可用于乐观锁
  "_primary_term" : 1, //主分片重新分配，如重启，就会变化
  "found" : true, //true就是找到数据了
  "_source" : { //数据
    "name" : "张三"
  }
}

2.4 更新文档

POST操作带_update会对比原来的数据，如果是一样的那就不会更新了
POST customer/external/1/_update
{
  "doc":{
    "name":"你好"
  }
}
POST操作不带_update会直接更新操作
POST customer/external/1
{
  "name":"你好"
}

2.5 删除文档

DELETE customer/external/1

2.6 bulk批量API

需要加_bulk，然后请求体中的index是id，下边的是要保存的内容
POST customer/external/_bulk
{"index":{"_id":1}}
{"name":"榨干"}
{"index":{"_id":2}}
{"name":"你瞅啥"}

2.7 查询操作  .   

先导入批量的数据，在进行查询操作。

1>.一种是通过REST request URI 发送搜索的参数，其中_search是固定写法，q=*是查询所有，sort=balance排序是按照balance排序的，asc是升序排序 GET customer/_search?q=*&sort=balance:asc 结果集，took是花费时间，timed_out没有超时，hits是命中的记录

2>.另一种是通过REST request body 来发送，query代表查询条件，match_all是查询所有，sort代表排序条件

GET customer/_search
{
  "query": {
    "match_all": {}
  },
  "sort": [
    {
      "balance": "asc"
    }
  ]
}

3>.分页操作，from是从第几条数据开始，size是一页多少个，默认是十条数据

4>.按需返回参数为，_source　　

GET customer/_search
{
  "query": {
    "match_all": {}
  },
  "sort": [
    {
      "balance": "asc"
    }
  ],
  "from": 11,
  "size": 2, 
  "_source": ["account_number","balance"]
}

　5>.全文检索，使用match操作，查询的结果是按照评分从高到低排序的　　　

GET customer/_search
{
  "query": {
    "match": {
      "age": 20
    }
  }
}

　6>.match_phrase的精确匹配，

GET customer/_search
{
  "query": {
    "match_phrase": {
      "age": 20
    }
  }
}

　7>.多字段匹配，multi_match　　

GET customer/_search
{
  "query": {
    "multi_match": {
      "query": "mill",
      "fields": ["address","email"]
    }
  }
}

　8>.复合查询bool，其中must是必须满足，must_not是必须不满足，should是应该满足，不过不满足的也能查出来，就是得分低，range是区间查询　

GET customer/_search
{
  "query": {
    "bool": {
      "must": [
        {"match": {
          "gender": "F"
        }},
        {"match": {
          "address": "Mill"
        }}
      ],
      "must_not": [
        {"match": {
          "age": "38"
        }}
      ],
      "should": [
        {"match": {
          "lastname": "Long"
        }}
      ]
    }
  }
}

　　9>.filter过滤，区间查询操作，而且filter不会计算相关性得分

GET customer/_search
{
  "query": {
  "bool": {
    "filter": [
      {"range": {
        "age": {
          "gte": 10,
          "lte": 30
        }
      }}
    ]
  }
  }
}

　　10>.team查询，一些精确字段的推荐使用team，而一些全文检索的推荐使用match　　

GET customer/_search
{
  "query": {
    "term": {
      "age": "28"
    }
  }
}

　11.keyword的作用：当有keyword的时候，就会精确查找，而没有keyword的时候，这个值会当成一个关键字

GET customer/_search
{
  "query": {"match": {
    "address.keyword": "789 Madison"
  }}
}

GET customer/_search
{
  "query": {"match_phrase": {
    "address": "789 Madison"
  }}
}

　

2.13 es分析功能（聚合函数）

搜索address中包含mill的所有人的年龄分布以及平均年龄，但不显示这些人的详情
其中，aggs代表使用聚合函数，terms为结果种类求和，avg为平均值，size为0则不显示详细信息
GET customer/_search
{
  "query": {
    "match": {
      "address": "mill"
    }
  },
  "aggs": {
    "ageagg": {
      "terms": {
        "field": "age",
        "size": 10
      }
    },
    "ageavg":{
      "avg": {
        "field": "age"
      }
    }
  },
  "size": 0
}

聚合中还可以有子聚合
GET customer/_search
{
  "query": {
    "match_all": {}
  },
  "aggs": {
    "ageagg": {
      "terms": {
        "field": "age",
        "size": 10
      },
      "aggs": {
        "ageAvg": {
          "avg": {
            "field": "balance"
          }
        }
      }
    }
  },
  "size": 0
}

3 rest-high-level-client整合ElasticSearch

3.1.导入依赖　　

	<!-- 修改springboot默认整合的es的版本 -->
        <properties>
            <java.version>1.8</java.version>
            <elasticsearch.version>7.6.2</elasticsearch.version>
        </properties>
    
        <!-- elasticsearch-rest-high-level-client -->
        <dependency>
            <groupId>org.elasticsearch.client</groupId>
            <artifactId>elasticsearch-rest-high-level-client</artifactId>
            <version>7.6.2</version>
        </dependency>
        
        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>fastjson</artifactId>
            <version>1.2.68</version>
        </dependency>

3.2.编写配置类

@Configuration
public class ElasticSearchClientConfig {
    @Bean
    public RestHighLevelClient restHighLevelClient(){
        RestHighLevelClient client = new RestHighLevelClient(
                RestClient.builder(
                        new HttpHost("自己的IP地址", 9200, "http")
                )
        );
        return client;
    }
}

3.3.进行es的索引操作

@Autowired
    @Qualifier("restHighLevelClient")
    private RestHighLevelClient client;
    //index名字，静态一般都是放在另一个类中的
    public static final String ES_INDEX="han_index";

    //创建索引
    @Test
    public void createIndex() throws IOException {
        //1. 创建索引
        CreateIndexRequest index = new CreateIndexRequest(ES_INDEX);
        //2. 客户端执行请求,请求后获得相应
        CreateIndexResponse response = client.indices().create(index, RequestOptions.DEFAULT);
        //3.打印结果
        System.out.println(response.toString());
    }
    //测试索引是否存在
    @Test
    public void exitIndex() throws IOException{
        //1.
        GetIndexRequest request = new GetIndexRequest(ES_INDEX);
        boolean exists = client.indices().exists(request, RequestOptions.DEFAULT);
        System.out.println("是否存在"+exists);
    }
    //删除索引
    @Test
    public void deleteIndex() throws IOException{
        DeleteIndexRequest request = new DeleteIndexRequest(ES_INDEX);
        AcknowledgedResponse response = client.indices().delete(request, RequestOptions.DEFAULT);
        System.out.println("是否删除"+response);
    }

3.4.es的文档操作　　

    @Autowired
    @Qualifier("restHighLevelClient")
    private RestHighLevelClient client;

    public static final String ES_INDEX="han_index";

    //创建文档
    @Test
    public void createDocument() throws IOException {
        //创建对象
        UserInfo userInfo = new UserInfo("张三",12);
        //创建请求
        IndexRequest request = new IndexRequest(ES_INDEX);
        //规则
        request.id("1").timeout(TimeValue.timeValueSeconds(1));
        //将数据放到请求中
        request.source(JSON.toJSONString(userInfo), XContentType.JSON);
        //客户端发送请求，获取相应的结果
        IndexResponse response = client.index(request, RequestOptions.DEFAULT);
        //打印一下
        System.out.println(response.toString());
        System.out.println(response.status());
    }

    //判断是否存在
    @Test
    public void exitDocument() throws IOException {
        GetRequest request = new GetRequest(ES_INDEX, "1");
        //不获取返回的_source 的上下文
        request.fetchSourceContext(new FetchSourceContext(false));
        request.storedFields("_none");

        boolean exists = client.exists(request, RequestOptions.DEFAULT);
        System.out.println(exists);
    }

    //获取文档信息
    @Test
    public void getDocument() throws IOException {
        GetRequest request = new GetRequest(ES_INDEX, "1");
        GetResponse response = client.get(request, RequestOptions.DEFAULT);
        System.out.println("获取到的结果"+response.getSourceAsString());
    }

    //更新文档
    @Test
    public void updateDocument() throws IOException {
        //创建对象
        UserInfo userInfo = new UserInfo("李四",12);

        UpdateRequest request = new UpdateRequest(ES_INDEX, "1");
        request.timeout("1s");

        request.doc(JSON.toJSONString(userInfo),XContentType.JSON);
        UpdateResponse response = client.update(request, RequestOptions.DEFAULT);
        System.out.println(response.status());
    }

    //删除文档
    @Test
    public void deleteDocument() throws IOException{
        DeleteRequest request = new DeleteRequest(ES_INDEX, "1");
        request.timeout("1s");

        DeleteResponse response = client.delete(request, RequestOptions.DEFAULT);
        System.out.println(response.status());
    }

    //批量添加
    @Test
    public void bulkDocument() throws IOException{
        BulkRequest request = new BulkRequest();
        request.timeout("10s");

        ArrayList<UserInfo> userInfos = new ArrayList<>();
        userInfos.add(new UserInfo("李四",1));
        userInfos.add(new UserInfo("李四",2));
        userInfos.add(new UserInfo("李四",3));
        userInfos.add(new UserInfo("李四",4));
        userInfos.add(new UserInfo("李四",5));
        userInfos.add(new UserInfo("李四",6));
        userInfos.add(new UserInfo("李四",7));

        //进行批处理请求
        for (int i = 0; i <userInfos.size() ; i++) {
            request.add(
                    new IndexRequest(ES_INDEX)
                    .id(""+(i+1))
                    .source(JSON.toJSONString(userInfos.get(i)),XContentType.JSON));
        }

        BulkResponse response = client.bulk(request, RequestOptions.DEFAULT);
        System.out.println(response.hasFailures());
    }

    //查询
    @Test
    public void SearchDocument() throws IOException{
        SearchRequest request = new SearchRequest(ES_INDEX);
        //构建搜索条件
        SearchSourceBuilder builder = new SearchSourceBuilder();

        //查询条件使用QueryBuilders工具来实现
        //QueryBuilders.termQuery 精准查询
        //QueryBuilders.matchAllQuery() 匹配全部
        MatchQueryBuilder matchQuery = QueryBuilders.matchQuery("name", "李四");
        builder.query(matchQuery);
        builder.timeout(new TimeValue(60, TimeUnit.SECONDS));

        request.source(builder);

        SearchResponse response = client.search(request, RequestOptions.DEFAULT);
        System.out.println("查询出的结果"+JSON.toJSONString(response.getHits()));
    }