Docker：https://blog.csdn.net/qq_40794973/category_9639934.html
ES中的filtered&filter：https://yuanyu.blog.csdn.net/article/details/112639371

http://https//hub.docker.com/_/elasticsearch?tab=tags&page=1&ordering=last_updated

https://www.elastic.co/guide/en/elasticsearch/reference/7.5/docker.html
https://hub.docker.com/_/kibana?tab=tags&page=1&ordering=last_updated
https://www.elastic.co/guide/en/kibana/current/docker.html

https://www.elastic.co/guide/cn/elasticsearch/guide/current/_who_should_read_this_book.html

https://www.elastic.co/guide/en/elasticsearch/client/java-rest/7.x/java-rest-high-search.html

1 部署elasticsearch

1、创建elasticsearch数据存储目录

rm -rf /mydata/elasticsearch
mkdir -p /mydata/elasticsearch/config /mydata/elasticsearch/data /mydata/elasticsearch/plugins/ik
echo "http.host: 0.0.0.0" >> /mydata/elasticsearch/config/elasticsearch.yml
### 保证权限（有目录映射可能会出现非root用户没用访问权限）
chmod -R 777 /mydata/elasticsearch/

2、下载IK安装分词器

### 下载
wget https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.4.2/elasticsearch-analysis-ik-7.4.2.zip
### 解压
unzip elasticsearch-analysis-ik-7.4.2.zip -d /mydata/elasticsearch/plugins/ik/
### 删除zip文件
rm -rf elasticsearch-analysis-ik-7.4.2.zip

3、启动elasticsearch

docker run \
--name es742 \
-p 9200:9200 \
-p 9300:9300 \
-e "discovery.type=single-node" \
-e ES_JAVA_OPTS="-Xms512m -Xmx512m" \
-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:7.4.2

4、查看es是否启动

[root@localhost ~]# curl http://127.0.0.1:9200/
{
  "name" : "db03fad7d132",
  "cluster_name" : "elasticsearch",
  "cluster_uuid" : "5SfOiSX-SJmxIFAuuv9Rwg",
  "version" : {
    "number" : "7.4.2",
    "build_flavor" : "default",
    "build_type" : "docker",
    "build_hash" : "2f90bbf7b93631e52bafb59b3b049cb44ec25e96",
    "build_date" : "2019-10-28T20:40:44.881551Z",
    "build_snapshot" : false,
    "lucene_version" : "8.2.0",
    "minimum_wire_compatibility_version" : "6.8.0",
    "minimum_index_compatibility_version" : "6.0.0-beta1"
  },
  "tagline" : "You Know, for Search"
}

2 部署kibana

docker run \
--name kb742 \
-p 5601:5601 \
-e ELASTICSEARCH_HOSTS=http://10.4.42.21:9200 \
-e "I18N_LOCALE=zh-CN" \
-d kibana:7.4.2
### kibana上测试分词器
POST _analyze
{
    "analyzer": "ik_smart",
    "text": "我是中国人"
}

3 访问

elasticsearch：http://10.4.42.21:9200/，kiban：http://10.4.42.21:5601/app/kibana

4 测试

1、插入数据

### 创建book索引
PUT /book/
{
  "settings": {
    "number_of_shards": 1,
    "number_of_replicas": 0
  },
  "mappings": {
    "properties": {
      "name":{
        "type": "text",
        "analyzer": "ik_max_word",
        "search_analyzer": "ik_smart"
      },
      "description":{
        "type": "text",
        "analyzer": "ik_max_word",
        "search_analyzer": "ik_smart"
      },
      "studymodel":{
        "type": "keyword"
      },
      "price":{
        "type": "double"
      },
      "timestamp": {
         "type": "date",
         "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"
      },
      "pic":{
        "type":"text",
        "index":false
      }
    }
  }
}
### 插入数据
PUT /book/_doc/1
{
    "name": "Bootstrap开发",
    "description": "Bootstrap是由Twitter推出的一个前台页面开发css框架，是一个非常流行的开发框架，此框架集成了多种页面效果。此开发框架包含了大量的CSS、JS程序代码，可以帮助开发者（尤其是不擅长css页面开发的程序人员）轻松的实现一个css，不受浏览器限制的精美界面css效果。",
    "studymodel": "201002",
    "price":38.6,
    "timestamp":"2019-08-25 19:11:35",
    "pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg",
    "tags": [ "bootstrap", "dev"]
}
PUT /book/_doc/2
{
    "name": "java编程思想",
    "description": "java语言是世界第一编程语言，在软件开发领域使用人数最多。",
    "studymodel": "201001",
    "price":68.6,
    "timestamp":"2019-08-25 19:11:35",
    "pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg",
    "tags": [ "java", "dev"]
}
PUT /book/_doc/3
{
    "name": "spring开发基础",
    "description": "spring 在java领域非常流行，java程序员都在用。",
    "studymodel": "201001",
    "price":88.6,
    "timestamp":"2019-08-24 19:11:35",
    "pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg",
    "tags": [ "spring", "java"]
}

2、curl查询

curl -XPOST http://10.4.42.21:9200/book/_search -H 'Content-Type: application/json' -d'
{
  "query": {
    "match": {
      "studymodel": "201001"
    }
  }
}'

3、springboot

<properties>
    <java.version>8</java.version>
    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    <project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
    <spring-boot.version>2.2.0.RELEASE</spring-boot.version>
    <es.version>7.3.0</es.version>
</properties>
<dependencyManagement>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-dependencies</artifactId>
            <version>${spring-boot.version}</version>
            <type>pom</type>
            <scope>import</scope>
        </dependency>
    </dependencies>
</dependencyManagement>
<dependencies>
    <!-- boot -->
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-web</artifactId>
    </dependency>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-test</artifactId>
        <scope>test</scope>
    </dependency>
    <!-- es客户端 -->
    <!-- https://mvnrepository.com/artifact/org.elasticsearch.client/elasticsearch-rest-high-level-client -->
    <dependency>
        <groupId>org.elasticsearch.client</groupId>
        <artifactId>elasticsearch-rest-high-level-client</artifactId>
        <version>${es.version}</version>
        <exclusions>
            <exclusion>
                <groupId>org.elasticsearch</groupId>
                <artifactId>elasticsearch</artifactId>
            </exclusion>
            <exclusion>
                <groupId>org.elasticsearch.client</groupId>
                <artifactId>elasticsearch-rest-client</artifactId>
            </exclusion>
        </exclusions>
    </dependency>
    <!-- https://mvnrepository.com/artifact/org.elasticsearch/elasticsearch -->
    <dependency>
        <groupId>org.elasticsearch</groupId>
        <artifactId>elasticsearch</artifactId>
        <version>${es.version}</version>
    </dependency>
    <!-- https://mvnrepository.com/artifact/org.elasticsearch.client/elasticsearch-rest-client -->
    <dependency>
        <groupId>org.elasticsearch.client</groupId>
        <artifactId>elasticsearch-rest-client</artifactId>
        <version>${es.version}</version>
    </dependency>
    <!-- https://mvnrepository.com/artifact/org.projectlombok/lombok -->
    <dependency>
        <groupId>org.projectlombok</groupId>
        <artifactId>lombok</artifactId>
        <version>1.18.16</version>
        <scope>provided</scope>
    </dependency>
</dependencies>
/**
 * https://www.jb51.net/article/197673.htm
 */
@Slf4j
public class TestSearchJsonOutput {
    private RestHighLevelClient restHighLevelClient;
    @Before
    public void init() {
        restHighLevelClient = new RestHighLevelClient(RestClient.builder(new HttpHost(ES_HOST, ES_PORT, "http")));
    }
    private static final com.fasterxml.jackson.databind.ObjectMapper objectMapper = new com.fasterxml.jackson.databind.ObjectMapper();
    private static final String ES_INDEX = "book";
    private static final String ES_HOST = "10.4.42.21";
    private static final Integer ES_PORT = 9200;
    @Test
    public void test_search() throws IOException {
        //1、构建搜索请求
        SearchRequest searchRequest = new SearchRequest(ES_INDEX);
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
        boolQueryBuilder.must(QueryBuilders.termQuery("studymodel", "201001"));
        boolQueryBuilder.should(QueryBuilders.rangeQuery("price").lte("90"));
        boolQueryBuilder.mustNot(QueryBuilders.matchQuery("description", "spring"));
        String[] includes = {"name", "description", "price"};
        searchSourceBuilder.fetchSource(includes, new String[]{});
        //第几页
        int page = 1;
        //每页几个
        int size = 4;
        //下标计算
        int from = (page - 1) * size;
        searchSourceBuilder.from(from);
        searchSourceBuilder.size(size);
        searchSourceBuilder.query(boolQueryBuilder);
        searchRequest.source(searchSourceBuilder);
        //2、执行搜索
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        logCurlString(searchSourceBuilder);
        //3、获取结果
        SearchHits hits = searchResponse.getHits();
        //数据数据
        SearchHit[] searchHits = hits.getHits();
        //for (SearchHit searchHit : searchHits) {
        //    Map<String, Object> source = searchHit.getSourceAsMap();
        //    System.out.println("res => \n" + JSON.toJSONString(source, true));
        //}
    }
    /**
     * 打印出es curl命令
     *
     * @param searchSourceBuilder
     */
    private void logCurlString(SearchSourceBuilder searchSourceBuilder) {
        String body = getPrettyFormat(searchSourceBuilder.toString());
        String pattern = "\ncurl -XPOST -H 'Content-Type: application/json' http://{}:{}/{}/_search?pretty -d'\n{}'";
        log.info(pattern, ES_HOST, ES_PORT, ES_INDEX, body);
    }
    /**
     * 格式化输出JSON字符串
     *
     * @return 格式化后的JSON字符串
     */
    private static String getPrettyFormat(String json) {
        String ret = "";
        try {
            Object obj = objectMapper.readValue(json, Object.class);
            ret = objectMapper.writerWithDefaultPrettyPrinter().writeValueAsString(obj);
        } catch (JsonProcessingException ignored) {
        }
        return ret;
    }
}