elasticSearch-api的具体操作步骤讲解

使用步骤

1.环境准备

用的是windows版,自行下载

链接: 下载地址

2.针对索引操作

这里是kibana上操作的(也可以用postman操作)：

#创建索引,指定文档id
PUT /test1/type1/1
{
  "name":"张三",
   "age":30

}
#创建索引规则(类似数据库建表)
PUT /test2
{
  "mappings": {
    "properties": {
      "name":{
        "type":"text"
      },
      "age":{
        "type": "integer"
      },
      "birthday":{
        "type": "date"
      }
    }
  }
}
#获取索引的信息,properties类型
GET test2
#创建索引,properties不指定类型会有默认类型
#也可以用作修改,但是必须写上全部字段,不然会丢失未写字段
PUT /test3/_doc/1
{
  "name":"张三",
  "age":30,
  "birth":"1991-06-23"
}
GET test3
#查看es健康状态
GET _cat/health
#查看所有索引状态
GET _cat/indices?v
#修改
POST /test3/_doc/1/_update
{
  "doc":{
    "name":"李四"
  }
}

3.针对doc操作(增删改)

代码如下(示例)：

#新增索引,并添加doc
POST /chen/user/1
{
  "name":"张三",
  "age":11,
  "desc":"一顿操作猛如虎,一看工资2500",
  "tags":["技术宅","温暖","直男"]
}
POST /chen/user/2
{
  "name":"李四",
  "age":12,
  "desc":"憨批",
  "tags":["渣男","旅游","交友"]
}
POST /chen/user/3
{
  "name":"王五",
  "age":13,
  "desc":"瓜怂",
  "tags":["靓女","旅游","美食"]
}
POST /chen/user/4
{
  "name":"刘六",
  "age":14,
  "desc":"锅盔",
  "tags":["衰仔","旅游","美食"]
}
#获取数据
GET chen/user/1
#更新数据
POST chen/user/1/_update
{
  "doc":{
    "name":"更新"
  }
}
#删除
DELETE chen/user/1
#条件查询,匹配度越高,_score(分值)越高
GET chen/user/_search?q=name:李
GET chen/user/_search?q=name:李四
#等价于上面
GET chen/user/_search
{
  "query": {
    "match": {
      "name": "李四"
    }
  }
}

4.针对doc操作(查)

查询1(示例)：

#_source结果过滤(指定需要字段结果集)
#sort排序
#from-size分页(类似limit )
#注意:这个查询是不可以些多个字段的(我试过了)
GET chen/user/_search
{
  "query": {
    "match": {
      "name": "李四"
    }
  },
  "_source": ["name","age"],
   "sort": [
    {
      "age": {
        "order": "asc"
      }
    }
  ],
  "from":0,
  "size":1
}
#多条件精确查询
#以下都是bool的二级属性
#must:必须
#should,满足任意条件
#must_not,表示不满足
GET chen/user/_search
{
  "query": {
    "bool": {
      "must": [
        {"match": {
          "name": "李四"
        }},
        {"match": {
          "age": 11
        }}
      ]
    }
  }
}
#过滤.注意filter是bool(多条件)的二级属性
GET chen/user/_search
{
  "query": {
    "bool": {
      "must": [
        {"match": {
          "name": "李四"
        }}
      ],
      "filter": {
        "range": {
          "age": {
            "gte": 10,
            "lte": 20
          }
        }
      }
    }
  }
}
#分词器依然有效
#多个条件空格隔开就行,只要满足其中一个,就会被逮到
GET chen/user/_search
{
  "query": {
    "match": {
      "tags": "男 技术"
    }
  }
}
#精确查询,结果只能为1,多条直接不显示
GET chen/user/_search
{
  "query": {
    "term": {
      "name": "李四"
    }
  }
}

查询2(示例)：

#新建索引
PUT test4
{
  "mappings": {
    "properties": {
      "name":{
        "type": "text"
      },
      "desc":{
        "type": "keyword"
      }
    }
  }
}
#插入数据
PUT test4/_doc/1
{
  "name":"张三name",
  "desc":"张三desc"
}
PUT test4/_doc/2
{
  "name":"张三name2",
  "desc":"张三desc2"
}
#分词器查询(并不是查询索引里的数据,而是将text的内容用分词器拆分的结果)
GET _analyze
{
  "analyzer": "keyword",
  "text": ["张三name"]
}
GET _analyze
{
  "analyzer": "standard",
  "text": "张三name"
}
GET test4/_search
{
  "query": {
    "term": {
      "name": "张"
    }
  }
}
#==keyword不会被分词器解析==
GET test4/_search
{
  "query": {
    "term": {
      "desc": "张三desc"
    }
  }
}

查询3(示例)：

PUT test4/_doc/3
{
  "t1":"22",
  "t2":"2020-4-6"
}
PUT test4/_doc/4
{
  "t1":"33",
  "t2":"2020-4-7"
}
#精确查询多个值
GET test4/_search
{
  "query": {
    "bool": {
      "should": [
        {
          "term": {
            "t1": "22"
          }
        },
        {
          "term": {
            "t1": "33"
          }
        }
      ]
    }
  }
}
#highlight:高亮
#pre_tags,post_tags:自定义高亮条件,前缀后缀
GET chen/user/_search
{
  "query": {
    "match": {
      "name": "李四"
    }
  },
  "highlight": {
    "pre_tags": "<p class='key' style='color:red'",
    "post_tags": "</p>",
    "fields": {
      "name":{}
    }
  }
}

5.java-api

索引操作：

public class ES_Index {
    private static final String HOST_NAME = "localhost";
    private static final Integer PORT = 9200;
    private static RestHighLevelClient client;

    //创建ES客户端
    static {
        RestClientBuilder restClientBuilder = RestClient.builder(new HttpHost(HOST_NAME, PORT));
        client = new RestHighLevelClient(restClientBuilder);
    }

    //关闭ES客户端
    public void close() {
        if (null != client) {
            try {
                client.close();
            } catch (IOException e) {
                e.printStackTrace();
            }
        }
    }
    //创建索引
    public void addIndex() throws IOException {
        //创建索引
        CreateIndexRequest request = new CreateIndexRequest("chen");
        CreateIndexResponse response = client.indices().create(request, RequestOptions.DEFAULT);
        //响应状态
        System.out.println("索引创建操作: " + response.isAcknowledged());
    }
    //查询索引
    public void selectIndex() throws IOException {
        GetIndexRequest request = new GetIndexRequest("chen");
        GetIndexResponse response = client.indices().get(request, RequestOptions.DEFAULT);
        System.out.println("索引查询操作: " +response.getAliases());
        System.out.println("索引查询操作: " +response.getMappings());
        System.out.println("索引查询操作: " +response.getSettings());
    }
    //删除索引
    public void deleteIndex() throws IOException {
        DeleteIndexRequest request = new DeleteIndexRequest("chen");
        AcknowledgedResponse response = client.indices().delete(request, RequestOptions.DEFAULT);
        System.out.println("索引删除操作: "+response.isAcknowledged());
    }
    public static void main(String[] args) throws IOException {
        ES_Index index=new ES_Index();
        //index.addIndex();
        //index.selectIndex();
        index.deleteIndex();
        index.close();
    }
}

文档操作：

public class ES_Doc {
    private static final String HOST_NAME = "localhost";
    private static final Integer PORT = 9200;
    private static RestHighLevelClient client;

    //创建ES客户端
    static {
        RestClientBuilder restClientBuilder = RestClient.builder(new HttpHost(HOST_NAME, PORT));
        client = new RestHighLevelClient(restClientBuilder);
    }

    //关闭ES客户端
    public void close() {
        if (null != client) {
            try {
                client.close();
            } catch (IOException e) {
                e.printStackTrace();
            }
        }
    }

    //插入数据
    public void addDoc() throws IOException {
        IndexRequest request = new IndexRequest();
        User user = new User("张三", "男", 18);
        //向es插入数据,必须将数据转换为json格式
        String userJson = new ObjectMapper().writeValueAsString(user);
        request.index("user").id("1001").source(userJson, XContentType.JSON);
        IndexResponse response = client.index(request, RequestOptions.DEFAULT);
        System.out.println("文档创建操作: " + response.getResult());
    }

    //修改数据(局部修改)
    public void updateDoc() throws IOException {
        UpdateRequest request = new UpdateRequest();
        request.index("user").id("1001").doc(XContentType.JSON, "sex", "女");
        UpdateResponse response = client.update(request, RequestOptions.DEFAULT);
        System.out.println("文档修改操作: " + response.getResult());
    }

    //获取数据
    public void getDoc() throws IOException {
        GetRequest request = new GetRequest();
        request.index("user").id("1001");
        GetResponse response = client.get(request, RequestOptions.DEFAULT);
        User user = new ObjectMapper().readValue(response.getSourceAsString(), User.class);
        System.out.println("文档获取操作: " + user);
    }

    //删除数据
    public void deleteDoc() throws IOException {
        DeleteRequest request = new DeleteRequest();
        request.index("user").id("1001");
        DeleteResponse response = client.delete(request, RequestOptions.DEFAULT);
        System.out.println("文档删除操作: " + response.getResult());
    }

    //批量插入数据
    public void addBatch() throws IOException {
        BulkRequest request = new BulkRequest();
        request.add(new IndexRequest().index("user").id("1001").source(XContentType.JSON, "name", "张三", "sex", "男", "age", 10));
        request.add(new IndexRequest().index("user").id("1002").source(XContentType.JSON, "name", "李四", "sex", "男", "age", 20));
        request.add(new IndexRequest().index("user").id("1003").source(XContentType.JSON, "name", "王五", "sex", "女", "age", 30));
        request.add(new IndexRequest().index("user").id("1004").source(XContentType.JSON, "name", "赵六", "sex", "男", "age", 40));
        request.add(new IndexRequest().index("user").id("1005").source(XContentType.JSON, "name", "孙七", "sex", "女", "age", 50));
        BulkResponse response = client.bulk(request, RequestOptions.DEFAULT);
        System.out.println("文档批量新增操作: " + response.getTook());
        System.out.println("文档批量新增操作: " + !response.hasFailures());//是否失败
    }

    //批量删除数据
    public void deleteBatch() throws IOException {
        BulkRequest request = new BulkRequest();
        request.add(new DeleteRequest().index("user").id("1001"));
        request.add(new DeleteRequest().index("user").id("1002"));
        request.add(new DeleteRequest().index("user").id("1003"));
        request.add(new DeleteRequest().index("user").id("1004"));
        request.add(new DeleteRequest().index("user").id("1005"));
        BulkResponse response = client.bulk(request, RequestOptions.DEFAULT);
        System.out.println("文档批量删除操作: " + response.getTook());
        System.out.println("文档批量删除操作: " + !response.hasFailures());//是否失败
    }

    //查询(重点)
    public void searchDoc() throws IOException {
        SearchRequest request = new SearchRequest();
        request.indices("user");
        //1.查询索引中的全部数据
        //request.source(new SearchSourceBuilder().query(QueryBuilders.matchAllQuery()));
        //2.查询年龄为30的数据
        //request.source(new SearchSourceBuilder().query(QueryBuilders.termQuery("age", 30)));
        //3.分页查询,当前第0页,每页两条
        //request.source(new SearchSourceBuilder().query(QueryBuilders.matchAllQuery()).from(0).size(2));
        //4.排序,倒序
        //request.source(new SearchSourceBuilder().query(QueryBuilders.matchAllQuery()).sort("age", SortOrder.DESC));
        //5.过滤字段(排除和包含,也可以是数组)
        //request.source(new SearchSourceBuilder().fetchSource("name", null));
        //6.组合查询
        //BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
        //6.1 must相当于and
        //boolQueryBuilder.must(QueryBuilders.matchQuery("age", 30));
        //boolQueryBuilder.must(QueryBuilders.matchQuery("sex", "女"));
        //6.2 should相当于or
        //boolQueryBuilder.should(QueryBuilders.matchQuery("age", 30));
        //boolQueryBuilder.should(QueryBuilders.matchQuery("sex", "女"));
        //request.source(new SearchSourceBuilder().query(boolQueryBuilder));
        //7.范围查询
        //request.source(new SearchSourceBuilder().query(QueryBuilders.rangeQuery("age").gte(30).lte(40)));
        //8.模糊查询Fuzziness.ONE即只差1个字符
        //request.source(new SearchSourceBuilder().query(QueryBuilders.fuzzyQuery("name", "王五").fuzziness(Fuzziness.ONE)));
        //9.高亮显示
        //SearchSourceBuilder builder = new SearchSourceBuilder().query(QueryBuilders.matchPhraseQuery("name", "张三"));
        //builder.highlighter(new HighlightBuilder().preTags("<font color='red'>").postTags("</font>").field("name"));
        //request.source(builder);
        //10.聚合查询
        //SearchSourceBuilder builder = new SearchSourceBuilder();
        //MaxAggregationBuilder aggregationBuilder = AggregationBuilders.max("maxAge").field("age");
        //builder.aggregation(aggregationBuilder);
        //request.source(builder);
        //11.分组查询
        SearchSourceBuilder builder = new SearchSourceBuilder();
        TermsAggregationBuilder aggregationBuilder = AggregationBuilders.terms("ageGroup").field("age");
        builder.aggregation(aggregationBuilder);
        request.source(builder);
        SearchResponse response = client.search(request, RequestOptions.DEFAULT);
        SearchHits hits = response.getHits();
        System.out.println("--条数: " + hits.getTotalHits());
        System.out.println("--用时: " + response.getTook());
        hits.forEach((item)->{
            System.out.println("--数据: " + item.getSourceAsString());
        });
    }

    public static void main(String[] args) throws IOException {
        ES_Doc doc = new ES_Doc();
        //doc.addDoc();
        //doc.updateDoc();
        //doc.getDoc();
        //doc.deleteDoc();
        //doc.addBatch();
        //doc.deleteBatch();
        doc.searchDoc();
        doc.close();
    }
}

6.spring-data-elasticsearch

实体类: 关键在于@Document和@Field注解
shards 代表分片
replicas 代表副本

@Data
@NoArgsConstructor
@AllArgsConstructor
@Document(indexName = "product", shards = 3, replicas = 1)
public class Product {
 @Id
 private Long id;//商品唯一标识
 @Field(type = FieldType.Text)
 private String title;//商品名称
 @Field(type = FieldType.Keyword)
 private String category;//分类名称
 @Field(type = FieldType.Double)
 private Double price;//商品价格
 @Field(type = FieldType.Keyword,index = false)
 private String images;//图片地址
}

dao层: 这样就已经可以了,类似mybatis-plus的BaseMapper,封装好了一些操作

@Repository
public interface ProductDao extends ElasticsearchRepository<Product,Long> {
}

yaml :不用怎么配置,默认就去找localhost:9200

测试 :不知道为啥dao的很多方法都过时了,看源码注释让回去用elasticsearchRestTemplate,感觉更繁琐

@SpringBootTest
class ElasticsearchApplicationTests {
    @Autowired
    ElasticsearchRestTemplate elasticsearchRestTemplate;
    @Autowired
    ProductDao productDao;

    @Test
    void createIndex() {
        //创建索引，系统初始化会自动创建索引
        System.out.println("创建索引");
    }

    @Test
    void deleteIndex() {
        //创建索引，系统初始化会自动创建索引
        boolean flg = elasticsearchRestTemplate.deleteIndex(Product.class);
        System.out.println("删除索引 = " + flg);
    }

    //新增数据
    @Test
    void addDoc() {
        Product product = new Product();
        product.setId(1001L);
        product.setTitle("华为手机");
        product.setCategory("手机");
        product.setPrice(2999.0);
        product.setImages("www.huawei.com");
        productDao.save(product);
    }

    //修改
    @Test
    void updateDoc() {
        Product product = new Product();
        product.setId(1001L);
        product.setTitle("小米手机");
        product.setCategory("手机");
        product.setPrice(4999.0);
        product.setImages("www.xiaomi.com");
        productDao.save(product);
    }

    //根据 id 查询
    @Test
    void findById() {
        Product product = productDao.findById(1001L).get();
        System.out.println(product);
    }

    //查询所有
    @Test
    void findAll() {
        Iterable<Product> products = productDao.findAll();
        for (Product product : products) {
            System.out.println(product);
        }
    }

    //删除
    @Test
    public void delete() {
        productDao.deleteById(1001L);
    }

    //批量新增
    @Test
    public void saveAll() {
        List<Product> productList = new ArrayList<>();
        for (int i = 0; i < 10; i++) {
            Product product = new Product();
            product.setId((long) i);
            product.setTitle("[" + i + "]小米手机");
            product.setCategory("手机");
            product.setPrice(1999.0 + i);
            product.setImages("http://www.atguigu/xm.jpg");
            productList.add(product);
        }
        productDao.saveAll(productList);
    }

    //分页查询
    @Test
    void findByPageable() {
        Sort orders = Sort.by(Sort.Direction.DESC, "id");
        Pageable pageable = PageRequest.of(0, 5, orders);
        Page<Product> products = productDao.findAll(pageable);
        products.forEach(System.out::println);
    }

    /**
     * term 查询
     * search(termQueryBuilder) 调用搜索方法，参数查询构建器对象
     */
    @Test
    void termQuery() {
        TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("category", "手机");
        Iterable<Product> products = productDao.search(termQueryBuilder);
        products.forEach(System.out::println);
    }

    /**
     * term 查询加分页
     */
    @Test
    void termQueryByPage() {
        PageRequest pageRequest = PageRequest.of(0, 5);
        TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("category", "手机");
        Iterable<Product> products = productDao.search(termQueryBuilder, pageRequest);
        products.forEach(System.out::println);
    }
}

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