Java elasticSearch-api的具體操作步驟講解

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使用步驟

1.環境準備

用的是windows版,自行下載

鏈接: 下載地址

2.針對索引操作

這裡是kibana上操作的(也可以用postman操作)：

在這裡插入圖片描述 

#創建索引,指定文檔id
PUT /test1/type1/1
{
  "name":"張三",
   "age":30
  
}
#創建索引規則(類似數據庫建表)
PUT /test2
{
  "mappings": {
    "properties": {
      "name":{
        "type":"text"
      },
      "age":{
        "type": "integer"
      },
      "birthday":{
        "type": "date"
      }
    }
  }
}
#獲取索引的信息,properties類型
GET test2
#創建索引,properties不指定類型會有默認類型
#也可以用作修改,但是必須寫上全部字段,不然會丟失未寫字段
PUT /test3/_doc/1
{
  "name":"張三",
  "age":30,
  "birth":"1991-06-23"
}
GET test3
#查看es健康狀態
GET _cat/health
#查看所有索引狀態
GET _cat/indices?v
#修改
POST /test3/_doc/1/_update
{
  "doc":{
    "name":"李四"
  }
}

3.針對doc操作(增刪改)

代碼如下(示例)：

#新增索引,並添加doc
POST /chen/user/1
{
  "name":"張三",
  "age":11,
  "desc":"一頓操作猛如虎,一看工資2500",
  "tags":["技術宅","溫暖","直男"]
}
POST /chen/user/2
{
  "name":"李四",
  "age":12,
  "desc":"憨批",
  "tags":["渣男","旅遊","交友"]
}
POST /chen/user/3
{
  "name":"王五",
  "age":13,
  "desc":"瓜慫",
  "tags":["靚女","旅遊","美食"]
}
POST /chen/user/4
{
  "name":"劉六",
  "age":14,
  "desc":"鍋盔",
  "tags":["衰仔","旅遊","美食"]
}
#獲取數據
GET chen/user/1
#更新數據
POST chen/user/1/_update
{
  "doc":{
    "name":"更新"
  }
}
#刪除
DELETE chen/user/1
#條件查詢,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
#等價於上面
GET chen/user/_search
{
  "query": {
    "match": {
      "name": "李四"
    }
  }
}

4.針對doc操作(查)

查詢1(示例)：

#_source結果過濾(指定需要字段結果集)
#sort排序
#from-size分頁(類似limit )
#註意:這個查詢是不可以些多個字段的(我試過瞭)
GET chen/user/_search
{
  "query": {
    "match": {
      "name": "李四"
    }
  },
  "_source": ["name","age"],
   "sort": [
    {
      "age": {
        "order": "asc"
      }
    }
  ],
  "from":0,
  "size":1
}
#多條件精確查詢
#以下都是bool的二級屬性
#must:必須
#should,滿足任意條件
#must_not,表示不滿足
GET chen/user/_search
{
  "query": {
    "bool": {
      "must": [
        {"match": {
          "name": "李四"
        }},
        {"match": {
          "age": 11
        }}
      ]
    }
  }
}
#過濾.註意filter是bool(多條件)的二級屬性
GET chen/user/_search
{
  "query": {
    "bool": {
      "must": [
        {"match": {
          "name": "李四"
        }}
      ],
      "filter": {
        "range": {
          "age": {
            "gte": 10,
            "lte": 20
          }
        }
      }
    }
  }
}
#分詞器依然有效
#多個條件空格隔開就行,隻要滿足其中一個,就會被逮到
GET chen/user/_search
{
  "query": {
    "match": {
      "tags": "男 技術"
    }
  }
}
#精確查詢,結果隻能為1,多條直接不顯示
GET chen/user/_search
{
  "query": {
    "term": {
      "name": "李四"
    }
  }
}

查詢2(示例)：

#新建索引
PUT test4
{
  "mappings": {
    "properties": {
      "name":{
        "type": "text"
      },
      "desc":{
        "type": "keyword"
      }
    }
  }
}
#插入數據
PUT test4/_doc/1
{
  "name":"張三name",
  "desc":"張三desc"
}
PUT test4/_doc/2
{
  "name":"張三name2",
  "desc":"張三desc2"
}
#分詞器查詢(並不是查詢索引裡的數據,而是將text的內容用分詞器拆分的結果)
GET _analyze
{
  "analyzer": "keyword",
  "text": ["張三name"]
}
GET _analyze
{
  "analyzer": "standard",
  "text": "張三name"
}
GET test4/_search
{
  "query": {
    "term": {
      "name": "張"
    }
  }
}
#==keyword不會被分詞器解析==
GET test4/_search
{
  "query": {
    "term": {
      "desc": "張三desc"
    }
  }
}

查詢3(示例)：

PUT test4/_doc/3
{
  "t1":"22",
  "t2":"2020-4-6"
}
PUT test4/_doc/4
{
  "t1":"33",
  "t2":"2020-4-7"
}
#精確查詢多個值
GET test4/_search
{
  "query": {
    "bool": {
      "should": [
        {
          "term": {
            "t1": "22"
          }
        },
        {
          "term": {
            "t1": "33"
          }
        }
      ]
    }
  }
}
#highlight:高亮
#pre_tags,post_tags:自定義高亮條件,前綴後綴
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;

    //創建ES客戶端
    static {
        RestClientBuilder restClientBuilder = RestClient.builder(new HttpHost(HOST_NAME, PORT));
        client = new RestHighLevelClient(restClientBuilder);
    }

    //關閉ES客戶端
    public void close() {
        if (null != client) {
            try {
                client.close();
            } catch (IOException e) {
                e.printStackTrace();
            }
        }
    }
    //創建索引
    public void addIndex() throws IOException {
        //創建索引
        CreateIndexRequest request = new CreateIndexRequest("chen");
        CreateIndexResponse response = client.indices().create(request, RequestOptions.DEFAULT);
        //響應狀態
        System.out.println("索引創建操作: " + response.isAcknowledged());
    }
    //查詢索引
    public void selectIndex() throws IOException {
        GetIndexRequest request = new GetIndexRequest("chen");
        GetIndexResponse response = client.indices().get(request, RequestOptions.DEFAULT);
        System.out.println("索引查詢操作: " +response.getAliases());
        System.out.println("索引查詢操作: " +response.getMappings());
        System.out.println("索引查詢操作: " +response.getSettings());
    }
    //刪除索引
    public void deleteIndex() throws IOException {
        DeleteIndexRequest request = new DeleteIndexRequest("chen");
        AcknowledgedResponse response = client.indices().delete(request, RequestOptions.DEFAULT);
        System.out.println("索引刪除操作: "+response.isAcknowledged());
    }
    public static void main(String[] args) throws IOException {
        ES_Index index=new ES_Index();
        //index.addIndex();
        //index.selectIndex();
        index.deleteIndex();
        index.close();
    }
}

文檔操作：

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

    //創建ES客戶端
    static {
        RestClientBuilder restClientBuilder = RestClient.builder(new HttpHost(HOST_NAME, PORT));
        client = new RestHighLevelClient(restClientBuilder);
    }

    //關閉ES客戶端
    public void close() {
        if (null != client) {
            try {
                client.close();
            } catch (IOException e) {
                e.printStackTrace();
            }
        }
    }

    //插入數據
    public void addDoc() throws IOException {
        IndexRequest request = new IndexRequest();
        User user = new User("張三", "男", 18);
        //向es插入數據,必須將數據轉換為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("文檔創建操作: " + response.getResult());
    }

    //修改數據(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("文檔修改操作: " + response.getResult());
    }

    //獲取數據
    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("文檔獲取操作: " + user);
    }

    //刪除數據
    public void deleteDoc() throws IOException {
        DeleteRequest request = new DeleteRequest();
        request.index("user").id("1001");
        DeleteResponse response = client.delete(request, RequestOptions.DEFAULT);
        System.out.println("文檔刪除操作: " + response.getResult());
    }

    //批量插入數據
    public void addBatch() throws IOException {
        BulkRequest request = new BulkRequest();
        request.add(new IndexRequest().index("user").id("1001").source(XContentType.JSON, "name", "張三", "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", "趙六", "sex", "男", "age", 40));
        request.add(new IndexRequest().index("user").id("1005").source(XContentType.JSON, "name", "孫七", "sex", "女", "age", 50));
        BulkResponse response = client.bulk(request, RequestOptions.DEFAULT);
        System.out.println("文檔批量新增操作: " + response.getTook());
        System.out.println("文檔批量新增操作: " + !response.hasFailures());//是否失敗
    }

    //批量刪除數據
    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("文檔批量刪除操作: " + response.getTook());
        System.out.println("文檔批量刪除操作: " + !response.hasFailures());//是否失敗
    }

    //查詢(重點)
    public void searchDoc() throws IOException {
        SearchRequest request = new SearchRequest();
        request.indices("user");
        //1.查詢索引中的全部數據
        //request.source(new SearchSourceBuilder().query(QueryBuilders.matchAllQuery()));
        //2.查詢年齡為30的數據
        //request.source(new SearchSourceBuilder().query(QueryBuilders.termQuery("age", 30)));
        //3.分頁查詢,當前第0頁,每頁兩條
        //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.過濾字段(排除和包含,也可以是數組)
        //request.source(new SearchSourceBuilder().fetchSource("name", null));
        //6.組合查詢
        //BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
        //6.1 must相當於and
        //boolQueryBuilder.must(QueryBuilders.matchQuery("age", 30));
        //boolQueryBuilder.must(QueryBuilders.matchQuery("sex", "女"));
        //6.2 should相當於or
        //boolQueryBuilder.should(QueryBuilders.matchQuery("age", 30));
        //boolQueryBuilder.should(QueryBuilders.matchQuery("sex", "女"));
        //request.source(new SearchSourceBuilder().query(boolQueryBuilder));
        //7.范圍查詢
        //request.source(new SearchSourceBuilder().query(QueryBuilders.rangeQuery("age").gte(30).lte(40)));
        //8.模糊查詢Fuzziness.ONE即隻差1個字符
        //request.source(new SearchSourceBuilder().query(QueryBuilders.fuzzyQuery("name", "王五").fuzziness(Fuzziness.ONE)));
        //9.高亮顯示
        //SearchSourceBuilder builder = new SearchSourceBuilder().query(QueryBuilders.matchPhraseQuery("name", "張三"));
        //builder.highlighter(new HighlightBuilder().preTags("<font color='red'>").postTags("</font>").field("name"));
        //request.source(builder);
        //10.聚合查詢
        //SearchSourceBuilder builder = new SearchSourceBuilder();
        //MaxAggregationBuilder aggregationBuilder = AggregationBuilders.max("maxAge").field("age");
        //builder.aggregation(aggregationBuilder);
        //request.source(builder);
        //11.分組查詢
        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("--條數: " + hits.getTotalHits());
        System.out.println("--用時: " + response.getTook());
        hits.forEach((item)->{
            System.out.println("--數據: " + 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

實體類: 關鍵在於@Document和@Field註解
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;//商品唯一標識
 @Field(type = FieldType.Text)
 private String title;//商品名稱
 @Field(type = FieldType.Keyword)
 private String category;//分類名稱
 @Field(type = FieldType.Double)
 private Double price;//商品價格
 @Field(type = FieldType.Keyword,index = false)
 private String images;//圖片地址
}

dao層: 這樣就已經可以瞭,類似mybatis-plus的BaseMapper,封裝好瞭一些操作

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

yaml :不用怎麼配置,默認就去找localhost:9200

測試 :不知道為啥dao的很多方法都過時瞭,看源碼註釋讓回去用elasticsearchRestTemplate,感覺更繁瑣

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

    @Test
    void createIndex() {
        //創建索引，系統初始化會自動創建索引
        System.out.println("創建索引");
    }

    @Test
    void deleteIndex() {
        //創建索引，系統初始化會自動創建索引
        boolean flg = elasticsearchRestTemplate.deleteIndex(Product.class);
        System.out.println("刪除索引 = " + flg);
    }

    //新增數據
    @Test
    void addDoc() {
        Product product = new Product();
        product.setId(1001L);
        product.setTitle("華為手機");
        product.setCategory("手機");
        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("小米手機");
        product.setCategory("手機");
        product.setPrice(4999.0);
        product.setImages("www.xiaomi.com");
        productDao.save(product);
    }

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

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

    //刪除
    @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 + "]小米手機");
            product.setCategory("手機");
            product.setPrice(1999.0 + i);
            product.setImages("http://www.atguigu/xm.jpg");
            productList.add(product);
        }
        productDao.saveAll(productList);
    }

    //分頁查詢
    @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 查詢
     * search(termQueryBuilder) 調用搜索方法，參數查詢構建器對象
     */
    @Test
    void termQuery() {
        TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("category", "手機");
        Iterable<Product> products = productDao.search(termQueryBuilder);
        products.forEach(System.out::println);
    }

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

到此這篇關於elasticSearch-api的具體操作步驟講解的文章就介紹到這瞭,更多相關elasticSearch-api詳解內容請搜索WalkonNet以前的文章或繼續瀏覽下面的相關文章希望大傢以後多多支持WalkonNet！

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