Elasticsearch快速入门

前置知识

在开始本教程之前，建议您具备以下基础知识：

• Java开发环境
• Maven项目管理
• Spring Boot基础
• Elasticsearch基本概念（参考上一篇文章）

环境准备

1. 安装Elasticsearch

1. 下载Elasticsearch：官方下载页面
2. 解压下载的文件
3. 运行Elasticsearch：

# Windows
bin\elasticsearch.bat

# Linux/Mac
bin/elasticsearch

2. 验证安装

访问 http://localhost:9200 ，如果看到类似以下JSON响应，说明安装成功：

{
  "name" : "node-1",
  "cluster_name" : "elasticsearch",
  "version" : {
    "number" : "7.17.0"
  },
  "tagline" : "You Know, for Search"
}

Spring Boot集成

1. 添加依赖

pom.xml

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-elasticsearch</artifactId>
</dependency>

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-web</artifactId>
</dependency>

<dependency>
    <groupId>org.projectlombok</groupId>
    <artifactId>lombok</artifactId>
    <optional>true</optional>
</dependency>

2. 配置连接

# application.yml
spring:
  elasticsearch:
    uris: http://localhost:9200

3. 创建实体类

package com.example.es.model;

import lombok.Data;
import org.springframework.data.annotation.Id;
import org.springframework.data.elasticsearch.annotations.Document;
import org.springframework.data.elasticsearch.annotations.Field;
import org.springframework.data.elasticsearch.annotations.FieldType;

@Data
@Document(indexName = "products")
public class Product {
    @Id
    private String id;
    
    @Field(type = FieldType.Text, analyzer = "ik_max_word")
    private String name;
    
    @Field(type = FieldType.Keyword)
    private String category;
    
    @Field(type = FieldType.Double)
    private Double price;
    
    @Field(type = FieldType.Text, analyzer = "ik_max_word")
    private String description;
}

4. 创建Repository

package com.example.es.repository;

import com.example.es.model.Product;
import org.springframework.data.elasticsearch.repository.ElasticsearchRepository;

public interface ProductRepository extends ElasticsearchRepository<Product, String> {
    // 继承ElasticsearchRepository后自动拥有基本的CRUD方法
}

5. 创建Service

package com.example.es.service;

import com.example.es.model.Product;
import com.example.es.repository.ProductRepository;
import lombok.RequiredArgsConstructor;
import org.springframework.data.elasticsearch.core.ElasticsearchOperations;
import org.springframework.data.elasticsearch.core.SearchHits;
import org.springframework.data.elasticsearch.core.query.Criteria;
import org.springframework.data.elasticsearch.core.query.CriteriaQuery;
import org.springframework.stereotype.Service;

@Service
@RequiredArgsConstructor
public class ProductService {
    private final ProductRepository productRepository;
    private final ElasticsearchOperations elasticsearchOperations;
    
    // 保存产品
    public Product save(Product product) {
        return productRepository.save(product);
    }
    
    // 根据ID查询
    public Product findById(String id) {
        return productRepository.findById(id).orElse(null);
    }
    
    // 搜索产品
    public SearchHits<Product> search(String keyword) {
        Criteria criteria = new Criteria("name").matches(keyword)
            .or(new Criteria("description").matches(keyword));
        
        return elasticsearchOperations.search(
            new CriteriaQuery(criteria), Product.class
        );
    }
}

使用示例

1. 创建Controller

package com.example.es.controller;

import com.example.es.model.Product;
import com.example.es.service.ProductService;
import lombok.RequiredArgsConstructor;
import org.springframework.data.elasticsearch.core.SearchHits;
import org.springframework.web.bind.annotation.*;

@RestController
@RequestMapping("/products")
@RequiredArgsConstructor
public class ProductController {
    private final ProductService productService;
    
    @PostMapping
    public Product create(@RequestBody Product product) {
        return productService.save(product);
    }
    
    @GetMapping("/{id}")
    public Product findById(@PathVariable String id) {
        return productService.findById(id);
    }
    
    @GetMapping("/search")
    public SearchHits<Product> search(@RequestParam String keyword) {
        return productService.search(keyword);
    }
}

2. 测试API

# 创建产品
curl -X POST http://localhost:8080/products \
  -H 'Content-Type: application/json' \
  -d '{
    "name": "iPhone 13",
    "category": "手机",
    "price": 5999.00,
    "description": "Apple最新款手机，搭载A15处理器"
  }'

# 搜索产品
curl http://localhost:8080/products/search?keyword=iPhone

高级查询示例

1. 复合查询

// 在ProductService中添加
public SearchHits<Product> advancedSearch(
    String keyword, String category, Double minPrice, Double maxPrice) {
    
    BoolQueryBuilder boolQuery = QueryBuilders.boolQuery();
    
    // 关键词匹配
    if (keyword != null) {
        boolQuery.must(QueryBuilders.multiMatchQuery(keyword, "name", "description"));
    }
    
    // 分类过滤
    if (category != null) {
        boolQuery.filter(QueryBuilders.termQuery("category", category));
    }
    
    // 价格区间
    if (minPrice != null || maxPrice != null) {
        RangeQueryBuilder rangeQuery = QueryBuilders.rangeQuery("price");
        if (minPrice != null) rangeQuery.gte(minPrice);
        if (maxPrice != null) rangeQuery.lte(maxPrice);
        boolQuery.filter(rangeQuery);
    }
    
    NativeSearchQuery searchQuery = new NativeSearchQueryBuilder()
        .withQuery(boolQuery)
        .build();
    
    return elasticsearchOperations.search(searchQuery, Product.class);
}

2. 聚合查询

// 在ProductService中添加
public Map<String, Double> getPriceStats() {
    TermsAggregationBuilder categoryAgg = AggregationBuilders
        .terms("by_category")
        .field("category")
        .subAggregation(AggregationBuilders
            .stats("price_stats")
            .field("price"));
    
    NativeSearchQuery searchQuery = new NativeSearchQueryBuilder()
        .addAggregation(categoryAgg)
        .build();
    
    SearchHits<Product> searchHits = elasticsearchOperations
        .search(searchQuery, Product.class);
    
    // 处理聚合结果
    Map<String, Double> stats = new HashMap<>();
    // ... 解析聚合结果的代码
    return stats;
}

总结

本文通过实例演示了：

1. ✅ 环境搭建
2. ✅ Spring Boot集成
3. ✅ 基本CRUD操作
4. ✅ 搜索功能实现
5. ✅ 高级查询示例

下一步学习

• 了解更多高级特性
• 学习性能优化
• 探索聚合分析

希望这篇文章对您有所帮助！如果您有任何问题，欢迎在评论区讨论。