3.ES查询常用实例演示

一灰灰blog约 1980 字大约 7 分钟

本文将作为es系列第三篇，结合常见的实例，来演示下如何通过RestHighLevelClient来实现es的各种查询支持

I. 项目搭建

1. 项目依赖

本项目借助SpringBoot 2.2.1.RELEASE + maven 3.5.3 + IDEA进行开发

开一个web服务用于测试

<dependencies>
    <dependency>
        <groupId>org.elasticsearch.client</groupId>
        <artifactId>elasticsearch-rest-high-level-client</artifactId>
    </dependency>
</dependencies>

2. 配置信息

配置文件application.yml，注意下面的配置信息，下面采用的是由我们自己来解析配置的方式

elasticsearch:
  host: localhost
  port: 9200
  user: elastic
  pwd: test123
  connTimeout: 3000
  socketTimeout: 5000
  connectionRequestTimeout: 500

II. 实例演示

0. 准备

在开始之前，先准备插入几条数据，这里会借助上一篇CURD博文中的插入接口

【搜索系列】ES文档基本操作CURD实例演示 | 一灰灰Blogopen in new window

在开始之前就准备两条数据

@Component
public class TermQueryDemo {
    private BasicCurdDemo basicCurdDemo;
    @Autowired
    private RestHighLevelClient client;
    @Autowired
    private RequestOptions requestOptions;

    private String TEST_ID = "11123-33345-66543-55231";
    private String TEST_ID_2 = "11123-33345-66543-55232";

    private String index = "term-demo";

    public TermQueryDemo(BasicCurdDemo basicCurdDemo) throws IOException {
        this.basicCurdDemo = basicCurdDemo;
        Map<String, Object> doc = newMap("name", "一灰灰", "age", 10, "skills", Arrays.asList("java", "python"), "site", "blog.hhui.top");
        basicCurdDemo.addDoc(index, doc, TEST_ID);
        doc = newMap("name", "二灰灰", "age", 16, "skills", Arrays.asList("js", "html"));
        basicCurdDemo.addDoc(index, doc, TEST_ID_2);
    }

    @PreDestroy
    public void remove() throws IOException {
        basicCurdDemo.delete(index, TEST_ID);
        basicCurdDemo.delete(index, TEST_ID_2);
    }
}

1. 全量查询

即查询所有的文档，如借助kibanan的控制台，发起的请求形如

GET index/_search
{
  "query": {
    "match_all": {}
  }
}

于此对应的java实现如下

/**
 * 全量查询
 *
 * @throws IOException
 */
private void queryAll() throws IOException {
    SearchRequest searchRequest = new SearchRequest(index);
    searchRequest.types("_doc");

    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    // 查询所有的文档
    searchSourceBuilder.query(QueryBuilders.matchAllQuery());
    searchRequest.source(searchSourceBuilder);

    SearchResponse searchResponse = client.search(searchRequest, requestOptions);
    System.out.println("mathAll: " + searchResponse.toString());
}

注意上面的实现：

初始化SearchRequest实例，用于构建请求相关数据
SearchSourceBuilder 来填充查询条件
client.search(searchRequest, requestOptions) 执行查询请求，第二个参数为请求参数，这里主要是设置请求时的权限验证信息

通常来说，实际的业务场景中，不太可能出现上面这种没有任何限制的查全量数据，即便真的有查全量数据的case，更常见的是分页查询，如下

private void queryAll() throws IOException {
    SearchRequest searchRequest = new SearchRequest(index);
    searchRequest.types("_doc");

    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    int page = 1;
    //每页记录数
    int size = 2;
    //计算出记录起始下标
    int from = (page - 1) * size;
    //起始记录下标，从0开始
    searchSourceBuilder.from(from);
    //每页显示的记录数
    searchSourceBuilder.size(size);
    // 根据age字段进行倒排
    searchSourceBuilder.sort(new FieldSortBuilder("age").order(SortOrder.DESC));
    // 查询所有的文档
    searchSourceBuilder.query(QueryBuilders.matchAllQuery());
    searchRequest.source(searchSourceBuilder);

    SearchResponse searchResponse = client.search(searchRequest, requestOptions);
    System.out.println("mathAll: " + searchResponse.toString());
}

2. 根据Field值精确查询

即es中常说的term查询，具体实现如下

/**
 * term精确查询
 *
 * @throws IOException
 */
private void term() throws IOException {
    SearchRequest searchRequest = new SearchRequest(index);
    searchRequest.types("_doc");

    // termQuery: 精确查询
    // SpanTermQuery: 词距查询
    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.query(QueryBuilders.termQuery("site", "blog.hhui.top"));
    searchRequest.source(searchSourceBuilder);
    SearchResponse response = client.search(searchRequest, requestOptions);
    System.out.println("term: " + response.toString());
}

从上面的实现也可以看出，查询的套路没啥区别，无非就是SearchSourceBuilder中的参数构造不一样；上面主要通过

QueryBuilders.termQuery("site", "blog.hhui.top") 来构建 term的查询条件，表明查询 site=blog.hhui.top 的文档

中文查询不到问题

在我们实际使用过程中，如果value为中文，在查询时，可能会遇到命名有对应的数据，但是就查不到，主要原因就在于分词，如对于中文的查询，可以考虑下面这种方式

private void term2() throws IOException {
    SearchRequest searchRequest = new SearchRequest(index);
    searchRequest.types("_doc");

    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    // 对于中文查询，需要注意分词的场景, 如果直接使用 "name : 一灰灰" 的方式进行查询，则啥也不会返回
    // elasticsearch 里默认的IK分词器是会将每一个中文都进行了分词的切割，所以你直接想查一整个词，或者一整句话是无返回结果的。
    // 在此种情况下，我们可以通过指定 keyword 的方式来处理, 设置关键词搜索（不进行分词）
    searchSourceBuilder.query(QueryBuilders.termQuery("name.keyword", "一灰灰"));

    searchRequest.source(searchSourceBuilder);
    SearchResponse response = client.search(searchRequest, requestOptions);
    System.out.println("term2: " + response.toString());
}

3. Field值in查询

另外一个常见的就是多值查询，也就是我们常说的 field in (val1, val2...)，这个对应的就是es中的terms查询

/**
 * 相当于in查询
 * {"terms": { "name": ["一灰灰", "二灰灰] }}
 *
 * @throws IOException
 */
private void multTerm() throws IOException {
    SearchRequest searchRequest = new SearchRequest(index);
    searchRequest.types("_doc");

    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.query(QueryBuilders.termsQuery("name.keyword", "一灰灰", "二灰灰"));

    searchRequest.source(searchSourceBuilder);
    SearchResponse response = client.search(searchRequest, requestOptions);
    System.out.println("term: " + response.toString());
}

4. 范围查询

对于数值类型的Field，同样是支持比较、范围查询的，对应的是es中 range

/**
 * 范围查询
 * { "range": { "age": { "gt":8, "lt": 12 } }}
 *
 * @throws IOException
 */
private void range() throws IOException {
    SearchRequest searchRequest = new SearchRequest(index);
    searchRequest.types("_doc");

    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.query(QueryBuilders.rangeQuery("age").gt(8).lt(12));
    searchRequest.source(searchSourceBuilder);
    SearchResponse response = client.search(searchRequest, requestOptions);
    System.out.println("range: " + response.toString());
}

注意上面的查询有条件

QueryBuilders.rangeQuery("age").gt(8).lt(12)
表示查询 age > 8 && age < 12
gte: 表示 >=
lte: 表示 <=

5. Field是否存在查询

es不同于mysql的在于它的field可以动态新增，当我们希望查询包含某个字段的文档时，可以考虑 exists

/**
 * 根据字段是否存在查询
 *
 * @throws IOException
 */
private void exists() throws IOException {
    SearchRequest searchRequest = new SearchRequest(index);
    searchRequest.types("_doc");

    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.query(QueryBuilders.existsQuery("site"));
    searchRequest.source(searchSourceBuilder);
    SearchResponse response = client.search(searchRequest, requestOptions);
    System.out.println("exists: " + response.toString());
}

6. 模糊查询

es作为搜索引擎，更常见的是模糊匹配，比如match查询

/**
   * 根据字段匹配查询
   *
   * @throws IOException
   */
  private void match() throws IOException {
      SearchRequest searchRequest = new SearchRequest(index);
      searchRequest.types("_doc");

      SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
      searchSourceBuilder.query(QueryBuilders.matchQuery("name", "灰"));
      searchRequest.source(searchSourceBuilder);
      SearchResponse response = client.search(searchRequest, requestOptions);
      System.out.println("matchQuery: " + response.toString());
  }

多Field中进行查询

/**
 * 多字段中查询
 *
 * @throws IOException
 */
private void multiMatch() throws IOException {
    SearchRequest searchRequest = new SearchRequest(index);
    searchRequest.types("_doc");

    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.query(QueryBuilders.multiMatchQuery("灰", "name", "site"));
    searchRequest.source(searchSourceBuilder);
    SearchResponse response = client.search(searchRequest, requestOptions);
    System.out.println("multiMatchQuery: " + response.toString());
}

在es的语法支持中，除了match，还有一个wildcard，可以使用?来代指单字符，*来代指0..n字符

/**
 * 模糊查询 ? 单字符  * 0..n字符
 *
 * @throws IOException
 */
private void wild() throws IOException {
    SearchRequest searchRequest = new SearchRequest(index);
    searchRequest.types("_doc");

    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.query(QueryBuilders.wildcardQuery("site", "*top"));
    searchRequest.source(searchSourceBuilder);
    SearchResponse response = client.search(searchRequest, requestOptions);
    System.out.println("wildcard: " + response.toString());
}

7. 正则匹配

private void regexp() throws IOException {
    SearchRequest searchRequest = new SearchRequest(index);
    searchRequest.types("_doc");

    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.query(QueryBuilders.regexpQuery("site", ".*hhui.*"));
    searchRequest.source(searchSourceBuilder);
    SearchResponse response = client.search(searchRequest, requestOptions);
    System.out.println("regexpQuery: " + response.toString());
}

8. 前缀查询

private void prefix() throws IOException {
    SearchRequest searchRequest = new SearchRequest(index);
    searchRequest.types("_doc");

    SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
    searchSourceBuilder.query(QueryBuilders.prefixQuery("site", "blog"));
    searchRequest.source(searchSourceBuilder);
    SearchResponse response = client.search(searchRequest, requestOptions);
    System.out.println("prefixQuery: " + response.toString());
}

9.小结

本文虽然介绍了一些常见的查询case，但注意并不仅仅只有这些，比如

查询指定Feild的内容
排序
分组聚合
多查询条件组合：and/or
高亮
...

更多的使用实例，敬请期待...，欢迎感兴趣的小伙伴，点赞收藏评论一波😝

III. 不能错过的源码和相关知识点

0. 项目

系列博文

源码

1. 微信公众号: 一灰灰Blog

尽信书则不如，以上内容，纯属一家之言，因个人能力有限，难免有疏漏和错误之处，如发现bug或者有更好的建议，欢迎批评指正，不吝感激

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一灰灰Blog个人博客 https://blog.hhui.topopen in new window
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3.ES查询常用实例演示

# I. 项目搭建

# 1. 项目依赖

# 2. 配置信息

# II. 实例演示

# 0. 准备

# 1. 全量查询

# 2. 根据Field值精确查询

# 3. Field值in查询

# 4. 范围查询

# 5. Field是否存在查询

# 6. 模糊查询

# 7. 正则匹配

# 8. 前缀查询

# 9.小结

# III. 不能错过的源码和相关知识点

# 0. 项目

# 1. 微信公众号: 一灰灰Blog