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查询语法

Elasticsearch 提供了强大的 Query DSL（Domain Specific Language）查询语言。本章介绍各种查询方式。

基本查询结构​

GET /articles/_search
{
  "query": {
    // 查询条件
  },
  "from": 0,           # 分页起始位置
  "size": 10,          # 返回文档数量
  "sort": [            # 排序
    { "created_at": "desc" }
  ],
  "_source": [         # 返回字段
    "title",
    "author"
  ]
}

全文查询​

match 查询​

最常用的全文查询，会对查询词进行分词：

GET /articles/_search
{
  "query": {
    "match": {
      "title": "Elasticsearch 教程"
    }
  }
}

# 带参数
GET /articles/_search
{
  "query": {
    "match": {
      "title": {
        "query": "Elasticsearch 教程",
        "operator": "and",     # 默认 or，改为 and 要求所有词都匹配
        "minimum_should_match": "75%"  # 至少匹配 75% 的词
      }
    }
  }
}

解释：

  • operator：or 表示任意一个词匹配即可，and 表示所有词都必须匹配
  • minimum_should_match：控制至少匹配多少个词

match_phrase 查询​

精确匹配短语，词的顺序也必须一致：

GET /articles/_search
{
  "query": {
    "match_phrase": {
      "title": "Elasticsearch 入门教程"
    }
  }
}

# 允许词之间的间隔（slop）
GET /articles/_search
{
  "query": {
    "match_phrase": {
      "title": {
        "query": "Elasticsearch 教程",
        "slop": 2    # 允许中间间隔 2 个词
      }
    }
  }
}

multi_match 查询​

在多个字段中搜索：

GET /articles/_search
{
  "query": {
    "multi_match": {
      "query": "Python 教程",
      "fields": ["title", "content", "author"],
      "type": "best_fields"   # 默认，使用最高分的字段
    }
  }
}

# 不同的匹配类型
GET /articles/_search
{
  "query": {
    "multi_match": {
      "query": "Python 教程",
      "fields": ["title^3", "content"],  # title 权重 x3
      "type": "most_fields"   # 将所有匹配字段的分数相加
    }
  }
}

type 参数说明：

类型说明
best_fields默认，使用最高分字段的分数
most_fields所有匹配字段的分数相加
cross_fields跨字段匹配，适合人名等
phrase在每个字段上执行 match_phrase
phrase_prefix短语前缀匹配

query_string 查询​

支持 Lucene 查询语法的高级查询：

GET /articles/_search
{
  "query": {
    "query_string": {
      "query": "title:(Elasticsearch OR Python) AND author:张三",
      "default_field": "content"
    }
  }
}

精确查询​

term 查询​

精确匹配，不分词：

GET /articles/_search
{
  "query": {
    "term": {
      "status": "published"
    }
  }
}

# 对于数值字段
GET /articles/_search
{
  "query": {
    "term": {
      "views": 1000
    }
  }
}

注意：term 查询不会对查询词分词，适合 keyword、数值、日期等精确字段。

terms 查询​

匹配多个值（类似 SQL 的 IN）：

GET /articles/_search
{
  "query": {
    "terms": {
      "category": ["Python", "Java", "Go"]
    }
  }
}

# 从另一个查询获取 terms
GET /articles/_search
{
  "query": {
    "terms": {
      "author": {
        "index": "authors",
        "id": "1",
        "path": "favorite_authors"
      }
    }
  }
}

range 查询​

范围查询：

GET /articles/_search
{
  "query": {
    "range": {
      "views": {
        "gte": 1000,      # 大于等于
        "lte": 10000,     # 小于等于
        "boost": 2.0      # 权重
      }
    }
  }
}

# 日期范围
GET /articles/_search
{
  "query": {
    "range": {
      "created_at": {
        "gte": "2024-01-01",
        "lt": "2024-02-01",
        "time_zone": "+08:00"
      }
    }
  }
}

# 相对日期
GET /articles/_search
{
  "query": {
    "range": {
      "created_at": {
        "gte": "now-7d/d",   # 7 天前，向下取整到天
        "lt": "now/d"        # 今天
      }
    }
  }
}

exists 查询​

检查字段是否存在：

GET /articles/_search
{
  "query": {
    "exists": {
      "field": "author"
    }
  }
}

# 查找字段为空的文档
GET /articles/_search
{
  "query": {
    "bool": {
      "must_not": {
        "exists": {
          "field": "author"
        }
      }
    }
  }
}

ids 查询​

根据 ID 查询：

GET /articles/_search
{
  "query": {
    "ids": {
      "values": ["1", "2", "3"]
    }
  }
}

复合查询​

bool 查询​

组合多个查询条件：

GET /articles/_search
{
  "query": {
    "bool": {
      "must": [                        # 必须匹配，参与评分
        { "match": { "title": "Python" } }
      ],
      "must_not": [                    # 必须不匹配
        { "term": { "status": "draft" } }
      ],
      "should": [                      # 可选匹配，增加评分
        { "term": { "category": "技术" } },
        { "term": { "tags": "教程" } }
      ],
      "filter": [                      # 必须匹配，不参与评分
        { "range": { "views": { "gte": 100 } } }
      ],
      "minimum_should_match": 1        # should 至少匹配几个
    }
  }
}

must vs filter：

类型是否参与评分是否缓存使用场景
must是否需要相关性评分
filter否是精确过滤，性能更好

boosting 查询​

降低某些文档的评分：

GET /articles/_search
{
  "query": {
    "boosting": {
      "positive": {
        "match": { "title": "Python" }
      },
      "negative": {
        "term": { "category": "广告" }
      },
      "negative_boost": 0.5    # 匹配 negative 的文档评分乘以 0.5
    }
  }
}

constant_score 查询​

忽略相关性评分：

GET /articles/_search
{
  "query": {
    "constant_score": {
      "filter": {
        "term": { "status": "published" }
      },
      "boost": 1.2
    }
  }
}

嵌套查询​

nested 查询​

查询嵌套对象：

# 假设有以下文档结构
{
  "title": "文章标题",
  "comments": [
    { "user": "张三", "content": "好文章" },
    { "user": "李四", "content": "学习了" }
  ]
}

# 查询嵌套对象
GET /articles/_search
{
  "query": {
    "nested": {
      "path": "comments",
      "query": {
        "bool": {
          "must": [
            { "match": { "comments.user": "张三" } },
            { "match": { "comments.content": "好文章" } }
          ]
        }
      },
      "inner_hits": {}    # 返回匹配的嵌套文档
    }
  }
}

has_child / has_parent 查询​

查询父子关系的文档：

# 查询有特定评论的文章
GET /articles/_search
{
  "query": {
    "has_child": {
      "type": "comment",
      "query": {
        "match": { "content": "好文章" }
      }
    }
  }
}

高亮显示​

GET /articles/_search
{
  "query": {
    "match": { "content": "Elasticsearch" }
  },
  "highlight": {
    "fields": {
      "content": {
        "pre_tags": ["<em>"],
        "post_tags": ["</em>"],
        "fragment_size": 150,       # 片段大小
        "number_of_fragments": 3    # 返回片段数量
      }
    }
  }
}

排序​

基本排序​

GET /articles/_search
{
  "query": { "match_all": {} },
  "sort": [
    { "views": "desc" },
    { "created_at": "desc" }
  ]
}

按相关性评分排序​

GET /articles/_search
{
  "query": {
    "match": { "title": "Python" }
  },
  "sort": [
    "_score",
    { "views": "desc" }
  ]
}

按脚本排序​

GET /articles/_search
{
  "query": { "match_all": {} },
  "sort": {
    "_script": {
      "type": "number",
      "script": {
        "source": "doc['likes'].value + doc['views'].value"
      },
      "order": "desc"
    }
  }
}

分页​

基本分页​

GET /articles/_search
{
  "query": { "match_all": {} },
  "from": 0,    # 起始位置（从 0 开始）
  "size": 10    # 每页数量
}

深度分页问题​

from + size 不能超过 10000（默认），深度分页会消耗大量内存。

search_after 分页​

适合深度分页和实时数据：

# 第一页
GET /articles/_search
{
  "query": { "match_all": {} },
  "size": 10,
  "sort": [
    { "created_at": "desc" },
    { "_id": "desc" }
  ]
}

# 使用上一页最后一条数据的排序值获取下一页
GET /articles/_search
{
  "query": { "match_all": {} },
  "size": 10,
  "sort": [
    { "created_at": "desc" },
    { "_id": "desc" }
  ],
  "search_after": ["2024-01-15T10:30:00", "abc123"]
}

scroll 滚动查询​

适合大批量数据导出：

# 创建滚动上下文，保持 1 分钟
GET /articles/_search?scroll=1m
{
  "query": { "match_all": {} },
  "size": 1000
}

# 使用 scroll_id 继续获取
GET /_search/scroll
{
  "scroll": "1m",
  "scroll_id": "FGluY2x1ZGVfY29udGV4dF91dWlkDXF1ZXJ5QW5kRmV0Y2gBFl..."
}

# 清除滚动上下文
DELETE /_search/scroll
{
  "scroll_id": "FGluY2x1ZGVfY29udGV4dF91dWlkDXF1ZXJ5QW5kRmV0Y2gBFl..."
}

建议器​

term suggester（词项建议）​

用于拼写纠错：

POST /articles/_search
{
  "suggest": {
    "my-suggestion": {
      "text": "pyton tutoril",
      "term": {
        "field": "title"
      }
    }
  }
}

completion suggester（自动补全）​

# 创建索引时配置
PUT /articles
{
  "mappings": {
    "properties": {
      "title": {
        "type": "text"
      },
      "title_suggest": {
        "type": "completion"
      }
    }
  }
}

# 查询建议
POST /articles/_search
{
  "suggest": {
    "title-suggest": {
      "prefix": "pyth",
      "completion": {
        "field": "title_suggest"
      }
    }
  }
}

实战示例​

综合搜索​

GET /articles/_search
{
  "query": {
    "bool": {
      "must": [
        {
          "multi_match": {
            "query": "Python 异步编程",
            "fields": ["title^2", "content"],
            "type": "best_fields"
          }
        }
      ],
      "filter": [
        { "term": { "status": "published" } },
        { "range": { "views": { "gte": 100 } } }
      ],
      "should": [
        { "term": { "category": { "value": "Python", "boost": 2 } } },
        { "term": { "tags": "教程" } }
      ]
    }
  },
  "sort": [
    "_score",
    { "created_at": "desc" }
  ],
  "from": 0,
  "size": 20,
  "highlight": {
    "fields": {
      "title": {},
      "content": {
        "fragment_size": 150
      }
    }
  },
  "_source": ["title", "author", "summary", "created_at", "views"]
}

小结​

本章我们学习了：

  1. 全文查询（match、match_phrase、multi_match）
  2. 精确查询（term、terms、range）
  3. 复合查询（bool、boosting）
  4. 嵌套查询
  5. 高亮显示
  6. 排序和分页
  7. 建议器

练习​

  1. 实现一个商品搜索，支持关键词搜索和分类过滤
  2. 实现文章搜索并高亮显示关键词
  3. 使用 search_after 实现深度分页
  4. 实现搜索词拼写纠错功能

参考资源​