映射与统计

当我们在进行搜索的事情，我们会发现有一些奇怪的事情。比如有一些内容似乎是被打破了：在我们的索引中有12条推文，中有一个包含了2014-09-15这个日期，但是看看下面的查询结果中的总数量：

GET /_search?q=2014              # 12 results
GET /_search?q=2014-09-15        # 12 results !
GET /_search?q=date:2014-09-15   # 1  result
GET /_search?q=date:2014         # 0  results !

为什么我们使用字段_all搜索全年就会返回所有推文，而使用字段date搜索年份却没有结果呢？为什么使用两者所得到的结果是不同的？

推测大概是因为我们的数据在_all和date在索引时没有被相同处理。我们来看看Elasticsearch是如何处理我们的文档结构的。我们可以对gb的tweet使用mapping请求：

GET /gb/_mapping/tweet

我们得到：

{
   "gb": {
      "mappings": {
         "tweet": {
            "properties": {
               "date": {
                  "type": "date",
                  "format": "dateOptionalTime"
               },
               "name": {
                  "type": "string"
               },
               "tweet": {
                  "type": "string"
               },
               "user_id": {
                  "type": "long"
               }
            }
         }
      }
   }
}

Elasticsearch会根据系统自动判断字段类型并生成一个映射。返回结果告诉我们date字段被识别成了date类型。_all没有出现是因为他是默认字段，但是我们知道字段_all实际上是string类型的。

所以类型为date的字段和类型为string的字段的索引方式是不同的。

So fields of type date and fields of type string are indexed differently, and can thus be searched differently. That's not entirely surprising. You might expect that each of the core data types -- strings, numbers, booleans and dates -- might be indexed slightly differently. And this is true: there are slight differences.

But by far the biggest difference is actually between fields that represent exact values (which can include string fields) and fields that represent full text. This distinction is really important -- it's the thing that separates a search engine from all other databases.