1.5.3 Executing Searches

我们已经了解了一些基础的搜索参数，现在我们来更深入地学习下 Query DSL。 首先我们来看一下查询请求返回的 document 键值对。默认情况下，完整的 JSON 文档都会作为 source 来返回（hits 中的 _source 字段）。如果你不希望整个文档被返回，我们也可以通过特殊的命令来要求 Elasticsearch 返回部分源文档即可。

下面这个示例就演示了怎么告诉 Elasticsearch 只需要返回源文档的account_number和balance信息：

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match_all": {} },
  "_source": ["account_number", "balance"]
}'

注意一下上面这个命令的运行结果，_source字段依然还是会被返回，但是它里面的内容被精简了，现在_source中只包含account_number和balance。

如果你有一定的 SQL 基础，那么上述这个特性从概念上来讲，其实就跟 SQL SELECT FROM 类似。

看完了查询请求返回的 document 键值对，我们现在再来看下 query 部分。我们已经知道match_all是用来匹配所有的文档的。那现在我们再来介绍一种新的查询方式叫做 match query 即按条件查询，或者也可以理解成基于字段的查询（即一个查询条件是针对某个或某些字段的）。

这个示例演示的是查出 account number 是 20 的数据：

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match": { "account_number": 20 } }
}'

这个例子查询的是所有地址中含有“mill”的账户：

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match": { "address": "mill" } }
}'

这个例子查询的是所有地址中含有“mill”或者“lane”的账户：

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match": { "address": "mill lane" } }
}'

这个示例是一种新的，叫做 match_phrase 的查询方式，它会查询中所有地址信息中包含“mill lane”短语的账户信息：

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match_phrase": { "address": "mill lane" } }
}'

现在我们介绍下 bool(ean) query 。bool 查询允许我们用布尔逻辑将相近的查询组合成更复杂的查询。

下面这个示例在 bool 查询中整合了2个 match 查询，查出了所有 address 中既含有“mill”又含有“lane”的数据：

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "must": [
        { "match": { "address": "mill" } },
        { "match": { "address": "lane" } }
      ]
    }
  }
}'

在上一个示例中，bool must子句中的各个查询条件只有都被满足的时候，整个 must 查询子句才会被认为是 true。

和上面那个例子不同的是，下面这个例子查出了 address 中含有“mill”或者“lane”的数据：

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "should": [
        { "match": { "address": "mill" } },
        { "match": { "address": "lane" } }
      ]
    }
  }
}'

在上面这个示例中，bool should子句中指明了 2 个匹配条件，只要满足一条，就可以认为满足整个 bool should。

下面这个例子用两个match查询组合在一起，查询出了 address 中既没有“mill”也没有“lane”的数据：

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "must_not": [
        { "match": { "address": "mill" } },
        { "match": { "address": "lane" } }
      ]
    }
  }
}'

在上面这个示例中，bool must_not子句指定了一系列的限制条件，只有当这些条件都不被满足的时候，整个 bool 查询结果才会被认为是满足的。

我们可以任意地把must,should和must_not查询混合在一个bool查询中。甚至，我们可以在bool查询中再嵌入另一个bool查询来构建复杂的多层级的布尔逻辑。

下面这个示例查询出了所有不住在一个叫做 ID （美国爱达荷州 Idaho）的 40 岁中年人：

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "must": [
        { "match": { "age": "40" } }
      ],
      "must_not": [
        { "match": { "state": "ID" } }
      ]
    }
  }
}'

Now that we have seen a few of the basic search parameters, let’s dig in some more into the Query DSL. Let’s first take a look at the returned document fields. By default, the full JSON document is returned as part of all searches. This is referred to as the source (_source field in the search hits). If we don’t want the entire source document returned, we have the ability to request only a few fields from within source to be returned.

This example shows how to return two fields, account_number and balance (inside of _source), from the search:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match_all": {} },
  "_source": ["account_number", "balance"]
}'

Note that the above example simply reduces the _source field. It will still only return one field named _source but within it, only the fields account_number and balance are included.

If you come from a SQL background, the above is somewhat similar in concept to the SQL SELECT FROM field list.

Now let’s move on to the query part. Previously, we’ve seen how the match_all query is used to match all documents. Let’s now introduce a new query called the match query, which can be thought of as a basic fielded search query (i.e. a search done against a specific field or set of fields).

This example returns the account numbered 20:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match": { "account_number": 20 } }
}'

This example returns all accounts containing the term "mill" in the address:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match": { "address": "mill" } }
}'

This example returns all accounts containing the term "mill" or "lane" in the address:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match": { "address": "mill lane" } }
}'

This example is a variant of match (match_phrase) that returns all accounts containing the phrase "mill lane" in the address:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": { "match_phrase": { "address": "mill lane" } }
}'

Let’s now introduce the bool(ean) query. The bool query allows us to compose smaller queries into bigger queries using boolean logic.

This example composes two match queries and returns all accounts containing "mill" and "lane" in the address:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "must": [
        { "match": { "address": "mill" } },
        { "match": { "address": "lane" } }
      ]
    }
  }
}'

In the above example, the bool must clause specifies all the queries that must be true for a document to be considered a match.

In contrast, this example composes two match queries and returns all accounts containing "mill" or "lane" in the address:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "should": [
        { "match": { "address": "mill" } },
        { "match": { "address": "lane" } }
      ]
    }
  }
}'

In the above example, the bool should clause specifies a list of queries either of which must be true for a document to be considered a match.

This example composes two match queries and returns all accounts that contain neither "mill" nor "lane" in the address:

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "must_not": [
        { "match": { "address": "mill" } },
        { "match": { "address": "lane" } }
      ]
    }
  }
}'

In the above example, the bool must_not clause specifies a list of queries none of which must be true for a document to be considered a match.

We can combine must, should, and must_not clauses simultaneously inside a bool query. Furthermore, we can compose bool queries inside any of these bool clauses to mimic any complex multi-level boolean logic.

This example returns all accounts of anybody who is 40 years old but don’t live in ID(aho):

curl -XPOST 'localhost:9200/bank/_search?pretty' -d '
{
  "query": {
    "bool": {
      "must": [
        { "match": { "age": "40" } }
      ],
      "must_not": [
        { "match": { "state": "ID" } }
      ]
    }
  }
}'