Intervals query 根据匹配项的顺序和接近度返回文档。Intervals 查询使用匹配规则，由一小组定义构成。 然后将这些规则应用于指定字段中的术语。

这些定义产生跨越文本正文中的术语的最小间隔序列。 这些间隔可以通过父源进一步组合和过滤。

上述描述有点费解。我们先用一个简单的例子来进行说明。

示例请求

以下 intervals 搜索返回在 my_text 字段中包含 my favorite food 的文档，并且没有任何间隙，紧接着是在 my_text 字段中包含 hot water 或者 cold porridge。

此搜索将匹配 my_text 字段值为 my favorite food is cold porridge，但是 它不匹配 my_text 的值是 it's cold my favorite food is porridge。

我们首先来写入如下的两个文档：

PUT intervals_index/_doc/1
{"my_text": "my favorite food is cold porridge"
}PUT intervals_index/_doc/2
{"my_text": "it's cold my favorite food is porridge"
}PUT intervals_index/_doc/3
{"my_text": "he says my favorite food is banana, and he likes to drink hot water"
}PUT intervals_index/_doc/4
{"my_text": "my favorite fluid food is cold porridge"
}PUT intervals_index/_doc/5
{"my_text": "my favorite food is banana"
}PUT intervals_index/_doc/6
{"my_text": "my most favorite fluid food is cold porridge"
}

我做如下的查询：

GET intervals_index/_search
{"query": {"intervals" : {"my_text" : {"all_of" : {"ordered" : true,"intervals" : [{"match" : {"query" : "my favorite food","max_gaps" : 0,"ordered" : true}},{"any_of" : {"intervals" : [{ "match" : { "query" : "hot water" } },{ "match" : { "query" : "cold porridge" } }]}}]}}}}
}

上面命令返回的结果为：

{"took": 473,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 2,"relation": "eq"},"max_score": 0.3333333,"hits": [{"_index": "intervals_index","_id": "1","_score": 0.3333333,"_source": {"my_text": "my favorite food is cold porridge"}},{"_index": "intervals_index","_id": "3","_score": 0.111111104,"_source": {"my_text": "he says my favorite food is banana, and he likes to drink hot water"}}]}
}

从返回的结果中，我们可以看出来文档 1 及 3 匹配。其原因很简单。两个文档中都含有 my favorite food，并且在它的后面还接着 cold porridge 或者 hot water 尽管它们还是离它们有一定的距离。文档 4 没有匹配是因为在 my favorite food 中间多了一个 fluid 单词。我们在查询的要求中说明 max_gaps 为 0。如果我做如下的查询：

GET intervals_index/_search
{"query": {"intervals" : {"my_text" : {"all_of" : {"ordered" : true,"intervals" : [{"match" : {"query" : "my favorite food","max_gaps" : 1,"ordered" : true}},{"any_of" : {"intervals" : [{ "match" : { "query" : "hot water" } },{ "match" : { "query" : "cold porridge" } }]}}]}}}}
}

在上面，我们设置 max_gaps 为 1，那么匹配的结果变为：

{"took": 3,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 3,"relation": "eq"},"max_score": 0.3333333,"hits": [{"_index": "intervals_index","_id": "1","_score": 0.3333333,"_source": {"my_text": "my favorite food is cold porridge"}},{"_index": "intervals_index","_id": "4","_score": 0.25,"_source": {"my_text": "my favorite fluid food is cold porridge"}},{"_index": "intervals_index","_id": "3","_score": 0.111111104,"_source": {"my_text": "he says my favorite food is banana, and he likes to drink hot water"}}]}
}

很显然这次文档 4，也即 my favorite fluid food is cold porridge 也被搜索到。而文档 6，也即 my most favorite fluid food is cold porridge 没有被搜索到。

Intervals query 解决的问题

我们在一些论坛上经常看到一个非常常见的问题：“我如何创建一个匹配的查询，同时保留搜索词的顺序？”

他们中的许多人首先尝试使用  match_phrase，但有时他们也想使用 fuzzy 逻辑，而这不适用于 match_phrase。

在很多解决方案中我们可以发现使用 Span Queries 可以解决问题，但是很多问题可以通过使用 Intervals Query 来完美解决。

Intervals Query是一种基于顺序和匹配规则的查询类型。 这些规则是你要应用的查询条件。

今天我们可以使用以下规则：

• match：match 规则匹配分析的文本。
• prefix：prefix 规则匹配以指定字符集开头的术语
• wildcard：wildcard（通配符）规则使用通配符模式匹配术语。
• fuzzy：fuzzy 规则匹配与给定术语相似的术语，在 Fuzziness 定义的编辑距离内。
• all_of：all_of 规则返回跨越其他规则组合的匹配项。
• any_of：any_of 规则返回由其任何子规则生成的 intervals。

示例

我们先准备数据。我们想创建如下的一个 movies 的索引：

PUT movies
{"settings": {"analysis": {"analyzer": {"en_analyzer": {"tokenizer": "standard","filter": ["lowercase","stop"]},"shingle_analyzer": {"type": "custom","tokenizer": "standard","filter": ["lowercase","shingle_filter"]}},"filter": {"shingle_filter": {"type": "shingle","min_shingle_size": 2,"max_shingle_size": 3}}}},"mappings": {"properties": {"title": {"type": "text","analyzer": "en_analyzer","fields": {"suggest": {"type": "text","analyzer": "shingle_analyzer"}}},"actors": {"type": "text","analyzer": "en_analyzer","fields": {"keyword": {"type": "keyword","ignore_above": 256}}},"description": {"type": "text","analyzer": "en_analyzer","fields": {"keyword": {"type": "keyword","ignore_above": 256}}},"director": {"type": "text","fields": {"keyword": {"type": "keyword","ignore_above": 256}}},"genre": {"type": "text","fields": {"keyword": {"type": "keyword","ignore_above": 256}}},"metascore": {"type": "long"},"rating": {"type": "float"},"revenue": {"type": "float"},"runtime": {"type": "long"},"votes": {"type": "long"},"year": {"type": "long"},"title_suggest": {"type": "completion","analyzer": "simple","preserve_separators": true,"preserve_position_increments": true,"max_input_length": 50}}}
}

我们接下来使用 _bulk 命令来写入一些文档到这个索引中去。我们使用这个链接中的内容。我们使用如下的方法：

POST movies/_bulk
{"index": {}}
{"title": "Guardians of the Galaxy", "genre": "Action,Adventure,Sci-Fi", "director": "James Gunn", "actors": "Chris Pratt, Vin Diesel, Bradley Cooper, Zoe Saldana", "description": "A group of intergalactic criminals are forced to work together to stop a fanatical warrior from taking control of the universe.", "year": 2014, "runtime": 121, "rating": 8.1, "votes": 757074, "revenue": 333.13, "metascore": 76}
{"index": {}}
{"title": "Prometheus", "genre": "Adventure,Mystery,Sci-Fi", "director": "Ridley Scott", "actors": "Noomi Rapace, Logan Marshall-Green, Michael Fassbender, Charlize Theron", "description": "Following clues to the origin of mankind, a team finds a structure on a distant moon, but they soon realize they are not alone.", "year": 2012, "runtime": 124, "rating": 7, "votes": 485820, "revenue": 126.46, "metascore": 65}....

在上面，为了说明的方便，我省去了其它的文档。你需要把整个 movies.txt 的文件拷贝过来，并全部写入到 Elasticsearch 中。它共有1000 个文档。

我们想要检索符号如下条件的文件：

我们想要检索包含单词 mortal hero 的准确顺序 (ordered=true) 的文档，并且我们不打算在单词之间添加间隙 (max_gaps)，因此内容必须与 mortal hero 完全匹配。

GET movies/_search
{"query": {"intervals": {"description": {"match": {"query": "hero mortal","max_gaps": 0,"ordered": true}}}}
}

此搜索的结果将为空，因为未找到符合这些条件的文档。

让我们将 ordered 更改为 false，因为我们不关心顺序。

GET movies/_search
{"query": {"intervals": {"description": {"match": {"query": "hero mortal","max_gaps": 0,"ordered": false}}}}
}

上面搜索的结果为：

现在我们可以看到文件已经找到了。 请注意，在文档中的 description 是 “Mortal hero”。因为我们想测试相同顺序的术语，所以我们搜索 “mortal hero”：

GET movies/_search
{"query": {"intervals": {"description": {"match": {"query": "mortal hero","max_gaps": 0,"ordered": true}}}}
}

这次，我们可以看到和上面命令运行一样的结果。有一个文档被匹配。

让我们在下一个示例中使用 any_of 规则。 我们想要带有 “mortal hero” 或 “mortal man” 的​​文件。

GET movies/_search
{"query": {"intervals": {"description": {"any_of": {"intervals": [{"match": {"query": "mortal hero","max_gaps": 0,"ordered": true}},{"match": {"query": "mortal man","max_gaps": 0,"ordered": true}}]}}}}
}

上面命令返回结果：

请注意，我们成功了。 返回了两个匹配的文档。

我们也可以组合规则。 在示例中，让我们搜索 “the hunger games”，结果中至少有一个是 “part 1” 或 “part 2”。 请注意，这里我们使用角色 match 和 any_of。 

GET movies/_search
{"query": {"intervals" : {"title" : {"all_of" : {"intervals" : [{"match" : {"query" : "the hunger games","ordered" : true}},{"any_of" : {"intervals" : [{ "match" : { "query" : "part 1" } },{ "match" : { "query" : "part 2" } }]}}]}}}}
}

上面命令返回结果：

如上所示结果中只有两部电影。

间隔查询是一种按照搜索词顺序搜索文档的方法。阅读官方文档并了解如何通过它解决问题。