Elasticsearch : array of innner object vs. nested object

为了克服Arrays
of Inner Objects 扁平化内部对象而丢失对象内部数据之间的关联信息的不足，Elasticsearch提供了Nested
object。Nested object把每个内部对象做为一个独立的隐藏文件存储，从而保存了对象之间的独立性。对于nested object搜索，Elasticsearch也提供专门的搜索语法 -Querying
a Nested Object。通过下面的例子，大家可以体会一下nested object和array of inner objects的区别：

(1) 索引一个包含两个内部对象的文档，默认情况下，Elasticsearch会使用array of inner object方式为他们创建mapping并进行索引。

PUT /testindex/object/1

{

"binaries": [

{

"extension": "pptx",

"description": "fancy presentation",

"size": 999

},

{

"extension": "pdf",

"description": "fancy presentation for all to read",

"size": 10

}

]

}

(2) 查看一下Elasticsearch为其创建的mapping。

{

"testindex": {

"mappings": {

"object": {

"properties": {

"binaries": {

"properties": {

"description": {

"type": "string"

},

"extension": {

"type": "string"

},

"size": {

"type": "long"

}

}

}

}

}

}

}

}

(3) 接下来我们搜索一下包括 extersion = pptx 同时 size<100 binary对象的文档。

GET /testindex/object/_search

{

"query": {

"filtered": {

"filter": {

"bool": {

"must": [

{

"term": {

"extension": "pptx"

}

},

{

"range": {

"size": {

"lte": 100

}

}

}

]

}

}

}

}

}

(4) 当前索引中只包含一个文档，我们可以清楚看到该文档并不包含extersion = pptx 同时 size<100 的binary对象。可是搜索结果仍然返回了一个结果，有些出人意料哦！这正是array of inner object确定，因为inner object的结构被扁平化存储，所以搜索是在横过了多个inner objects进行的。

{

"took": 1,

"timed_out": false,

"_shards": {

"total": 2,

"successful": 2,

"failed": 0

},

"hits": {

"total": 1,

"max_score": 1,

"hits": [

{

"_index": "testindex",

"_type": "object",

"_id": "1",

"_score": 1,

"_source": {

"binaries": [

{

"extension": "pptx",

"description": "fancy presentation",

"size": 999

},

{

"extension": "pdf",

"description": "fancy presentation for all to read",

"size": 10

}

]

}

}

]

}

}

(5)接下来我们来看看nestedobject是如何解决这个问题的，首先创建一个专门的nestedobject设计的mapping：

PUT /testindex/_mapping/nestedobject

{

"nestedobject": {

"properties": {

"binaries": {

"type": "nested",

"properties": {

"extension": {

"type": "string"

},

"description": {

"type": "string"

},

"size": {

"type": "long"

}

}

}

}

}

}

(６) 索引一个和之前的一样的文档：

PUT /testindex/nestedobject/2

{

"binaries": [

{

"extension": "pptx",

"description": "fancy presentation",

"size": 999

},

{

"extension": "pdf",

"description": "fancy presentation for all to read",

"size": 10

}

]

}

(7) 再用nested query来一把同样搜索条件的搜索吧。真神奇啊，没有任何结果返回，哈哈哈！这就是nested object.

GET /testindex/nestedobject/_search

{

"query": {

"filtered": {

"filter": {

"nested": {

"path": "binaries",

"filter": {

"bool": {

"must": [

{

"term": {

"extension": "pptx"

}

},

{

"range": {

"size": {

"lte": 100

}

}

}

]

}

}

}

}

}

}

}

鱼和熊掌可皆得吗？ 当然。如果你既需要nested object同时也要扁平的object，在mapping中加入 include_in_parent即可，如下所示：

PUT /testindex/_mapping/nestedobject

{

"nestedobject": {

"properties": {

"binaries": {

"type": "nested",

"include_in_parent": true,

"properties": {

"extension": {

"type": "string"

},

"description": {

"type": "string"

},

"size": {

"type": "long"

}

}

}

}

}

}