Clinton Gormley
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[[mapping-nested-type]]
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=== Nested Type
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Nested objects/documents allow to map certain sections in the document
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indexed as nested allowing to query them as if they are separate docs
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joining with the parent owning doc.
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One of the problems when indexing inner objects that occur several times
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in a doc is that "cross object" search match will occur, for example:
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The `nested` type works like the <<mapping-object-type,`object` type>> except
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that an array of `objects` is flattened, while an array of `nested` objects
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allows each object to be queried independently. To explain, consider this
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document:
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[source,js]
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--------------------------------------------------
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{
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"obj1" : [
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"group" : "fans",
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"user" : [
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{
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"name" : "blue",
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"count" : 4
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"first" : "John",
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"last" : "Smith"
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},
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{
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"name" : "green",
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"count" : 6
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}
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"first" : "Alice",
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"last" : "White"
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},
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]
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}
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--------------------------------------------------
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Searching for name set to blue and count higher than 5 will match the
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doc, because in the first element the name matches blue, and in the
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second element, count matches "higher than 5".
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If the `user` field is of type `object`, this document would be indexed
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internally something like this:
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Nested mapping allows mapping certain inner objects (usually multi
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instance ones), for example:
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[source,js]
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--------------------------------------------------
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{
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"group" : "fans",
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"user.first" : [ "alice", "john" ],
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"user.last" : [ "smith", "white" ]
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}
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--------------------------------------------------
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The `first` and `last` fields are flattened, and the association between
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`alice` and `white` is lost. This document would incorrectly match a query
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for `alice AND smith`.
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If the `user` field is of type `nested`, each object is indexed as a separate
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document, something like this:
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[source,js]
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--------------------------------------------------
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{ <1>
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"user.first" : "alice",
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"user.last" : "white"
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}
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{ <1>
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"user.first" : "john",
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"user.last" : "smith"
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}
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{ <2>
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"group" : "fans"
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}
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--------------------------------------------------
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<1> Hidden nested documents.
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<2> Visible ``parent'' document.
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By keeping each nested object separate, the association between the
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`user.first` and `user.last` fields is maintained. The query for `alice AND
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smith` would *not* match this document.
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Searching on nested docs can be done using either the
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<<query-dsl-nested-query,nested query>> or
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<<query-dsl-nested-filter,nested filter>>.
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==== Mapping
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The mapping for `nested` fields is the same as `object` fields, except that it
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uses type `nested`:
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[source,js]
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--------------------------------------------------
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{
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"type1" : {
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"properties" : {
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"obj1" : {
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"users" : {
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"type" : "nested",
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"properties": {
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"name" : {"type": "string", "index": "not_analyzed"},
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"count" : {"type": "integer"}
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"first" : {"type": "string" },
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"last" : {"type": "string" }
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}
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}
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}
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@ -48,26 +89,60 @@ instance ones), for example:
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}
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--------------------------------------------------
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The above will cause all `obj1` to be indexed as a nested doc. The
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mapping is similar in nature to setting `type` to `object`, except that
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it's `nested`. Nested object fields can be defined explicitly as in the
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example above or added dynamically in the same way as for the root object.
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NOTE: changing an `object` type to `nested` type requires reindexing.
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Note: changing an object type to nested type requires reindexing.
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You may want to index inner objects both as `nested` fields *and* as flattened
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`object` fields, eg for highlighting. This can be achieved by setting
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`include_in_parent` to `true`:
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The `nested` object fields can also be automatically added to the
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immediate parent by setting `include_in_parent` to true, and also
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included in the root object by setting `include_in_root` to true.
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[source,js]
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--------------------------------------------------
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{
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"type1" : {
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"properties" : {
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"users" : {
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"type" : "nested",
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"include_in_parent": true,
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"properties": {
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"first" : {"type": "string" },
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"last" : {"type": "string" }
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}
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}
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}
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}
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}
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--------------------------------------------------
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Nested docs will also automatically use the root doc `_all` field.
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The result of indexing our example document would be something like this:
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Searching on nested docs can be done using either the
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<<query-dsl-nested-query,nested query>> or
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<<query-dsl-nested-filter,nested filter>>.
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[source,js]
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--------------------------------------------------
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{ <1>
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"user.first" : "alice",
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"user.last" : "white"
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}
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{ <1>
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"user.first" : "john",
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"user.last" : "smith"
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}
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{ <2>
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"group" : "fans",
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"user.first" : [ "alice", "john" ],
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"user.last" : [ "smith", "white" ]
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}
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--------------------------------------------------
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<1> Hidden nested documents.
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<2> Visible ``parent'' document.
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[float]
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==== Internal Implementation
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Nested fields may contain other nested fields. The `include_in_parent` object
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refers to the direct parent of the field, while the `include_in_root`
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parameter refers only to the topmost ``root'' object or document.
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Nested docs will automatically use the root doc `_all` field only.
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.Internal Implementation
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*********************************************
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Internally, nested objects are indexed as additional documents, but,
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since they can be guaranteed to be indexed within the same "block", it
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allows for extremely fast joining with parent docs.
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@ -84,3 +159,4 @@ the `nested` query scope.
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The `_source` field is always associated with the parent document and
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because of that field values via the source can be fetched for nested object.
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*********************************************
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