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Jul 1, 2016
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non-binary gender option in term aggr. example #19188

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e0859f9
non-binary gender option in term aggr. example
Jun 30, 2016
bccf95f
replace gender with music genre for term aggregation docs
Jul 1, 2016
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76 changes: 40 additions & 36 deletions docs/reference/aggregations/bucket/terms-aggregation.asciidoc
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Original file line number Diff line number Diff line change
Expand Up @@ -9,8 +9,8 @@ Example:
--------------------------------------------------
{
"aggs" : {
"genders" : {
"terms" : { "field" : "gender" }
"genres" : {
"terms" : { "field" : "genre" }
}
}
}
Expand All @@ -24,16 +24,20 @@ Response:
...
"aggregations" : {
"genders" : {
"genres" : {
"doc_count_error_upper_bound": 0, <1>
"sum_other_doc_count": 0, <2>
"buckets" : [ <3>
{
"key" : "male",
"key" : "jazz",
"doc_count" : 10
},
{
"key" : "female",
"key" : "rock",
"doc_count" : 10
},
{
"key" : "electronic",
"doc_count" : 10
},
]
Expand Down Expand Up @@ -249,9 +253,9 @@ Ordering the buckets by their `doc_count` in an ascending manner:
--------------------------------------------------
{
"aggs" : {
"genders" : {
"genres" : {
"terms" : {
"field" : "gender",
"field" : "genre",
"order" : { "_count" : "asc" }
}
}
Expand All @@ -265,9 +269,9 @@ Ordering the buckets alphabetically by their terms in an ascending manner:
--------------------------------------------------
{
"aggs" : {
"genders" : {
"genres" : {
"terms" : {
"field" : "gender",
"field" : "genre",
"order" : { "_term" : "asc" }
}
}
Expand All @@ -282,13 +286,13 @@ Ordering the buckets by single value metrics sub-aggregation (identified by the
--------------------------------------------------
{
"aggs" : {
"genders" : {
"genres" : {
"terms" : {
"field" : "gender",
"order" : { "avg_height" : "desc" }
"field" : "genre",
"order" : { "avg_play_count" : "desc" }
},
"aggs" : {
"avg_height" : { "avg" : { "field" : "height" } }
"avg_play_count" : { "avg" : { "field" : "play_count" } }
}
}
}
Expand All @@ -301,13 +305,13 @@ Ordering the buckets by multi value metrics sub-aggregation (identified by the a
--------------------------------------------------
{
"aggs" : {
"genders" : {
"genres" : {
"terms" : {
"field" : "gender",
"order" : { "height_stats.avg" : "desc" }
"field" : "genre",
"order" : { "playback_stats.avg" : "desc" }
},
"aggs" : {
"height_stats" : { "stats" : { "field" : "height" } }
"playback_stats" : { "stats" : { "field" : "play_count" } }
}
}
}
Expand Down Expand Up @@ -345,14 +349,14 @@ PATH := <AGG_NAME>[<AGG_SEPARATOR><AGG_NAME>]*[<METRIC_SEPARATOR
"aggs" : {
"countries" : {
"terms" : {
"field" : "address.country",
"order" : { "females>height_stats.avg" : "desc" }
"field" : "artist.country",
"order" : { "rock>playback_stats.avg" : "desc" }
},
"aggs" : {
"females" : {
"filter" : { "term" : { "gender" : "female" }},
"rock" : {
"filter" : { "term" : { "genre" : "rock" }},
"aggs" : {
"height_stats" : { "stats" : { "field" : "height" }}
"playback_stats" : { "stats" : { "field" : "play_count" }}
}
}
}
Expand All @@ -361,7 +365,7 @@ PATH := <AGG_NAME>[<AGG_SEPARATOR><AGG_NAME>]*[<METRIC_SEPARATOR
}
--------------------------------------------------

The above will sort the countries buckets based on the average height among the female population.
The above will sort the artist's countries buckets based on the average play count among the rock songs.

Multiple criteria can be used to order the buckets by providing an array of order criteria such as the following:

Expand All @@ -371,14 +375,14 @@ Multiple criteria can be used to order the buckets by providing an array of orde
"aggs" : {
"countries" : {
"terms" : {
"field" : "address.country",
"order" : [ { "females>height_stats.avg" : "desc" }, { "_count" : "desc" } ]
"field" : "artist.country",
"order" : [ { "rock>playback_stats.avg" : "desc" }, { "_count" : "desc" } ]
},
"aggs" : {
"females" : {
"filter" : { "term" : { "gender" : { "female" }}},
"rock" : {
"filter" : { "term" : { "genre" : { "rock" }}},
"aggs" : {
"height_stats" : { "stats" : { "field" : "height" }}
"playback_stats" : { "stats" : { "field" : "play_count" }}
}
}
}
Expand All @@ -387,7 +391,7 @@ Multiple criteria can be used to order the buckets by providing an array of orde
}
--------------------------------------------------

The above will sort the countries buckets based on the average height among the female population and then by
The above will sort the artist's countries buckets based on the average play count among the rock songs and then by
their `doc_count` in descending order.

NOTE: In the event that two buckets share the same values for all order criteria the bucket's term value is used as a
Expand Down Expand Up @@ -441,9 +445,9 @@ Generating the terms using a script:
--------------------------------------------------
{
"aggs" : {
"genders" : {
"genres" : {
"terms" : {
"script" : "doc['gender'].value"
"script" : "doc['genre'].value"
}
}
}
Expand All @@ -456,12 +460,12 @@ This will interpret the `script` parameter as an `inline` script with the defaul
--------------------------------------------------
{
"aggs" : {
"genders" : {
"genres" : {
"terms" : {
"script" : {
"file": "my_script",
"params": {
"field": "gender"
"field": "genre"
}
}
}
Expand All @@ -479,10 +483,10 @@ TIP: for indexed scripts replace the `file` parameter with an `id` parameter.
--------------------------------------------------
{
"aggs" : {
"genders" : {
"genres" : {
"terms" : {
"field" : "gender",
"script" : "'Gender: ' +_value"
"field" : "genre",
"script" : "'Genre: ' +_value"
}
}
}
Expand Down