manual/chinese/Searching/Faceted_search.md
分面搜索对于现代搜索应用来说，与自动补全、拼写纠正和搜索关键词高亮同样重要，尤其是在电子商务产品中。
当处理大量数据和各种相互关联的属性时，例如尺寸、颜色、制造商或其他因素，分面搜索就派上用场了。在查询海量数据时，搜索结果常常包含许多不符合用户预期的条目。分面搜索使最终用户能够明确定义他们希望搜索结果满足的条件。
在 Manticore Search 中，有一项优化功能，它会保留原始查询的结果集，并在每个分面计算中重复使用。由于聚合操作应用于已计算好的文档子集，因此速度很快，总执行时间通常仅比初始查询稍长一些。分面可以添加到任何查询中，分面可以是任何属性或表达式。分面结果包括分面值和分面计数。可以通过在查询末尾声明分面，使用 SQL SELECT 语句访问分面。
分面值可以来自属性、JSON 属性内的 JSON 属性或表达式。分面值也可以使用别名，但别名在所有结果集（主查询结果集和其他分面结果集）中必须是唯一的。分面值源自聚合的属性/表达式，但也可以来自另一个属性/表达式。
FACET {expr_list} [BY {expr_list} ] [DISTINCT {field_name}] [ORDER BY {expr | FACET()} {ASC | DESC}] [LIMIT [offset,] count]
多个分面声明必须用空格分隔。
分面可以在 aggs 节点中定义：
"aggs" :
{
"group name" :
{
"terms" :
{
"field":"attribute name",
"size": 1000
}
"sort": [ {"attribute name": { "order":"asc" }} ]
}
}
其中：
group name 是分配给聚合的别名field 值必须包含要进行分面的属性或表达式的名称size 指定结果中包含的最大桶数。未指定时，继承主查询的限制。更多详细信息可以在分面结果大小部分找到。sort 指定一个属性数组和/或附加属性，使用与主查询中的"sort"参数相同的语法。结果集将包含一个 aggregations 节点，其中包含返回的分面，key 是聚合值，doc_count 是聚合计数。
"aggregations": {
"group name": {
"buckets": [
{
"key": 10,
"doc_count": 1019
},
{
"key": 9,
"doc_count": 954
},
{
"key": 8,
"doc_count": 1021
},
{
"key": 7,
"doc_count": 1011
},
{
"key": 6,
"doc_count": 997
}
]
}
}
SELECT *, price AS aprice FROM facetdemo LIMIT 10 FACET price LIMIT 10 FACET brand_id LIMIT 5;
+------+-------+----------+---------------------+------------+-------------+---------------------------------------+------------+--------+
| id | price | brand_id | title | brand_name | property | j | categories | aprice |
+------+-------+----------+---------------------+------------+-------------+---------------------------------------+------------+--------+
| 1 | 306 | 1 | Product Ten Three | Brand One | Six_Ten | {"prop1":66,"prop2":91,"prop3":"One"} | 10,11 | 306 |
| 2 | 400 | 10 | Product Three One | Brand Ten | Four_Three | {"prop1":69,"prop2":19,"prop3":"One"} | 13,14 | 400 |
...
| 9 | 560 | 6 | Product Two Five | Brand Six | Eight_Two | {"prop1":90,"prop2":84,"prop3":"One"} | 13,14 | 560 |
| 10 | 229 | 9 | Product Three Eight | Brand Nine | Seven_Three | {"prop1":84,"prop2":39,"prop3":"One"} | 12,13 | 229 |
+------+-------+----------+---------------------+------------+-------------+---------------------------------------+------------+--------+
10 rows in set (0.00 sec)
+-------+----------+
| price | count(*) |
+-------+----------+
| 306 | 7 |
| 400 | 13 |
...
| 229 | 9 |
| 595 | 10 |
+-------+----------+
10 rows in set (0.00 sec)
+----------+----------+
| brand_id | count(*) |
+----------+----------+
| 1 | 1013 |
| 10 | 998 |
| 5 | 1007 |
| 8 | 1033 |
| 7 | 965 |
+----------+----------+
5 rows in set (0.00 sec)
POST /search -d '
{
"table" : "facetdemo",
"query" : {"match_all" : {} },
"limit": 5,
"aggs" :
{
"group_property" :
{
"terms" :
{
"field":"price"
}
},
"group_brand_id" :
{
"terms" :
{
"field":"brand_id"
}
}
}
}
'
{
"took": 3,
"timed_out": false,
"hits": {
"total": 10000,
"hits": [
{
"_id": 1,
"_score": 1,
"_source": {
"price": 197,
"brand_id": 10,
"brand_name": "Brand Ten",
"categories": [
10
]
}
},
...
{
"_id": 5,
"_score": 1,
"_source": {
"price": 805,
"brand_id": 7,
"brand_name": "Brand Seven",
"categories": [
11,
12,
13
]
}
}
]
},
"aggregations": {
"group_property": {
"buckets": [
{
"key": 1000,
"doc_count": 11
},
{
"key": 999,
"doc_count": 12
},
...
{
"key": 991,
"doc_count": 7
}
]
},
"group_brand_id": {
"buckets": [
{
"key": 10,
"doc_count": 1019
},
{
"key": 9,
"doc_count": 954
},
{
"key": 8,
"doc_count": 1021
},
{
"key": 7,
"doc_count": 1011
},
{
"key": 6,
"doc_count": 997
}
]
}
}
}
$index->setName('facetdemo');
$search = $index->search('');
$search->limit(5);
$search->facet('price','price');
$search->facet('brand_id','group_brand_id');
$results = $search->get();
Array
(
[price] => Array
(
[buckets] => Array
(
[0] => Array
(
[key] => 1000
[doc_count] => 11
)
[1] => Array
(
[key] => 999
[doc_count] => 12
)
[2] => Array
(
[key] => 998
[doc_count] => 7
)
[3] => Array
(
[key] => 997
[doc_count] => 14
)
[4] => Array
(
[key] => 996
[doc_count] => 8
)
)
)
[group_brand_id] => Array
(
[buckets] => Array
(
[0] => Array
(
[key] => 10
[doc_count] => 1019
)
[1] => Array
(
[key] => 9
[doc_count] => 954
)
[2] => Array
(
[key] => 8
[doc_count] => 1021
)
[3] => Array
(
[key] => 7
[doc_count] => 1011
)
[4] => Array
(
[key] => 6
[doc_count] => 997
)
)
)
)
res =searchApi.search({"table":"facetdemo","query":{"match_all":{}},"limit":5,"aggs":{"group_property":{"terms":{"field":"price",}},"group_brand_id":{"terms":{"field":"brand_id"}}}})
{'aggregations': {u'group_brand_id': {u'buckets': [{u'doc_count': 1019,
u'key': 10},
{u'doc_count': 954,
u'key': 9},
{u'doc_count': 1021,
u'key': 8},
{u'doc_count': 1011,
u'key': 7},
{u'doc_count': 997,
u'key': 6}]},
u'group_property': {u'buckets': [{u'doc_count': 11,
u'key': 1000},
{u'doc_count': 12,
u'key': 999},
{u'doc_count': 7,
u'key': 998},
{u'doc_count': 14,
u'key': 997},
{u'doc_count': 8,
u'key': 996}]}},
'hits': {'hits': [{u'_id': u'1',
u'_score': 1,
u'_source': {u'brand_id': 10,
u'brand_name': u'Brand Ten',
u'categories': [10],
u'price': 197,
u'property': u'Six',
u'title': u'Product Eight One'}},
{u'_id': u'2',
u'_score': 1,
u'_source': {u'brand_id': 6,
u'brand_name': u'Brand Six',
u'categories': [12, 13, 14],
u'price': 671,
u'property': u'Four',
u'title': u'Product Nine Seven'}},
{u'_id': u'3',
u'_score': 1,
u'_source': {u'brand_id': 3,
u'brand_name': u'Brand Three',
u'categories': [13, 14, 15],
u'price': 92,
u'property': u'Six',
u'title': u'Product Five Four'}},
{u'_id': u'4',
u'_score': 1,
u'_source': {u'brand_id': 10,
u'brand_name': u'Brand Ten',
u'categories': [11],
u'price': 713,
u'property': u'Five',
u'title': u'Product Eight Nine'}},
{u'_id': u'5',
u'_score': 1,
u'_source': {u'brand_id': 7,
u'brand_name': u'Brand Seven',
u'categories': [11, 12, 13],
u'price': 805,
u'property': u'Two',
u'title': u'Product Ten Three'}}],
'max_score': None,
'total': 10000},
'profile': None,
'timed_out': False,
'took': 4}
res = await searchApi.search({"table":"facetdemo","query":{"match_all":{}},"limit":5,"aggs":{"group_property":{"terms":{"field":"price",}},"group_brand_id":{"terms":{"field":"brand_id"}}}})
{'aggregations': {u'group_brand_id': {u'buckets': [{u'doc_count': 1019,
u'key': 10},
{u'doc_count': 954,
u'key': 9},
{u'doc_count': 1021,
u'key': 8},
{u'doc_count': 1011,
u'key': 7},
{u'doc_count': 997,
u'key': 6}]},
u'group_property': {u'buckets': [{u'doc_count': 11,
u'key': 1000},
{u'doc_count': 12,
u'key': 999},
{u'doc_count': 7,
u'key': 998},
{u'doc_count': 14,
u'key': 997},
{u'doc_count': 8,
u'key': 996}]}},
'hits': {'hits': [{u'_id': u'1',
u'_score': 1,
u'_source': {u'brand_id': 10,
u'brand_name': u'Brand Ten',
u'categories': [10],
u'price': 197,
u'property': u'Six',
u'title': u'Product Eight One'}},
{u'_id': u'2',
u'_score': 1,
u'_source': {u'brand_id': 6,
u'brand_name': u'Brand Six',
u'categories': [12, 13, 14],
u'price': 671,
u'property': u'Four',
u'title': u'Product Nine Seven'}},
{u'_id': u'3',
u'_score': 1,
u'_source': {u'brand_id': 3,
u'brand_name': u'Brand Three',
u'categories': [13, 14, 15],
u'price': 92,
u'property': u'Six',
u'title': u'Product Five Four'}},
{u'_id': u'4',
u'_score': 1,
u'_source': {u'brand_id': 10,
u'brand_name': u'Brand Ten',
u'categories': [11],
u'price': 713,
u'property': u'Five',
u'title': u'Product Eight Nine'}},
{u'_id': u'5',
u'_score': 1,
u'_source': {u'brand_id': 7,
u'brand_name': u'Brand Seven',
u'categories': [11, 12, 13],
u'price': 805,
u'property': u'Two',
u'title': u'Product Ten Three'}}],
'max_score': None,
'total': 10000},
'profile': None,
'timed_out': False,
'took': 4}
res = await searchApi.search({"table":"facetdemo","query":{"match_all":{}},"limit":5,"aggs":{"group_property":{"terms":{"field":"price",}},"group_brand_id":{"terms":{"field":"brand_id"}}}});
{"took":0,"timed_out":false,"hits":{"total":10000,"hits":[{"_id": 1,"_score":1,"_source":{"price":197,"brand_id":10,"brand_name":"Brand Ten","categories":[10],"title":"Product Eight One","property":"Six"}},{"_id": 2,"_score":1,"_source":{"price":671,"brand_id":6,"brand_name":"Brand Six","categories":[12,13,14],"title":"Product Nine Seven","property":"Four"}},{"_id": 3,"_score":1,"_source":{"price":92,"brand_id":3,"brand_name":"Brand Three","categories":[13,14,15],"title":"Product Five Four","property":"Six"}},{"_id": 4,"_score":1,"_source":{"price":713,"brand_id":10,"brand_name":"Brand Ten","categories":[11],"title":"Product Eight Nine","property":"Five"}},{"_id": 5,"_score":1,"_source":{"price":805,"brand_id":7,"brand_name":"Brand Seven","categories":[11,12,13],"title":"Product Ten Three","property":"Two"}}]}}
aggs = new HashMap<String,Object>(){{
put("group_property", new HashMap<String,Object>(){{
put("terms", new HashMap<String,Object>(){{
put("field","price");
}});
}});
put("group_brand_id", new HashMap<String,Object>(){{
put("terms", new HashMap<String,Object>(){{
put("field","brand_id");
}});
}});
}};
searchRequest = new SearchRequest();
searchRequest.setIndex("facetdemo");
searchRequest.setLimit(5);
query = new HashMap<String,Object>();
query.put("match_all",null);
searchRequest.setQuery(query);
searchRequest.setAggs(aggs);
searchResponse = searchApi.search(searchRequest);
class SearchResponse {
took: 0
timedOut: false
aggregations: {group_property={buckets=[{key=1000, doc_count=11}, {key=999, doc_count=12}, {key=998, doc_count=7}, {key=997, doc_count=14}, {key=996, doc_count=8}]}, group_brand_id={buckets=[{key=10, doc_count=1019}, {key=9, doc_count=954}, {key=8, doc_count=1021}, {key=7, doc_count=1011}, {key=6, doc_count=997}]}}
hits: class SearchResponseHits {
maxScore: null
total: 10000
hits: [{_id=1, _score=1, _source={price=197, brand_id=10, brand_name=Brand Ten, categories=[10], title=Product Eight One, property=Six}}, {_id=2, _score=1, _source={price=671, brand_id=6, brand_name=Brand Six, categories=[12, 13, 14], title=Product Nine Seven, property=Four}}, {_id=3, _score=1, _source={price=92, brand_id=3, brand_name=Brand Three, categories=[13, 14, 15], title=Product Five Four, property=Six}}, {_id=4, _score=1, _source={price=713, brand_id=10, brand_name=Brand Ten, categories=[11], title=Product Eight Nine, property=Five}}, {_id=5, _score=1, _source={price=805, brand_id=7, brand_name=Brand Seven, categories=[11, 12, 13], title=Product Ten Three, property=Two}}]
}
profile: null
}
var agg1 = new Aggregation("group_property", "price");
var agg2 = new Aggregation("group_brand_id", "brand_id");
object query = new { match_all=null };
var searchRequest = new SearchRequest("facetdemo", query);
searchRequest.Limit = 5;
searchRequest.Aggs = new List<Aggregation> {agg1, agg2};
var searchResponse = searchApi.Search(searchRequest);
class SearchResponse {
took: 0
timedOut: false
aggregations: {group_property={buckets=[{key=1000, doc_count=11}, {key=999, doc_count=12}, {key=998, doc_count=7}, {key=997, doc_count=14}, {key=996, doc_count=8}]}, group_brand_id={buckets=[{key=10, doc_count=1019}, {key=9, doc_count=954}, {key=8, doc_count=1021}, {key=7, doc_count=1011}, {key=6, doc_count=997}]}}
hits: class SearchResponseHits {
maxScore: null
total: 10000
hits: [{_id=1, _score=1, _source={price=197, brand_id=10, brand_name=Brand Ten, categories=[10], title=Product Eight One, property=Six}}, {_id=2, _score=1, _source={price=671, brand_id=6, brand_name=Brand Six, categories=[12, 13, 14], title=Product Nine Seven, property=Four}}, {_id=3, _score=1, _source={price=92, brand_id=3, brand_name=Brand Three, categories=[13, 14, 15], title=Product Five Four, property=Six}}, {_id=4, _score=1, _source={price=713, brand_id=10, brand_name=Brand Ten, categories=[11], title=Product Eight Nine, property=Five}}, {_id=5, _score=1, _source={price=805, brand_id=7, brand_name=Brand Seven, categories=[11, 12, 13], title=Product Ten Three, property=Two}}]
}
profile: null
}
let query = SearchQuery::new();
let aggTerms1 = AggTerms::new("price");
let agg1 = Aggregation {
terms: Some(Box::new(aggTerms1)),
..Default::default(),
};
let aggTerms2 = AggTerms::new("brand_id");
let agg2 = Aggregation {
terms: Some(Box::new(aggTerms2)),
..Default::default(),
};
let mut aggs = HashMap::new();
aggs.insert("group_property".to_string(), agg1);
aggs.insert("group_brand_id".to_string(), agg2);
let search_req = SearchRequest {
table: "facetdemo".to_string(),
query: Some(Box::new(query)),
aggs: serde_json::json!(aggs),
limit: serde_json::json!(5),
..Default::default(),
};
let search_res = search_api.search(search_req).await;
class SearchResponse {
took: 0
timedOut: false
aggregations: {group_property={buckets=[{key=1000, doc_count=11}, {key=999, doc_count=12}, {key=998, doc_count=7}, {key=997, doc_count=14}, {key=996, doc_count=8}]}, group_brand_id={buckets=[{key=10, doc_count=1019}, {key=9, doc_count=954}, {key=8, doc_count=1021}, {key=7, doc_count=1011}, {key=6, doc_count=997}]}}
hits: class SearchResponseHits {
maxScore: null
total: 10000
hits: [{_id=1, _score=1, _source={price=197, brand_id=10, brand_name=Brand Ten, categories=[10], title=Product Eight One, property=Six}}, {_id=2, _score=1, _source={price=671, brand_id=6, brand_name=Brand Six, categories=[12, 13, 14], title=Product Nine Seven, property=Four}}, {_id=3, _score=1, _source={price=92, brand_id=3, brand_name=Brand Three, categories=[13, 14, 15], title=Product Five Four, property=Six}}, {_id=4, _score=1, _source={price=713, brand_id=10, brand_name=Brand Ten, categories=[11], title=Product Eight Nine, property=Five}}, {_id=5, _score=1, _source={price=805, brand_id=7, brand_name=Brand Seven, categories=[11, 12, 13], title=Product Ten Three, property=Two}}]
}
profile: null
}
res = await searchApi.search({
index: 'test',
query: { match_all:{} },
aggs: {
name_group: {
terms: { field : 'name' }
},
cat_group: {
terms: { field: 'cat' }
}
}
});
{
"took": 0,
"timed_out": false,
"hits": {
"total": 5,
"hits": [
{
"_id": 1,
"_score": 1,
"_source": {
"content": "Text 1",
"name": "Doc 1",
"cat": 1
}
},
...
{
"_id": 5,
"_score": 1,
"_source": {
"content": "Text 5",
"name": "Doc 5",
"cat": 4
}
}
]
},
"aggregations": {
"name_group": {
"buckets": [
{
"key": "Doc 1",
"doc_count": 1
},
...
{
"key": "Doc 5",
"doc_count": 1
}
]
},
"cat_group": {
"buckets": [
{
"key": 1,
"doc_count": 2
},
...
{
"key": 4,
"doc_count": 1
}
]
}
}
}
query := map[string]interface{} {}
searchRequest.SetQuery(query)
aggByName := manticoreclient.NewAggregation()
aggTerms := manticoreclient.NewAggregationTerms()
aggTerms.SetField("name")
aggByName.SetTerms(aggTerms)
aggByCat := manticoreclient.NewAggregation()
aggTerms.SetField("cat")
aggByCat.SetTerms(aggTerms)
aggs := map[string]Aggregation{} { "name_group": aggByName, "cat_group": aggByCat }
searchRequest.SetAggs(aggs)
res, _, _ := apiClient.SearchAPI.Search(context.Background()).SearchRequest(*searchRequest).Execute()
{
"took": 0,
"timed_out": false,
"hits": {
"total": 5,
"hits": [
{
"_id": 1,
"_score": 1,
"_source": {
"content": "Text 1",
"name": "Doc 1",
"cat": 1
}
},
...
{
"_id": 5,
"_score": 1,
"_source": {
"content": "Text 5",
"name": "Doc 5",
"cat": 4
}
}
]
},
"aggregations": {
"name_group": {
"buckets": [
{
"key": "Doc 1",
"doc_count": 1
},
...
{
"key": "Doc 5",
"doc_count": 1
}
]
},
"cat_group": {
"buckets": [
{
"key": 1,
"doc_count": 2
},
...
{
"key": 4,
"doc_count": 1
}
]
}
}
}
可以通过聚合另一个属性或表达式对数据进行分面。例如，如果文档同时包含品牌ID和名称，我们可以在分面中返回品牌名称，但聚合品牌ID。这可以通过使用 FACET {expr1} BY {expr2} 来实现。
SELECT * FROM facetdemo FACET brand_name by brand_id;
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
| id | price | brand_id | title | brand_name | property | j | categories |
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
| 1 | 306 | 1 | Product Ten Three | Brand One | Six_Ten | {"prop1":66,"prop2":91,"prop3":"One"} | 10,11 |
| 2 | 400 | 10 | Product Three One | Brand Ten | Four_Three | {"prop1":69,"prop2":19,"prop3":"One"} | 13,14 |
....
| 19 | 855 | 1 | Product Seven Two | Brand One | Eight_Seven | {"prop1":63,"prop2":78,"prop3":"One"} | 10,11,12 |
| 20 | 31 | 9 | Product Four One | Brand Nine | Ten_Four | {"prop1":79,"prop2":42,"prop3":"One"} | 12,13,14 |
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
20 rows in set (0.00 sec)
+-------------+----------+
| brand_name | count(*) |
+-------------+----------+
| Brand One | 1013 |
| Brand Ten | 998 |
| Brand Five | 1007 |
| Brand Nine | 944 |
| Brand Two | 990 |
| Brand Six | 1039 |
| Brand Three | 1016 |
| Brand Four | 994 |
| Brand Eight | 1033 |
| Brand Seven | 965 |
+-------------+----------+
10 rows in set (0.00 sec)
POST /sql -d "SELECT brand_name, brand_id FROM facetdemo FACET brand_name by brand_id"
{
"took": 0,
"timed_out": false,
"hits": {
"total": 20,
"total_relation": "eq",
"hits": [
{
"_id": 1,
"_score": 1500,
"_source": {
"brand_name": "Brand One",
"brand_id": 1
}
},
{
"_id": 2,
"_score": 1500,
"_source": {
"brand_name": "Brand Ten",
"brand_id": 10
}
},
...
{
"_id": 20,
"_score": 1500,
"_source": {
"brand_name": "Brand Nine",
"brand_id": 9
}
},
]
},
"aggregations": {
"brand_name": {
"buckets": [
{
"key": "Brand One",
"doc_count": 1013
},
{
"key": "Brand Ten",
"doc_count": 998
},
...
{
"key": "Brand Seven",
"doc_count": 965
},
]
}
}
}
如果需要从 FACET 返回的桶中移除重复项，可以使用 DISTINCT field_name，其中 field_name 是您希望用于去重的字段。如果您对分布式表进行 FACET 查询，并且不确定表中是否有唯一的ID（表应该是本地的且具有相同的模式），也可以是 id（这是默认值）。
如果查询中有多个 FACET 声明，field_name 在所有声明中应该相同。
DISTINCT 会在 count(*) 列之前返回一个额外的列 count(distinct ...)，使您无需进行另一个查询即可获得两个结果。
SELECT brand_name, property FROM facetdemo FACET brand_name distinct property;
+-------------+----------+
| brand_name | property |
+-------------+----------+
| Brand Nine | Four |
| Brand Ten | Four |
| Brand One | Five |
| Brand Seven | Nine |
| Brand Seven | Seven |
| Brand Three | Seven |
| Brand Nine | Five |
| Brand Three | Eight |
| Brand Two | Eight |
| Brand Six | Eight |
| Brand Ten | Four |
| Brand Ten | Two |
| Brand Four | Ten |
| Brand One | Nine |
| Brand Four | Eight |
| Brand Nine | Seven |
| Brand Four | Five |
| Brand Three | Four |
| Brand Four | Two |
| Brand Four | Eight |
+-------------+----------+
20 rows in set (0.00 sec)
+-------------+--------------------------+----------+
| brand_name | count(distinct property) | count(*) |
+-------------+--------------------------+----------+
| Brand Nine | 3 | 3 |
| Brand Ten | 2 | 3 |
| Brand One | 2 | 2 |
| Brand Seven | 2 | 2 |
| Brand Three | 3 | 3 |
| Brand Two | 1 | 1 |
| Brand Six | 1 | 1 |
| Brand Four | 4 | 5 |
+-------------+--------------------------+----------+
8 rows in set (0.00 sec)
POST /sql -d 'SELECT brand_name, property FROM facetdemo FACET brand_name distinct property'
{
"took": 0,
"timed_out": false,
"hits": {
"total": 20,
"total_relation": "eq",
"hits": [
{
"_score": 1,
"_source": {
"brand_name": "Brand Nine",
"property": "Four"
}
},
{
"_score": 1,
"_source": {
"brand_name": "Brand Ten",
"property": "Four"
}
},
...
{
"_score": 1,
"_source": {
"brand_name": "Brand Four",
"property": "Eight"
}
}
]
},
"aggregations": {
"brand_name": {
"buckets": [
{
"key": "Brand Nine",
"doc_count": 3,
"count(distinct property)": 3
},
{
"key": "Brand Ten",
"doc_count": 3,
"count(distinct property)": 2
},
...
{
"key": "Brand Two",
"doc_count": 1,
"count(distinct property)": 1
},
{
"key": "Brand Six",
"doc_count": 1,
"count(distinct property)": 1
},
{
"key": "Brand Four",
"doc_count": 5,
"count(distinct property)": 4
}
]
}
}
}
分面可以基于表达式进行聚合。一个经典的例子是按特定范围对价格进行分段：
<!-- request SQL -->SELECT * FROM facetdemo FACET INTERVAL(price,200,400,600,800) AS price_range ;
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+-------------+
| id | price | brand_id | title | brand_name | property | j | categories | price_range |
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+-------------+
| 1 | 306 | 1 | Product Ten Three | Brand One | Six_Ten | {"prop1":66,"prop2":91,"prop3":"One"} | 10,11 | 1 |
...
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+-------------+
20 rows in set (0.00 sec)
+-------------+----------+
| price_range | count(*) |
+-------------+----------+
| 0 | 1885 |
| 3 | 1973 |
| 4 | 2100 |
| 2 | 1999 |
| 1 | 2043 |
+-------------+----------+
5 rows in set (0.01 sec)
POST /search -d '
{
"table": "facetdemo",
"query":
{
"match_all": {}
},
"expressions":
{
"price_range": "INTERVAL(price,200,400,600,800)"
},
"aggs":
{
"group_property":
{
"terms":
{
"field": "price_range"
}
}
}
}
{
"took": 3,
"timed_out": false,
"hits": {
"total": 10000,
"hits": [
{
"_id": 1,
"_score": 1,
"_source": {
"price": 197,
"brand_id": 10,
"brand_name": "Brand Ten",
"categories": [
10
],
"price_range": 0
}
},
...
{
"_id": 20,
"_score": 1,
"_source": {
"price": 227,
"brand_id": 3,
"brand_name": "Brand Three",
"categories": [
12,
13
],
"price_range": 1
}
}
]
},
"aggregations": {
"group_property": {
"buckets": [
{
"key": 4,
"doc_count": 2100
},
{
"key": 3,
"doc_count": 1973
},
{
"key": 2,
"doc_count": 1999
},
{
"key": 1,
"doc_count": 2043
},
{
"key": 0,
"doc_count": 1885
}
]
}
}
}
$index->setName('facetdemo');
$search = $index->search('');
$search->limit(5);
$search->expression('price_range','INTERVAL(price,200,400,600,800)');
$search->facet('price_range','group_property');
$results = $search->get();
print_r($results->getFacets());
Array
(
[group_property] => Array
(
[buckets] => Array
(
[0] => Array
(
[key] => 4
[doc_count] => 2100
)
[1] => Array
(
[key] => 3
[doc_count] => 1973
)
[2] => Array
(
[key] => 2
[doc_count] => 1999
)
[3] => Array
(
[key] => 1
[doc_count] => 2043
)
[4] => Array
(
[key] => 0
[doc_count] => 1885
)
)
)
)
res =searchApi.search({"table":"facetdemo","query":{"match_all":{}},"expressions":{"price_range":"INTERVAL(price,200,400,600,800)"},"aggs":{"group_property":{"terms":{"field":"price_range"}}}})
{'aggregations': {u'group_brand_id': {u'buckets': [{u'doc_count': 1019,
u'key': 10},
{u'doc_count': 954,
u'key': 9},
{u'doc_count': 1021,
u'key': 8},
{u'doc_count': 1011,
u'key': 7},
{u'doc_count': 997,
u'key': 6}]},
u'group_property': {u'buckets': [{u'doc_count': 11,
u'key': 1000},
{u'doc_count': 12,
u'key': 999},
{u'doc_count': 7,
u'key': 998},
{u'doc_count': 14,
u'key': 997},
{u'doc_count': 8,
u'key': 996}]}},
'hits': {'hits': [{u'_id': u'1',
u'_score': 1,
u'_source': {u'brand_id': 10,
u'brand_name': u'Brand Ten',
u'categories': [10],
u'price': 197,
u'property': u'Six',
u'title': u'Product Eight One'}},
{u'_id': u'2',
u'_score': 1,
u'_source': {u'brand_id': 6,
u'brand_name': u'Brand Six',
u'categories': [12, 13, 14],
u'price': 671,
u'property': u'Four',
u'title': u'Product Nine Seven'}},
{u'_id': u'3',
u'_score': 1,
u'_source': {u'brand_id': 3,
u'brand_name': u'Brand Three',
u'categories': [13, 14, 15],
u'price': 92,
u'property': u'Six',
u'title': u'Product Five Four'}},
{u'_id': u'4',
u'_score': 1,
u'_source': {u'brand_id': 10,
u'brand_name': u'Brand Ten',
u'categories': [11],
u'price': 713,
u'property': u'Five',
u'title': u'Product Eight Nine'}},
{u'_id': u'5',
u'_score': 1,
u'_source': {u'brand_id': 7,
u'brand_name': u'Brand Seven',
u'categories': [11, 12, 13],
u'price': 805,
u'property': u'Two',
u'title': u'Product Ten Three'}}],
'max_score': None,
'total': 10000},
'profile': None,
'timed_out': False,
'took': 0}
res = await searchApi.search({"table":"facetdemo","query":{"match_all":{}},"expressions":{"price_range":"INTERVAL(price,200,400,600,800)"},"aggs":{"group_property":{"terms":{"field":"price_range"}}}})
{'aggregations': {u'group_brand_id': {u'buckets': [{u'doc_count': 1019,
u'key': 10},
{u'doc_count': 954,
u'key': 9},
{u'doc_count': 1021,
u'key': 8},
{u'doc_count': 1011,
u'key': 7},
{u'doc_count': 997,
u'key': 6}]},
u'group_property': {u'buckets': [{u'doc_count': 11,
u'key': 1000},
{u'doc_count': 12,
u'key': 999},
{u'doc_count': 7,
u'key': 998},
{u'doc_count': 14,
u'key': 997},
{u'doc_count': 8,
u'key': 996}]}},
'hits': {'hits': [{u'_id': u'1',
u'_score': 1,
u'_source': {u'brand_id': 10,
u'brand_name': u'Brand Ten',
u'categories': [10],
u'price': 197,
u'property': u'Six',
u'title': u'Product Eight One'}},
{u'_id': u'2',
u'_score': 1,
u'_source': {u'brand_id': 6,
u'brand_name': u'Brand Six',
u'categories': [12, 13, 14],
u'price': 671,
u'property': u'Four',
u'title': u'Product Nine Seven'}},
{u'_id': u'3',
u'_score': 1,
u'_source': {u'brand_id': 3,
u'brand_name': u'Brand Three',
u'categories': [13, 14, 15],
u'price': 92,
u'property': u'Six',
u'title': u'Product Five Four'}},
{u'_id': u'4',
u'_score': 1,
u'_source': {u'brand_id': 10,
u'brand_name': u'Brand Ten',
u'categories': [11],
u'price': 713,
u'property': u'Five',
u'title': u'Product Eight Nine'}},
{u'_id': u'5',
u'_score': 1,
u'_source': {u'brand_id': 7,
u'brand_name': u'Brand Seven',
u'categories': [11, 12, 13],
u'price': 805,
u'property': u'Two',
u'title': u'Product Ten Three'}}],
'max_score': None,
'total': 10000},
'profile': None,
'timed_out': False,
'took': 0}
res = await searchApi.search({"table":"facetdemo","query":{"match_all":{}},"expressions":{"price_range":"INTERVAL(price,200,400,600,800)"},"aggs":{"group_property":{"terms":{"field":"price_range"}}}});
{"took":0,"timed_out":false,"hits":{"total":10000,"hits":[{"_id": 1,"_score":1,"_source":{"price":197,"brand_id":10,"brand_name":"Brand Ten","categories":[10],"title":"Product Eight One","property":"Six","price_range":0}},{"_id": 2,"_score":1,"_source":{"price":671,"brand_id":6,"brand_name":"Brand Six","categories":[12,13,14],"title":"Product Nine Seven","property":"Four","price_range":3}},{"_id": 3,"_score":1,"_source":{"price":92,"brand_id":3,"brand_name":"Brand Three","categories":[13,14,15],"title":"Product Five Four","property":"Six","price_range":0}},{"_id": 4,"_score":1,"_source":{"price":713,"brand_id":10,"brand_name":"Brand Ten","categories":[11],"title":"Product Eight Nine","property":"Five","price_range":3}},{"_id": 5,"_score":1,"_source":{"price":805,"brand_id":7,"brand_name":"Brand Seven","categories":[11,12,13],"title":"Product Ten Three","property":"Two","price_range":4}},{"_id": 6,"_score":1,"_source":{"price":420,"brand_id":2,"brand_name":"Brand Two","categories":[10,11],"title":"Product Two One","property":"Six","price_range":2}},{"_id": 7,"_score":1,"_source":{"price":412,"brand_id":9,"brand_name":"Brand Nine","categories":[10],"title":"Product Four Nine","property":"Eight","price_range":2}},{"_id": 8,"_score":1,"_source":{"price":300,"brand_id":9,"brand_name":"Brand Nine","categories":[13,14,15],"title":"Product Eight Four","property":"Five","price_range":1}},{"_id": 9,"_score":1,"_source":{"price":728,"brand_id":1,"brand_name":"Brand One","categories":[11],"title":"Product Nine Six","property":"Four","price_range":3}},{"_id": 10,"_score":1,"_source":{"price":622,"brand_id":3,"brand_name":"Brand Three","categories":[10,11],"title":"Product Six Seven","property":"Two","price_range":3}},{"_id": 11,"_score":1,"_source":{"price":462,"brand_id":5,"brand_name":"Brand Five","categories":[10,11],"title":"Product Ten Two","property":"Eight","price_range":2}},{"_id": 12,"_score":1,"_source":{"price":939,"brand_id":7,"brand_name":"Brand Seven","categories":[12,13],"title":"Product Nine Seven","property":"Six","price_range":4}},{"_id": 13,"_score":1,"_source":{"price":948,"brand_id":8,"brand_name":"Brand Eight","categories":[12],"title":"Product Ten One","property":"Six","price_range":4}},{"_id": 14,"_score":1,"_source":{"price":900,"brand_id":9,"brand_name":"Brand Nine","categories":[12,13,14],"title":"Product Ten Nine","property":"Three","price_range":4}},{"_id": 15,"_score":1,"_source":{"price":224,"brand_id":3,"brand_name":"Brand Three","categories":[13],"title":"Product Two Six","property":"Four","price_range":1}},{"_id": 16,"_score":1,"_source":{"price":713,"brand_id":10,"brand_name":"Brand Ten","categories":[12],"title":"Product Two Four","property":"Six","price_range":3}},{"_id": 17,"_score":1,"_source":{"price":510,"brand_id":2,"brand_name":"Brand Two","categories":[10],"title":"Product Ten Two","property":"Seven","price_range":2}},{"_id": 18,"_score":1,"_source":{"price":702,"brand_id":10,"brand_name":"Brand Ten","categories":[12,13],"title":"Product Nine One","property":"Three","price_range":3}},{"_id": 19,"_score":1,"_source":{"price":836,"brand_id":4,"brand_name":"Brand Four","categories":[10,11,12],"title":"Product Four Five","property":"Two","price_range":4}},{"_id": 20,"_score":1,"_source":{"price":227,"brand_id":3,"brand_name":"Brand Three","categories":[12,13],"title":"Product Three Four","property":"Ten","price_range":1}}]}}
searchRequest = new SearchRequest();
expressions = new HashMap<String,Object>(){{
put("price_range","INTERVAL(price,200,400,600,800)");
}};
searchRequest.setExpressions(expressions);
aggs = new HashMap<String,Object>(){{
put("group_property", new HashMap<String,Object>(){{
put("terms", new HashMap<String,Object>(){{
put("field","price_range");
}});
}});
}};
searchRequest.setIndex("facetdemo");
searchRequest.setLimit(5);
query = new HashMap<String,Object>();
query.put("match_all",null);
searchRequest.setQuery(query);
searchRequest.setAggs(aggs);
searchResponse = searchApi.search(searchRequest);
class SearchResponse {
took: 0
timedOut: false
aggregations: {group_property={buckets=[{key=4, doc_count=2100}, {key=3, doc_count=1973}, {key=2, doc_count=1999}, {key=1, doc_count=2043}, {key=0, doc_count=1885}]}}
hits: class SearchResponseHits {
maxScore: null
total: 10000
hits: [{_id=1, _score=1, _source={price=197, brand_id=10, brand_name=Brand Ten, categories=[10], title=Product Eight One, property=Six, price_range=0}}, {_id=2, _score=1, _source={price=671, brand_id=6, brand_name=Brand Six, categories=[12, 13, 14], title=Product Nine Seven, property=Four, price_range=3}}, {_id=3, _score=1, _source={price=92, brand_id=3, brand_name=Brand Three, categories=[13, 14, 15], title=Product Five Four, property=Six, price_range=0}}, {_id=4, _score=1, _source={price=713, brand_id=10, brand_name=Brand Ten, categories=[11], title=Product Eight Nine, property=Five, price_range=3}}, {_id=5, _score=1, _source={price=805, brand_id=7, brand_name=Brand Seven, categories=[11, 12, 13], title=Product Ten Three, property=Two, price_range=4}}]
}
profile: null
}
var expr = new Dictionary<string, string> { {"price_range", "INTERVAL(price,200,400,600,800"} } ;
var agg = new Aggregation("group_property", "price_range");
object query = new { match_all=null };
var searchRequest = new SearchRequest("facetdemo", query);
searchRequest.Limit = 5;
searchRequest.Expressions = new List<Object> {expr};
searchRequest.Aggs = new List<Aggregation> {agg};
var searchResponse = searchApi.Search(searchRequest);
class SearchResponse {
took: 0
timedOut: false
aggregations: {group_property={buckets=[{key=4, doc_count=2100}, {key=3, doc_count=1973}, {key=2, doc_count=1999}, {key=1, doc_count=2043}, {key=0, doc_count=1885}]}}
hits: class SearchResponseHits {
maxScore: null
total: 10000
hits: [{_id=1, _score=1, _source={price=197, brand_id=10, brand_name=Brand Ten, categories=[10], title=Product Eight One, property=Six, price_range=0}}, {_id=2, _score=1, _source={price=671, brand_id=6, brand_name=Brand Six, categories=[12, 13, 14], title=Product Nine Seven, property=Four, price_range=3}}, {_id=3, _score=1, _source={price=92, brand_id=3, brand_name=Brand Three, categories=[13, 14, 15], title=Product Five Four, property=Six, price_range=0}}, {_id=4, _score=1, _source={price=713, brand_id=10, brand_name=Brand Ten, categories=[11], title=Product Eight Nine, property=Five, price_range=3}}, {_id=5, _score=1, _source={price=805, brand_id=7, brand_name=Brand Seven, categories=[11, 12, 13], title=Product Ten Three, property=Two, price_range=4}}]
}
profile: null
}
let query = SearchQuery::new();
let aggTerms1 = AggTerms::new("price_range");
let agg1 = Aggregation {
terms: Some(Box::new(aggTerms1)),
..Default::default(),
};
let mut aggs = HashMap::new();
aggs.insert("group_property".to_string(), agg1);
let mut expr = HashMap::new();
expr.insert("price_range".to_string(), "INTERVAL(price,200,400,600,800");
let expressions: [HashMap; 1] = [expr];
let search_req = SearchRequest {
table: "facetdemo".to_string(),
query: Some(Box::new(query)),
expressions: serde_json::json!(expressions),
aggs: serde_json::json!(aggs),
limit: serde_json::json!(5),
..Default::default(),
};
let search_res = search_api.search(search_req).await;
class SearchResponse {
took: 0
timedOut: false
aggregations: {group_property={buckets=[{key=4, doc_count=2100}, {key=3, doc_count=1973}, {key=2, doc_count=1999}, {key=1, doc_count=2043}, {key=0, doc_count=1885}]}}
hits: class SearchResponseHits {
maxScore: null
total: 10000
hits: [{_id=1, _score=1, _source={price=197, brand_id=10, brand_name=Brand Ten, categories=[10], title=Product Eight One, property=Six, price_range=0}}, {_id=2, _score=1, _source={price=671, brand_id=6, brand_name=Brand Six, categories=[12, 13, 14], title=Product Nine Seven, property=Four, price_range=3}}, {_id=3, _score=1, _source={price=92, brand_id=3, brand_name=Brand Three, categories=[13, 14, 15], title=Product Five Four, property=Six, price_range=0}}, {_id=4, _score=1, _source={price=713, brand_id=10, brand_name=Brand Ten, categories=[11], title=Product Eight Nine, property=Five, price_range=3}}, {_id=5, _score=1, _source={price=805, brand_id=7, brand_name=Brand Seven, categories=[11, 12, 13], title=Product Ten Three, property=Two, price_range=4}}]
}
profile: null
}
res = await searchApi.search({
index: 'test',
query: { match_all:{} },
expressions: { cat_range: "INTERVAL(cat,1,3)" }
aggs: {
expr_group: {
terms: { field : 'cat_range' }
}
}
});
{
"took": 0,
"timed_out": false,
"hits": {
"total": 5,
"hits": [
{
"_id": 1,
"_score": 1,
"_source": {
"content": "Text 1",
"name": "Doc 1",
"cat": 1,
"cat_range": 1
}
},
...
{
"_id": 5,
"_score": 1,
"_source": {
"content": "Text 5",
"name": "Doc 5",
"cat": 4,
"cat_range": 2,
}
}
]
},
"aggregations": {
"expr_group": {
"buckets": [
{
"key": 0,
"doc_count": 0
},
{
"key": 1,
"doc_count": 3
},
{
"key": 2,
"doc_count": 2
}
]
}
}
}
query := map[string]interface{} {}
searchRequest.SetQuery(query)
exprs := map[string]string{} { "cat_range": "INTERVAL(cat,1,3)" }
searchRequest.SetExpressions(exprs)
aggByExpr := manticoreclient.NewAggregation()
aggTerms := manticoreclient.NewAggregationTerms()
aggTerms.SetField("cat_range")
aggByExpr.SetTerms(aggTerms)
aggs := map[string]Aggregation{} { "expr_group": aggByExpr }
searchRequest.SetAggs(aggs)
res, _, _ := apiClient.SearchAPI.Search(context.Background()).SearchRequest(*searchRequest).Execute()
{
"took": 0,
"timed_out": false,
"hits": {
"total": 5,
"hits": [
{
"_id": 1,
"_score": 1,
"_source": {
"content": "Text 1",
"name": "Doc 1",
"cat": 1,
"cat_range": 1
}
},
...
{
"_id": 5,
"_score": 1,
"_source": {
"content": "Text 5",
"name": "Doc 5",
"cat": 4,
"cat_range": 2
}
}
]
},
"aggregations": {
"expr_group": {
"buckets": [
{
"key": 0,
"doc_count": 0
},
{
"key": 1,
"doc_count": 3
},
{
"key": 2,
"doc_count": 2
}
]
}
}
}
Facets可以对多级分组进行聚合，结果集与查询执行多级分组时的结果相同：
<!-- request SQL -->SELECT *,INTERVAL(price,200,400,600,800) AS price_range FROM facetdemo
FACET price_range AS price_range,brand_name ORDER BY brand_name asc;
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+-------------+
| id | price | brand_id | title | brand_name | property | j | categories | price_range |
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+-------------+
| 1 | 306 | 1 | Product Ten Three | Brand One | Six_Ten | {"prop1":66,"prop2":91,"prop3":"One"} | 10,11 | 1 |
...
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+-------------+
20 rows in set (0.00 sec)
+--------------+-------------+----------+
| fprice_range | brand_name | count(*) |
+--------------+-------------+----------+
| 1 | Brand Eight | 197 |
| 4 | Brand Eight | 235 |
| 3 | Brand Eight | 203 |
| 2 | Brand Eight | 201 |
| 0 | Brand Eight | 197 |
| 4 | Brand Five | 230 |
| 2 | Brand Five | 197 |
| 1 | Brand Five | 204 |
| 3 | Brand Five | 193 |
| 0 | Brand Five | 183 |
| 1 | Brand Four | 195 |
...
POST /sql?mode=raw -d "SELECT brand_name,INTERVAL(price,200,400,600,800) AS price_range FROM facetdemo FACET price_range AS price_range,brand_name ORDER BY brand_name asc"
[
{
"columns": [
{
"brand_name": {
"type": "string"
}
},
{
"price_range": {
"type": "long"
}
}
],
"data": [
{
"brand_name": "Brand One",
"price_range": 1
},
...
],
"total": 20,
"error": "",
"warning": ""
},
{
"columns": [
{
"fprice_range": {
"type": "long"
}
},
{
"brand_name": {
"type": "string"
}
},
{
"count(*)": {
"type": "long long"
}
}
],
"data": [
{
"fprice_range": 1,
"brand_name": "Brand Eight",
"count(*)": 197
},
{
"fprice_range": 4,
"brand_name": "Brand Eight",
"count(*)": 235
},
...
{
"fprice_range": 0,
"brand_name": "Brand Five",
"count(*)": 183
},
{
"fprice_range": 1,
"brand_name": "Brand Four",
"count(*)": 195
}
],
"total": 10,
"error": "",
"warning": ""
}
]
Facets可以通过构造固定大小的桶来对值进行直方图聚合。 键函数是：
key_of_the_bucket = interval + offset * floor ( ( value - offset ) / interval )
直方图参数interval必须为正数，直方图参数offset必须为正数且小于interval。默���情况下，桶以数组形式返回。直方图参数keyed使得响应以字典形式返回桶键。
SELECT COUNT(*), HISTOGRAM(price, {hist_interval=100}) as price_range FROM facets GROUP BY price_range ORDER BY price_range ASC;
+----------+-------------+
| count(*) | price_range |
+----------+-------------+
| 5 | 0 |
| 5 | 100 |
| 1 | 300 |
| 4 | 400 |
| 1 | 500 |
| 3 | 700 |
| 1 | 900 |
+----------+-------------+
POST /search -d '
{
"size": 0,
"table": "facets",
"aggs": {
"price_range": {
"histogram": {
"field": "price",
"interval": 300
}
}
}
}'
{
"took": 0,
"timed_out": false,
"hits": {
"total": 20,
"total_relation": "eq",
"hits": []
},
"aggregations": {
"price_range": {
"buckets": [
{
"key": 0,
"doc_count": 10
},
{
"key": 300,
"doc_count": 6
},
{
"key": 600,
"doc_count": 3
},
{
"key": 900,
"doc_count": 1
}
]
}
}
}
POST /search -d '
{
"size": 0,
"table": "facets",
"aggs": {
"price_range": {
"histogram": {
"field": "price",
"interval": 300,
"keyed": true
}
}
}
}'
{
"took": 0,
"timed_out": false,
"hits": {
"total": 20,
"total_relation": "eq",
"hits": []
},
"aggregations": {
"price_range": {
"buckets": {
"0": {
"key": 0,
"doc_count": 10
},
"300": {
"key": 300,
"doc_count": 6
},
"600": {
"key": 600,
"doc_count": 3
},
"900": {
"key": 900,
"doc_count": 1
}
}
}
}
}
Facets可以对日期直方图值进行聚合，这与普通直方图类似。不同之处在于，区间由日期或时间表达式指定。此类表达式需要特殊支持，因为区间长度不总是固定的。值会根据以下键函数四舍五入到最近的桶：
key_of_the_bucket = interval * floor ( value / interval )
直方图参数calendar_interval理解月份具有不同的天数。
与calendar_interval不同，fixed_interval参数使用固定数量的单位，无论其在日历中的位置如何，都不会偏离。但是fixed_interval无法处理如周或月这样的单位，因为月不是一个固定数量。尝试为fixed_interval指定如周或月这样的单位将导致错误。
接受的区间在日期直方图表达式中描述。默认情况下，桶以数组形式返回。直方图参数keyed使得响应以字典形式返回桶键。
在 JSON 查询中，date_histogram 还支持 time_zone 和 offset 与 calendar_interval 一起使用：
time_zone 更改用于四舍五入日历桶和格式化 key_as_string 的时区。它必须是服务器支持的 IANA 时区名称，例如 Asia/Novosibirsk。不支持像 +03:00 这样的数字 UTC 偏移量。offset 在四舍五入之前通过固定量移动日历桶边界。它可以是使用与 fixed_interval 相同单位的固定间隔字符串，例如 3h，或者以秒为单位的整数，例如 10800。该值可以以 + 或 - 前缀。time_zone 和 offset 不支持 fixed_interval。
SELECT count(*), DATE_HISTOGRAM(tm, {calendar_interval='month'}) AS months FROM idx_dates GROUP BY months ORDER BY months ASC
+----------+------------+
| count(*) | months |
+----------+------------+
| 442 | 1485907200 |
| 744 | 1488326400 |
| 720 | 1491004800 |
| 230 | 1493596800 |
+----------+------------+
POST /search -d '
{
"table": "idx_dates",
"size": 0,
"aggs": {
"months": {
"date_histogram": {
"field": "tm",
"keyed": true,
"calendar_interval": "month"
}
}
}
}'
{
"timed_out": false,
"hits": {
"total": 2136,
"total_relation": "eq",
"hits": []
},
"aggregations": {
"months": {
"buckets": {
"2017-02-01T00:00:00": {
"key": 1485907200,
"key_as_string": "2017-02-01T00:00:00",
"doc_count": 442
},
"2017-03-01T00:00:00": {
"key": 1488326400,
"key_as_string": "2017-03-01T00:00:00",
"doc_count": 744
},
"2017-04-01T00:00:00": {
"key": 1491004800,
"key_as_string": "2017-04-01T00:00:00",
"doc_count": 720
},
"2017-05-01T00:00:00": {
"key": 1493596800,
"key_as_string": "2017-05-01T00:00:00",
"doc_count": 230
}
}
}
}
}
Facets可以对一组范围进行聚合。值会与桶范围进行检查，其中每个桶包括from值并排除to值。
将keyed属性设置为true使得响应以字典形式返回桶键，而不是数组。
SELECT COUNT(*), RANGE(price, {range_to=150},{range_from=150,range_to=300},{range_from=300}) price_range FROM facets GROUP BY price_range ORDER BY price_range ASC;
+----------+-------------+
| count(*) | price_range |
+----------+-------------+
| 8 | 0 |
| 2 | 1 |
| 10 | 2 |
+----------+-------------+
POST /search -d '
{
"size": 0,
"table": "facets",
"aggs": {
"price_range": {
"range": {
"field": "price",
"ranges": [
{
"to": 99
},
{
"from": 99,
"to": 550
},
{
"from": 550
}
]
}
}
}
}'
{
"took": 0,
"timed_out": false,
"hits": {
"total": 20,
"total_relation": "eq",
"hits": []
},
"aggregations": {
"price_range": {
"buckets": [
{
"key": "*-99",
"to": 99,
"doc_count": 5
},
{
"key": "99-550",
"from": 99,
"to": 550,
"doc_count": 11
},
{
"key": "550-*",
"from": 550,
"doc_count": 4
}
]
}
}
}
POST /search -d '
{
"size":0,
"table":"facets",
"aggs":{
"price_range":{
"range":{
"field":"price",
"keyed":true,
"ranges":[
{
"from":100,
"to":399
},
{
"from":399
}
]
}
}
}
}'
{
"took": 0,
"timed_out": false,
"hits": {
"total": 20,
"total_relation": "eq",
"hits": []
},
"aggregations": {
"price_range": {
"buckets": {
"100-399": {
"from": 100,
"to": 399,
"doc_count": 6
},
"399-*": {
"from": 399,
"doc_count": 9
}
}
}
}
}
Facets可以对一组日期范围进行聚合，这与普通范围类似。不同之处在于，from和to值可以使用日期数学表达式表示。此聚合包括from值并排除每个范围的to值。将keyed属性设置为true使得响应以字典形式返回桶键，而不是数组。
SELECT COUNT(*), DATE_RANGE(tm, {range_to='2017||+2M/M'},{range_from='2017||+2M/M',range_to='2017||+5M/M'},{range_from='2017||+5M/M'}) AS points FROM idx_dates GROUP BY points ORDER BY points ASC;
+----------+--------+
| count(*) | points |
+----------+--------+
| 442 | 0 |
| 1464 | 1 |
| 230 | 2 |
+----------+--------+
POST /search -d '
{
"table": "idx_dates",
"size": 0,
"aggs": {
"points": {
"date_range": {
"field": "tm",
"keyed": true,
"ranges": [
{
"to": "2017||+2M/M"
},
{
"from": "2017||+2M/M",
"to": "2017||+4M/M"
},
{
"from": "2017||+4M/M",
"to": "2017||+5M/M"
},
{
"from": "2017||+5M/M"
}
]
}
}
}
}'
{
"timed_out": false,
"hits": {
"total": 2136,
"total_relation": "eq",
"hits": []
},
"aggregations": {
"points": {
"buckets": {
"*-2017-03-01T00:00:00": {
"to": "2017-03-01T00:00:00",
"doc_count": 442
},
"2017-03-01T00:00:00-2017-04-01T00:00:00": {
"from": "2017-03-01T00:00:00",
"to": "2017-04-01T00:00:00",
"doc_count": 744
},
"2017-04-01T00:00:00-2017-05-01T00:00:00": {
"from": "2017-04-01T00:00:00",
"to": "2017-05-01T00:00:00",
"doc_count": 720
},
"2017-05-01T00:00:00-*": {
"from": "2017-05-01T00:00:00",
"doc_count": 230
}
}
}
}
}
Facets支持ORDER BY子句，就像标准查询一样。每个Facet可以有自己的排序方式，Facet的排序不会影响主结果集的排序，这由主查询的ORDER BY决定。排序可以基于属性名、计数（使用COUNT(*)、COUNT(DISTINCT attribute_name)）或特殊的FACET()函数，该函数提供聚合数据值。默认情况下，带有ORDER BY COUNT(*)的查询将按降序排序。
SELECT * FROM facetdemo
FACET brand_name BY brand_id ORDER BY FACET() ASC
FACET brand_name BY brand_id ORDER BY brand_name ASC
FACET brand_name BY brand_id order BY COUNT(*) DESC;
FACET brand_name BY brand_id order BY COUNT(*);
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
| id | price | brand_id | title | brand_name | property | j | categories |
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
| 1 | 306 | 1 | Product Ten Three | Brand One | Six_Ten | {"prop1":66,"prop2":91,"prop3":"One"} | 10,11 |
...
| 20 | 31 | 9 | Product Four One | Brand Nine | Ten_Four | {"prop1":79,"prop2":42,"prop3":"One"} | 12,13,14 |
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
20 rows in set (0.01 sec)
+-------------+----------+
| brand_name | count(*) |
+-------------+----------+
| Brand One | 1013 |
| Brand Two | 990 |
| Brand Three | 1016 |
| Brand Four | 994 |
| Brand Five | 1007 |
| Brand Six | 1039 |
| Brand Seven | 965 |
| Brand Eight | 1033 |
| Brand Nine | 944 |
| Brand Ten | 998 |
+-------------+----------+
10 rows in set (0.01 sec)
+-------------+----------+
| brand_name | count(*) |
+-------------+----------+
| Brand Eight | 1033 |
| Brand Five | 1007 |
| Brand Four | 994 |
| Brand Nine | 944 |
| Brand One | 1013 |
| Brand Seven | 965 |
| Brand Six | 1039 |
| Brand Ten | 998 |
| Brand Three | 1016 |
| Brand Two | 990 |
+-------------+----------+
10 rows in set (0.01 sec)
+-------------+----------+
| brand_name | count(*) |
+-------------+----------+
| Brand Six | 1039 |
| Brand Eight | 1033 |
| Brand Three | 1016 |
| Brand One | 1013 |
| Brand Five | 1007 |
| Brand Ten | 998 |
| Brand Four | 994 |
| Brand Two | 990 |
| Brand Seven | 965 |
| Brand Nine | 944 |
+-------------+----------+
10 rows in set (0.01 sec)
POST /search -d '
{
"table":"table_name",
"aggs":{
"group_property":{
"terms":{
"field":"a"
},
"sort":[
{
"count(*)":{
"order":"desc"
}
}
]
}
}
}'
{
"took": 0,
"timed_out": false,
"hits": {
"total": 6,
"total_relation": "eq",
"hits": [
{
"_id": 1515697460415037554,
"_score": 1,
"_source": {
"a": 1
}
},
{
"_id": 1515697460415037555,
"_score": 1,
"_source": {
"a": 2
}
},
{
"_id": 1515697460415037556,
"_score": 1,
"_source": {
"a": 2
}
},
{
"_id": 1515697460415037557,
"_score": 1,
"_source": {
"a": 3
}
},
{
"_id": 1515697460415037558,
"_score": 1,
"_source": {
"a": 3
}
},
{
"_id": 1515697460415037559,
"_score": 1,
"_source": {
"a": 3
}
}
]
},
"aggregations": {
"group_property": {
"buckets": [
{
"key": 3,
"doc_count": 3
},
{
"key": 2,
"doc_count": 2
},
{
"key": 1,
"doc_count": 1
}
]
}
}
}
默认情况下，每个Facet结果集仅限于20个值。可以通过LIMIT子句单独为每个Facet控制Facet值的数量，提供返回值的数量格式LIMIT count或使用偏移量LIMIT offset, count。
返回的最大Facet值数量受查询的max_matches设置限制。如果您想实现动态max_matches（限制max_matches为偏移量+每页以提高性能），必须考虑到过低的max_matches值可能会影响Facet值的数量。在这种情况下，应使用足以覆盖Facet值数量的最小max_matches值。
SELECT * FROM facetdemo
FACET brand_name BY brand_id ORDER BY FACET() ASC LIMIT 0,1
FACET brand_name BY brand_id ORDER BY brand_name ASC LIMIT 2,4
FACET brand_name BY brand_id order BY COUNT(*) DESC LIMIT 4;
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
| id | price | brand_id | title | brand_name | property | j | categories |
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
| 1 | 306 | 1 | Product Ten Three | Brand One | Six_Ten | {"prop1":66,"prop2":91,"prop3":"One"} | 10,11 |
...
| 20 | 31 | 9 | Product Four One | Brand Nine | Ten_Four | {"prop1":79,"prop2":42,"prop3":"One"} | 12,13,14 |
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
20 rows in set (0.01 sec)
+-------------+----------+
| brand_name | count(*) |
+-------------+----------+
| Brand One | 1013 |
+-------------+----------+
1 rows in set (0.01 sec)
+-------------+----------+
| brand_name | count(*) |
+-------------+----------+
| Brand Four | 994 |
| Brand Nine | 944 |
| Brand One | 1013 |
| Brand Seven | 965 |
+-------------+----------+
4 rows in set (0.01 sec)
+-------------+----------+
| brand_name | count(*) |
+-------------+----------+
| Brand Six | 1039 |
| Brand Eight | 1033 |
| Brand Three | 1016 |
+-------------+----------+
3 rows in set (0.01 sec)
POST /search -d '
{
"table" : "facetdemo",
"query" : {"match_all" : {} },
"limit": 5,
"aggs" :
{
"group_property" :
{
"terms" :
{
"field":"price",
"size":1,
}
},
"group_brand_id" :
{
"terms" :
{
"field":"brand_id",
"size":3
}
}
}
}
'
{
"took": 3,
"timed_out": false,
"hits": {
"total": 10000,
"hits": [
{
"_id": 1,
"_score": 1,
"_source": {
"price": 197,
"brand_id": 10,
"brand_name": "Brand Ten",
"categories": [
10
]
}
},
...
{
"_id": 5,
"_score": 1,
"_source": {
"price": 805,
"brand_id": 7,
"brand_name": "Brand Seven",
"categories": [
11,
12,
13
]
}
}
]
},
"aggregations": {
"group_property": {
"buckets": [
{
"key": 1000,
"doc_count": 11
}
]
},
"group_brand_id": {
"buckets": [
{
"key": 10,
"doc_count": 1019
},
{
"key": 9,
"doc_count": 954
},
{
"key": 8,
"doc_count": 1021
}
]
}
}
}
$index->setName('facetdemo');
$search = $index->search('');
$search->limit(5);
$search->facet('price','price',1);
$search->facet('brand_id','group_brand_id',3);
$results = $search->get();
print_r($results->getFacets());
Array
(
[price] => Array
(
[buckets] => Array
(
[0] => Array
(
[key] => 1000
[doc_count] => 11
)
)
)
[group_brand_id] => Array
(
[buckets] => Array
(
[0] => Array
(
[key] => 10
[doc_count] => 1019
)
[1] => Array
(
[key] => 9
[doc_count] => 954
)
[2] => Array
(
[key] => 8
[doc_count] => 1021
)
)
)
)
res =searchApi.search({"table":"facetdemo","query":{"match_all":{}},"limit":5,"aggs":{"group_property":{"terms":{"field":"price","size":1,}},"group_brand_id":{"terms":{"field":"brand_id","size":3}}}})
{'aggregations': {u'group_brand_id': {u'buckets': [{u'doc_count': 1019,
u'key': 10},
{u'doc_count': 954,
u'key': 9},
{u'doc_count': 1021,
u'key': 8}]},
u'group_property': {u'buckets': [{u'doc_count': 11,
u'key': 1000}]}},
'hits': {'hits': [{u'_id': u'1',
u'_score': 1,
u'_source': {u'brand_id': 10,
u'brand_name': u'Brand Ten',
u'categories': [10],
u'price': 197,
u'property': u'Six',
u'title': u'Product Eight One'}},
{u'_id': u'2',
u'_score': 1,
u'_source': {u'brand_id': 6,
u'brand_name': u'Brand Six',
u'categories': [12, 13, 14],
u'price': 671,
u'property': u'Four',
u'title': u'Product Nine Seven'}},
{u'_id': u'3',
u'_score': 1,
u'_source': {u'brand_id': 3,
u'brand_name': u'Brand Three',
u'categories': [13, 14, 15],
u'price': 92,
u'property': u'Six',
u'title': u'Product Five Four'}},
{u'_id': u'4',
u'_score': 1,
u'_source': {u'brand_id': 10,
u'brand_name': u'Brand Ten',
u'categories': [11],
u'price': 713,
u'property': u'Five',
u'title': u'Product Eight Nine'}},
{u'_id': u'5',
u'_score': 1,
u'_source': {u'brand_id': 7,
u'brand_name': u'Brand Seven',
u'categories': [11, 12, 13],
u'price': 805,
u'property': u'Two',
u'title': u'Product Ten Three'}}],
'max_score': None,
'total': 10000},
'profile': None,
'timed_out': False,
'took': 0}
res = await searchApi.search({"table":"facetdemo","query":{"match_all":{}},"limit":5,"aggs":{"group_property":{"terms":{"field":"price","size":1,}},"group_brand_id":{"terms":{"field":"brand_id","size":3}}}})
{'aggregations': {u'group_brand_id': {u'buckets': [{u'doc_count': 1019,
u'key': 10},
{u'doc_count': 954,
u'key': 9},
{u'doc_count': 1021,
u'key': 8}]},
u'group_property': {u'buckets': [{u'doc_count': 11,
u'key': 1000}]}},
'hits': {'hits': [{u'_id': u'1',
u'_score': 1,
u'_source': {u'brand_id': 10,
u'brand_name': u'Brand Ten',
u'categories': [10],
u'price': 197,
u'property': u'Six',
u'title': u'Product Eight One'}},
{u'_id': u'2',
u'_score': 1,
u'_source': {u'brand_id': 6,
u'brand_name': u'Brand Six',
u'categories': [12, 13, 14],
u'price': 671,
u'property': u'Four',
u'title': u'Product Nine Seven'}},
{u'_id': u'3',
u'_score': 1,
u'_source': {u'brand_id': 3,
u'brand_name': u'Brand Three',
u'categories': [13, 14, 15],
u'price': 92,
u'property': u'Six',
u'title': u'Product Five Four'}},
{u'_id': u'4',
u'_score': 1,
u'_source': {u'brand_id': 10,
u'brand_name': u'Brand Ten',
u'categories': [11],
u'price': 713,
u'property': u'Five',
u'title': u'Product Eight Nine'}},
{u'_id': u'5',
u'_score': 1,
u'_source': {u'brand_id': 7,
u'brand_name': u'Brand Seven',
u'categories': [11, 12, 13],
u'price': 805,
u'property': u'Two',
u'title': u'Product Ten Three'}}],
'max_score': None,
'total': 10000},
'profile': None,
'timed_out': False,
'took': 0}
res = await searchApi.search({"table":"facetdemo","query":{"match_all":{}},"limit":5,"aggs":{"group_property":{"terms":{"field":"price","size":1,}},"group_brand_id":{"terms":{"field":"brand_id","size":3}}}});
{"took":0,"timed_out":false,"hits":{"total":10000,"hits":[{"_id": 1,"_score":1,"_source":{"price":197,"brand_id":10,"brand_name":"Brand Ten","categories":[10],"title":"Product Eight One","property":"Six"}},{"_id": 2,"_score":1,"_source":{"price":671,"brand_id":6,"brand_name":"Brand Six","categories":[12,13,14],"title":"Product Nine Seven","property":"Four"}},{"_id": 3,"_score":1,"_source":{"price":92,"brand_id":3,"brand_name":"Brand Three","categories":[13,14,15],"title":"Product Five Four","property":"Six"}},{"_id": 4,"_score":1,"_source":{"price":713,"brand_id":10,"brand_name":"Brand Ten","categories":[11],"title":"Product Eight Nine","property":"Five"}},{"_id": 5,"_score":1,"_source":{"price":805,"brand_id":7,"brand_name":"Brand Seven","categories":[11,12,13],"title":"Product Ten Three","property":"Two"}}]}}
searchRequest = new SearchRequest();
aggs = new HashMap<String,Object>(){{
put("group_property", new HashMap<String,Object>(){{
put("terms", new HashMap<String,Object>(){{
put("field","price");
put("size",1);
}});
}});
put("group_brand_id", new HashMap<String,Object>(){{
put("terms", new HashMap<String,Object>(){{
put("field","brand_id");
put("size",3);
}});
}});
}};
searchRequest.setIndex("facetdemo");
searchRequest.setLimit(5);
query = new HashMap<String,Object>();
query.put("match_all",null);
searchRequest.setQuery(query);
searchRequest.setAggs(aggs);
searchResponse = searchApi.search(searchRequest);
class SearchResponse {
took: 0
timedOut: false
aggregations: {group_property={buckets=[{key=1000, doc_count=11}]}, group_brand_id={buckets=[{key=10, doc_count=1019}, {key=9, doc_count=954}, {key=8, doc_count=1021}]}}
hits: class SearchResponseHits {
maxScore: null
total: 10000
hits: [{_id=1, _score=1, _source={price=197, brand_id=10, brand_name=Brand Ten, categories=[10], title=Product Eight One, property=Six}}, {_id=2, _score=1, _source={price=671, brand_id=6, brand_name=Brand Six, categories=[12, 13, 14], title=Product Nine Seven, property=Four}}, {_id=3, _score=1, _source={price=92, brand_id=3, brand_name=Brand Three, categories=[13, 14, 15], title=Product Five Four, property=Six}}, {_id=4, _score=1, _source={price=713, brand_id=10, brand_name=Brand Ten, categories=[11], title=Product Eight Nine, property=Five}}, {_id=5, _score=1, _source={price=805, brand_id=7, brand_name=Brand Seven, categories=[11, 12, 13], title=Product Ten Three, property=Two}}]
}
profile: null
}
var agg1 = new Aggregation("group_property", "price");
agg1.Size = 1;
var agg2 = new Aggregation("group_brand_id", "brand_id");
agg2.Size = 3;
agg2.Size = 100;
object query = new { match_all=null };
var searchRequest = new SearchRequest("facetdemo", query);
searchRequest.Aggs = new List<Aggregation> {agg1, agg2};
var searchResponse = searchApi.Search(searchRequest);
class SearchResponse {
took: 0
timedOut: false
aggregations: {group_property={buckets=[{key=1000, doc_count=11}]}, group_brand_id={buckets=[{key=10, doc_count=1019}, {key=9, doc_count=954}, {key=8, doc_count=1021}]}}
hits: class SearchResponseHits {
maxScore: null
total: 10000
hits: [{_id=1, _score=1, _source={price=197, brand_id=10, brand_name=Brand Ten, categories=[10], title=Product Eight One, property=Six}}, {_id=2, _score=1, _source={price=671, brand_id=6, brand_name=Brand Six, categories=[12, 13, 14], title=Product Nine Seven, property=Four}}, {_id=3, _score=1, _source={price=92, brand_id=3, brand_name=Brand Three, categories=[13, 14, 15], title=Product Five Four, property=Six}}, {_id=4, _score=1, _source={price=713, brand_id=10, brand_name=Brand Ten, categories=[11], title=Product Eight Nine, property=Five}}, {_id=5, _score=1, _source={price=805, brand_id=7, brand_name=Brand Seven, categories=[11, 12, 13], title=Product Ten Three, property=Two}}]
}
profile: null
}
let query = SearchQuery::new();
let aggTerms1 = AggTerms {
field: "price".to_string(),
size: Some(1),
};
let agg1 = Aggregation {
terms: Some(Box::new(aggTerms1)),
..Default::default(),
};
let aggTerms1 = AggTerms {
field: "brand_id".to_string(),
size: Some(3),
};
let agg2 = Aggregation {
terms: Some(Box::new(aggTerms2)),
..Default::default(),
};
let mut aggs = HashMap::new();
aggs.insert("group_property".to_string(), agg1);
aggs.insert("group_brand_id".to_string(), agg2);
let search_req = SearchRequest {
table: "facetdemo".to_string(),
query: Some(Box::new(query)),
aggs: serde_json::json!(aggs),
limit: serde_json::json!(5),
..Default::default(),
};
let search_res = search_api.search(search_req).await;
class SearchResponse {
took: 0
timedOut: false
aggregations: {group_property={buckets=[{key=1000, doc_count=11}]}, group_brand_id={buckets=[{key=10, doc_count=1019}, {key=9, doc_count=954}, {key=8, doc_count=1021}]}}
hits: class SearchResponseHits {
maxScore: null
total: 10000
hits: [{_id=1, _score=1, _source={price=197, brand_id=10, brand_name=Brand Ten, categories=[10], title=Product Eight One, property=Six}}, {_id=2, _score=1, _source={price=671, brand_id=6, brand_name=Brand Six, categories=[12, 13, 14], title=Product Nine Seven, property=Four}}, {_id=3, _score=1, _source={price=92, brand_id=3, brand_name=Brand Three, categories=[13, 14, 15], title=Product Five Four, property=Six}}, {_id=4, _score=1, _source={price=713, brand_id=10, brand_name=Brand Ten, categories=[11], title=Product Eight Nine, property=Five}}, {_id=5, _score=1, _source={price=805, brand_id=7, brand_name=Brand Seven, categories=[11, 12, 13], title=Product Ten Three, property=Two}}]
}
profile: null
}
res = await searchApi.search({
index: 'test',
query: { match_all:{} },
aggs: {
name_group: {
terms: { field : 'name', size: 1 }
},
cat_group: {
terms: { field: 'cat' }
}
}
});
{
"took": 0,
"timed_out": false,
"hits": {
"total": 5,
"hits": [
{
"_id": 1,
"_score": 1,
"_source": {
"content": "Text 1",
"name": "Doc 1",
"cat": 1
}
},
...
{
"_id": 5,
"_score": 1,
"_source": {
"content": "Text 5",
"name": "Doc 5",
"cat": 4
}
}
]
},
"aggregations": {
"name_group": {
"buckets": [
{
"key": "Doc 1",
"doc_count": 1
}
]
},
"cat_group": {
"buckets": [
{
"key": 1,
"doc_count": 2
},
...
{
"key": 4,
"doc_count": 1
}
]
}
}
}
query := map[string]interface{} {}
searchRequest.SetQuery(query)
aggByName := manticoreclient.NewAggregation()
aggTerms := manticoreclient.NewAggregationTerms()
aggTerms.SetField("name")
aggByName.SetTerms(aggTerms)
aggByName.SetSize(1)
aggByCat := manticoreclient.NewAggregation()
aggTerms.SetField("cat")
aggByCat.SetTerms(aggTerms)
aggs := map[string]Aggregation{} { "name_group": aggByName, "cat_group": aggByCat }
searchRequest.SetAggs(aggs)
res, _, _ := apiClient.SearchAPI.Search(context.Background()).SearchRequest(*searchRequest).Execute()
{
"took": 0,
"timed_out": false,
"hits": {
"total": 5,
"hits": [
{
"_id": 1,
"_score": 1,
"_source": {
"content": "Text 1",
"name": "Doc 1",
"cat": 1
}
},
...
{
"_id": 5,
"_score": 1,
"_source": {
"content": "Text 5",
"name": "Doc 5",
"cat": 4
}
}
]
},
"aggregations": {
"name_group": {
"buckets": [
{
"key": "Doc 1",
"doc_count": 1
}
]
},
"cat_group": {
"buckets": [
{
"key": 1,
"doc_count": 2
},
...
{
"key": 4,
"doc_count": 1
}
]
}
}
}
当使用SQL时，带有 facets 的搜索会返回多个结果集。MySQL客户端/库/连接器所使用的 必须 支持多个结果集，以便访问 facets 结果集。
<!-- example Performance -->内部，FACET 是执行多查询的一个快捷方式，其中第一个查询包含主要搜索查询，批次中的其余查询各自包含聚类。正如多查询的情况一样，对于带有 facets 的搜索，常见的查询优化可以启动，这意味着搜索查询只执行一次，而 facets 则在搜索查询结果上操作，每个 facet 只增加总查询时间的一小部分。
要检查 facets 搜索是否以优化模式运行，可以在 查询日志 中查找，其中所有记录的查询将包含一个 xN 字符串，N 是优化组中运行的查询数量。或者，可以检查 SHOW META 语句的输出，该语句将显示一个 multiplier 指标：
SELECT * FROM facetdemo FACET brand_id FACET price FACET categories;
SHOW META LIKE 'multiplier';
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
| id | price | brand_id | title | brand_name | property | j | categories |
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
| 1 | 306 | 1 | Product Ten Three | Brand One | Six_Ten | {"prop1":66,"prop2":91,"prop3":"One"} | 10,11 |
...
+----------+----------+
| brand_id | count(*) |
+----------+----------+
| 1 | 1013 |
...
+-------+----------+
| price | count(*) |
+-------+----------+
| 306 | 7 |
...
+------------+----------+
| categories | count(*) |
+------------+----------+
| 10 | 2436 |
...
+---------------+-------+
| Variable_name | Value |
+---------------+-------+
| multiplier | 4 |
+---------------+-------+
1 row in set (0.00 sec)
POST /sql?mode=raw -d "SELECT brand_name FROM facetdemo FACET brand_id FACET price FACET categories; SHOW META LIKE 'multiplier'"
[
{
"columns": [
{
"brand_name": {
"type": "string"
}
}
],
"data": [
{
"brand_name": "Brand One"
},
...
],
"total": 20,
"error": "",
"warning": ""
},
{
"columns": [
{
"brand_id": {
"type": "long"
}
},
{
"count(*)": {
"type": "long long"
}
}
],
"data": [
{
"brand_id": 1,
"count(*)": 1013
},
...
],
"total": 20,
"error": "",
"warning": ""
},
{
"columns": [
{
"price": {
"type": "long"
}
},
{
"count(*)": {
"type": "long long"
}
}
],
"data": [
{
"price": 306,
"count(*)": 7
},
...
],
"total": 20,
"error": "",
"warning": ""
},
{
"columns": [
{
"categories": {
"type": "string"
}
},
{
"count(*)": {
"type": "long long"
}
}
],
"data": [
{
"categories": "10,11",
"count(*)": 2436
},
...
],
"total": 15,
"error": "",
"warning": ""
},
{
"columns": [
{
"Variable_name": {
"type": "string"
}
},
{
"Value": {
"type": "string"
}
}
],
"data": [
{
"Variable_name": "multiplier",
"Value": "4"
}
],
"total": 1,
"error": "",
"warning": ""
}
]