manual/russian/Searching/Faceted_search.md
Фасетный поиск так же важен для современного поискового приложения, как автодополнение, исправление орфографии и подсветка ключевых слов поиска, особенно в электронной коммерции.
Фасетный поиск полезен при работе с большими объемами данных и различными взаимосвязанными свойствами, такими как размер, цвет, производитель или другие факторы. При запросе огромных объемов данных результаты поиска часто включают множество записей, не соответствующих ожиданиям пользователя. Фасетный поиск позволяет конечному пользователю явно определить критерии, которым должны соответствовать его результаты поиска.
В Manticore Search есть оптимизация, которая сохраняет набор результатов исходного запроса и повторно использует его для каждого расчета фасета. Поскольку агрегации применяются к уже вычисленному подмножеству документов, они выполняются быстро, и общее время выполнения часто может быть лишь немного больше, чем у первоначального запроса. Фасеты могут быть добавлены к любому запросу, и фасетом может быть любой атрибут или выражение. Результат фасета включает значения фасета и количество фасетов. Доступ к фасетам можно получить с помощью оператора SQL SELECT, объявив их в самом конце запроса.
Значения фасета могут происходить из атрибута, свойства JSON внутри атрибута JSON или выражения. Значения фасета также могут иметь псевдонимы, но псевдоним должен быть уникальным во всех наборах результатов (основной набор результатов запроса и другие наборы результатов фасетов). Значение фасета получается из агрегированного атрибута/выражения, но также может происходить из другого атрибута/выражения.
FACET {expr_list} [BY {expr_list} ] [DISTINCT {field_name}] [ORDER BY {expr | FACET()} {ASC | DESC}] [LIMIT [offset,] count]
Несколько объявлений фасетов должны быть разделены пробелом.
Фасеты могут быть определены в узле aggs:
"aggs" :
{
"group name" :
{
"terms" :
{
"field":"attribute name",
"size": 1000
}
"sort": [ {"attribute name": { "order":"asc" }} ]
}
}
где:
group name - это псевдоним, присвоенный агрегацииfield должен содержать имя атрибута или выражения, по которому выполняется фасетированиеsize указывает максимальное количество групп для включения в результат. Если не указан, наследует лимит основного запроса. Подробнее можно узнать в разделе Размер результата фасета.sort указывает массив атрибутов и/или дополнительных свойств, используя тот же синтаксис, что и параметр "sort" в основном запросе.Набор результатов будет содержать узел aggregations с возвращенными фасетами, где key - это агрегированное значение, а doc_count - количество агрегаций.
"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
}
]
}
}
}
Данные могут быть фасетированы путем агрегации другого атрибута или выражения. Например, если документы содержат как идентификатор бренда, так и его название, мы можем вернуть в фасете названия брендов, но агрегировать идентификаторы брендов. Это можно сделать с помощью FACET {expr1} BY {expr2}
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
},
]
}
}
}
Если вам нужно удалить дубликаты из групп, возвращаемых FACET, вы можете использовать DISTINCT field_name, где field_name - это поле, по которому вы хотите выполнить дедупликацию. Это также может быть id (который используется по умолчанию), если вы выполняете запрос FACET к распределенной таблице и не уверены, есть ли у вас уникальные идентификаторы в таблицах (таблицы должны быть локальными и иметь одинаковую схему).
Если у вас несколько объявлений FACET в запросе, field_name должен быть одинаковым во всех них.
DISTINCT возвращает дополнительный столбец count(distinct ...) перед столбцом count(*), позволяя получить оба результата без необходимости делать другой запрос.
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
}
]
}
}
}
Фасеты могут агрегировать по выражениям. Классический пример - сегментация цен по определенным диапазонам:
<!-- 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
}
]
}
}
}
Фасеты могут агрегировать по многоуровневой группировке, при этом результирующий набор будет таким же, как если бы запрос выполнял многоуровневую группировку:
<!-- 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": ""
}
]
Фасеты могут агрегировать по гистограммным значениям, создавая фиксированные интервалы (бакеты) для значений. Ключевая функция:
key_of_the_bucket = interval + offset * floor ( ( value - offset ) / interval )
Аргумент гистограммы interval должен быть положительным, а аргумент гистограммы offset должен быть положительным и меньше interval. По умолчанию бакеты возвращаются в виде массива. Аргумент гистограммы keyed преобразует ответ в словарь с ключами бакетов.
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
}
}
}
}
}
Фасеты могут агрегировать по гистограммным значениям дат, что аналогично обычной гистограмме. Разница в том, что интервал задаётся с помощью выражения даты или времени. Такие выражения требуют специальной поддержки, потому что интервалы не всегда имеют фиксированную длину. Значения округляются до ближайшего бакета с использованием следующей ключевой функции:
key_of_the_bucket = interval * floor ( value / interval )
Параметр гистограммы calendar_interval учитывает, что месяцы имеют разное количество дней.
В отличие от calendar_interval, параметр fixed_interval использует фиксированное количество единиц и не отклоняется, независимо от того, на какую дату календаря он приходится. Однако fixed_interval не может обрабатывать единицы, такие как месяцы, потому что месяц — это не фиксированная величина. Попытка указать единицы, такие как недели или месяцы, для fixed_interval приведёт к ошибке.
Допустимые интервалы описаны в выражении date_histogram. По умолчанию бакеты возвращаются в виде массива. Аргумент гистограммы keyed преобразует ответ в словарь с ключами бакетов.
В JSON-запросах date_histogram также поддерживает time_zone и offset с calendar_interval:
time_zone изменяет часовой пояс, используемый для округления календарных сегментов и форматирования key_as_string. Это должно быть имя часового пояса IANA, поддерживаемое сервером, например Asia/Novosibirsk. Числовые смещения UTC, такие как +03:00, не поддерживаются.offset сдвигает границы календарных сегментов на фиксированную величину перед округлением. Это может быть строка фиксированного интервала, использующая те же единицы, что и fixed_interval, например 3h, или целое число секунд, например 10800. Значение может иметь префикс + или -.time_zone и offset не поддерживаются с 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
}
}
}
}
}
Фасеты могут агрегировать по набору диапазонов. Значения проверяются на соответствие диапазону бакета, где каждый бакет включает значение from и исключает значение to из диапазона.
Установка свойства keyed в true преобразует ответ в словарь с ключами бакетов, а не в массив.
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
}
}
}
}
}
Фасеты могут агрегировать по набору диапазонов дат, что аналогично обычному диапазону. Разница в том, что значения from и to могут быть выражены с помощью выражений Date math. Эта агрегация включает значение from и исключает значение to для каждого диапазона. Установка свойства keyed в true преобразует ответ в словарь с ключами бакетов, а не в массив.
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
}
}
}
}
}
Фасеты поддерживают предложение ORDER BY, как и стандартный запрос. Каждый фасет может иметь свою собственную сортировку, и сортировка фасета не влияет на порядок основного результирующего набора, который определяется предложением ORDER BY основного запроса. Сортировка может выполняться по имени атрибута, количеству (с использованием COUNT(*), COUNT(DISTINCT attribute_name)) или специальной функции FACET(), которая предоставляет агрегированные значения данных. По умолчанию запрос с ORDER BY COUNT(*) будет сортировать по убыванию.
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
}
]
}
}
}
По умолчанию каждый результирующий набор фасета ограничен 20 значениями. Количество значений фасета можно контролировать с помощью предложения LIMIT индивидуально для каждого фасета, указав либо количество возвращаемых значений в формате LIMIT count, либо со смещением как LIMIT offset, count.
Максимальное количество возвращаемых значений фасета ограничено настройкой max_matches запроса. Если вы хотите реализовать динамический max_matches (ограничивая max_matches до offset + per page для лучшей производительности), следует учитывать, что слишком низкое значение max_matches может повлиять на количество значений фасета. В этом случае следует использовать минимальное значение max_matches, достаточное для покрытия количества значений фасета.
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
}
]
}
}
}
При использовании SQL поиск с фасетами возвращает несколько наборов результатов. Используемый клиент/библиотека/коннектор MySQL обязательно должен поддерживать множественные наборы результатов для доступа к наборам результатов фасетов.
<!-- example Performance -->Внутренне FACET является сокращением для выполнения мультизапроса, где первый запрос содержит основной поисковый запрос, а остальные запросы в пакете содержат каждый свою кластеризацию. Как и в случае с мультизапросом, для фасетного поиска может сработать общая оптимизация запросов, что означает, что поисковый запрос выполняется только один раз, а фасеты работают с результатом поискового запроса, причем каждый фасет добавляет лишь небольшую долю времени к общему времени выполнения запроса.
Чтобы проверить, работал ли фасетный поиск в оптимизированном режиме, вы можете посмотреть в журнал запросов, где все залогированные запросы будут содержать строку xN, где N — количество запросов, выполненных в оптимизированной группе. Альтернативно, вы можете проверить вывод оператора SHOW META, который отобразит метрику multiplier:
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)
"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": ""
}
]
],
"total": 1,
"error": "",
"warning": ""
}
]