聚合嵌套 ElasticSearch 中的字典
[英]Aggregating on dictionaries in nest ElasticSearch
問題描述
所以我有一組索引產品，其中包含一個帶有單個鍵的字典和一個值列表，我正在嘗試使用它們構建一個多面搜索。 但是我是一個非常有彈性的新手。
Product Product {
Dictionary<string, List<string>> Properties
//extra fields removed for simplicity
}
屬性可能類似於
["Color":["Blue","Yellow","Red"],"Size":["Small","Medium","Large"]
或者
["Material":["Wood"], "Shape":["Circle","Square"], "Size":["Tiny","Medium","Large","Huge"]
我正在尋找編寫幾個聚合，它們將返回鍵和這些鍵的值。 即如果上面的例子要被索引，第一個聚合將返回一個包含"Color","Size","Material","Shape"的桶
第二個聚合將返回 4 個桶，每個桶都有每個鍵的唯一值。 即Size:["Tiny","small","medium","large","huge"]等
我意識到我需要一個嵌套聚合，但是我的嘗試都沒有帶回存儲桶中的任何東西。 任何指針將不勝感激。 這是我到目前為止所擁有的。
var ProductsQuery = client.Search<Product>(s => s
.Index("products")
.Query(q => q.MatchAll())
.Aggregations(a => a
.Nested("properties", n => n
.Path(p => p.Properties.Suffix("keyword"))
.Aggregations(a => a
.Terms("property-keys", t => t
.Field(f => f.Properties.Keys.Suffix("keyword"))))));
編輯一些要求的細節：
當前的屬性映射（似乎正在為每個鍵創建一個新映射，我不確定這是否是典型的？）我沒有把整個 object 映射放在這里，因為它相當大。 產品有很多領域：
"properties" : {
"properties" : {
"Colour" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Equipment" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Football Age" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Football Size" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Frame Weight" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Garment" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Head Shape" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Level" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Product" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Size" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Sport" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Surface" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Type" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Unit" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Weight" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"comparer" : {
"type" : "object"
},
"count" : {
"type" : "integer"
},
"item" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"keys" : {
"properties" : {
"count" : {
"type" : "integer"
}
}
},
"values" : {
"properties" : {
"count" : {
"type" : "integer"
}
}
}
}
}
和一些索引文件
"hits" : [
{
"_index" : "products-20-01-2021-13-49-08",
"_type" : "_doc",
"_id" : "134550",
"_score" : 1.0,
"_source" : {
"properties" : {
"Type" : [
"Sleds"
],
"Product" : [
"Sleds"
],
"Colour" : [
"Black"
]
}
}
},
{
"_index" : "products-20-01-2021-13-49-08",
"_type" : "_doc",
"_id" : "134566",
"_score" : 1.0,
"_source" : {
"properties" : {
"Sport" : [
"Fitness"
],
"Type" : [
"Corner",
"Edge",
"Middle"
],
"Size" : [
"10mm",
"15mm",
"20mm"
],
"Product" : [
"Floor Matting"
]
}
}
},
{
"_index" : "products-20-01-2021-13-49-08",
"_type" : "_doc",
"_id" : "134576",
"_score" : 1.0,
"_source" : {
"properties" : {
"Sport" : [
"Rugby"
],
"Type" : [
"Skills Training"
],
"Equipment" : [
"Rugby Balls"
],
"Size" : [
"4",
"5"
],
"Level" : [
"Skills"
]
}
}
},
{
"_index" : "products-20-01-2021-13-49-08",
"_type" : "_doc",
"_id" : "134579",
"_score" : 1.0,
"_source" : {
"properties" : {
"Sport" : [
"Rugby"
],
"Type" : [
"Match Union"
],
"Equipment" : [
"Rugby Balls"
],
"Size" : [
"4",
"5"
],
"Level" : [
"Club",
" School"
],
"Unit" : [
"12 Pack",
"Each"
],
"Colour" : [
"Blue",
"Red",
"White"
]
}
}
},
{
"_index" : "products-20-01-2021-13-49-08",
"_type" : "_doc",
"_id" : "134600",
"_score" : 1.0,
"_source" : {
"properties" : {
"Sport" : [
"Rugby"
],
"Size" : [
"Large",
"Medium",
"Small",
"X/Large",
"X/Small",
"XX/Small",
"XXX/Small"
],
"Garment" : [
"Gloves"
],
"Colour" : [
"Red"
]
}
}
},
{
"_index" : "products-20-01-2021-13-49-08",
"_type" : "_doc",
"_id" : "134601",
"_score" : 1.0,
"_source" : {
"properties" : {
"Sport" : [
"Netball"
],
"Size" : [
"Large",
"X/Large",
"X/Small",
"XX/Small",
"XXX/Small"
],
"Garment" : [
"Gloves"
],
"Colour" : [
"Red"
]
}
}
},
{
"_index" : "products-20-01-2021-13-49-08",
"_type" : "_doc",
"_id" : "134609",
"_score" : 1.0,
"_source" : {
"properties" : {
"Sport" : [
"Netball"
],
"Size" : [
"Large",
"Medium",
"Small",
"X/Large",
"X/Small",
"XXX/Small"
],
"Garment" : [
"Gloves"
],
"Colour" : [
"Black",
"Green"
]
}
}
},
{
"_index" : "products-20-01-2021-13-49-08",
"_type" : "_doc",
"_id" : "134617",
"_score" : 1.0,
"_source" : {
"properties" : {
"Sport" : [
"Football"
],
"Type" : [
"Training"
],
"Football Size" : [
"2"
],
"Equipment" : [
"Footballs"
],
"Size" : [
"4",
"5"
],
"Unit" : [
"12 Pack",
"Each"
],
"Weight" : [
"290",
"360"
],
"Surface" : [
"Grass",
" Astroturf"
],
"Football Age" : [
"9-14 years",
" 14+ years"
]
}
}
},
{
"_index" : "products-20-01-2021-13-49-08",
"_type" : "_doc",
"_id" : "134548",
"_score" : 1.0,
"_source" : {
"properties" : {
"Type" : [
"Sleds"
],
"Product" : [
"Sleds"
],
"Colour" : [
"Black",
"Grey"
]
}
}
},
{
"_index" : "products-20-01-2021-13-49-08",
"_type" : "_doc",
"_id" : "134558",
"_score" : 1.0,
"_source" : {
"properties" : {
"Sport" : [
"Squash"
],
"Equipment" : [
"Squash Rackets"
],
"Size" : [
"27\""
],
"Head Shape" : [
"Bridged Closed Throat"
],
"Frame Weight" : [
"Over 160g"
]
}
}
}
]
1 個解決方案
解決方案1
0 已采納 2021-01-20 16:44:20
首先，為了獲得這些存儲桶，您可以使用 Query DSL 說以下內容：
POST products-*/_search
{
"size": 0,
"aggs": {
"by_Colour": {
"terms": {
"field": "properties.Colour.keyword"
}
},
"by_Size": {
"terms": {
"field": "properties.Size.keyword"
}
}
}
}
然后需要將其翻譯成 NEST 代碼——我相信那里有很多例子。
但是您的觀察是正確的——ES 自動創建了許多映射。 我建議不要使用當前的數據格式，而是建議使用 go：
{
"properties": [
{
"key": "Type",
"values": ["Sleds"]
},
{
"key": "Product",
"values": ["Sleds"]
},
{
"key": "Colour",
"values": ["Black"]
}
]
}
並制作nested類型的properties 。
這樣，您將查詢共享路徑properties.key並聚合properties.values.keyword 。
請記住， nested字段類型需要它們自己的實際nested映射——如果沒有正確的映射，您將無法使用嵌套查詢。
NEST ElasticSearch刪除類型
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