我最近开始学习弹性搜索，并且我的查询的搜索结果有所不同。下面提供了名为“products”的索引的映射（我正在粘贴来自我的 Kibana 控制台工具的响应）：
{
"products" : {
"mappings" : {
"properties" : {
"in_stock" : {
"type" : "long"
},
"name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"price" : {
"type" : "long"
},
"tags" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
}
}
}
索引中的数据如下（我正在粘贴来自我的 Kibana 控制台工具的响应）：
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 16,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "products",
"_type" : "_doc",
"_id" : "202",
"_score" : 1.0,
"_source" : {
"name" : "Vegetable Chopper",
"price" : 10,
"in_stock" : 250,
"tags" : [
"kitchen appliances",
"vegetable slicer",
"chopper"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "203",
"_score" : 1.0,
"_source" : {
"name" : "Dish Washer",
"price" : 90,
"in_stock" : 60,
"tags" : [
"kitchen appliances",
"electrical",
"electric washer"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "205",
"_score" : 1.0,
"_source" : {
"name" : "Microwave Oven",
"price" : 100,
"in_stock" : 50,
"tags" : [
"kitchen appliances",
"electricals",
"oven",
"oven toaster",
"microwave"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "206",
"_score" : 1.0,
"_source" : {
"name" : "Mixer Grinder",
"price" : 55,
"in_stock" : 130,
"tags" : [
"kitchen appliances",
"electricals",
"mixer",
"grinder",
"juicer",
"food processor"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "207",
"_score" : 1.0,
"_source" : {
"name" : "Fruit Juicer",
"price" : 40,
"in_stock" : 100,
"tags" : [
"kitchen appliances",
"electicals",
"juicer",
"mixer",
"electric juicer",
"juice maker"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "208",
"_score" : 1.0,
"_source" : {
"name" : "Knife Set",
"price" : 15,
"in_stock" : 250,
"tags" : [
"kitchen knife",
"steel knives",
"cutlery"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "209",
"_score" : 1.0,
"_source" : {
"name" : "Rice Maker",
"price" : 85,
"in_stock" : 60,
"tags" : [
"kitchen appliances",
"electricals",
"electric rice cooker",
"electric pressure cooker"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "210",
"_score" : 1.0,
"_source" : {
"name" : "Induction Cooktop",
"price" : 30,
"in_stock" : 150,
"tags" : [
"kitchen appliances",
"electricals",
"hot plate heater",
"electric hot place",
"induction cooker",
"induction stove"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "211",
"_score" : 1.0,
"_source" : {
"name" : "Coffee Maker",
"price" : 50,
"in_stock" : 100,
"tags" : [
"kitchen appliances",
"electricals"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "212",
"_score" : 1.0,
"_source" : {
"name" : "Wine Glasses Set",
"price" : 50,
"in_stock" : 70,
"tags" : [
"kitchen and dining",
"glassware",
"stemware"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "213",
"_score" : 1.0,
"_source" : {
"name" : "Dinner Set",
"price" : 100,
"in_stock" : 40,
"tags" : [
"kitchen and dining",
"crockery",
"full dinner set"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "214",
"_score" : 1.0,
"_source" : {
"name" : "Whiskey Glasses Set",
"price" : 60,
"in_stock" : 50,
"tags" : [
"kitchen and dining",
"glassware",
"whiskey glasses",
"old fashioned glass",
"rocks glass",
"short tumbler"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "215",
"_score" : 1.0,
"_source" : {
"name" : "Mug And Saucer Set",
"price" : 35,
"in_stock" : 60,
"tags" : [
"kitchen and dining",
"mug set",
"mugs and saucer",
"crockery set"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "201",
"_score" : 1.0,
"_source" : {
"name" : "Milk Frother",
"price" : 25,
"in_stock" : 15,
"tags" : [
"kitchen appliances",
"electricals",
"milk"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "200",
"_score" : 1.0,
"_source" : {
"name" : "Espresso Maker",
"price" : 180,
"in_stock" : 5,
"tags" : [
"kitchen appliances",
"electrical",
"coffee maker"
]
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "204",
"_score" : 1.0,
"_source" : {
"name" : "Pressure Fryer",
"price" : 120,
"in_stock" : 50,
"tags" : [
"air fryer",
"kitchen appliances",
"electric fryer",
"fryer",
"health fryer"
]
}
}
]
}
}
使用下面的查询查询数据后，我只匹配六条记录：查询 - 1
GET /products/_search
{
"query": {"terms" : {"tags": ["kitchen appliances","electricals"]}}
}
匹配的文档 ID 为 (201,205,206,209,210,211)
当我执行以下查询时，我匹配了 11 条记录：Query-2
GET /products/_search
{
"query": {"terms" : {"tags.keyword": ["kitchen appliances","electricals"]}}
}
与第二个查询匹配的文档 ID 为：(200,201,202,203,204,205,206,207,209,210,211)
有人能解释一下这两个查询有什么区别吗？为什么 Query-1 是 Query-2 的一个子集，即使两个查询都是在同一个字段上执行的？