弹性搜索:嵌套属性中的布尔查询 [英] Elastic Search: Bool Query in nested properties
问题描述
假设我的数据结构如下:
Lets assume I have data structured like this:
{ "id": "120400871755634330808993320",
"name": "Metaalschroef binnenzeskant, DIN 912 RVS A4-80",
"description": "m16x70 cilinderschroef bzk a4-80 din912 klasse 80",
"fullDescription": "Metaalschroef met een binnenzeskant cilinderkop",
"synonyms": [],
"properties": [
{
"name": "draad",
"value": "16",
"sort": 99
},
{
"name": "lengte",
"value": "70",
"sort": 99
},
{
"name": "materiaal",
"value": "roestvaststaal",
"sort": 99
},
{
"name": "kwaliteit (materiaal)",
"value": "A4",
"sort": 99
},
{
"name": "DIN",
"value": "912",
"sort": 99
},
{
"name": "AISI",
"value": "316",
"sort": 99
},
{
"name": "draadsoort",
"value": "metrisch",
"sort": 99
},
{
"name": "Merk",
"value": "Elcee Holland",
"sort": 1
}
]
}
如何编写布尔查询，在其中选择所有具有名称为"draad"，值为"16"的属性和名称为"lengte"且值为"70"的文档.
How do I write a boolean query where I select all documents that have a property with name "draad" and value "16" and a property with name "lengte" and value "70".
现在我有了这个，但是它返回0个结果:
Right now I have this but it returns 0 results:
"query" : {
"nested" : {
"path" : "properties",
"query" : {
"bool" : {
"must" : [{
"bool" : {
"must" : [{
"term" : {
"properties.name" : "Merk"
}
}, {
"term" : {
"properties.value" : "Facom"
}
}
]
}
}, {
"bool" : {
"must" : [{
"term" : {
"properties.name" : "materiaal"
}
}, {
"term" : {
"properties.value" : "kunststof"
}
}
]
}
}
]
}
}
}
}
将最高级别的必须"替换为应该"会返回太多结果，这很有意义，因为它可以转换为或".
Replacing the highest level "must" with "should" returns too many results, which makes sense as it translates to an "or".
推荐答案
我找到了运行良好的解决方案！
I found a solution that is working very well!
我的属性对象现在看起来像这样:
My property object now looks like this:
{
"name": "breedte(mm)",
"value": "1000",
"unit": "mm",
"sort": 99,
"nameSlug": "breedte-mm",
"slug": "breedte-mm-1000"
},
我添加了一个slug(包含用于键+值的规范化字符串)和一个nameslug，其是名称的规范化字符串.
I added a slug (containing a normalized string for key + value) and a nameslug which is a normalized string for the name.
我的索引是这样映射的:
My index is mapped like this:
"properties": {
"type": "nested",
"include_in_parent": true,
"properties": {
"name": {
"type": "keyword"
},
"nameSlug": {
"type": "keyword"
},
"slug": {
"type": "keyword"
},
"sort": {
"type": "long"
},
"unit": {
"type": "text",
"index": false
},
"value": {
"type": "keyword"
}
}
}
此处的"include_in_parent"很重要.它允许我执行以下查询:
The "include_in_parent" is important here. It allows me to do the query below:
"query": {
"bool": {
"must": [
{
"terms": {
"properties.slug": [
"merk-orbis",
"merk-bahco"
]
}
},
{
"terms": {
"properties.slug": [
"materiaal-staal",
"materiaal-kunststof"
]
}
}
]
}
},
此查询搜索"merk"为"Orbis"或"Bahco"且"material"为"staal"或"kunststof"的所有文档.
This queries searches for all documents where "merk" is "Orbis" or "Bahco" and where "materiaal" is "staal" or "kunststof".
我的聚合看起来像这样:
My aggregations look like this:
"merk_query": {
"filter": {
"bool": {
"must": [
{
"terms": {
"properties.slug": [
"materiaal-staal",
"materiaal-kunststof"
]
}
}
]
}
},
"aggs": {
"merk_facets": {
"nested": {
"path": "properties"
},
"aggs": {
"merk_only": {
"filter": {
"term": {
"properties.nameSlug": {
"value": "merk"
}
}
},
"aggs": {
"facets": {
"terms": {
"field": "properties.name",
"size": 1
},
"aggs": {
"facetvalues": {
"terms": {
"field": "properties.value",
"size": 10
}
}
}
}
}
}
}
}
}
},
我运行filteraggregate过滤所有与构面匹配的文档(但不是我正在构建的当前文档).
I run filteraggregate which filters all documents that match a facet (but not the current one I am bulding).
此结果的结果是这样的:
The result of this aggragate is something like this:
"merk_query": {
"doc_count": 7686,
"merk_facets": {
"doc_count": 68658,
"merk_only": {
"doc_count": 7659,
"facets": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "Merk",
"doc_count": 7659,
"facetvalues": {
"doc_count_error_upper_bound": 10,
"sum_other_doc_count": 438,
"buckets": [
{
"key": "Orbis",
"doc_count": 6295
},
{
"key": "DX",
"doc_count": 344
},
{
"key": "AXA",
"doc_count": 176
},
{
"key": "Talen Tools",
"doc_count": 127
},
{
"key": "Nemef",
"doc_count": 73
},
{
"key": "bonfix",
"doc_count": 67
},
{
"key": "Bahco",
"doc_count": 64
},
{
"key": "Henderson",
"doc_count": 27
},
{
"key": "Maasland Groep",
"doc_count": 25
},
{
"key": "SYSTEC",
"doc_count": 23
}
]
}
}
]
}
}
}
}
},
这是浏览器的最终结果:
And this is the end result in the browser:
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