# 根据员工信息和研发中心互相搜索父子数据
我们已经建立了父子关系的数据模型之后，就要基于这个模型进行各种搜索和聚合了
搜索有 1980 年以后出生的员工的研发中心
GET /company/rd_center/_search
{
"query": {
"has_child": {
"type": "employee",
"query": {
"range": {
"birthday": {
"gte": "1980-01-01"
}
}
}
}
}
}
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 1,
"hits": [
{
"_index": "company",
"_type": "rd_center",
"_id": "1",
"_score": 1,
"_source": {
"name": "北京研发总部",
"city": "北京",
"country": "中国"
}
},
{
"_index": "company",
"_type": "rd_center",
"_id": "3",
"_score": 1,
"_source": {
"name": "硅谷人工智能实验室",
"city": "硅谷",
"country": "美国"
}
}
]
}
}
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搜索有名叫张三的员工的研发中心
GET /company/rd_center/_search
{
"query": {
"has_child": {
"type": "employee",
"query": {
"term": {
"name.keyword": "张三"
}
}
}
}
}
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 1,
"hits": [
{
"_index": "company",
"_type": "rd_center",
"_id": "1",
"_score": 1,
"_source": {
"name": "北京研发总部",
"city": "北京",
"country": "中国"
}
}
]
}
}
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搜索有至少 2 个以上员工的研发中心
GET /company/rd_center/_search
{
"query": {
"has_child": {
"type": "employee",
"min_children": 2,
"query": {
"match_all": {}
}
}
}
}
{
"took": 4,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 1,
"hits": [
{
"_index": "company",
"_type": "rd_center",
"_id": "1",
"_score": 1,
"_source": {
"name": "北京研发总部",
"city": "北京",
"country": "中国"
}
}
]
}
}
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搜索在中国的研发中心的员工
GET /company/employee/_search
{
"query": {
"has_parent": {
"parent_type": "rd_center",
"query": {
"term": {
"country.keyword": "中国"
}
}
}
}
}
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 1,
"hits": [
{
"_index": "company",
"_type": "employee",
"_id": "3",
"_score": 1,
"_routing": "2",
"_parent": "2",
"_source": {
"name": "王二",
"birthday": "1979-04-01",
"hobby": "爬山"
}
},
{
"_index": "company",
"_type": "employee",
"_id": "1",
"_score": 1,
"_routing": "1",
"_parent": "1",
"_source": {
"name": "张三",
"birthday": "1970-10-24",
"hobby": "爬山"
}
},
{
"_index": "company",
"_type": "employee",
"_id": "2",
"_score": 1,
"_routing": "1",
"_parent": "1",
"_source": {
"name": "李四",
"birthday": "1982-05-16",
"hobby": "游泳"
}
}
]
}
}
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# 总结
- 在子中查询父中的字段使用 has_parent
- 在父中查询子中的字段使用 has_child