我有一个弹性搜索查询，它返回一堆如下所示的对象：
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 1,
"hits": [
{
"_index": "searchdb",
"_type": "profile",
"_id": "1825",
"_score": 1,
"_source": {
"id": 1825,
"market": "Chicago",
"geo_location": {
"lat": 41.1234,
"lon": -87.5678
},
"hourly_values": [
{
"datetime": "1997-07-16T19:00:00.00+00:00",
"seconds": 1200
},
{
"datetime": "1997-07-16T19:20:00.00+00:00",
"seconds": 1200
},
{
"datetime": "1997-07-16T19:20:00.00+00:00",
"seconds": 1200
}
]
}
},
{
"_index": "searchdb",
"_type": "profile",
"_id": "1808",
"_score": 1,
"_source": {
"id": 1808,
"market": "Chicago",
"geo_location": {
"lat": 41.1234,
"lon": -87.5678
},
"hourly_values": [
{
"datetime": "1997-07-16T19:00:00.00+00:00",
"seconds": 900
},
{
"datetime": "1997-07-16T19:20:00.00+00:00",
"seconds": 1200
},
{
"datetime": "1997-07-16T19:20:00.00+00:00",
"seconds": 800
}
]
}
}
]
}
我想返回相同的结果，但是返回的每个对象的秒字段的聚合。
我的查询现在看起来像这样：
{
"query": {
"filtered":{
"filter":{
"geo_distance":{
"distance":"1km",
"geo_location":{
"lat":"41.1234",
"lon":"-87.5678"
}
}
}
}
},
"aggregations": {
"seconds_sum": {
"sum": {
"field": "hourly_values.seconds"
}
}
}
}
上面只是汇总了所有对象的所有秒数。我无法弄清楚如何只聚合每个对象的秒数，并将该聚合返回给对象，所以我最终会得到这样的结果：
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 1,
"hits": [
{
"_index": "searchdb",
"_type": "profile",
"_id": "1825",
"_score": 1,
"_source": {
"id": 1825,
"market": "Chicago",
"geo_location": {
"lat": 41.1234,
"lon": -87.5678
},
"seconds":3600
}
},
{
"_index": "searchdb",
"_type": "profile",
"_id": "1808",
"_score": 1,
"_source": {
"id": 1808,
"market": "Chicago",
"geo_location": {
"lat": 41.1234,
"lon": -87.5678
},
"seconds":2900
}
}
]
}
或类似的......
答案 0 :(得分：2)
这很容易。首先，您需要将hourly_values存储为nested objects。
您必须使用terms按唯一值进行汇总，在这种情况下，它可能是id，只有这样您才需要sum。总结一下：
PUT /test
{
"mappings": {
"data": {
"properties": {
"id": {
"type": "integer"
},
"geo_location": {
"type": "geo_point"
},
"hourly_values": {
"type": "nested",
"properties": {
"datetime": {
"type": "date"
},
"seconds": {
"type": "integer"
}
}
}
}
}
}
}
PUT /test/data/1
{
"id": 1825,
"market": "Chicago",
"geo_location": {
"lat": 41.1234,
"lon": -87.5678
},
"hourly_values": [
{
"datetime": "1997-07-16T19:00:00.00+00:00",
"seconds": 1200
},
{
"datetime": "1997-07-16T19:20:00.00+00:00",
"seconds": 1200
},
{
"datetime": "1997-07-16T19:20:00.00+00:00",
"seconds": 1200
}
]
}
PUT /test/data/2
{
"id": 1808,
"market": "Chicago",
"geo_location": {
"lat": 41.1234,
"lon": -87.5678
},
"hourly_values": [
{
"datetime": "1997-07-16T19:00:00.00+00:00",
"seconds": 900
},
{
"datetime": "1997-07-16T19:20:00.00+00:00",
"seconds": 1200
},
{
"datetime": "1997-07-16T19:20:00.00+00:00",
"seconds": 800
}
]
}
POST /test/_search
{
"size": 0,
"aggs": {
"Ids": {
"terms": {
"field": "id",
"size": 0
},
"aggs": {
"Nesting": {
"nested": {
"path": "hourly_values"
},
"aggs": {
"SumSeconds": {
"sum": {
"field": "hourly_values.seconds"
}
}
}
}
}
}
}
}
{
"took": 7,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 0,
"hits": []
},
"aggregations": {
"Ids": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": 1808,
"doc_count": 1,
"Nesting": {
"doc_count": 3,
"SumSeconds": {
"value": 2900
}
}
},
{
"key": 1825,
"doc_count": 1,
"Nesting": {
"doc_count": 3,
"SumSeconds": {
"value": 3600
}
}
}
]
}
}
}
如果您还想在它们旁边返回文档，可以将Top Hit聚合与嵌套Sum一起使用：
POST /test/_search
{
"size": 0,
"aggs": {
"Ids": {
"terms": {
"field": "id",
"size": 0
},
"aggs": {
"Objects": {
"top_hits": {
"_source": ["id", "market", "geo_location"],
"size": 1
}
},
"Nesting": {
"nested": {
"path": "hourly_values"
},
"aggs": {
"SumSeconds": {
"sum": {
"field": "hourly_values.seconds"
}
}
}
}
}
}
}
}
这会带回来：
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 0,
"hits": []
},
"aggregations": {
"Ids": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": 1808,
"doc_count": 1,
"Nesting": {
"doc_count": 3,
"SumSeconds": {
"value": 2900
}
},
"Objects": {
"hits": {
"total": 1,
"max_score": 1,
"hits": [
{
"_index": "test",
"_type": "data",
"_id": "2",
"_score": 1,
"_source": {
"market": "Chicago",
"geo_location": {
"lon": -87.5678,
"lat": 41.1234
},
"id": 1808
}
}
]
}
}
},
{
"key": 1825,
"doc_count": 1,
"Nesting": {
"doc_count": 3,
"SumSeconds": {
"value": 3600
}
},
"Objects": {
"hits": {
"total": 1,
"max_score": 1,
"hits": [
{
"_index": "test",
"_type": "data",
"_id": "1",
"_score": 1,
"_source": {
"market": "Chicago",
"geo_location": {
"lon": -87.5678,
"lat": 41.1234
},
"id": 1825
}
}
]
}
}
}
]
}
}
}