What should be the bucket path for nested term aggregation? - elasticsearch

Question

I want to do pipeline aggregation on my elasticsearch aggregation. Here is my query body
{
"aggs": {
"user_info": {
"terms": {
"field": "user_id"
},
"aggs": {
"product_info": {
"terms": {
"field": "product_id"
},
"aggs": {
"total_item_price": {
"sum": {
"field": "selling_price"
}
}
}
}
}
},
"price_percentile": {
"percentiles_bucket": {
"buckets_path": "user_info.product_info.total_item_price"
}
}
}
}
This is giving me error that
No aggregation found for path [user_info.product_info.total_item_price]
What should be the path for bucket if such nested aggregation is there? Or is it not possible to find percentiles for such bucket arrangement in elasticsearch.
P.S I am using elasticsearch 6.5

Answer 1

#jzzfs answer is also somewhat right. I approached it in a different way. I reversed my aggregations and it fulfilled my use case. But in general, you can't do nested bucket percentiles for now.
{
"aggs": {
"product_info": {
"terms": {
"field": "product_id"
},
"aggs": {
"user_info": {
"terms": {
"field": "user_id"
},
"aggs": {
"total_item_price": {
"sum": {
"field": "selling_price"
}
}
}
},
"pb": {
"percentiles_bucket": {
"buckets_path": "user_info>total_item_price"
}
}
}
}
}
}

Answer 2

First, don't use dots in the path -- use > instead:
GET stack/_search
{
"aggs": {
"user_info": {
"terms": {
"field": "user_id"
},
"aggs": {
"product_info": {
"terms": {
"field": "product_id"
},
"aggs": {
"total_item_price": {
"sum": {
"field": "selling_price"
}
}
}
}
}
},
"pb": {
"percentiles_bucket": {
"buckets_path": "user_info>product_info>total_item_price"
}
}
}
}
which yields "buckets_path must reference either a number value or a single value numeric metric aggregation, got: [Object[]] at aggregation [product_info]" so it's not gonna work.
Here are our options:
Aggregate globally but just under the bucketed product info (without the users):
GET stack/_search
{
"aggs": {
"product_info": {
"terms": {
"field": "product_id"
},
"aggs": {
"total_item_price": {
"sum": {
"field": "selling_price"
}
}
}
},
"pb": {
"percentiles_bucket": {
"buckets_path": "product_info>total_item_price"
}
}
}
}
Use filtered aggregations in order to mimic the original intent:
GET stack/_search
{
"aggs": {
"user_123": { <-- keeping the agg name consistent w/ the filter
"filter": {
"term": {
"user_id": 123 <-- actual filter
}
},
"aggs": {
"product_info": {
"terms": {
"field": "product_id"
},
"aggs": {
"total_item_price": {
"sum": {
"field": "selling_price"
}
}
}
},
"pb": {
"percentiles_bucket": {
"buckets_path": "product_info>total_item_price"
}
}
}
}
}
}
You can then have as many user_xyz subaggregations as you like -- provided you gather their IDs beforehand.