group by nested and non nested fields in es - elasticsearch

Question

Hi i am trying to do group by nested and non nested fields.I want to do group by on 1 non nested fields(from_district) ,1 nested field(truck_number) and max on nested field(truck_number.score).
Requirement -: to get max score of each truck in all districts if truck is present in that district for a given sp_id
eg-:
District1 ,truck1, 0.9,
District2 ,truck1, 0.8,
District1 ,truck2, 1.8,
District2 ,truck3, 0.7,
District3 ,truck4, 1.7
Below is my mapping
{
"sp_ranked_indent" : {
"mappings" : {
"properties" : {
"from_district" : {
"type" : "keyword"
},
"sp_id" : {
"type" : "long"
},
"to_district" : {
"type" : "keyword"
},
"truck_ranking_document" : {
"type" : "nested",
"properties" : {
"score" : {
"type" : "float"
},
"truck_number" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
}
}
}
}
}
Below is the query that i tried but it is not grouping by nested and non nested field and also the max truck score is incorrect
{
"size": 0,
"query": {
"terms": {
"sp_id": [650128],
"boost": 1.0
}
},
"aggregations": {
"NESTED_AGG": {
"nested": {
"path": "truck_ranking_document"
},
"aggregations": {
"max_score": {
"max": {
"field": "truck_ranking_document.score"
}
},
"truck_numer": {
"terms": {
"field": "truck_ranking_document.truck_number.keyword",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [{
"_count": "desc"
}, {
"_key": "asc"
}]
}
},
"fromdistrictagg": {
"reverse_nested": {},
"aggregations": {
"fromDistrict": {
"terms": {
"field": "from_district",
"size": 10,
"min_doc_count": 1,
"shard_min_doc_count": 0,
"show_term_doc_count_error": false,
"order": [{
"_count": "desc"
}, {
"_key": "asc"
}]
}
}
}
}
}
}
}
}

Answer 1

I think this can be done using term and nested aggregation. Below query will produce output in follwing format
District1
Truck1
Max score
Truck2
Max score
Truck3
Max score
District2
Truck1
Max score
Truck2
Max score
Truck3
Max score
Query:
{
"query": {
"terms": {
"sp_id": [
1
]
}
},
"aggs": {
"district": {
"terms": {
"field": "from_district",
"size": 10
},
"aggs": {
"trucks": {
"nested": {
"path": "truck_ranking_document"
},
"aggs": {
"truck_no": {
"terms": {
"field": "truck_ranking_document.truck_number.keyword",
"size": 10
},
"aggs": {
"max_score": {
"max": {
"field": "truck_ranking_document.score"
}
},
"select": {
"bucket_selector": {
"buckets_path": {
"score": "max_score"
},
"script": "if(params.score>0) return true;"
}
}
}
}
}
},
"min_bucket_selector": {
"bucket_selector": {
"buckets_path": {
"count": "trucks>truck_no._bucket_count"
},
"script": {
"inline": "params.count != 0"
}
}
}
}
}
}
}
Result:
"aggregations" : {
"district" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "District1",
"doc_count" : 1,
"trucks" : {
"doc_count" : 2,
"truck_no" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "1",
"doc_count" : 1,
"max_score" : {
"value" : 2.0
}
},
{
"key" : "3",
"doc_count" : 1,
"max_score" : {
"value" : 3.0
}
}
]
}
}
}
]
}
Composite Aggregation
Composite aggregation response contains an after_key
"after_key" : {
"district" : "District4"
}
you need to use the after parameter to retrieve the next results
{
"aggs": {
"my_buckets": {
"composite": {
"size": 100,
"sources": [
{
"district": {
"terms": {
"field": "from_district"
}
}
}
]
},
"aggs": {
"trucks": {
"nested": {
"path": "truck_ranking_document"
},
"aggs": {
"truck_no": {
"terms": {
"field": "truck_ranking_document.truck_number.keyword",
"size": 10
},
"aggs": {
"max_score": {
"max": {
"field": "truck_ranking_document.score"
}
},
"select": {
"bucket_selector": {
"buckets_path": {
"score": "max_score"
},
"script": "if(params.score>0) return true;"
}
}
}
}
}
}
}
}
}
}