Elasticsearch sorting based on multiple aggeration - sorting

Question

I try to get my data with different aggeration criterias afterwards I want to order it based on one of aggeration criteria. In this specific case I want to get my data to be ordered descendly based on "Monthly_Income/ SUM" criteria.
I searched and tried lots of thing but none of them worked for me. Could you give me the answer because I am new on elasticsearch.
what I searched so far and couldn't solve the problem ;
"ordering_by_a_sub_aggregation,
Sorting Based on "Deep" Metrics,
search-aggregations-bucket-terms-aggregation-script,
search-aggregations-bucket-multi-terms-aggregation
To visualize the problem. I always get the belowing result however I tried lots of methods but I couldn't achieve to get desired result.
undesired result
desired result
Request
`
{
"query": {
"bool": {
"must": [],
"must_not": []
}
},
"size": 0,
"aggs": {
"GENDER": {
"terms": {
"field": "GENDER.keyword",
"size": 10000000,
"missing": "N/A"
// ,"order": {"MARTIAL_STATUS>Monthly_Income_0.max" : "desc" }
},
"aggs": {
"MARTIAL_STATUS": {
"terms": {
"field": "MARTIAL_STATUS.keyword",
"size": 10000000,
"missing": "N/A"
// ,"order": {"Monthly_Income_0.value" : "desc" }
},
"aggs": {
"Monthly_Income_0": {
"sum": {
"field": "Monthly_Income"
}
},
"Monthly_Income_1": {
"value_count": {
"field": "Monthly_Income"
}
},
"SALE_PRICE_2": {
"sum": {
"field": "SALE_PRICE"
}
}
// ,"sort_by_percentage": {
// "bucket_sort": {
// "sort": [ { "Monthly_Income_0.value": { "order": "desc" } } ]
// }
// }
}
}
}
}
}
}
`
Response
`
{
"took": 0,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 10000,
"relation": "gte"
},
"max_score": null,
"hits": []
},
"aggregations": {
"GENDER": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "Male",
"doc_count": 40959,
"MARTIAL_STATUS": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "Married",
"doc_count": 35559,
"SALE_PRICE_2": {
"value": 2.530239767013672E9
},
"Monthly_Income_0": {
"value": 3.59618565E8
},
"Monthly_Income_1": {
"value": 35559
}
},
{
"key": "Single",
"doc_count": 5399,
"SALE_PRICE_2": {
"value": 3.7742297754296875E8
},
"Monthly_Income_0": {
"value": 5.3465554E7
},
"Monthly_Income_1": {
"value": 5399
}
},
{
"key": "N/A",
"doc_count": 1,
"SALE_PRICE_2": {
"value": 87344.203125
},
"Monthly_Income_0": {
"value": 40000.0
},
"Monthly_Income_1": {
"value": 1
}
}
]
}
},
{
"key": "Female",
"doc_count": 7777,
"MARTIAL_STATUS": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "Married",
"doc_count": 5299,
"SALE_PRICE_2": {
"value": 3.9976638293359375E8
},
"Monthly_Income_0": {
"value": 4.4994796E7
},
"Monthly_Income_1": {
"value": 5299
}
},
{
"key": "Single",
"doc_count": 2477,
"SALE_PRICE_2": {
"value": 1.8698677312695312E8
},
"Monthly_Income_0": {
"value": 1.8793502E7
},
"Monthly_Income_1": {
"value": 2477
}
},
{
"key": "N/A",
"doc_count": 1,
"SALE_PRICE_2": {
"value": 101006.8203125
},
"Monthly_Income_0": {
"value": 10000.0
},
"Monthly_Income_1": {
"value": 1
}
}
]
}
}
]
}
}
}
`
I try to order based on an aggerate column but I couldn't able to achieve

Answer 1

My understanding of your issue is that you want to group by on combination of gender and marital status
I have used runtime mapping to concatenate fields "gender" and marital status and used term aggregation to group by on run time field and sorted groups based on sum.
{
"size": 0,
"runtime_mappings": {
"gender-maritalstatus": {
"type": "keyword",
"script": {
"source": """
def gender='NA';
def maritalstatus='NA';
if(doc['Gender.keyword'].size()!=0)
gender= doc['Gender.keyword'].value;
if(doc['Marital_Status.keyword'].size()!=0)
maritalstatus= doc['Marital_Status.keyword'].value;
emit(gender+'-'+maritalstatus);
"""
}
}
},
"aggs": {
"gender-marital-grouping": {
"terms": {
"field": "gender-maritalstatus",
"order": {
"monthly_income": "desc"
},
"size": 10
},
"aggs": {
"monthly_income": {
"sum": {
"field": "Monthly_Income"
}
}
}
}
}
}
Result
"buckets" : [
{
"key" : "Female-Single",
"doc_count" : 2,
"monthly_income" : {
"value" : 300.0
}
},
{
"key" : "Male-Married",
"doc_count" : 2,
"monthly_income" : {
"value" : 200.0
}
},
{
"key" : "Female-NA",
"doc_count" : 1,
"monthly_income" : {
"value" : 100.0
}
},
{
"key" : "Male-NA",
"doc_count" : 1,
"monthly_income" : {
"value" : 100.0
}
},
{
"key" : "Male-Single",
"doc_count" : 1,
"monthly_income" : {
"value" : 100.0
}
}
]