Run aggregation on multiple fields in elastic search - elasticsearch

Question

I am working on a used cars marketplace website similar to https://www.kijijiautos.ca.
I want to make an aggregation on my dataset, to get the number of cars with for eg "Ford" and in the same aggregation I want to get the total number of used cars, new cars and other specifications
I tried the following:
GET auto/_search
{
"size": 0,
"aggs": {
"stats": {
"multi_terms": {
"terms": [{"field": "Make"}, {"field": "Type"}]
}
}
}
}
I got the following result
{
"took" : 149,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 10000,
"relation" : "gte"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"stats" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 14378,
"buckets" : [
{
"key" : [
"BMW",
"Used"
],
"key_as_string" : "BMW|Used",
"doc_count" : 2826
},
{
"key" : [
"Volkswagen",
"Used"
],
"key_as_string" : "Volkswagen|Used",
"doc_count" : 2592
},
{
"key" : [
"Audi",
"Used"
],
"key_as_string" : "Audi|Used",
"doc_count" : 2310
},
{
"key" : [
"Opel",
"Used"
],
"key_as_string" : "Opel|Used",
"doc_count" : 1494
},
{
"key" : [
"Ford",
"Used"
],
"key_as_string" : "Ford|Used",
"doc_count" : 1485
},
{
"key" : [
"Renault",
"Used"
],
"key_as_string" : "Renault|Used",
"doc_count" : 1303
},
{
"key" : [
"Peugeot",
"Used"
],
"key_as_string" : "Peugeot|Used",
"doc_count" : 1196
},
{
"key" : [
"Fiat",
"Used"
],
"key_as_string" : "Fiat|Used",
"doc_count" : 1149
},
{
"key" : [
"Skoda",
"Used"
],
"key_as_string" : "Skoda|Used",
"doc_count" : 668
},
{
"key" : [
"SEAT",
"Used"
],
"key_as_string" : "SEAT|Used",
"doc_count" : 629
}
]
}
}
}
but that's not what I am expecting
what I expect is the following :
{
// first bucket
[
{
"doc_count" : 123,
"key" : "BMW"
}
// other makes here
]
// second bucket
[
{
"doc_count" : 2500,
"key" : "Used"
},
{
"doc_count" : 500,
"key" : "New"
}
]
}
If this is possible in elasticsearch then please help me write this query
thank you

Answer 1

I found the solution for my problem, and I would like to leave it here for ref. ( found the solution here )
the idea is to specify multiple aggregations inside the aggs object that's all
GET auto/_search
{
"size": 0,
"aggs": {
// aggregate on types
"types": {
"terms": {
"field": "Type",
"size": 10
}
},
// aggregate on makes
"makes": {
"terms": {
"field": "Make",
"size": 10
}
},
// aggregate on body types
"body type": {
"terms": {
"field": "Body Type",
"size": 10
}
}
}
}
the result was as expected
{
"took" : 10,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 10000,
"relation" : "gte"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"types" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "Used",
"doc_count" : 22414
},
{
"key" : "New",
"doc_count" : 3021
},
{
"key" : "Pre-registered",
"doc_count" : 2071
},
{
"key" : "Demonstration",
"doc_count" : 1427
},
{
"key" : "Employee's car",
"doc_count" : 900
},
{
"key" : "Antique / Classic",
"doc_count" : 195
},
{
"key" : "Automatic",
"doc_count" : 1
},
{
"key" : "Metallic",
"doc_count" : 1
}
]
},
"makes" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 9814,
"buckets" : [
{
"key" : "Volkswagen",
"doc_count" : 3295
},
{
"key" : "BMW",
"doc_count" : 3212
},
{
"key" : "Audi",
"doc_count" : 2768
},
{
"key" : "Ford",
"doc_count" : 2109
},
{
"key" : "Opel",
"doc_count" : 1840
},
{
"key" : "Fiat",
"doc_count" : 1692
},
{
"key" : "Renault",
"doc_count" : 1691
},
{
"key" : "Peugeot",
"doc_count" : 1458
},
{
"key" : "Skoda",
"doc_count" : 1193
},
{
"key" : "SEAT",
"doc_count" : 958
}
]
},
"body type" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "Sedans",
"doc_count" : 8410
},
{
"key" : "Off-Road/Pick-up",
"doc_count" : 6498
},
{
"key" : "Station wagon",
"doc_count" : 4894
},
{
"key" : "Compact",
"doc_count" : 3516
},
{
"key" : "Van",
"doc_count" : 1844
},
{
"key" : "Transporter",
"doc_count" : 1539
},
{
"key" : "Coupe",
"doc_count" : 1144
},
{
"key" : "Convertible",
"doc_count" : 1104
},
{
"key" : "Other",
"doc_count" : 654
}
]
}
}
}