I have log data in the Elasticsearch index.
`"hits": [
{
"_index": "event_log",
"_type": "log_type",
"_id": "2-d-kmoBazYRVz7KCQIj",
"_score": 1,
"_source": {
"user_id": 123,
"event": "click",
"category": "abc",
"product_id": 1112,
"bkt": "A"
}
},
{
"_index": "event_log",
"_type": "log_type",
"_id": "3ed-kmoBazYRVz7KCQLX",
"_score": 1,
"_source": {
"user_id": 456,
"event": "click",
"category": "abc",
"product_id": 112,
"bkt": "A"
}
},
{
"_index": "event_log",
"_type": "log_type",
"_id": "3ud-kmoBazYRVz7KCgIy",
"_score": 1,
"_source": {
"user_id": 1234,
"event": "click",
"category": "abc",
"product_id": 1112,
"bkt": "B"
}
},
{
"_index": "event_log",
"_type": "log_type",
"_id": "4Od-kmoBazYRVz7KCgLr",
"_score": 1,
"_source": {
"user_id": 4567,
"event": "click",
"category": "xyz",
"product_id": 1118,
"bkt": "B"
}
},
{
"_index": "event_log",
"_type": "log_type",
"_id": "4ud-kmoBazYRVz7KkwL2",
"_score": 1,
"_source": {
"user_id": 123,
"event": "cart",
"category": "xyz",
"product_id": 1,
"bkt": "A"
}
},
{
"_index": "event_log",
"_type": "log_type",
"_id": "2ud-kmoBazYRVz7KCALB",
"_score": 1,
"_source": {
"user_id": 123,
"event": "cart",
"category": "xyz",
"product_id": 11,
"bkt": "A"
}
},
{
"_index": "event_log",
"_type": "log_type",
"_id": "3-d-kmoBazYRVz7KCgKP",
"_score": 1,
"_source": {
"user_id": 4567,
"event": "click",
"category": "abc",
"product_id": 111,
"bkt": "B"
}
},
{
"_index": "event_log",
"_type": "log_type",
"_id": "3Od-kmoBazYRVz7KCQJ8",
"_score": 1,
"_source": {
"user_id": 456,
"event": "click",
"category": "abc",
"product_id": 111,
"bkt": "A"
}
},
{
"_index": "event_log",
"_type": "log_type",
"_id": "4ed-kmoBazYRVz7KCwJH",
"_score": 1,
"_source": {
"user_id": 4567,
"event": "click",
"category": "xyz",
"product_id": 1128,
"bkt": "B"
}
}
]}
I want to get the aggregation by category, bkt, event. As well as I want to aggregate user_id by category, bkt. I have two separate queries for that
Count of record aggregated by category, bkt, event.
GET event_log/_search
{"size" : 0,
"aggs": {
"category_id": {
"terms": { "field": "category.keyword" },
"aggs": {
"ab_bucket": {
"terms": { "field": "bkt.keyword" },
"aggs": {
"event_type": {
"terms": { "field": "event.keyword" }
}
}
}
}
}
}
}
The result is
"aggregations": {
"category_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "abc",
"doc_count": 5,
"ab_bucket": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "A",
"doc_count": 3,
"event_type": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "click",
"doc_count": 3
}
]
}
},
{
"key": "B",
"doc_count": 2,
"event_type": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "click",
"doc_count": 2
}
]
}
}
]
}
},
Users aggregated by category, bkt.
GET event_log/_search
{"size" : 0,
"aggs": {
"category_id": {
"terms": { "field": "category.keyword" },
"aggs": {
"ab_bucket": {
"terms": { "field": "bkt.keyword" },
"aggs": {
"total_uniq_users" : {
"cardinality": {
"field" : "user_id"
}
}
}
}
}
}
}
}
The result is
"aggregations": {
"category_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "abc",
"doc_count": 5,
"ab_bucket": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "A",
"doc_count": 3,
"total_uniq_users": {
"value": 2
}
},
{
"key": "B",
"doc_count": 2,
"total_uniq_users": {
"value": 2
}
}
]
}
},
Is there a way to combine both the queries and obtain the expected result as a single result