summing a bunch of values given a condition in elasticsearch - elasticsearch

Question

Given the following elasticsearch document, how would I construct a search that would sum the values of the seconds column for a given datetime range?
See below for my current query.
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 1,
"hits": [
{
"_index": "searchdb",
"_type": "profile",
"_id": "1825",
"_score": 1,
"_source": {
"id": 1825,
"market": "Chicago",
"geo_location": {
"lat": 41.1234,
"lon": -87.5678
},
"hourly_values": [
{
"datetime": "1997-07-16T19:00:00.00+00:00",
"seconds": 1200
},
{
"datetime": "1997-07-16T19:20:00.00+00:00",
"seconds": 1200
},
{
"datetime": "1997-07-16T19:20:00.00+00:00",
"seconds": 1200
}
]
}
},
{
"_index": "searchdb",
"_type": "profile",
"_id": "1808",
"_score": 1,
"_source": {
"id": 1808,
"market": "Chicago",
"geo_location": {
"lat": 41.1234,
"lon": -87.5678
},
"hourly_values": [
{
"datetime": "1997-07-16T19:00:00.00+00:00",
"seconds": 900
},
{
"datetime": "1997-07-16T19:20:00.00+00:00",
"seconds": 1200
},
{
"datetime": "1997-07-16T19:20:00.00+00:00",
"seconds": 800
}
]
}
}
]
}
Below is my current query. The problem with it is it doesn't take into consideration the datetime field. I need to be able to sum only the seconds values that fall within a given datetime range in the query.
{
"aggs": {
"Ids": {
"terms": {
"field": "id",
"size": 0
},
"aggs": {
"Nesting": {
"nested": {
"path": "hourly_values"
},
"aggs": {
"availability": {
"sum": {
"field": "hourly_values.seconds"
}
}
}
}
}
}
}
}
I know you can use a range, something like this:
"filter" : {
"range" : { "timestamp" : { "from" : "now/1d+9.5h", "to" : "now/1d+16h" }}
}
but I can't figure out how to integrate that into my query to get the desired output.
For clarity, my desired output is to return each of the objects returned from the query, and the values of the summation of the seconds fields, but I only want to sum the values for the given time range.

Answer 1

I think this can be done with filter aggregation
Try this
{
"aggs": {
"Ids": {
"terms": {
"field": "id",
"size": 0
},
"aggs": {
"Nesting": {
"nested": {
"path": "hourly_values"
},
"aggs": {
"filtered_result": {
"filter": {
"query": {
"range": {
"hourly_values.datetime": {
"gt": "1997-07-16T19:10:00.00+00:00",
"lt": "1997-07-16T19:22:00.00+00:00"
}
}
}
},
"aggs": {
"availability": {
"sum": {
"field": "hourly_values.seconds"
}
}
}
}
}
}
}
}
},
"size": 0
}
The result I get
"aggregations": {
"Ids": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "1808",
"doc_count": 1,
"Nesting": {
"doc_count": 3,
"filtered_result": {
"doc_count": 2,
"availability": {
"value": 2000
}
}
}
},
{
"key": "1825",
"doc_count": 1,
"Nesting": {
"doc_count": 3,
"filtered_result": {
"doc_count": 2,
"availability": {
"value": 2400
}
}
}
}
]
}
}
Does this help?