减去弹性搜索索引中的两个字段

Question

I am trying to do some analysis over the fields indexed in elastic search.

2 of the fields are 'start_time' and 'end_time'. I would basically want to group the difference of these 2 fields ie ('end_time' - 'start_time') for my analysis. But, I'm not able to find a direct answer to this question.

Request you to help in this.

** Edit **

Based on the answer by PPearcy below, I have explored terms aggregations and I have applied it on the index. However, I have not yet applied script in the query as I'm still exploring terms aggregation. But, I am facing another problem here:-

My index contains 3,513,903 documents with a size of 2.1 GB. Here is my query:-

$ curl -X GET http://localhost:9200/rum_beacon/rum/_search -d '{"aggs":{"resp":{"terms":{"field":"response_start"}}}}' 2>/dev/null| python -c "import sys, json, pprint; j=json.load(sys.stdin); buckets=j['aggregations']['resp']['buckets'];m=map(lambda x: x,buckets); pprint.pprint( m)"

[{u'doc_count': 124219, u'key': 0, u'key_as_string': u'0'},
 {u'doc_count': 73779, u'key': 1, u'key_as_string': u'1'},
 {u'doc_count': 27135, u'key': 2, u'key_as_string': u'2'},
 {u'doc_count': 10569, u'key': 3, u'key_as_string': u'3'},
 {u'doc_count': 6065, u'key': 4, u'key_as_string': u'4'},
 {u'doc_count': 4498, u'key': 157, u'key_as_string': u'157'},
 {u'doc_count': 4473, u'key': 144, u'key_as_string': u'144'},
 {u'doc_count': 4461, u'key': 162, u'key_as_string': u'162'},
 {u'doc_count': 4443, u'key': 164, u'key_as_string': u'164'},
 {u'doc_count': 4434, u'key': 155, u'key_as_string': u'155'}]

**The problem:**

I'm not able to get the results for all the response_start fields. I get only 10 values in the response json.

**What I've tried**

I tried giving the size field in the json request, but, I still get only 10 values in the response:-

$ curl -X GET http://localhost:9200/rum_beacon/rum/_search -d '{"size":50,"aggs":{"resp":{"terms":{"field":"response_start"}}}}' 2>/dev/null| python -c "import sys, json, pprint; j=json.load(sys.stdin); buckets=j['aggregations']['resp']['buckets'];m=map(lambda x: x,buckets); pprint.pprint( m)"


[{u'doc_count': 124219, u'key': 0, u'key_as_string': u'0'},
 {u'doc_count': 73779, u'key': 1, u'key_as_string': u'1'},
 {u'doc_count': 27135, u'key': 2, u'key_as_string': u'2'},
 {u'doc_count': 10569, u'key': 3, u'key_as_string': u'3'},
 {u'doc_count': 6065, u'key': 4, u'key_as_string': u'4'},
 {u'doc_count': 4498, u'key': 157, u'key_as_string': u'157'},
 {u'doc_count': 4473, u'key': 144, u'key_as_string': u'144'},
 {u'doc_count': 4461, u'key': 162, u'key_as_string': u'162'},
 {u'doc_count': 4443, u'key': 164, u'key_as_string': u'164'},
 {u'doc_count': 4434, u'key': 155, u'key_as_string': u'155'}]

Answer 1

Take a look at aggregates on script fields: http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/search-aggregations.html

For your case, you would be doing a terms aggregate on a script field as specified here: http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/search-aggregations-bucket-terms-aggregation.html