# Use nested doc\_count in terms aggregation

**URL:** <https://discuss.elastic.co/t/use-nested-doc-count-in-terms-aggregation/79863>\
**Category:** Elasticsearch\
**Created:** [March 24, 2017, 8:23am UTC](https://discuss.elastic.co/t/use-nested-doc-count-in-terms-aggregation/79863 "2017-03-24T08:23:00Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![tomr](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/tomr/32/48260_2.png) [@tomr](https://discuss.elastic.co/u/tomr)\
**Post date:** [March 24, 2017, 8:23am UTC](https://discuss.elastic.co/t/use-nested-doc-count-in-terms-aggregation/79863/1 "2017-03-24T08:23:00Z")

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I have documents of the form

```
{
  "item": "name",
  "@timestamp": <date>,
  "category": [
    { "key": "something", "doc_count": num },
    { "key": "otherthing", "doc_count": num },
    { "key": "thirdthing", "doc_count": num }
  ]
}

```

Mapping has [category][key] as `keyword` and [category][doc\_count] as `long`.

There are a few thousand documents for each value of [item], with a lot of repetition of the values for `key` but variation in the value for `doc_count`. The data is derived from 5-minutely snapshots of high traffic web logs. I'm trying to run something like a `terms` agg, but I want to add up all the values of `doc_count` rather than just counting the instances of `key` itself. Ultimately I want to show the top N values based on those totals. (I realise the counts will be approximate a la sharding approximations - that's fine)

It's unclear to me whether I should be trying a `nested` agg combo of some sort, or perhaps a `terms` agg with a `sum` subagg. A little clue as to how I should get started would be very much appreciated.

tia,  
Tom

---

<div class="post-metadata">

**Author:** ![tomr](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/tomr/32/48260_2.png) [@tomr](https://discuss.elastic.co/u/tomr)\
**Post date:** [March 27, 2017, 7:11am UTC](https://discuss.elastic.co/t/use-nested-doc-count-in-terms-aggregation/79863/2 "2017-03-27T07:11:30Z")

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I thnk I've figured this out, thanks to reading this a few times: [http://stackoverflow.com/questions/30583679/elasticsearch-terms-and-sum-aggregation](http://stackoverflow.com/questions/30583679/elasticsearch-terms-and-sum-aggregation)

In short, it's a nested agg with `path` set to `category`, with a `terms` agg on `category.key` under that, and a `sum` agg on `category.doc_count` under the `terms` agg.

I'm not yet sure whether I'm actually getting an accurate figure - in other words, whether all sums are calculated and then I get the top 10 results, or whether only the top 10 most popular terms have their sums calculated. Given the enormous response time I'm seeing, I guess it's the former. Next I'll look into whether I can do a `top_hits` agg instead of either the `terms` or `sum` agg to improve performance.

For the time being, my query looks like

```
{
  "aggs": {
    "nested_categories": {
      "nested": {
        "path": "category"
      },
      "aggs": {
        "category_terms": { 
          "terms": {
            "field": "category.key"
          },
          "aggs": {
            "category_sums": {
              "sum": { 
                "field": "category.doc_count"  
              }
            }
          }
        }
      }
    }
  }

```

The output produced looks like:

```
{
  "took": 22000,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "failed": 0
  },
  "hits": {
    "total": 152872,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "nested_categories": {
      "doc_count": 679153,
      "category_terms": {
        "doc_count_error_upper_bound": 0,
        "sum_other_doc_count": 174340,
        "buckets": [
          {
            "key": "key1",
            "doc_count": 124980,
            "client_url_sums": {
              "value": 10920199
            }
          },
          {
            "key": "key2",
            "doc_count": 124149,
            "category_sums": {
              "value": 10714383
            }
          },
          {
            "key": "key3",
            "doc_count": 93561,
            "category_sums": {
              "value": 16788697
            }
          }
        ]
      }
    }
  }
}
```

---

<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [April 24, 2017, 7:11am UTC](https://discuss.elastic.co/t/use-nested-doc-count-in-terms-aggregation/79863/3 "2017-04-24T07:11:43Z")

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