Cumulative sum aggregation

Cumulative sum aggregation

A parent pipeline aggregation which calculates the cumulative sum of a specified metric in a parent histogram (or date_histogram) aggregation. The specified metric must be numeric and the enclosing histogram must have min_doc_count set to 0 (default for histogram aggregations).

Syntax

A cumulative_sum aggregation looks like this in isolation:

  1. {
  2.   "cumulative_sum": {
  3.     "buckets_path": "the_sum"
  4.   }
  5. }

Table 60. cumulative_sum Parameters

Parameter NameDescriptionRequiredDefault Value

buckets_path

The path to the buckets we wish to find the cumulative sum for (see buckets_path Syntax for more details)

Required

format

DecimalFormat pattern for the output value. If specified, the formatted value is returned in the aggregation’s value_as_string property

Optional

null

The following snippet calculates the cumulative sum of the total monthly sales:

  1. resp = client.search(
  2.     index="sales",
  3.     size=0,
  4.     aggs={
  5.         "sales_per_month": {
  6.             "date_histogram": {
  7.                 "field": "date",
  8.                 "calendar_interval": "month"
  9.             },
  10.             "aggs": {
  11.                 "sales": {
  12.                     "sum": {
  13.                         "field": "price"
  14.                     }
  15.                 },
  16.                 "cumulative_sales": {
  17.                     "cumulative_sum": {
  18.                         "buckets_path": "sales"
  19.                     }
  20.                 }
  21.             }
  22.         }
  23.     },
  24. )
  25. print(resp)
  1. response = client.search(
  2.   index: 'sales',
  3.   body: {
  4.     size: 0,
  5.     aggregations: {
  6.       sales_per_month: {
  7.         date_histogram: {
  8.           field: 'date',
  9.           calendar_interval: 'month'
  10.         },
  11.         aggregations: {
  12.           sales: {
  13.             sum: {
  14.               field: 'price'
  15.             }
  16.           },
  17.           cumulative_sales: {
  18.             cumulative_sum: {
  19.               buckets_path: 'sales'
  20.             }
  21.           }
  22.         }
  23.       }
  24.     }
  25.   }
  26. )
  27. puts response
  1. const response = await client.search({
  2.   index: "sales",
  3.   size: 0,
  4.   aggs: {
  5.     sales_per_month: {
  6.       date_histogram: {
  7.         field: "date",
  8.         calendar_interval: "month",
  9.       },
  10.       aggs: {
  11.         sales: {
  12.           sum: {
  13.             field: "price",
  14.           },
  15.         },
  16.         cumulative_sales: {
  17.           cumulative_sum: {
  18.             buckets_path: "sales",
  19.           },
  20.         },
  21.       },
  22.     },
  23.   },
  24. });
  25. console.log(response);
  1. POST /sales/_search
  2. {
  3.   "size": 0,
  4.   "aggs": {
  5.     "sales_per_month": {
  6.       "date_histogram": {
  7.         "field": "date",
  8.         "calendar_interval": "month"
  9.       },
  10.       "aggs": {
  11.         "sales": {
  12.           "sum": {
  13.             "field": "price"
  14.           }
  15.         },
  16.         "cumulative_sales": {
  17.           "cumulative_sum": {
  18.             "buckets_path": "sales" 
  19.           }
  20.         }
  21.       }
  22.     }
  23.   }
  24. }

buckets_path instructs this cumulative sum aggregation to use the output of the sales aggregation for the cumulative sum

And the following may be the response:

  1. {
  2.    "took": 11,
  3.    "timed_out": false,
  4.    "_shards": ...,
  5.    "hits": ...,
  6.    "aggregations": {
  7.       "sales_per_month": {
  8.          "buckets": [
  9.             {
  10.                "key_as_string": "2015/01/01 00:00:00",
  11.                "key": 1420070400000,
  12.                "doc_count": 3,
  13.                "sales": {
  14.                   "value": 550.0
  15.                },
  16.                "cumulative_sales": {
  17.                   "value": 550.0
  18.                }
  19.             },
  20.             {
  21.                "key_as_string": "2015/02/01 00:00:00",
  22.                "key": 1422748800000,
  23.                "doc_count": 2,
  24.                "sales": {
  25.                   "value": 60.0
  26.                },
  27.                "cumulative_sales": {
  28.                   "value": 610.0
  29.                }
  30.             },
  31.             {
  32.                "key_as_string": "2015/03/01 00:00:00",
  33.                "key": 1425168000000,
  34.                "doc_count": 2,
  35.                "sales": {
  36.                   "value": 375.0
  37.                },
  38.                "cumulative_sales": {
  39.                   "value": 985.0
  40.                }
  41.             }
  42.          ]
  43.       }
  44.    }
  45. }