2015-05-21 05:39:38 -04:00
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[[search-aggregations-pipeline-sum-bucket-aggregation]]
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2015-05-06 09:20:25 -04:00
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=== Sum Bucket Aggregation
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2015-08-14 04:51:09 -04:00
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coming[2.0.0-beta1]
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2015-06-30 05:30:33 -04:00
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experimental[]
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2015-05-21 05:39:38 -04:00
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A sibling pipeline aggregation which calculates the sum across all bucket of a specified metric in a sibling aggregation.
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The specified metric must be numeric and the sibling aggregation must be a multi-bucket aggregation.
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==== Syntax
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A `sum_bucket` aggregation looks like this in isolation:
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[source,js]
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--------------------------------------------------
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{
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"sum_bucket": {
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"buckets_path": "the_sum"
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}
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}
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--------------------------------------------------
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.`sum_bucket` Parameters
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|===
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|Parameter Name |Description |Required |Default Value
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|`buckets_path` |The path to the buckets we wish to find the sum for (see <<buckets-path-syntax>> for more
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details) |Required |
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|`gap_policy` |The policy to apply when gaps are found in the data (see <<gap-policy>> for more
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details)|Optional, defaults to `skip` ||
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|`format` |format to apply to the output value of this aggregation |Optional, defaults to `null` |
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|===
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The following snippet calculates the sum of all the total monthly `sales` buckets:
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[source,js]
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--------------------------------------------------
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{
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"aggs" : {
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"sales_per_month" : {
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"date_histogram" : {
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"field" : "date",
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"interval" : "month"
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},
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"aggs": {
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"sales": {
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"sum": {
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"field": "price"
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}
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}
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}
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},
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"sum_monthly_sales": {
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"sum_bucket": {
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"buckets_path": "sales_per_month>sales" <1>
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}
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}
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}
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}
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--------------------------------------------------
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<1> `buckets_path` instructs this sum_bucket aggregation that we want the sum of the `sales` aggregation in the
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`sales_per_month` date histogram.
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And the following may be the response:
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[source,js]
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--------------------------------------------------
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{
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"aggregations": {
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"sales_per_month": {
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"buckets": [
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{
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"key_as_string": "2015/01/01 00:00:00",
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"key": 1420070400000,
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"doc_count": 3,
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"sales": {
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"value": 550
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}
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},
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{
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"key_as_string": "2015/02/01 00:00:00",
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"key": 1422748800000,
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"doc_count": 2,
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"sales": {
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"value": 60
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}
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},
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{
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"key_as_string": "2015/03/01 00:00:00",
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"key": 1425168000000,
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"doc_count": 2,
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"sales": {
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"value": 375
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}
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}
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]
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},
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"sum_monthly_sales": {
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"value": 985
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}
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}
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}
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--------------------------------------------------
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