Sum Bucket Aggregation · Elasticsearch 5.4 中文文檔

# Sum Bucket Aggregation 原文鏈接 : [https://www.elastic.co/guide/en/elasticsearch/reference/5.4/search-aggregations-pipeline-sum-bucket-aggregation.html](https://www.elastic.co/guide/en/elasticsearch/reference/5.4/search-aggregations-pipeline-sum-bucket-aggregation.html) 譯文鏈接 : [Sum Bucket Aggregation](/display/Elasticsearch/Sum+Bucket+Aggregation) 貢獻者 : @蘇濤，[ApacheCN](/display/~apachecn)，[Apache中文網](/display/~apachechina) 警告此功能是實驗性的，可能會在將來的版本中完全更改或刪除。Elastic將采取最大的努力來解決此問題，但實驗功能不受SLA官方功能的支持。總和桶聚合用于計算一組聚合創建的所有桶中指定度量的和。指定的度量必須是數字型而且這個組聚合必須是多桶聚合。 ### 語法 sum_bucket聚合結構如下： ``` { "sum_bucket": { "buckets_path": "the_sum" } } ``` `max_bucket`?參數如下： | 參數名稱 | 描述 | 是否必填 | 默認值 | | --- | --- | --- | --- | | buckets_path | 想要計算總和的桶路徑，點擊?[the section called “`buckets_path`?Syntax](https://www.elastic.co/guide/en/elasticsearch/reference/5.4/search-aggregations-pipeline.html#buckets-path-syntax "buckets_path Syntaxedit")[edit](https://github.com/elastic/elasticsearch/edit/5.4/docs/reference/aggregations/pipeline.asciidoc "Edit this page on GitHub")”查看更多細節 | 必填 | ? | | gap_policy | 當數據缺口出現時采用的策略，點擊[the section called “Dealing with gaps in the data](https://www.elastic.co/guide/en/elasticsearch/reference/5.4/search-aggregations-pipeline.html#gap-policy "Dealing with gaps in the dataedit")[edit](https://github.com/elastic/elasticsearch/edit/5.4/docs/reference/aggregations/pipeline.asciidoc "Edit this page on GitHub")”查看更多細節 | 可選 | skip | | format | 用于規范聚合輸出值的格式 | 可選 | null | 以下代碼段計算所有月銷售總額的總和： ``` POST /sales/_search { "size": 0, "aggs" : { "sales_per_month" : { "date_histogram" : { "field" : "date", "interval" : "month" }, "aggs": { "sales": { "sum": { "field": "price" } } } }, "sum_monthly_sales": { "sum_bucket": { "buckets_path": "sales_per_month>sales" #1 } } } } ``` | 1 | buckets_path指示這個sum_bucket聚合是要得到sales_per_month日期直方圖中的sales聚合sum的總和 | 可能得到如下的響應： ``` { "took": 11, "timed_out": false, "_shards": ..., "hits": ..., "aggregations": { "sales_per_month": { "buckets": [ { "key_as_string": "2015/01/01 00:00:00", "key": 1420070400000, "doc_count": 3, "sales": { "value": 550.0 } }, { "key_as_string": "2015/02/01 00:00:00", "key": 1422748800000, "doc_count": 2, "sales": { "value": 60.0 } }, { "key_as_string": "2015/03/01 00:00:00", "key": 1425168000000, "doc_count": 2, "sales": { "value": 375.0 } } ] }, "sum_monthly_sales": { "value": 985.0 } } } ```