elasticsearch中一个键中所有嵌套对象的弹性堆栈聚合

ztigrdn8  于 2021-06-10  发布在  ElasticSearch
关注(0)|答案(1)|浏览(309)

我在“提交”索引中有一个文件，看起来像这样，

  1. {
  2.   "took" : 18,
  3.   "timed_out" : false,
  4.   "_shards" : {
  5.     "total" : 5,
  6.     "successful" : 5,
  7.     "skipped" : 0,
  8.     "failed" : 0
  9.   },
  10.   "hits" : {
  11.     "total" : 1,
  12.     "max_score" : 1.0,
  13.     "hits" : [
  14.       {
  15.         "_index" : "submissions",
  16.         "_type" : "_doc",
  17.         "_id" : "90_169",
  18.         "_score" : 1.0,
  19.         "_source" : {
  20.           "id" : "90_169",
  21.           "locked" : false,
  22.           "account_id" : 5,
  23.           "campaign_id" : 90,
  24.           "contact_id" : 1179,
  25.           "submission_id" : 169,
  26.           "answers" : [
  27.             {
  28.               "question_id" : 8451,
  29.               "answer_bool" : true
  30.             },
  31.             {
  32.               "question_id" : 8452,
  33.               "answer_bool" : false
  34.             },
  35.             {
  36.               "question_id" : 8453,
  37.               "answer_bool" : true
  38.             },
  39.             {
  40.               "question_id" : 8454,
  41.               "answer_bool" : false
  42.             }
  43.           ]
  44.         }
  45.       }
  46.     ]
  47.   }
  48. }

这只是一份文件。
我想对所有问题进行聚合，得到一个最终的bucket聚合，其中显示每个问题id的true和false的数量。
关于如何做到这一点有什么见解吗？

elasticsearchelastic-stack

1条答案

按热度按时间
f0ofjuux

f0ofjuux1#

您需要使用嵌套聚合以及术语和筛选器聚合
添加索引Map、数据、搜索查询和搜索结果的工作示例
索引Map：

  1. {
  2.   "mappings": {
  3.     "properties": {
  4.       "answers": {
  5.         "type": "nested"
  6.       }
  7.     }
  8.   }
  9. }

索引数据：

  1. {
  2.   "id": "90_169",
  3.   "locked": false,
  4.   "account_id": 5,
  5.   "campaign_id": 90,
  6.   "contact_id": 1179,
  7.   "submission_id": 169,
  8.   "answers": [
  9.     {
  10.       "question_id": 8451,
  11.       "answer_bool": true
  12.     },
  13.     {
  14.       "question_id": 8452,
  15.       "answer_bool": false
  16.     },
  17.     {
  18.       "question_id": 8453,
  19.       "answer_bool": true
  20.     },
  21.     {
  22.       "question_id": 8454,
  23.       "answer_bool": false
  24.     }
  25.   ]
  26. }
  27. {
  28.   "id": "90_169",
  29.   "locked": false,
  30.   "account_id": 5,
  31.   "campaign_id": 90,
  32.   "contact_id": 1179,
  33.   "submission_id": 169,
  34.   "answers": [
  35.     {
  36.       "question_id": 8451,
  37.       "answer_bool": true
  38.     },
  39.     {
  40.       "question_id": 8452,
  41.       "answer_bool": false
  42.     },
  43.     {
  44.       "question_id": 8453,
  45.       "answer_bool": true
  46.     },
  47.     {
  48.       "question_id": 8454,
  49.       "answer_bool": true
  50.     }
  51.   ]
  52. }
  53. {
  54.   "id": "90_169",
  55.   "locked": false,
  56.   "account_id": 5,
  57.   "campaign_id": 90,
  58.   "contact_id": 1179,
  59.   "submission_id": 169,
  60.   "answers": [
  61.     {
  62.       "question_id": 8451,
  63.       "answer_bool": true
  64.     },
  65.     {
  66.       "question_id": 8452,
  67.       "answer_bool": false
  68.     },
  69.     {
  70.       "question_id": 8453,
  71.       "answer_bool": true
  72.     },
  73.     {
  74.       "question_id": 8454,
  75.       "answer_bool": true
  76.     }
  77.   ]
  78. }

搜索查询：

  1. {
  2.   "size": 0,
  3.   "aggs": {
  4.     "nested_Agg": {
  5.       "nested": {
  6.         "path": "answers"
  7.       },
  8.       "aggs": {
  9.         "id": {
  10.           "terms": {
  11.             "field": "answers.question_id"
  12.           },
  13.           "aggs": {
  14.             "true_count": {
  15.               "filter": {
  16.                 "term": {
  17.                   "answers.answer_bool": "true"
  18.                 }
  19.               }
  20.             },
  21.             "false_count": {
  22.               "filter": {
  23.                 "term": {
  24.                   "answers.answer_bool": "false"
  25.                 }
  26.               }
  27.             }
  28.           }
  29.         }
  30.       }
  31.     }
  32.   }
  33. }

搜索结果：

  1. "aggregations": {
  2.     "nested_Agg": {
  3.       "doc_count": 12,
  4.       "id": {
  5.         "doc_count_error_upper_bound": 0,
  6.         "sum_other_doc_count": 0,
  7.         "buckets": [
  8.           {
  9.             "key": 8451,
  10.             "doc_count": 3,
  11.             "false_count": {
  12.               "doc_count": 0
  13.             },
  14.             "true_count": {
  15.               "doc_count": 3
  16.             }
  17.           },
  18.           {
  19.             "key": 8452,
  20.             "doc_count": 3,
  21.             "false_count": {
  22.               "doc_count": 3
  23.             },
  24.             "true_count": {
  25.               "doc_count": 0
  26.             }
  27.           },
  28.           {
  29.             "key": 8453,
  30.             "doc_count": 3,
  31.             "false_count": {
  32.               "doc_count": 0
  33.             },
  34.             "true_count": {
  35.               "doc_count": 3
  36.             }
  37.           },
  38.           {
  39.             "key": 8454,
  40.             "doc_count": 3,
  41.             "false_count": {
  42.               "doc_count": 1
  43.             },
  44.             "true_count": {
  45.               "doc_count": 2
  46.             }
  47.           }
  48.         ]
  49.       }
  50.     }
  51.   }
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