减去具有不同时间戳的两个文档之间的数字字段

假设我有这些数据样本：

{
    "date": "2019-06-16",
    "rank": 150
    "name": "doc 1"
}

{
    "date": "2019-07-16",
    "rank": 100
    "name": "doc 1"
}

{
    "date": "2019-06-16",
    "rank": 50
    "name": "doc 2"
}

{
    "date": "2019-07-16",
    "rank": 80
    "name": "doc 2"
}

预期结果是从具有不同日期（旧日期 - 新日期）的两个相同名称的文档中减去排名字段：

{
    "name": "doc 1",
    "diff_rank": 50
}

{
    "name": "doc 2",
    "diff_rank": -30
}

并按diff_rank如果可能的话，否则我会在得到结果后手动排序。

我尝试过的是使用date_histogram and serial_diff但有些结果缺少diff_rank我确信数据存在的某种价值：

{
   "aggs" : {
        "group_by_name": {
            "terms": {
                "field": "name"
            },
            "aggs": {
                "days": {
                    "date_histogram": {
                        "field": "date",
                        "interval": "day"
                     },
                    "aggs": {
                        "the_rank": {
                            "sum": {
                                "field": "rank"
                            }
                        },
                        "diff_rank": {
                           "serial_diff": {
                              "buckets_path": "the_rank",
                              "lag" : 30 // 1 month or 30 days in this case
                           }
                        }
                    }
                }
            }
        }
    }
}

非常感谢您帮助解决我的上述问题！

最后，我从官方文档中找到了一个方法，使用Filter https://www.elastic.co/guide/en/elasticsearch/reference/6.5/search-aggregations-bucket-filter-aggregation.html, 桶脚本 https://www.elastic.co/guide/en/elasticsearch/reference/6.5/search-aggregations-pipeline-bucket-script-aggregation.html聚合和桶排序 https://www.elastic.co/guide/en/elasticsearch/reference/6.5/search-aggregations-pipeline-bucket-sort-aggregation.html对结果进行排序。这是最终的代码片段：

{
    "size": 0,
    "aggs" : {
        "group_by_name": {
            "terms": {
                "field": "name",
                "size": 50,
                "shard_size": 10000
            },
            "aggs": {
                "last_month_rank": {
                    "filter": {
                        "term": {"date": "2019-06-17"}
                     },
                    "aggs": {
                        "rank": {
                            "sum": {
                                "field": "rank"
                            }
                        }
                    }
                },
                "latest_rank": {
                    "filter": {
                        "term": {"date": "2019-07-17"}
                     },
                    "aggs": {
                        "rank": {
                            "sum": {
                                "field": "rank"
                            }
                        }
                    }
                },
                "diff_rank": {
                    "bucket_script": {
                        "buckets_path": {
                          "lastMonthRank": "last_month_rank>rank",
                          "latestRank": "latest_rank>rank"
                        },
                        "script": "params.lastMonthRank - params.latestRank"
                    }
                },
                "rank_bucket_sort": {
                    "bucket_sort": {
                        "sort": [
                            {"diff_rank": {"order": "desc"}}
                        ],
                        "size": 50
                    }
                }
            }
        }
    }
}