elasticsearch嵌套文档查询

Question

我是elasticsearch的新手，对如何进行过滤器、查询和聚合有一些想法，但不确定如何解决下面的问题。我希望能够从下面显示的文档中只查询公司的最新交付（日期和crate_quantity）。我不确定如何去做。有没有办法使用最大聚合从每个文档中只提取最近的交付？

POST /sanfrancisco/devlivery
{
"company1": {
    "delivery": [
        {
            "date": "01/01/2013",
            "crate_quantity": 5
        },
        {
            "date": "01/12/2013",
            "crate_quantity": 3
        },
        {
            "date": "01/24/2013",
            "crate_quantity": 2
        }
    ]
}
}

POST /sanfrancisco/devlivery
{
"company2": {
    "delivery": [
        {
            "date": "01/01/2015",
            "crate_quantity": 14
        },
        {
            "date": "12/31/2014",
            "crate_quantity": 20
        },
        {
            "date": "11/24/2014",
            "crate_quantity": 13
        }
    ]
}
}

Answer 1

如果您希望一次为一家公司提供最新的交付，我可能会使用父/子关系进行设置。我用公司作为父母，孩子作为孩子。

我还添加了自定义日期格式，以便您的日期将按照您期望的方式排序。

我这样设置索引：

DELETE /test_index

PUT /test_index
{
   "settings": {
      "number_of_shards": 1,
      "number_of_replicas": 0
   },
   "mappings": {
      "company": {
         "properties": {
            "name": {
               "type": "string",
               "index": "not_analyzed"
            }
         }
      },
      "delivery": {
         "_parent": {
            "type": "company"
         },
         "properties": {
            "crate_quantity": {
               "type": "long"
            },
            "date": {
               "type": "date",
               "format": "MM/dd/yyyy"
            }
         }
      }
   }
}

然后使用批量api为文档编制索引：

PUT /test_index/_bulk
{"index": {"_index":"test_index", "_type":"company", "_id":1}}
{"name":"company1"}
{"index": {"_index":"test_index", "_type":"delivery", "_id":1, "_parent":1}}
{"date": "01/01/2013", "crate_quantity": 5}
{"index": {"_index":"test_index", "_type":"delivery", "_id":2, "_parent":1}}
{"date": "01/12/2013", "crate_quantity": 3}
{"index": {"_index":"test_index", "_type":"delivery", "_id":3, "_parent":1}}
{"date": "01/24/2013",  "crate_quantity": 2}
{"index": {"_index":"test_index", "_type":"company", "_id":2}}
{"name":"company2"}
{"index": {"_index":"test_index", "_type":"delivery", "_id":4, "_parent":2}}
{"date": "01/01/2015", "crate_quantity": 14}
{"index": {"_index":"test_index", "_type":"delivery", "_id":5, "_parent":2}}
{"date": "12/31/2014",  "crate_quantity": 20}
{"index": {"_index":"test_index", "_type":"delivery", "_id":6, "_parent":2}}
{"date": "11/24/2014",  "crate_quantity": 13 }

POST /test_index/delivery/_search
{
   "size": 1,
   "sort": [
      {
         "date": {
            "order": "desc"
         }
      }
   ],
   "filter": {
      "has_parent": {
         "type": "company",
         "query": {
            "term": {
               "name": {
                  "value": "company1"
               }
            }
         }
      }
   }
}
...
{
   "took": 2,
   "timed_out": false,
   "_shards": {
      "total": 1,
      "successful": 1,
      "failed": 0
   },
   "hits": {
      "total": 3,
      "max_score": null,
      "hits": [
         {
            "_index": "test_index",
            "_type": "delivery",
            "_id": "3",
            "_score": null,
            "_source": {
               "date": "01/24/2013",
               "crate_quantity": 2
            },
            "sort": [
               1358985600000
            ]
         }
      ]
   }
}

这是我在试验时使用的代码：

http://sense.qbox.io/gist/c519b0654448c8b7b0c7c85d613f1e88c0ad1d19