Elasticsearch 5.4.3 聚合分组

Posted 2020-10-07 wangchuanfu

第一个分析需求：计算每个tag下的商品数量

GET /ecommerce/product/_search
{
  "aggs": {
    "group_by_tags": {
      "terms": { "field": "tags" }
    }
  }
}

将文本field的fielddata属性设置为true

PUT /ecommerce/_mapping/product
{
  "properties": {
    "tags": {
      "type": "text",
      "fielddata": true
    }
  }
}

GET /ecommerce/product/_search
{
  "size": 0,
  "aggs": {
    "all_tags": {
      "terms": { "field": "tags" }
    }
  }
}

{
  "took": 20,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 4,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "group_by_tags": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": "fangzhu",
          "doc_count": 2
        },
        {
          "key": "meibai",
          "doc_count": 2
        },
        {
          "key": "qingxin",
          "doc_count": 1
        }
      ]
    }
  }
}

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第二个聚合分析的需求：对名称中包含yagao的商品，计算每个tag下的商品数量

GET /ecommerce/product/_search
{
  "size": 0,
  "query": {
    "match": {
      "name": "yagao"
    }
  },
  "aggs": {
    "all_tags": {
      "terms": {
        "field": "tags"
      }
    }
  }
}

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第三个聚合分析的需求：先分组，再算每组的平均值，计算每个tag下的商品的平均价格

GET /ecommerce/product/_search
{
    "size": 0,
    "aggs" : {
        "group_by_tags" : {
            "terms" : { "field" : "tags" },
            "aggs" : {
                "avg_price" : {
                    "avg" : { "field" : "price" }
                }
            }
        }
    }
}

{
  "took": 8,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 4,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "group_by_tags": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": "fangzhu",
          "doc_count": 2,
          "avg_price": {
            "value": 27.5
          }
        },
        {
          "key": "meibai",
          "doc_count": 2,
          "avg_price": {
            "value": 40
          }
        },
        {
          "key": "qingxin",
          "doc_count": 1,
          "avg_price": {
            "value": 40
          }
        }
      ]
    }
  }
}

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第四个数据分析需求：计算每个tag下的商品的平均价格，并且按照平均价格降序排序

GET /ecommerce/product/_search
{
    "size": 0,
    "aggs" : {
        "all_tags" : {
            "terms" : { "field" : "tags", "order": { "avg_price": "desc" } },
            "aggs" : {
                "avg_price" : {
                    "avg" : { "field" : "price" }
                }
            }
        }
    }
}

我们现在全部都是用es的restful api在学习和讲解es的所欲知识点和功能点，但是没有使用一些编程语言去讲解（比如java），原因有以下：

1、es最重要的api，让我们进行各种尝试、学习甚至在某些环境下进行使用的api，就是restful api。如果你学习不用es restful api，比如我上来就用java api来讲es，也是可以的，但是你根本就漏掉了es知识的一大块，你都不知道它最重要的restful api是怎么用的
2、讲知识点，用es restful api，更加方便，快捷，不用每次都写大量的java代码，能加快讲课的效率和速度，更加易于同学们关注es本身的知识和功能的学习
3、我们通常会讲完es知识点后，开始详细讲解java api，如何用java api执行各种操作
4、我们每个篇章都会搭配一个项目实战，项目实战是完全基于java去开发的真实项目和系统

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第五个数据分析需求：按照指定的价格范围区间进行分组，然后在每组内再按照tag进行分组，最后再计算每组的平均价格

GET /ecommerce/product/_search
{
  "size": 0,
  "aggs": {
    "group_by_price": {
      "range": {
        "field": "price",
        "ranges": [
          {
            "from": 0,
            "to": 20
          },
          {
            "from": 20,
            "to": 40
          },
          {
            "from": 40,
            "to": 50
          }
        ]
      },
      "aggs": {
        "group_by_tags": {
          "terms": {
            "field": "tags"
          },
          "aggs": {
            "average_price": {
              "avg": {
                "field": "price"
              }
            }
          }
        }
      }
    }
  }
}