1、家电卖场案例背景
以一个家电卖场中的电视销售数据为背景，来对各种品牌，各种颜色的电视的销量和销售额，进行各种各样角度的分析
创建索引并手动设置映射
PUT /tvs
{
"mappings": {
"sales": {
"properties": {
"price": {
"type": "long"
},
"color": {
"type": "keyword"
},
"brand": {
"type": "keyword"
},
"sold_date": {
"type": "date"
}
}
}
}
}
四个field：价格、颜色、品牌、销售时间。
填充数据
POST /tvs/sales/_bulk
{ "index": {}}
{ "price" : 1000, "color" : "红色", "brand" : "长虹", "sold_date" : "2016-10-28" }
{ "index": {}}
{ "price" : 2000, "color" : "红色", "brand" : "长虹", "sold_date" : "2016-11-05" }
{ "index": {}}
{ "price" : 3000, "color" : "绿色", "brand" : "小米", "sold_date" : "2016-05-18" }
{ "index": {}}
{ "price" : 1500, "color" : "蓝色", "brand" : "TCL", "sold_date" : "2016-07-02" }
{ "index": {}}
{ "price" : 1200, "color" : "绿色", "brand" : "TCL", "sold_date" : "2016-08-19" }
{ "index": {}}
{ "price" : 2000, "color" : "红色", "brand" : "长虹", "sold_date" : "2016-11-05" }
{ "index": {}}
{ "price" : 8000, "color" : "红色", "brand" : "三星", "sold_date" : "2017-01-01" }
{ "index": {}}
{ "price" : 2500, "color" : "蓝色", "brand" : "小米", "sold_date" : "2017-02-12" }
响应结果
{
"took": 61,
"errors": false,
"items": [
{
"index": {
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYE",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"created": true,
"status": 201
}
},
{
"index": {
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYF",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"created": true,
"status": 201
}
},
{
"index": {
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYG",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"created": true,
"status": 201
}
},
{
"index": {
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYH",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"created": true,
"status": 201
}
},
{
"index": {
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYI",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"created": true,
"status": 201
}
},
{
"index": {
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYJ",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"created": true,
"status": 201
}
},
{
"index": {
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYK",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"created": true,
"status": 201
}
},
{
"index": {
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYL",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"created": true,
"status": 201
}
}
]
}
查询
GET tvs/sales/_search
响应结果
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 8,
"max_score": 1,
"hits": [
{
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYI",
"_score": 1,
"_source": {
"price": 1200,
"color": "绿色",
"brand": "TCL",
"sold_date": "2016-08-19"
}
},
{
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYK",
"_score": 1,
"_source": {
"price": 8000,
"color": "红色",
"brand": "三星",
"sold_date": "2017-01-01"
}
},
{
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYE",
"_score": 1,
"_source": {
"price": 1000,
"color": "红色",
"brand": "长虹",
"sold_date": "2016-10-28"
}
},
{
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYF",
"_score": 1,
"_source": {
"price": 2000,
"color": "红色",
"brand": "长虹",
"sold_date": "2016-11-05"
}
},
{
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYG",
"_score": 1,
"_source": {
"price": 3000,
"color": "绿色",
"brand": "小米",
"sold_date": "2016-05-18"
}
},
{
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYJ",
"_score": 1,
"_source": {
"price": 2000,
"color": "红色",
"brand": "长虹",
"sold_date": "2016-11-05"
}
},
{
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYH",
"_score": 1,
"_source": {
"price": 1500,
"color": "蓝色",
"brand": "TCL",
"sold_date": "2016-07-02"
}
},
{
"_index": "tvs",
"_type": "sales",
"_id": "AX1PKYdDl-iNu-QvdWYL",
"_score": 1,
"_source": {
"price": 2500,
"color": "蓝色",
"brand": "小米",
"sold_date": "2017-02-12"
}
}
]
}
}
GET /tvs/sales/_search
{
"aggs": {
"popular_colors": {
"terms": {
"field": "color"
}
}
},
"size": 0
}
size：只获取聚合结果，而不要执行聚合的原始数据 aggs：固定语法，要对一份数据执行分组聚合操作 popular_colors：就是对每个aggs，都要起一个名字，这个名字是随意的，你随便取什么都ok terms：根据字段的值进行分组 field：根据指定的字段的值进行分组
响应结果
{
"took": 16,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 8,
"max_score": 0,
"hits": []
},
"aggregations": {
"popular_colors": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "红色",
"doc_count": 4
},
{
"key": "绿色",
"doc_count": 2
},
{
"key": "蓝色",
"doc_count": 2
}
]
}
}
}
hits.hits：因为我们指定了size是0，所以hits.hits就是空的，否则会把执行聚合的那些原始数据给你返回回来 aggregations：聚合结果 popular_color：我们指定的某个聚合的名称 buckets：根据我们指定的field划分出的buckets key：每个bucket对应的那个值 doc_count：这个bucket分组内，有多少个数据 每种颜色对应的bucket中的数据的数量，其实就是这种颜色的销量， 默认的排序规则：按照doc_count降序排序
