白话Elasticsearch38-深入聚合数据分析之案例实战 下钻分析之统计每季度每个品牌的销售额
白话Elasticsearch38-深入聚合数据分析之案例实战 下钻分析之统计每季度每个品牌的销售额
小小工匠
发布于 2021-08-17 14:59:31
发布于 2021-08-17 14:59:31
在这里插入图片描述
概述
继续跟中华石杉老师学习ES，第38篇
课程地址： https://www.roncoo.com/view/55
案例
需求： 统计每季度每个品牌的销售额
原始数据：
在这里插入图片描述
Step1. 先按照季度进行bucket分组
首先按照季度 bucket分组 ，使用 date_histogram ， 季度interval->quarter
GET /tvs/sales/_search
{
"size": 0,
"aggs": {
"group_by_sold_date": {
"date_histogram": {
"field": "sold_date",
"interval": "quarter",
"min_doc_count": 0,
"format": "yyyy-MM-dd",
"extended_bounds": {
"min": "2016-04-01",
"max": "2017-03-31"
}
}
}
}
}返回：
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Step2.然后对每个季度bucket中，下钻 ，按照品牌继续分组,对每个品牌求销售额
GET /tvs/sales/_search
{
"size": 0,
"aggs": {
"group_by_sold_date": {
"date_histogram": {
"field": "sold_date",
"interval": "quarter",
"min_doc_count": 0,
"format": "yyyy-MM-dd",
"extended_bounds": {
"min": "2016-04-01",
"max": "2017-03-31"
}
},
"aggs": {
"group_by_brand": {
"terms": {
"field": "brand"
},
"aggs": {
"brand_sum_price": {
"sum": {
"field": "price"
}
}
}
}
}
}
}
}返回：
{
"took": 9,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 8,
"max_score": 0,
"hits": []
},
"aggregations": {
"group_by_sold_date": {
"buckets": [
{
"key_as_string": "2016-04-01",
"key": 1459468800000,
"doc_count": 1,
"group_by_brand": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "小米",
"doc_count": 1,
"brand_sum_price": {
"value": 3000
}
}
]
}
},
{
"key_as_string": "2016-07-01",
"key": 1467331200000,
"doc_count": 2,
"group_by_brand": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "TCL",
"doc_count": 2,
"brand_sum_price": {
"value": 2700
}
}
]
}
},
{
"key_as_string": "2016-10-01",
"key": 1475280000000,
"doc_count": 3,
"group_by_brand": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "长虹",
"doc_count": 3,
"brand_sum_price": {
"value": 5000
}
}
]
}
},
{
"key_as_string": "2017-01-01",
"key": 1483228800000,
"doc_count": 2,
"group_by_brand": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "三星",
"doc_count": 1,
"brand_sum_price": {
"value": 8000
}
},
{
"key": "小米",
"doc_count": 1,
"brand_sum_price": {
"value": 2500
}
}
]
}
}
]
}
}
}找个季度来验证下结果
原始数据：
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计算结果中的一部分：
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Step3. 其实也还可以计算每个季度所有品牌的 总销售额
GET /tvs/sales/_search
{
"size": 0,
"aggs": {
"group_by_sold_date": {
"date_histogram": {
"field": "sold_date",
"interval": "quarter",
"min_doc_count": 0,
"format": "yyyy-MM-dd",
"extended_bounds": {
"min": "2016-04-01",
"max": "2017-03-31"
}
},
"aggs": {
"group_by_brand": {
"terms": {
"field": "brand"
},
"aggs": {
"brand_sum_price": {
"sum": {
"field": "price"
}
}
}
},
"total_sum_price": {
"sum": {
"field": "price"
}
}
}
}
}
}返回：
GET /tvs/sales/_search
{
"size": 0,
"aggs": {
"group_by_sold_date": {
"date_histogram": {
"field": "sold_date",
"interval": "quarter",
"min_doc_count": 0,
"format": "yyyy-MM-dd",
"extended_bounds": {
"min": "2016-04-01",
"max": "2017-03-31"
}
},
"aggs": {
"group_by_brand": {
"terms": {
"field": "brand"
},
"aggs": {
"brand_sum_price": {
"sum": {
"field": "price"
}
}
}
},
"total_sum_price": {
"sum": {
"field": "price"
}
}
}
}
}
}继续用2017第一季度来验证下
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原始发表：2019/08/23 ，如有侵权请联系 cloudcommunity@tencent.com 删除
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