Elasticsearch聚合分析

朱雀 2022-04-25 02:06 209阅读 0赞

Elasticsearch聚合分析：

## 预先设置 ##

在进行聚合分析的是皇后首先把文本的field的fielddata属性设置为true

## 计算每个tag下的商品数量 ##

结果

<table> 
 <tbody> 
 <tr> 
 <td><pre>1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 </pre></td> 
 <td><pre>{
 "took": 11, "timed_out": false, "_shards": {
 "total": 5, "successful": 5, "failed": 0 }, "hits": {
 "total": 3, "max_score": 1, "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": 1 }, {
 "key": "qingxin", "doc_count": 1 } ] } } } </pre></td> 
 </tr> 
 </tbody> 
</table>

## 包含yagao的商品，计算每个tag下的商品数量 ##

## 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 ##

结果

<table> 
 <tbody> 
 <tr> 
 <td><pre>1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 </pre></td> 
 <td><pre>{
 "took": 22, "timed_out": false, "_shards": {
 "total": 5, "successful": 5, "failed": 0 }, "hits": {
 "total": 3, "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": 1, "avg_price": {
 "value": 30 } }, {
 "key": "qingxin", "doc_count": 1, "avg_price": {
 "value": 40 } } ] } } } </pre></td> 
 </tr> 
 </tbody> 
</table>

## 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 ##

结果

<table> 
 <tbody> 
 <tr> 
 <td><pre>1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 </pre></td> 
 <td><pre>{
 "took": 26, "timed_out": false, "_shards": {
 "total": 5, "successful": 5, "failed": 0 }, "hits": {
 "total": 3, "max_score": 0, "hits": [] }, "aggregations": {
 "all_tags": {
 "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ {
 "key": "qingxin", "doc_count": 1, "avg_price": {
 "value": 40 } }, {
 "key": "meibai", "doc_count": 1, "avg_price": {
 "value": 30 } }, {
 "key": "fangzhu", "doc_count": 2, "avg_price": {
 "value": 27.5 } } ] } } } </pre></td> 
 </tr> 
 </tbody> 
</table>

## 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 ##

<table> 
 <tbody> 
 <tr> 
 <td><pre>1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 </pre></td> 
 <td><pre>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" } } } } } } } } </pre></td> 
 </tr> 
 </tbody> 
</table>