基於Elasticsearch 為電商提供商品數據大數據查詢

前言

對於現代電商的產品，維度的多員花，與一套強大的搜索引擎，那是非常必要的。今天我們主要是描述我們在從事電商搜索引擎過程中的遇到的一些問題和經驗分享。

過程

數據準備

1、我們準備為我們需要做查找的數據做好一張視圖，方便我們分析數據查找維度，與查找場景需求。附加代碼，對於Mysql 創建視圖不清楚的，可以自行查找具體的文檔瞭解，在我們完成視圖創建後，我們就已經有了一張視圖表，供我們數據使用。

select `g`.`goods_id` AS `goods_id`,`g`.`publisher_sn` AS `publisher_sn`,`g`.`add_time` AS `add_time`,`g`.`last_update` AS `last_update`,`g`.`goods_name` AS `goods_name`,`g`.`fineness` AS `fineness`,`g`.`look` AS `look`,`g`.`cat_path` AS `cat_path`,`g`.`goods_number` AS `goods_number`,`g`.`shop_price` AS `shop_price`,`g`.`goods_weight` AS `weight`,`g`.`keywords` AS `keywords`,`g`.`goods_desc` AS `goods_desc`,`g`.`isbn` AS `isbn`,`a`.`attr_value` AS `author`,`b`.`attr_value` AS `publisher`,`c`.`attr_value` AS `yiname`,`m`.`age` AS `age`,`m`.`press_intro` AS `press_intro`,`m`.`author_info` AS `author_info`,`m`.`media_intro` AS `media_intro`,`m`.`catalog` AS `catalog`,`m`.`prologue` AS `prologue`,`m`.`selling_point_1` AS `selling_point_1`,`m`.`selling_point_2` AS `selling_point_2`,`m`.`selling_point_3` AS `selling_point_3`,`m`.`detail_intro_1` AS `detail_intro_1`,`m`.`detail_intro_2` AS `detail_intro_2`,`m`.`detail_intro_3` AS `detail_intro_3`,`m`.`wtao_intro` AS `wtao_intro`,`m`.`video_intro` AS `video_intro`,`co`.`positive` AS `positive`,`co`.`negative` AS `negative`,`s`.`name` AS `series_name`,`s`.`name_cn` AS `series_name_cn`,`v`.`title` AS `v_title`,`v`.`article` AS `v_article`,`k`.`bunch_no` AS `bunch_no` from ((((((((`sd_goods` `g` left join `sd_goods_attr` `c` on((`g`.`goods_id` = `c`.`goods_id`))) left join `sd_goods_attr` `a` on((`g`.`goods_id` = `a`.`goods_id`))) left join `sd_goods_attr` `b` on((`g`.`goods_id` = `b`.`goods_id`))) left join `sd_goods_more` `m` on((`g`.`goods_id` = `m`.`goods_id`))) left join `sd_cover_text` `co` on((`g`.`isbn` = `co`.`isbn`))) left join `sd_series_name` `s` on((`g`.`isbn` = `s`.`isbn`))) left join `nosql`.`video_words_result` `v` on((`g`.`isbn` = `v`.`isbn`))) left join `sd_bunch` `k` on((`g`.`isbn` = `k`.`isbn`))) where ((`c`.`attr_id` = 1) and (`a`.`attr_id` = 2) and (`b`.`attr_id` = 3))

2、創建查詢索引，在創建這塊的時候，需要主要創建過程中的類型的選擇，方便您在查詢過程中可以應用的更準確與方便。

PUT /products
{
 "settings": {
   "number_of_shards": 5,
   "number_of_replicas": 1
 },
 "mappings": {
     "properties": {
       "goods_id":{
         "type": "text"
       },
       "publisher_sn":{
           "type": "text"
       },
       "goods_name": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "keywords": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "weight":{
           "type":"keyword"
       },
       "goods_desc": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "author": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "publisher": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "yiname": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "fineness":{
           "type": "text"
       },
       "look":{
           "type": "text"
       },
       "isbn":{
           "type": "text"
       },
       "age":{
           "type": "text"
       },
       "press_intro": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "author_info": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "media_intro": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "positive": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "negative": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "series_name": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "series_name_cn": {
           "type": "text",
           "analyzer": "ik_smart"
       },
       "v_title":{
           "type": "text",
           "analyzer": "ik_smart"
       },
       "v_article":{
           "type": "text",
           "analyzer": "ik_smart"
       }
     }
 }
}

3、索引數據的添加，數據的添加方式更多的看具體的團隊的情況，我們這邊主要是使用Canal 來幫助我們完成數據的添加與新增數據的添加，在使用Canal的時候，需要有JAVA經驗，會更好的解決一些同步過程中的問題。

4、對於未使用現成數據同步工具的，自己也是可以根據具體場景寫Hook 來完成數據的添加，對於有不清楚的地方，可以聯繫我們瞭解。

5、對於 Elasticsearch 的部署搭建不熟悉的同步，可以參考我們的 Docker-composer 快速部署方式。

數據使用

數據查找應用，基於 SDK 查找, 對於 Query DSL 不熟悉的同步可以基於我們前面的 How to build a OR condition in Elasticsearch Query DSL 瞭解更多

本文來自 PMOSH，作者：PMOSH，轉載請註明原文鏈接：https://www.cnblogs.com/pmo-sh/p/e-commerce-product-use-by-elasticsearch.html

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