流量选品-变体销量趋势图

Pyspark_job/dwt/dwt_amazon_report.py

@@ -39,7 +39,8 @@ class DwtAmazonReport(Templates):
             asin_zr_counts as new_zr_count,
             asin_sp_counts as new_sp_count,
             asin_st_counts as new_total_count,
-            date_info as new_date_info_list 
+            date_info as new_date_info_list,
+            variation_bought_month as new_variation_monthly_sales
         from dwt_flow_asin
         where site_name = '{self.site_name}'
           and date_type = '{self.date_type}'
@@ -56,7 +57,8 @@ class DwtAmazonReport(Templates):
             zr_count as old_zr_count,
             sp_count as old_sp_count,
             total_count as old_total_count,
-            date_info_list as old_date_info_list 
+            date_info_list as old_date_info_list,
+            variation_monthly_sales as old_variation_monthly_sales
         from dwt_amazon_report
         where site_name = '{self.site_name}'
           and date_type = '{self.date_type}'
@@ -66,8 +68,9 @@ class DwtAmazonReport(Templates):
         self.df_asin_detail_old.show(10, truncate=True)
 
     def handle_data(self):
-        # 关联后的列名
-        join_columns = ['monthly_sales', 'zr_count', 'sp_count', 'total_count', 'date_info_list']
+        # 关联后的列名（新增字段放末尾）
+        join_columns = ['monthly_sales', 'zr_count', 'sp_count', 'total_count', 'date_info_list',
+                         'variation_monthly_sales']
         # 获取历史df对象中，date_info的数量，用来确定关联不到的历史asin填充多少个 -1
         old_date_info_first = self.df_asin_detail_old.select('old_date_info_list').distinct().first()
         if old_date_info_first is None: