结合使用collect_set()和over()函数 结合使用collect_set()和over()函数,我们可以实现更复杂的数据聚合分析。 以下是一个示例,演示如何使用collect_set()和over()函数来统计每个用户购买的商品数量: SELECTuser_id,product_id,COUNT(product_id)OVER(PARTITIONBYuser_id)ASpurchase_count,collect_set(product_id)OV...
在over中按照地区代码进行排序,然后在collect_set中把排好顺序的数据收集起来。 collect_set(areas) over(partition by zheng_shi_indicator order by guo_biao_di_yu_dai_ma asc rows between unbounded preceding and current row) areas_sort 1. 2. 3. 4. 但是结果会是这样的: 即:collect_set(a) over(...
注意:collect_set是一个set集合,不允许重复的记录插入 selectgridid,height,collect_list(cell) cellArray,collect_list(mrcount) mrcountArray,collect_list(weakmrcount) weakmrcountArrayfrom(selectgridid,height,cell,mrcount,weakmrcount,row_number()over(partitionbygridid,heightorderbymrcountdesc) rnfromtommy...
cast(rnasstring))elsecast(rnasstring)end,detail_address_name))),'^[0-9]*',''),',[0-9]*',',')asaddress_changefrom(selectname,detail_address_name,row_number()over(partitionbynameorderbylast_modification_timeasc)asrnfromhuman_address)agroupbyname; ...
SELECT collect_list(column_name) OVER (PARTITION BY some_column ORDER BY order_column) AS sorted_list FROM your_table; 注意:这里的OVER子句用于指定分区和排序,但collect_list本身不会根据ORDER BY排序,而是需要配合窗口函数(如ROW_NUMBER()等)或其他排序方法使用。实际上,对于简单的聚合排序,你可能需要先...
首先排序:row_number() over (partition by category order by cast(duration as int) desc) duration_rank,然后拼接concat_ws(',',collect_set(category)),但是得到的结果却是乱序的,产生这个问题的根本原因自然在MapReduce,如果启动了多于一个mapper/reducer来处理数据,select出来的数据顺序就几乎肯定与原始顺序不...
首先排序:row_number() over (partition by category order by cast(duration as int) desc) duration_rank,然后拼接concat_ws(',',collect_set(category)),但是得到的 结果却是乱序的,产生这个问题的根本原因自然在MapReduce,如果启动了多于一个mapper/reducer来处理数据,select出来的数据顺序就 几乎肯定与原始顺序...
首先排序:row_number() over (partition by category order by cast(duration as int) desc) duration_rank,然后拼接concat_ws(‘,‘,collect_set(category)),但是得到的结果却是乱序的,产生这个问题的根本原因自然在MapReduce,如果启动了多于一个mapper/reducer来处理数据,select出来的数据顺序就几乎肯定与原始顺序...
首先排序:row_number() over (partition by category order by cast(duration as int) desc) duration_rank,然后拼接concat_ws(',',collect_set(category)),但是得到的结果却是乱序的,产生这个问题的根本原因自然在MapReduce,如果启动了多于一个mapper/reducer来处理数据,select出来的数据顺序就几乎肯定与原始顺序不...
select gridid,height,cell,mrcount,weakmrcount,row_number()over(partition by gridid,height order by mrcount desc) rn from tommyduan_test group by gridid,height,cell,mrcount,weakmrcount ) t10 where rn<4 group by gridid,height;+---+---+---+---+---+--+ | gridid | height |...