performance - Hive:是否有更好的方法对列进行百分位排名？

Question

目前，要对 hive 中的列进行百分位数排名，我使用的是类似以下的内容。我正在尝试按项目所属的百分位数对列中的项目进行排名，为每个项目分配一个 0 到 1 的值。下面的代码分配了一个从 0 到 9 的值，本质上是说 char_percentile_rank 为 0 的项目在项目的后 10% 中，值为 9 的项目在前 10% 中.有更好的方法吗？

select item
    , characteristic
    , case when characteristic <= char_perc[0] then 0
        when characteristic <= char_perc[1] then 1
        when characteristic <= char_perc[2] then 2
        when characteristic <= char_perc[3] then 3
        when characteristic <= char_perc[4] then 4
        when characteristic <= char_perc[5] then 5
        when characteristic <= char_perc[6] then 6
        when characteristic <= char_perc[7] then 7
        when characteristic <= char_perc[8] then 8
        else 9
      end as char_percentile_rank
from (
    select split(item_id,'-')[0] as item
        , split(item_id,'-')[1] as characteristic
        , char_perc
    from (
        select collect_set(concat_ws('-',item,characteristic)) as item_set
            , PERCENTILE(BIGINT(characteristic),array(0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9)) as char_perc
        from(
            select item
                , sum(characteristic) as characteristic
            from table
            group by item
        ) t1
    ) t2
    lateral view explode(item_set) explodetable as item_id
) t3

注意:我必须执行 collect_set 以避免自连接，因为百分位数函数隐式执行 group by。

我发现百分位数函数非常慢(至少在这种用法中)。也许手动计算百分位数会更好？

Answer 1

尝试删除您的一个派生表

select item
    , characteristic
    , case when characteristic <= char_perc[0] then 0
        when characteristic <= char_perc[1] then 1
        when characteristic <= char_perc[2] then 2
        when characteristic <= char_perc[3] then 3
        when characteristic <= char_perc[4] then 4
        when characteristic <= char_perc[5] then 5
        when characteristic <= char_perc[6] then 6
        when characteristic <= char_perc[7] then 7
        when characteristic <= char_perc[8] then 8
        else 9
      end as char_percentile_rank
from (
     select item, characteristic,
         , PERCENTILE(BIGINT(characteristic),array(0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9)) over () as char_perc 
     from (
       select item
         , sum(characteristic) as characteristic             
       from table
       group by item            
     ) t1
) t2