sql - Oracle如何为多个列获取一个列中最常见的值？

Question

假设我有下表，如何按ID分组，并得到每一列中最常见的值 附:表很大，我需要对很多列执行此操作

ID  Col1  Col2  Col3....
1   A     null
1   A     X
1   B     null
1   A     Y
2   C     X
2   C     Y
2   A     Y
3   B     Z
3   A     Z
3   A     Z
3   B     X
3   B     Y

预期结果:

ID  Col1  Col2  Col3....
1   A     null
2   C     Y
3   B     Z

Answer 1

这是一种方法，使用解析函数和keep:

select id,
       min(col1) keep(dense_rank first order by cnt_col1 desc) as col1_mode,
       min(col2) keep(dense_rank first order by cnt_col2 desc) as col2_mode,
       min(col3) keep(dense_rank first order by cnt_col3 desc) as col3_mode
from (select id,
             count(*) over (partition by id, col1) as cnt_col1,
             count(*) over (partition by id, col2) as cnt_col2,
             count(*) over (partition by id, col3) as cnt_col3
      from t
     ) t
group by id;

最常见的值在统计中称为“众数”，Oracle 提供了一个函数来计算它。因此，更简单的方法是使用 stats_mode():

   select id,
         stats_mode(col1) as mode_col1,
         stats_mode(col2) as mode_col2,
         stats_mode(col3) as mode_col3
  from table t
  group by id;

编辑:

如评论中所述，stats_mode() 不计算 NULL 值。解决此问题的最简单方法是找到一些不在数据中的值并执行以下操作:

   select id,
          stats_mode(coalesce(col1, '<null>')) as mode_col1,
          stats_mode(coalesce(col2, '<null>')) as mode_col2,
          stats_mode(coalesce(col3, '<null>')) as mode_col3
  from table t
  group by id;

另一种方法是恢复到第一种方法或类似的方法:

select id,
       (case when sum(case when col1 = mode_col1 then 1 else 0 end) >= sum(case when col1 is null then 1 else 0 end)
             then mode_col1
             else NULL
        end) as mode_col1,
       (case when sum(case when col2 = mode_col2 then 1 else 0 end) >= sum(case when col2 is null then 1 else 0 end)
             then mode_col2
             else NULL
        end) as mode_col2,
       (case when sum(case when col3 = mode_col13 then 1 else 0 end) >= sum(case when col3 is null then 1 else 0 end)
             then mode_col3
             else NULL
        end) as mode_col3
from (select t.*,
             stats_mode(col1) over (partition by id) as mode_col1,
             stats_mode(col2) over (partition by id) as mode_col2,
             stats_mode(col3) over (partition by id) as mode_col3
      from table t
     ) t
group by id;