首先group by 的简单说明:

group by 一般和聚合函数一起使用才有意义,比如 count sum avg等,使用group by的两个要素:
   (1) 出现在select后面的字段 要么是是聚合函数中的,要么就是group by 中的.
   (2) 要筛选结果 可以先使用where 再用group by 或者先用group by 再用having

select count(a),b,c from test group by b,c;

可以看出 group by 两个条件的工作过程:

先对第一个条件b列的值 进行分组,分为 第一组:1-5, 第二组6-8,然后又对已经存在的两个分组用条件二 c列的值进行分组,发现第一组又可以分为两组 1-4,5

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" alt="" />

 SELECT
ConsumerId,
Topic,
COUNT(ConsumerId)
FROM
ali_ons_consumer
WHERE
STATUS != "Deleted"
GROUP BY
ConsumerId,
Topic
ORDER BY
ConsumerId DESC,
Topic DESC;

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