SELECT t2.city_name, COUNT(*) AS count FROM ( SELECT distinct cuid FROM map_huiyan_short_stay WHERE loc_x > 12993523 AND loc_x < 13012467 AND loc_y > 4773079 AND loc_y < 4789463 AND event_day = 20230605 ) t1 JOIN ( SELECT cuid, city_name FROM map_huiyan_long_stay_with_area WHERE event_day = 20230605 AND event_type = 'home' AND event_os = 'android' ) t2 ON t1.cuid = t2.cuid GROUP BY t2.city_name;在hive中,因为两表中数据量过大,我需要避免使用distinct,修改代码以实现相同的效果
时间: 2024-04-08 17:29:02 浏览: 16
在Hive中,如果你想避免使用DISTINCT关键字,可以尝试以下修改代码的方法来实现相同的效果:
```
SELECT t2.city_name, COUNT(*) AS count
FROM (
SELECT cuid
FROM (
SELECT cuid, row_number() OVER (PARTITION BY cuid) AS rn
FROM map_huiyan_short_stay
WHERE loc_x > 12993523 AND loc_x < 13012467 AND loc_y > 4773079 AND loc_y < 4789463 AND event_day = 20230605
) t
WHERE rn = 1
) t1
JOIN (
SELECT cuid, city_name
FROM map_huiyan_long_stay_with_area
WHERE event_day = 20230605 AND event_type = 'home' AND event_os = 'android'
) t2 ON t1.cuid = t2.cuid
GROUP BY t2.city_name;
```
在上述代码中,我们使用了窗口函数`row_number()`来对map_huiyan_short_stay表中的数据进行编号(按照cuid分组)。然后,在内层子查询中,选择了编号为1的记录,即每个cuid的第一条记录。这样就实现了去重的效果,而不需要使用DISTINCT关键字。
注意,在使用窗口函数时,需要使用`row_number() OVER (PARTITION BY cuid)`来进行分组和编号,其中`PARTITION BY cuid`表示按照cuid分组。
最后,根据修改后的代码进行GROUP BY操作,以获取每个城市的统计结果。