这种构造在Spark SQL中可能吗？

是的，是。在GROUP BY和ORDER BY子句中使用新列的两种方法可以使它在Spark SQL中工作
使用子查询的方法1：

SELECT timeHour, someThing FROM (SELECT  
      from_unixtime((starttime/1000)) AS timeHour
    , sum(...)                          AS someThing
    , starttime
FROM
    some_table) 
WHERE
    starttime >= 1000*unix_timestamp('2017-09-16 00:00:00')
      AND starttime <= 1000*unix_timestamp('2017-09-16 04:00:00')
GROUP BY
    timeHour
ORDER BY
    timeHour
LIMIT 10;

方法二使用WITH//优雅方式：

-- create alias 
WITH table_aliase AS(SELECT  
      from_unixtime((starttime/1000)) AS timeHour
    , sum(...)                          AS someThing
    , starttime
FROM
    some_table)

-- use the same alias as table
SELECT timeHour, someThing FROM table_aliase
WHERE
    starttime >= 1000*unix_timestamp('2017-09-16 00:00:00')
      AND starttime <= 1000*unix_timestamp('2017-09-16 04:00:00')
GROUP BY
    timeHour
ORDER BY
    timeHour
LIMIT 10;

Scala替代使用Spark DataFrame(Wo SQL)接口：

// This code may need additional import to work well

val df = .... //load the actual table as df

import org.apache.spark.sql.functions._

df.withColumn("timeHour", from_unixtime($"starttime"/1000))
  .groupBy($"timeHour")
  .agg(sum("...").as("someThing"))
  .orderBy($"timeHour")
  .show()

//another way - as per eliasah comment
df.groupBy(from_unixtime($"starttime"/1000).as("timeHour"))
  .agg(sum("...").as("someThing"))
  .orderBy($"timeHour")
  .show()

我在这里试着给自己一个答案。
在我看来，我们必须重写查询并重复计算GROUP BY子句中的SELECT表达式。例如：

select  
      from_unixtime((t.starttime/1000)) as timeHour
    , sum(...)                          as someThing
from
    some_table as t
where
    t.starttime>=1000*unix_timestamp('2017-09-16 00:00:00')
      and t.starttime<=1000*unix_timestamp('2017-09-16 04:00:00')
group by
    from_unixtime((t.starttime/1000))
order by
    from_unixtime((t.starttime/1000))
limit 10;