groupBy分组和使用agg聚合函数demo：

df.show+----+-----+---+|YEAR|MONTH|NUM|+----+-----+---+|2017|    1| 10||2017|    1|  5||2017|    2| 20||2018|    1|  5||2018|    1|  5|+----+-----+---+import org.apache.spark.sql.functions._df.groupBy("YEAR", "MONTH")  .agg(sum("NUM").as("sum_num"))  .show+----+-----+-------+|YEAR|MONTH|sum_num|+----+-----+-------+|2018|    1|   10.0||2017|    1|   15.0||2017|    2|   20.0|+----+-----+-------+//也可以这样写：df.groupBy("YEAR", "MONTH")  .agg("NUM"->"avg", ("MONTH", "count") )  .show+----+-----+--------+------------+|YEAR|MONTH|avg(NUM)|count(MONTH)|+----+-----+--------+------------+|2018|    1|     5.0|           2||2017|    1|     7.5|           2||2017|    2|    20.0|           1|+----+-----+--------+------------+