+----+------+--------------------+--------+-------------+
| id | name |    end time        |  value |    comment  |
---------------------------------------------------------
|1   |node1 |2017-03-24 08:30:00 |    5   | blabla      |
---------------------------------------------------------
|2   |node1 |2017-03-24 09:00:00 |    3   | blabla      |
---------------------------------------------------------
|3   |node1 |2017-03-24 09:30:00 |    8   | blabla      |
---------------------------------------------------------
|4   |node2 |2017-03-24 10:00:00 |    5   | blabla      |
---------------------------------------------------------
|5   |node2 |2017-03-24 10:30:00 |    3  | blabla      |
---------------------------------------------------------
|6   |node2 |2017-03-24 11:00:00 |    1   | blabla      |
---------------------------------------------------------
|7   |node2 |2017-03-24 11:30:00 |    3   | blabla      |
---------------------------------------------------------
|8   |node2 |2017-03-24 12:00:00 |    5  | blabla      |
---------------------------------------------------------

df.groupBy(
    col("name"),
    window(col("end time"), "2 hour", "30 minute")
)
.agg(max("value").as("2_hour_max_value"))
.filter(col("2_hour_max_value") < 6)
.select("name")
.distinct()