Hi 大家好
现在想对5分钟的kafka数据开窗，因为是DTS同步消息数据，会有update 和
delete，所以需要对相同user_id的数据根据事件时间倒序第一条，统计最后一次status(状态字段)共有多少人。
marketingMapDS: DataStream[(String, String, Long)]
|
tEnv.createTemporaryView("test", marketingMapDS,$"status", $"upd_user_id",
$"upd_time".rowtime)
val resultSQL =
"""
|SELECT t.status,
| COUNT(t.upd_user_id) as num
|FROM (
|SELECT *,
| ROW_NUMBER() OVER (PARTITION BY upd_user_id ORDER BY
upd_time DESC) as row_num
|FROM test
|) t
|WHERE t.row_num = 1
|GROUP BY t.status, TUMBLE(t.upd_time, INTERVAL '5' MINUTE)
|""".stripMargin
val table2 = tEnv.sqlQuery(resultSQL)
val resultDS = tEnv.toRetractStream[Row](table2)
|
这样写后会报以下错：
| Exception in thread "main" org.apache.flink.table.api.TableException:
GroupWindowAggregate doesn't support consuming update and delete changes which
is produced by node Rank(strategy=[UndefinedStrategy], rankType=[ROW_NUMBER],
rankRange=[rankStart=1, rankEnd=1], partitionBy=[upd_user_id],
orderBy=[upd_time DESC], select=[status, upd_user_id, upd_time]) |
所以想实现该需求，请问还可以怎么实现。。。
TABLE API 可以实现 类似 ROW_NUMBER() OVER 这样功能吗？
|
val table = tEnv.fromDataStream(marketingMapDS, $"status", $"upd_user_id",
$"upd_time".rowtime)
.window(Tumble over 5.millis on $"upd_time" as "w")
.groupBy($"w")
？？？
|
Flink新手一个。。。请大佬指点~
