Flink1.11如何实现Tumble Window后基于event time倒序取第一条作统计？

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.toRetractStreamRow |

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~*来自志愿者整理的flink邮件归档