Hi，问题已经找到了
你的kafka是3个分区，第一次消费你是边发送数据边消费，这时可以认为watermark就是按照你发送数据的顺序生成的，会按照你发送数据的顺序触发计算，所以得到的结果也是你预想的结果。
第二次消费，你的数据不再生产了，这时kafka中的数据可认为是历史数据，你的scan.startup.mode设置的是earliest-offset，这时候flink消费的也是历史数据，因为是3个分区，所以flink会先消费完1个分区内的数据，然后再依次消费另外2个分区的数据，kafka跨分区不能保证有序，所以这时候watermark是按照flink消费数据的顺序生成的，也就是按照如下顺序生成watermark的(此时部分数据会被当做迟到的数据遗弃掉)：
select * from iservVisit
type uuid clientTime
rowtime
iservVisit a 1600391663
2020-09-18T09:14:23
iservVisit b 1600391748
2020-09-18T09:15:48
iservVisit b 1600391823
2020-09-18T09:17:03
---此时触发2020-09-18 09:14 - 2020-09-18 09:16
iservVisit a 1600391857
2020-09-18T09:17:37
iservVisit c 1600391903
2020-09-18T09:18:23
iservVisit b 1600391938
2020-09-18T09:18:58
iservVisit b 1600391970
2020-09-18T09:19:30
---此时触发2020-09-18 09:16 - 2020-09-18 09:18
iservVisit a 1600392057
2020-09-18T09:20:57
iservVisit c 1600391684
2020-09-18T09:14:44
iservVisit c 1600391709
2020-09-18T09:15:09
iservVisit b 1600391781
2020-09-18T09:16:21
iservVisit a 1600391815
2020-09-18T09:16:55
iservVisit b 1600391851
2020-09-18T09:17:31
iservVisit a 1600391945
2020-09-18T09:19:05
iservVisit c 1600391936
2020-09-18T09:18:56
iservVisit c 1600391993
2020-09-18T09:19:53
iservVisit a 1600391690
2020-09-18T09:14:50
iservVisit c 1600391782
2020-09-18T09:16:22
iservVisit b 1600391822
2020-09-18T09:17:02
iservVisit a 1600391870
2020-09-18T09:17:50
iservVisit a 1600391889
2020-09-18T09:18:09
iservVisit b 1600391951
2020-09-18T09:19:11
iservVisit c 1600392016
2020-09-18T09:20:16
iservVisit a 1800392057
2027-01-20T04:54:17
---此时触发2020-09-18
09:18 - 2020-09-18 09:20 以及 2020-09-18 09:20 - 2020-09-18 09:22
PS： 你可以把你的topic设置成1个分区，这样就可以保证数据整体有序，每次查询得到的结果正确且一样的了。
如果分析的有误，敬请指正！
发件人： anonnius
发送时间： 2020-09-18 11:24
收件人： user-zh
主题： Flink sql 消费kafka的顺序是怎么样的 第二次运行sql的结果和第一次不同
hi: [求助] 我这里用flink-sql消费kafka数据, 通过窗口做pvuv的计算, 第一次和第二次计算的结果不一致, 不太了解为什么
0> mac本地环境
1> flink 1.11.1
2> kafka 0.10.2.2, topic为message-json, 分区为3, 副本为1
3> 使用的是sql-client.sh 环境
4> 先在sql-cli中创建了iservVisit表
create table iservVisit (
type string comment '时间类型',
uuid string comment '用户uri',
clientTime string comment '10位时间戳',
rowtime as to_timestamp(from_unixtime(cast(substring(coalesce(clientTime,
'0'), 1, 10) as bigint))), -- 计算列, 10位时间戳转为timestamp类型
WATERMARK for rowtime as rowtime - INTERVAL '1' MINUTE -- 计算列, 作为watermark
) with (
'connector' = 'kafka-0.10',
'topic' = 'message-json',
'properties.bootstrap.servers' = 'localhost:9092',
'properties.group.id' = 'consumer-rt',
'format' = 'json',
'json.ignore-parse-errors' = 'true',
'scan.startup.mode' = 'earliest-offset'
)
然后在sql-cli执行sql
select
tumble_start(rowtime, interval '2' MINUTE) as wStart,
tumble_end(rowtime, interval '2' MINUTE) as wEnd,
count(1) as pv,
count(distinct uuid) as uv
from iservVisit
group by tumble(rowtime, interval '2' MINUTE)
5> 向kafka生产者依次发送下面的json消息
{"type": "iservVisit", "uuid": "c", "clientTime": "1600391684"}
{"type": "iservVisit", "uuid": "a", "clientTime": "1600391663"}
{"type": "iservVisit", "uuid": "a", "clientTime": "1600391690"}
{"type": "iservVisit", "uuid": "c", "clientTime": "1600391709"}
{"type": "iservVisit", "uuid": "b", "clientTime": "1600391748"}
{"type": "iservVisit", "uuid": "c", "clientTime": "1600391782"}
{"type": "iservVisit", "uuid": "b", "clientTime": "1600391781"}
{"type": "iservVisit", "uuid": "b", "clientTime": "1600391823"}
{"type": "iservVisit", "uuid": "b", "clientTime": "1600391822"}
{"type": "iservVisit", "uuid": "a", "clientTime": "1600391815"}
{"type": "iservVisit", "uuid": "a", "clientTime": "1600391857"}
{"type": "iservVisit", "uuid": "a", "clientTime": "1600391870"}
{"type": "iservVisit", "uuid": "b", "clientTime": "1600391851"}
{"type": "iservVisit", "uuid": "c", "clientTime": "1600391903"}
{"type": "iservVisit", "uuid": "a", "clientTime": "1600391889"}
{"type": "iservVisit", "uuid": "a", "clientTime": "1600391945"}
{"type": "iservVisit", "uuid": "b", "clientTime": "1600391938"}
{"type": "iservVisit", "uuid": "b", "clientTime": "1600391951"}
{"type": "iservVisit", "uuid": "c", "clientTime": "1600391936"}
{"type": "iservVisit", "uuid": "b", "clientTime": "1600391970"}
{"type": "iservVisit", "uuid": "c", "clientTime": "1600392016"}
{"type": "iservVisit", "uuid": "c", "clientTime": "1600391993"}
{"type": "iservVisit", "uuid": "a", "clientTime": "1600392057"}
{"type": "iservVisit", "uuid": "a", "clientTime": "1800392057"}
6> 第一次结果(这里sql-cli的sql一直在运行)
wStart wEnd pv
uv
2020-09-18T09:14 2020-09-18T09:16 5
3
2020-09-18T09:16 2020-09-18T09:18 8
3
2020-09-18T09:18 2020-09-18T09:20 8
3
2020-09-18T09:20 2020-09-18T09:22 2
2
7> 第二次结果(退出[Quit]sql-cli中的sql, 在次运行)
wStart wEnd pv
uv
2020-09-18T09:14 2020-09-18T09:16 2
2
2020-09-18T09:16 2020-09-18T09:18 2
2
2020-09-18T09:18 2020-09-18T09:20 8
3
2020-09-18T09:20 2020-09-18T09:22 2
2
8> 详细过程以放入附件文件中
