Hi Friends,However, we found that the time attribute will be lost after table joining, which means that we cannot do the joining and aggregation at one SQL query statement. There will be no output after the above SQL querying, for SQL queries on streaming tables, the time_attr argument of the group window function https://ci.apache.org/projects/flink/flink-docs-release-1.12/dev/table/sql/queries.html#group-windows must refer to a valid time attribute that specifies the processing time or event time of rows. In wide_table, the time_attr of field eventInfo_eventTime has been lost.*来自志愿者整理的flink邮件归档
Hi!
As this mail is written in English I'm also forwarding this to the user mailing list.
Streaming joins do not retain row time attribute and this is the expected behavior. As you're windowing the results of joins I guess you're enriching the records from one stream with that join. Lookup joins [1] and event time temporal join [2] will retain row time and their results can be used by windowing operators later. Do they meet your needs?
[1] https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/dev/table/sql/queries/joins/#lookup-join [2] https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/dev/table/sql/queries/joins/#event-time-temporal-join*来自志愿者整理的flink邮件归档
版权声明:本文内容由阿里云实名注册用户自发贡献,版权归原作者所有,阿里云开发者社区不拥有其著作权,亦不承担相应法律责任。具体规则请查看《阿里云开发者社区用户服务协议》和《阿里云开发者社区知识产权保护指引》。如果您发现本社区中有涉嫌抄袭的内容,填写侵权投诉表单进行举报,一经查实,本社区将立刻删除涉嫌侵权内容。