The HiveTableSource (and many others) return isBounded() -> true. In this case it is not even possible for it to change over time, so I am a bit confused.
To me it sounds like you should always be able to join a stream against a bounded table, temporal or not it is pretty well defined. Maybe there is some fundamental concept that I dont understand, I don't have much experience with this to be fair. Gyula On Mon, Apr 20, 2020 at 4:03 PM Kurt Young <ykt...@gmail.com> wrote: > The reason here is Flink doesn't know the hive table is static. After you > create these two tables and > trying to join them, Flink will assume both table will be changing with > time. > > Best, > Kurt > > > On Mon, Apr 20, 2020 at 9:48 PM Gyula Fóra <gyula.f...@gmail.com> wrote: > >> Hi! >> >> The problem here is that I dont have a temporal table. >> >> I have a regular stream from kafka (with even time attribute) and a >> static table in hive. >> The Hive table is static, it doesn't change. It doesn't have any time >> attribute, it's not temporal. >> >> Gyula >> >> On Mon, Apr 20, 2020 at 3:43 PM godfrey he <godfre...@gmail.com> wrote: >> >>> Hi Gyual, >>> >>> Can you convert the regular join to lookup join (temporal join) [1], >>> and then you can use window aggregate. >>> >>> > I understand that the problem is that we cannot join with the Hive >>> table and still maintain the watermark/even time column. But why is this? >>> Regular join can't maintain the time attribute as increasing trend (one >>> record may be joined with a very old record), >>> that means the watermark does not also been guaranteed to increase. >>> >>> >>> https://ci.apache.org/projects/flink/flink-docs-release-1.10/dev/table/streaming/joins.html#join-with-a-temporal-table >>> >>> Best, >>> Godfrey >>> >>> Gyula Fóra <gyula.f...@gmail.com> 于2020年4月20日周一 下午4:46写道： >>> >>>> Hi All! >>>> >>>> We hit a the following problem with SQL and trying to understand if >>>> there is a valid workaround. >>>> >>>> We have 2 tables: >>>> >>>> *Kafka* >>>> timestamp (ROWTIME) >>>> item >>>> quantity >>>> >>>> *Hive* >>>> item >>>> price >>>> >>>> So we basically have incoming (ts, id, quantity) and we want to join it >>>> with the hive table to get the total price (price * quantity) got the >>>> current item. >>>> >>>> After this we want to create window aggregate on quantity*price >>>> windowed on timestamp (event time attribute). >>>> >>>> In any way we formulate this query we hit the following error: >>>> org.apache.flink.table.api.TableException: Rowtime attributes must not >>>> be in the input rows of a regular join. As a workaround you can cast the >>>> time attributes of input tables to TIMESTAMP before. >>>> >>>> I understand that the problem is that we cannot join with the Hive >>>> table and still maintain the watermark/even time column. But why is this? >>>> >>>> In datastream world I would just simply assign Max watermark to my >>>> enrichment input and join outputs will get the ts of the input record. Can >>>> I achieve something similar in SQL/Table api? >>>> >>>> Thank you! >>>> Gyula >>>> >>>>
