Hello,
No, I did not use Hequn’s work. I already had an implementation the
pre-processed the stream before feeding it nto the (now modified) SQL
expression.
Basically the SQL, instead of computing the AVG, just computes the COUNT and
SUM. I do the average computation on the resulting stream.
mode
>> (updating table rows by key) yet but only append mode, i.e, each event of
>> the data stream is appended to the table.
>> Hence, it is not possible to implement your use case using SQL.
>>
>> An upsert ingestion mode will be added in future version of Flink.
abase.
It might be worth to look into TableSinks [0] and the JavaDocs of the mentioned
classes.
Feel free to ask further questions if necessary.
Regards,
Timo
[0]
https://ci.apache.org/projects/flink/flink-docs-release-1.4/dev/table/sourceSinks.html#define-a-tablesink
Am 12/19/17 um 9:08
Hello,
I’m knew to Flink and I need some help. I’d like to use the SQL API for
processing an incoming stream that has the following characteristics:
* Each stream record has a key
* The record can be updated
* The record is of the form: reviewId -> (productId, rating)
For the above
