Hi Basant,
no, you cannot add data streams or re-wire your program during runtime.
As for any other program changes, you'd have to take a savepoint (to keep
operator state and exactly-once semantics) and restart the new program code
from there.
For a few combinations, I'd probably choose the sec
Thanks Nico.
As there are 2 ways to achieve this which is better ?
1st option -> dataStream.flatMap( ... ) -> this takes in out and provides
me N number of outputs, depending on my key combination . On each of the
output the same windowing logic is applied
or the one you suggested
2nd option ->
[back to the ml...]
also including your other mail's additional content...
> I have been able to do this by the following and repeating this for every
> key + window combination. So in the above case there would be 8 blocks like
> below. (4 combinations and 2 window period for each combination)
>
Hi Basanth,
Let's assume you have records of the form
Record = {timestamp, country, state, city, value}
Then you'd like to create aggregates, e.g. the average, for the following
combinations?
1) avg per country
2) avg per state and country
3) avg per city and state and country
* You could create
For example - this is a sample model from one of the Apache Apex
presentation.
I would want to aggregate for different combinations, and different time
buckets. What is the best way to do this in Flink ?
{"keys":[{"name":"campaignId","type":"integer"},
{"name":"adId","type":"integer"},
{"name":
Hi,
I want to aggregate hits by Country, State, City. I would these as tags in
my sample data.
How would I do aggregation at different levels ? Input data would be single
record
Should I do flatMap transformation first and create 3 records from 1 input
record, or is there a better way to do it ?
