I have a keyd stream of data that looks like:
{
summary:Integer
uid:String
key:String
.....
}
I need to aggregate the summary values in some time range, and once I achieved a specifc number , to flush the summary and all the of the UID'S that influenced the summary to database/log file.
after the first flush , I want to discare all the uid's from the memory , and just flush every new item immediatelly.
So I tried this aggregate function.
public class AggFunc implements AggregateFunction<Item, Acc, Tuple2<Integer,List<String>>>{
private static final long serialVersionUID = 1L;
@Override
public Acc createAccumulator() {
return new Acc());
}
@Override
public Acc add(Item value, Acc accumulator) {
accumulator.inc(value.getSummary());
accumulator.addUid(value.getUid);
return accumulator;
}
@Override
public Tuple2<Integer,List<String>> getResult(Acc accumulator) {
List<String> newL = Lists.newArrayList(accumulator.getUids());
accumulator.setUids(Lists.newArrayList());
return Tuple2.of(accumulator.getSum(), newL);
}
@Override
public Acc merge(Acc a, Acc b) {
.....
}
}
and in the aggregate process function , I flush the list to state, and if I need to save to dataBase I'm clearing the state and save flag in the state to indicate it.
But it seems crooked to me. And I'm not sure if that would work well for me.
Is there a better solution to this situation?