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Jonathan Halliday commented on CASSANDRA-4775:
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> Not sure we'd want to support avg (since it requires extra information to be
> stored, as you point out), but it would be easy to support some kind of
> reduce(Iterable<Column> with any scheme that stores per-column updates.
On reflection I don't think the extra data is really the problem. It's how to
present that data at the client that's tricky. Supporting a configurable
reducer for merging old+new local values and local+remote values is only one of
the ways that 'counters' can be made more flexible. By also making the datatype
of the column that reducer operates on a pluggable option you can achieve a
variety of additional behaviours. The existing counters become essentially
ReducibleThing<bigint,IntegerAdditionReducer> whilst HyperLogLog may use
ReducibleThing<bitset,BitwiseLogicalANDReducer> and the most general case is
ReducibleThing<blob,UserDefinedReducer> which would allow for custom 'merge /
conflict resolution' policies. In this model the implementation of avg would be
ReducibleThing<CompositeType(bigint:sum,bigint:count),TwoFieldIntegerAdditionReducer>
which does the right thing on the server, but leaves the client having to
manage the composite and calculate the average as sum/count rather than being
handed the single value directly.
> Counters 2.0
> ------------
>
> Key: CASSANDRA-4775
> URL: https://issues.apache.org/jira/browse/CASSANDRA-4775
> Project: Cassandra
> Issue Type: New Feature
> Components: Core
> Reporter: Arya Goudarzi
> Labels: counters
> Fix For: 2.0
>
>
> The existing partitioned counters remain a source of frustration for most
> users almost two years after being introduced. The remaining problems are
> inherent in the design, not something that can be fixed given enough
> time/eyeballs.
> Ideally a solution would give us
> - similar performance
> - less special cases in the code
> - potential for a retry mechanism
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