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https://issues.apache.org/jira/browse/CASSANDRA-4914?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14158569#comment-14158569
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Tyler Hobbs commented on CASSANDRA-4914:
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I'm thinking a bit about making this compatible with with UDFs. The problem
with this approach is that it relies on state that's not visible to the
aggregation functions.
An alternative that would be (more easily) compatible with UDFs is a
reduce-style aggregation. The reducer function takes two inputs: the current
state and the next value. You can optionally provide an initial state and a
finalizer function that is called with the final state after reducing. UDTs,
tuples, and collections should be sufficiently powerful to represent anything
that's needed for state.
In fact, Postgres's approach to user-defined aggregation functions is almost
exactly this:
http://www.postgresql.org/docs/8.3/static/sql-createaggregate.html. I think we
could slightly simplify their approach by inferring the data types.
> Aggregation functions in CQL
> ----------------------------
>
> Key: CASSANDRA-4914
> URL: https://issues.apache.org/jira/browse/CASSANDRA-4914
> Project: Cassandra
> Issue Type: New Feature
> Reporter: Vijay
> Assignee: Benjamin Lerer
> Labels: cql, docs
> Fix For: 3.0
>
> Attachments: CASSANDRA-4914-V2.txt, CASSANDRA-4914-V3.txt,
> CASSANDRA-4914-V4.txt, CASSANDRA-4914.txt
>
>
> The requirement is to do aggregation of data in Cassandra (Wide row of column
> values of int, double, float etc).
> With some basic agree gate functions like AVG, SUM, Mean, Min, Max, etc (for
> the columns within a row).
> Example:
> SELECT * FROM emp WHERE empID IN (130) ORDER BY deptID DESC;
>
> empid | deptid | first_name | last_name | salary
> -------+--------+------------+-----------+--------
> 130 | 3 | joe | doe | 10.1
> 130 | 2 | joe | doe | 100
> 130 | 1 | joe | doe | 1e+03
>
> SELECT sum(salary), empid FROM emp WHERE empID IN (130);
>
> sum(salary) | empid
> -------------+--------
> 1110.1 | 130
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