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https://issues.apache.org/jira/browse/CASSANDRA-18060?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17637750#comment-17637750
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Berenguer Blasi commented on CASSANDRA-18060:
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LGTM +1
> Add aggregation scalar functions on collections
> -----------------------------------------------
>
> Key: CASSANDRA-18060
> URL: https://issues.apache.org/jira/browse/CASSANDRA-18060
> Project: Cassandra
> Issue Type: New Feature
> Components: CQL/Semantics
> Reporter: Andres de la Peña
> Assignee: Andres de la Peña
> Priority: Normal
> Time Spent: 1h
> Remaining Estimate: 0h
>
> The new mechanism for dynamically building native functions introduced by
> CASSANDRA-17811 can be used to provide within-collection aggregation
> functions. We can use that mechanism to add new CQL functions to get:
> * The number of items in a collection.
> * The max/min items of a collection.
> * The sum/avg of the items of a numeric collection.
> * The keys or the values of a map.
> For example:
> {code:java}
> CREATE TABLE k.t (k int PRIMARY KEY, l list<int>, m map<int, int>);
> INSERT INTO t(k, l, m) VALUES (0, [1, 2, 3], {1:10, 2:20, 3:30});
> > SELECT map_keys(m), map_values(m) FROM t;
> system.map_keys(m) | system.map_values(m)
> --------------------+----------------------
> {1, 2, 3} | [10, 20, 30]
> > SELECT collection_count(m), collection_count(l) FROM t;
> system.collection_count(m) | system.collection_count(l)
> ----------------------------+----------------------------
> 3 | 3
> > SELECT collection_min(l), collection_max(l) FROM t;
> system.collection_min(l) | system.collection_max(l)
> --------------------------+--------------------------
> 1 | 3
> > SELECT collection_sum(l), collection_avg(l) FROM t;
> system.collection_sum(l) | system.collection_avg(l)
> --------------------------+--------------------------
> 6 | 2
> {code}
> Note that this type of aggregation is different from the kind of aggregation
> provided by {{min}}, {{max}}, {{sum}} and {{avg}}, which aggregate entire
> collections across rows. Here we only aggregate the items of a collection row
> per row.
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