slim bouguerra created HIVE-19586:
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Summary: Optimize Count(distinct X) pushdown based on the storage
capabilities
Key: HIVE-19586
URL: https://issues.apache.org/jira/browse/HIVE-19586
Project: Hive
Issue Type: Improvement
Components: Druid integration, Logical Optimizer
Reporter: slim bouguerra
Assignee: slim bouguerra
Fix For: 3.0.0
h1. Goal
Provide a way to rewrite queries with combination of COUNT(Distinct) and
Aggregates like SUM as a series of Group By.
This can be useful to push down to Druid queries like
{code}
select count(DISTINCT interval_marker), count (distinct dim), sum(num_l) FROM
druid_test_table GROUP BY `__time`, `zone` ;
{code}
In general this can be useful to be used in cases where storage handlers can
not perform count (distinct column)
h1. How to do it.
Use the Calcite rule {code}
org.apache.calcite.rel.rules.AggregateExpandDistinctAggregatesRule{code} that
breaks down Count distinct to a single Group by with Grouping sets or multiple
series of Group by that might be linked with Joins if multiple counts are
present.
FYI today Hive does have a similar rule {code}
org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveExpandDistinctAggregatesRule{code},
but it only provides a rewrite to Grouping sets based plan.
I am planing to use the actual Calcite rule, [~ashutoshc] any concerns or
caveats to be aware of?
h2. Concerns/questions
Need to have a way to switch between Grouping sets or Simple chained group by
based on the plan cost. For instance for Druid based scan it makes always sense
(at least today) to push down a series of Group by and stitch result sets in
Hive later (as oppose to scan everything).
But this might be not true for other storage handler that can handle Grouping
sets it is better to push down the Grouping sets as one table scan.
Am still unsure how i can lean on the cost optimizer to select the best plan,
[~ashutoshc]/[~jcamachorodriguez] any inputs?
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