feat: support SELECT DISTINCT id FROM t ORDER BY id LIMIT n query use GroupedTopKAggregateStream
#19653
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… GroupedTopKAggregateStream
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haohuaijin
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Jan 10, 2026
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| let mut cols = self.priority_map.emit()?; | ||
| // For DISTINCT case (no aggregate expressions), only use the group key column | ||
| // since the schema only has one field and key/value are the same | ||
| if self.aggregate_arguments.is_empty() { | ||
| cols.truncate(1); | ||
| } |
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we can further improve this part, because for the query
select distinct id from t order by id limit 10it do not have any aggregate, so we only need mantain the topk heap, and skip the group keys
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Thanks for your reviews @kosiew, already apply suggestion |
alamb
reviewed
Jan 16, 2026
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| /// Create deterministic data for DISTINCT benchmarks with predictable trace_ids | ||
| /// This ensures consistent results across benchmark runs | ||
| #[allow(dead_code)] |
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without this, clippy will have warn
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🤔 -- I am not sure why but maybe it has to do with feature flags or something
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I think it is code that is only used for benchmarks that I wasn't sure how else to allow. Perhaps it needs to be moved into the benchmark?
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Which issue does this PR close?
Rationale for this change
see issue #19638
What changes are included in this PR?
LimitOptionsstruct limit field with bothlimitand optionaldescendingordering directionTopKAggregationoptimizer rule to DISTINCT queries by recognizingGROUP BYqueries without aggregates and setting thedescendingflag based on ordering directionGroupedTopKAggregateStreamto handle DISTINCT by using group key as both priority queue key and value for DISTINCT operationsdescendingfield toAggLimitmessage for serialization/deserializationbenchmark result
Are these changes tested?
yes, add test case in aggregates_topk.slt
Are there any user-facing changes?
no