Run single phase aggregation when possible #131485
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Hi @dnhatn, I've created a changelog YAML for you. |
elasticsearchmachine
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Pinging @elastic/es-analytical-engine (Team:Analytics) |
| rate_bytes_in:double | time_bucket:datetime | ||
| null | 2024-05-10T00:01:00.000Z | ||
| 28.80297619047619 | 2024-05-10T00:15:00.000Z | ||
| 28.802976190476194 | 2024-05-10T00:15:00.000Z |
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side effect of running a single-phase aggregation for avg
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Heya, cool stuff!
A little bit of a drive-by, but I noticed that there is opportunity for simplification, please have a look at my comment.
That said, I see that you requested review from @fang-xing-esql and @ivancea - folks, it'd be great if (one of) you could remain main reviewer, as I won't be able to deeply review this atm. Thank you :)
| * For example, in FROM .. | STATS first | STATS second, the STATS second aggregation | ||
| * can be executed in a single phase on the coordinator instead of two phases. | ||
| */ | ||
| public class SinglePhaseAggregate extends PhysicalOptimizerRules.OptimizerRule<AggregateExec> { |
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This should work, but it's actively working against code in the mapper that already distinguishes between "happens on the coordinator, only" vs. "happens partially on data nodes", see here.
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It looks good to me! The new rule looks sensible in any case. But as I understand it, what Alex comments would be the ideal way: Not splitting in phases to begin with, and splitting aggs only when needed.
Maybe this is ok too, as the rule can be easily removed later. But I would investigate the other way. I believe it will be quite more complex tho...
Edit: Btw, this was 3 months old? Did something change since then that enables this PR again, or was it just "forgotten" there?
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@alex-spies @ivancea I started with Mapper, but that class is quite fragile, so I added a separate rule instead. I will try to get this in for time-series soon, and then follow up by replacing the rule with changes in Mapper. Thanks for reviewing. |
I started this three months ago for time-series, but didn't spend much time on it since the difference was smaller. Now, the impact is more noticeable for low-latency queries and queries with large final results. |
Follow-up to #131485. Interestingly, the physical plan optimizer tests seem to pick up more cases when we map to a SINGLE agg directly.
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A STATS command following a reduce operation, such as another Stats, Limit, TopN, Inline Stats, or Fork, is executed on the coordinator and can be performed in a single phase. This is useful for time-series queries where we execute two aggregations: first per time-series, then across time-series.