Partial Partial Aggregates
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arXiv
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866910079369871360 |
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| author | Brisson, Claude |
| author_facet | Brisson, Claude |
| contents | We introduce partial partial aggregates (PPA), a query optimization technique for distributed engines that pushes only the local compute phase of an aggregate operation through joins. A query that aggregates after a join involves two logical operations, each requiring a network shuffle. Pushing a full aggregate (COMPUTE$\rightarrow$DISTRIBUTE$\rightarrow$MERGE) below the join introduces a third shuffle. In the specific case where the join key is included in the grouping key and the join is FK-PK, the full pushed aggregate can eliminate the top-level aggregate entirely, making it the preferred choice. In all other key configurations, the top aggregate must remain, and the extra shuffle is wasteful. A PPA pushes only COMPUTE, achieving data reduction before the join without the extra shuffle. The technique relies on the distributive property of aggregates and requires accurate NDV estimation for cost-based decisions. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2603_26698 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Partial Partial Aggregates Brisson, Claude Databases 68P15 We introduce partial partial aggregates (PPA), a query optimization technique for distributed engines that pushes only the local compute phase of an aggregate operation through joins. A query that aggregates after a join involves two logical operations, each requiring a network shuffle. Pushing a full aggregate (COMPUTE$\rightarrow$DISTRIBUTE$\rightarrow$MERGE) below the join introduces a third shuffle. In the specific case where the join key is included in the grouping key and the join is FK-PK, the full pushed aggregate can eliminate the top-level aggregate entirely, making it the preferred choice. In all other key configurations, the top aggregate must remain, and the extra shuffle is wasteful. A PPA pushes only COMPUTE, achieving data reduction before the join without the extra shuffle. The technique relies on the distributive property of aggregates and requires accurate NDV estimation for cost-based decisions. |
| title | Partial Partial Aggregates |
| topic | Databases 68P15 |
| url | https://arxiv.org/abs/2603.26698 |