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Under memory pressure the Partial aggregate emits its groups early and continues with an empty table. The skip probe then paired the cumulative input rows with only the groups since the last emit, so it stayed below the ratio threshold even for unique keys and the stream kept hashing. Count the groups emitted early and pass them to the probe together with the groups still in the table, in both `PartialHashAggregateStream` and the legacy `GroupedHashAggregateStream`. Closes apache#27350
vinycalves
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Nov 12, 2026
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One logic question; no code suggestions.
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Could counting early-emitted groups make the probe skip a low-cardinality query before later duplicates reduce it? Is there a test for that?
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good question. I was actually thinking about the same yesterday, what would happen if high cardinality groups come first and break the pattern, planning to resume this today
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Which issue does this PR close?
Rationale for this change
Under memory pressure the Partial aggregate emits its groups early and continues with an empty table. The skip probe then compared all input rows with only the groups since the last emit, so it stayed below
skip_partial_aggregation_probe_ratio_thresholdeven for unique keys. The query sends the same rows downstream either way, but spends several times the Partial CPU hashing them.What changes are included in this PR?
PartialHashAggregateStreamand the legacyGroupedHashAggregateStreamcount the groups they emit early and pass them toSkipAggregationProbetogether with the groups still in the table. The sum is the output row count so far, so the probe measures the reduction the Partial actually achieves.What is the testing strategy for this PR?
test_partial_aggregation_skips_after_early_emitsruns both streams over unique keys with a memory limit that forces early emits before the probe threshold. Onmainboth skip 0 rows.datafusion-cliwith the query from the issue (2M unique keys,target_partitions = 2),AggregateExec: mode=Partial, 3 runs:mainemits / skipped / CPUmemory_limit = '4M'-m 16M --mem-pool-type fairWith 20M rows over 200K keys, 8 partitions and a fair 32M pool, Partial CPU drops from 345 ms to 46 ms. Queries that still reduce well under memory pressure (20K or 2K keys) keep aggregating.
Are there any user-facing changes?
No API changes. Memory-limited queries over high-cardinality keys now skip partial aggregation, as they already do without a limit.