Feat/hll dict size optimization clean by deeppatel710 · Pull Request #18144 · apache/pinot

deeppatel710 · 2026-04-09T07:28:41Z

Summary

Fixes the performance bottleneck in DISTINCTCOUNTHLL for dictionary-encoded columns with high cardinality (reported in #17336).

DISTINCTCOUNTHLL currently always accumulates dictionary IDs into a RoaringBitmap before converting to HLL at finalization. For high-cardinality columns
(14M+ distinct values), bitmap insertions dominate execution time at O(n log n), causing queries to take 6-10 seconds.

This adds an optional third argument dictSizeThreshold (default: 100,000). When dictionary.length() > dictSizeThreshold, dictionary values are offered
directly to the HyperLogLog, bypassing the bitmap entirely. Since DISTINCTCOUNTHLL already returns an approximate result, exact bitmap deduplication is
unnecessary — HLL handles duplicate offers gracefully.

The same root cause was fixed for DISTINCT_COUNT_SMART_HLL in #17411, which demonstrated 4x-10x CPU reduction for high-cardinality workloads. This PR
applies the equivalent optimization to the more commonly used DISTINCTCOUNTHLL function.

Usage

DISTINCTCOUNTHLL(col)             -- default threshold (100K)
DISTINCTCOUNTHLL(col, 12)         -- custom log2m, default threshold
DISTINCTCOUNTHLL(col, 12, 50000)  -- custom log2m and threshold     
DISTINCTCOUNTHLL(col, 12, 0)      -- disable optimization (threshold = Integer.MAX_VALUE)                                                                      

Changes                                                                                                                                                        
                                                          
- DistinctCountHLLAggregationFunction: added DEFAULT_DICT_SIZE_THRESHOLD = 100_000, _dictSizeThreshold field, optional 3rd constructor arg, and direct-HLL path
 in all 6 aggregation paths (non-group-by SV/MV, group-by SV/MV with SV/MV group keys)
- Tests: added 4 new test cases covering parameter defaults, custom threshold, disabled optimization, and correctness of direct-HLL path vs bitmap path        
                                                                                                                                                               
Test plan
                                                                                                                                                               
- All existing HLL tests pass                                                                                                                                  
- New tests verify parameter parsing and approximate correctness of direct-HLL path
- Manual benchmark against high-cardinality column (expected ~4-10x speedup matching #17411 results)

deeppatel710 · 2026-04-09T07:29:06Z

@Jackie-Jiang can you take a look at this optimization PR and leave a feedback please? Thanks

xiangfu0

Found one high-signal correctness issue; see inline comment.

xiangfu0 · 2026-04-11T13:02:57Z

    if (dictionary != null) {
      int[] dictIds = blockValSet.getDictionaryIdsSV();
-      getDictIdBitmap(aggregationResultHolder, dictionary).addN(dictIds, 0, length);
+      if (dictionary.length() > _dictSizeThreshold) {


This dictionary-size branch is not safe because the same aggregation result holder is reused across all scanned segments. If one segment stores a DictIdsWrapper and a later segment crosses the threshold, the next getHyperLogLog() call will cast the existing holder state to the wrong type and fail with ClassCastException. DISTINCTCOUNTHLL needs a stable holder representation here, or an explicit conversion when switching between bitmap-backed and direct-HLL aggregation.

Thanks for the review, @xiangfu0! Great catch on the type-safety concern.

You're right that mixing the bitmap and HLL paths in the same result holder is unsafe. To be precise about when this can bite: within a single consuming (realtime) segment, the dictionary grows as new data is ingested. If one doc-batch sees a dictionary below the threshold (stores DictIdsWrapper) and a subsequent batch on the same scan sees the grown dictionary above the threshold, getHyperLogLog() would cast the existing DictIdsWrapper to HyperLogLog and throw a ClassCastException.
The fix centralizes the defense in both getHyperLogLog() helpers — they now check instanceof DictIdsWrapper and convert to HyperLogLog before returning. This covers all 6 aggregation paths since they all funnel through these two methods. Added a regression test that simulates the dictionary-growth scenario directly.

codecov-commenter · 2026-04-12T08:09:17Z

Codecov Report

❌ Patch coverage is 88.23529% with 4 lines in your changes missing coverage. Please review.
✅ Project coverage is 63.39%. Comparing base (3eff094) to head (d243cad).
⚠️ Report is 61 commits behind head on master.

Files with missing lines	Patch %	Lines
.../function/DistinctCountHLLAggregationFunction.java	88.23%	4 Missing ⚠️

Additional details and impacted files

@@             Coverage Diff              @@
##             master   #18144      +/-   ##
============================================
- Coverage     63.48%   63.39%   -0.10%     
- Complexity     1627     1668      +41     
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  Branches      30540    30774     +234     
============================================
+ Hits         125306   125940     +634     
- Misses        62019    62660     +641     
- Partials      10040    10073      +33

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java-21	`63.39% <88.23%> (-0.08%)`	⬇️
temurin	`63.39% <88.23%> (-0.10%)`	⬇️
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unittests1	`55.34% <88.23%> (-0.13%)`	⬇️
unittests2	`34.91% <0.00%> (-0.07%)`	⬇️

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Jackie-Jiang

If the bottleneck is from poor performance of RoaringBitmap insertion, should we switch to a BitSet solution? Even with 1M cardinality, BitSet memory overhead is negligible (128KB). I believe the performance should be much better than directly aggregating HLL

deeppatel710 · 2026-04-14T05:40:42Z

@Jackie-Jiang
Thanks for the suggestion to switch to BitSet — after thinking through this more carefully, it's clearly the right call.

The root cause of the RoaringBitmap slowdown for high-cardinality dicts isn't just insertion count — it's the container-type transition that happens at ~4096 entries (ArrayContainer → BitmapContainer), which involves an O(n) copy of all existing entries. This makes random high-cardinality insertions particularly painful.

BitSet sidesteps this entirely: O(1) set() with no container management, and memory is a flat dictSize / 8 bytes (128 KB for a 1M-entry dict as you noted — negligible).

Also realized this allows us to remove the dictSizeThreshold complexity from the previous iteration entirely. The threshold was meant to avoid bitmap overhead by falling back to direct-HLL for large dicts but since HLL uses max-register semantics, offering the same hash twice has no effect. BitSet deduplication and direct-HLL insertion produce identical accuracy, so the optimization is always worthwhile with no
threshold knob needed.

Updated in the latest commit:

DictIdsWrapper now uses java.util.BitSet instead of RoaringBitmap
Function signature reverts to 1–2 arguments (column + optional log2m)
All threshold branches and the 3-arg constructor removed
Tests updated: removed threshold/bypass tests, added BitSet deduplication correctness, large-dict accuracy, and multi-batch accumulation tests

The Pinot Binary Compatibility Check failure is pre-existing on master and affects all open PRs currently (e.g. #18189). It's related to ColumnStatistics/MapColumnStatistics changes in pinot-segment-spi, which this PR doesn't touch.

…high-cardinality columns For dictionary-encoded columns with high cardinality (e.g., 14M+ distinct values), DISTINCTCOUNTHLL spent O(n log n) time inserting dictionary IDs into a RoaringBitmap before converting to HLL at finalization. This mirrors the performance issue originally reported for DISTINCTCOUNTSMARTHLL (fixed in apache#17411). This commit introduces an optional third argument `dictSizeThreshold` (default: 100,000). When the dictionary size exceeds the threshold, dictionary values are offered directly to the HyperLogLog without going through a RoaringBitmap first. Since DISTINCTCOUNTHLL already produces an approximate result, bitmap deduplication is not needed for correctness in high-cardinality scenarios — HLL handles duplicate offers gracefully. The optimization applies to all aggregation paths: - Non-group-by SV and MV - Group-by SV (both SV and MV group keys) - Group-by MV (both SV and MV group keys) Usage: DISTINCTCOUNTHLL(col) -- default threshold (100K) DISTINCTCOUNTHLL(col, 12) -- custom log2m, default threshold DISTINCTCOUNTHLL(col, 12, 50000) -- custom log2m and threshold DISTINCTCOUNTHLL(col, 12, 0) -- disable optimization (threshold = MAX_VALUE) Expected speedup for high-cardinality columns: 4x-10x, consistent with the benchmark results demonstrated for DISTINCTCOUNTSMARTHLL in apache#17411. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

…n DISTINCTCOUNTHLL In consuming (realtime) segments, the dictionary grows during ingestion. If a prior block used the bitmap path (dict size below threshold) and a later block sees the grown dictionary above the threshold, getHyperLogLog() would cast the existing DictIdsWrapper result to HyperLogLog and throw ClassCastException. Fix: check instanceof DictIdsWrapper in both getHyperLogLog() helpers and convert to HyperLogLog before returning, so the holder type always stays consistent regardless of when the threshold is crossed. Also adds a regression test that simulates this exact scenario. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

…ng test Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Switch DictIdsWrapper from RoaringBitmap to java.util.BitSet for deduplicating dictionary IDs before offering to HyperLogLog. BitSet gives O(1) set operations with no container-type transition overhead (RoaringBitmap transitions ArrayContainer→BitmapContainer at ~4096 entries, causing O(n) copies for random high-cardinality inserts). Memory overhead is dictSize/8 bytes (e.g. 128 KB for a 1M-entry dict), which is negligible compared to the segment data already in memory. This also removes the _dictSizeThreshold complexity introduced in the previous iteration. The threshold was added to avoid the RoaringBitmap overhead for large dicts by falling back to direct-HLL, but since HLL is idempotent (max-register semantics), deduplication via BitSet and direct-HLL insertion produce identical accuracy. With BitSet, the optimization is always beneficial and needs no threshold knob. Changes: - DictIdsWrapper now holds a BitSet instead of a RoaringBitmap - Removed _dictSizeThreshold, getDictSizeThreshold(), and the 3-arg constructor; function signature reverts to 1 or 2 arguments - Removed all threshold-branch logic from 6 aggregation methods - getDictIdBitmap() helper renamed to getDictIdBitSet() - convertToHyperLogLog() uses BitSet.nextSetBit() iteration - Updated tests: removed threshold/bypass tests, added BitSet deduplication correctness, large-dict, and multi-batch accumulation Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

…of per-group BitSet BitSet deduplication in aggregateSVGroupBySV/aggregateMVGroupBySV/aggregateSVGroupByMV/aggregateMVGroupByMV was allocating one BitSet(dictSize/8 bytes) per group. With 100K groups × 3M-entry dict → 37.5 GB → OOM. HyperLogLog uses max-register semantics so duplicate offer() calls are no-ops — deduplication before HLL is unnecessary for accuracy. For group-by, offers values directly to HLL. BitSet deduplication is kept only for the non-group-by aggregation path (one BitSet per segment, bounded and cheap). Also removes the now-unused getDictIdBitSet(GroupByResultHolder, int, Dictionary) helper and simplifies extractGroupByResult to remove the DictIdsWrapper branch that can no longer occur. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

…erLogLog per group HyperLogLog(log2m=14) pre-allocates ~16KB of registers upfront per group, regardless of how many distinct values that group actually sees. With many groups (e.g. numGroupsLimit=MAX_INT) and a high-cardinality group-by key, this causes OOM before the CPU kill threshold is reached. Restore the group-by dict-encoded path to use a RoaringBitmap (via new GroupByDictIdsWrapper), which is sparse: memory is proportional to the number of distinct dict IDs seen per group (~2 bytes each), not to 2^log2m. At extraction time, convert to HyperLogLog by iterating the bitmap once. The BitSet optimization (DictIdsWrapper) is preserved for the non-group-by aggregation path, where a single BitSet per segment is bounded and cheap (dictSize/8 bytes regardless of numGroups). Summary of design: - Non-group-by aggregation: ONE BitSet across full dict (fast, bounded) - Group-by: ONE RoaringBitmap per group (sparse, scales with cardinality) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

deeppatel710 · 2026-04-21T05:35:54Z

@xiangfu0 all checks have passed - can you review this PR? this could be a massive improvement

deeppatel710 · 2026-04-21T06:05:54Z

Binary Compatibility Check Failure — Pre-existing on Master

The pinot-segment-spi compat failure (ColumnStatistics/MapColumnStatistics) is not caused by this PR.

It was introduced by PR #18170 ("Refactor ColumnStatistics: clean up interface, add isAscii"), merged to master on Apr 12. Our branch has zero diff against master for pinot-segment-spi:

git diff apache/master -- pinot-segment-spi/

→ no output.

This failure will affect every PR rebased on current master until the compat issue in master is resolved.

Jackie-Jiang

Nice

Jackie-Jiang · 2026-04-22T02:43:41Z

+   * Uses a {@link RoaringBitmap} (sparse) so memory scales with distinct values per group, not dictionary size.
   */
-  protected static RoaringBitmap getDictIdBitmap(AggregationResultHolder aggregationResultHolder,
+  protected static GroupByDictIdsWrapper getDictIdBitmap(GroupByResultHolder groupByResultHolder, int groupKey,


Consider directly returning the RoaringBitmap to align with the method name and be more explicit

Done — both getDictIdBitmap and getDictIdBitSet now return RoaringBitmap and BitSet directly. The wrappers (GroupByDictIdsWrapper / DictIdsWrapper) are still stored in the result holder so the dictionary is available at extraction time, but the helper methods now return the inner data structure directly, matching the pattern in BaseDistinctAggregateAggregationFunction. The now-unused helper methods (add, addDictIds, set) were removed from both wrapper classes.

Jackie-Jiang · 2026-04-22T02:43:50Z

+  /**
+   * Returns the {@link DictIdsWrapper} from the result holder, creating a new one if absent.
+   */
+  protected static DictIdsWrapper getDictIdBitSet(AggregationResultHolder aggregationResultHolder,


Consider directly returning the BitSet to align with the method name and be more explicit

Done — same as above.

@Jackie-Jiang can you merge this too? Thanks

Jackie-Jiang · 2026-04-23T07:47:26Z

@deeppatel710 Did you push the change?

…tmap/getDictIdBitSet - getDictIdBitmap now returns wrapper._dictIdBitmap (RoaringBitmap) directly - getDictIdBitSet now returns dictIdsWrapper._bitSet (BitSet) directly - Removed now-unused helper methods from DictIdsWrapper and GroupByDictIdsWrapper - Updated all call sites to use the raw types directly - Test: assert reference equality in batch-reuse test to directly verify wrapper reuse Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

deeppatel710 · 2026-04-26T08:12:08Z

@Jackie-Jiang sorry, missed that commit. Just pushed! Can you review it? Thanks

xiangfu0 reviewed Apr 11, 2026

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Jackie-Jiang added the enhancement Improvement to existing functionality label Apr 11, 2026

Jackie-Jiang reviewed Apr 13, 2026

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Deep Patel and others added 7 commits April 19, 2026 19:10

docs: clarify dictSizeThreshold default value rationale in comment

cac3eba

Improve test: remove fragile class-name assertion in threshold-crossi…

9629ff4

…ng test Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

ci: retrigger integration tests (flaky test in Set 1 temurin-11)

ab75335

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

deeppatel710 force-pushed the feat/hll-dict-size-optimization-clean branch from 271b095 to 86fd8d7 Compare April 20, 2026 02:12

Jackie-Jiang approved these changes Apr 22, 2026

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deeppatel710 requested a review from xiangfu0 April 22, 2026 06:15

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deeppatel710 commented Apr 9, 2026

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