perf: Use DataFusion's `count_udaf` instead of `SUM(IF(expr IS NOT NULL, 1, 0))` by andygrove · Pull Request #2407 · apache/datafusion-comet

andygrove · 2025-09-16T16:47:28Z

Which issue does this PR close?

Rationale for this change

Use DataFusion's count_udaf instead of translating count(expr) to sum(if(expr is not null, 1, 0)).

When we tried to use count_udaf (about a year ago - see #744) we ran into performance issues, which is why we added the sum workaround, but this is no longer needed.

What changes are included in this PR?

How are these changes tested?

I ran CometAggregateSuite:

================================================================================================
Grouped Aggregate (single group key + single aggregate COUNT)
================================================================================================

OpenJDK 64-Bit Server VM 17.0.16+8-Ubuntu-0ubuntu122.04.1 on Linux 6.8.0-79-generic
AMD Ryzen 9 7950X3D 16-Core Processor
Grouped HashAgg Exec: single group key (cardinality 100), single aggregate COUNT:  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
----------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL Parquet - Spark (COUNT)                                                                 239            248          15         43.9          22.8       1.0X
SQL Parquet - Comet (COUNT)                                                                 191            195           3         54.9          18.2       1.2X

OpenJDK 64-Bit Server VM 17.0.16+8-Ubuntu-0ubuntu122.04.1 on Linux 6.8.0-79-generic
AMD Ryzen 9 7950X3D 16-Core Processor
Grouped HashAgg Exec: single group key (cardinality 1024), single aggregate COUNT:  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
-----------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL Parquet - Spark (COUNT)                                                                  239            248          15         43.9          22.8       1.0X
SQL Parquet - Comet (COUNT)                                                                  198            202           4         52.8          18.9       1.2X

OpenJDK 64-Bit Server VM 17.0.16+8-Ubuntu-0ubuntu122.04.1 on Linux 6.8.0-79-generic
AMD Ryzen 9 7950X3D 16-Core Processor
Grouped HashAgg Exec: single group key (cardinality 1048576), single aggregate COUNT:  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
--------------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL Parquet - Spark (COUNT)                                                                    2471           2472           1          4.2         235.7       1.0X
SQL Parquet - Comet (COUNT)                                                                    1043           1044           2         10.1          99.4       2.4X


================================================================================================
Grouped Aggregate (multiple group keys + single aggregate COUNT)
================================================================================================

OpenJDK 64-Bit Server VM 17.0.16+8-Ubuntu-0ubuntu122.04.1 on Linux 6.8.0-79-generic
AMD Ryzen 9 7950X3D 16-Core Processor
Grouped HashAgg Exec: multiple group keys (cardinality 100), single aggregate COUNT:  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
-------------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL Parquet - Spark (COUNT)                                                                    516            532          25         20.3          49.2       1.0X
SQL Parquet - Comet (COUNT)                                                                    263            269           5         39.9          25.0       2.0X

OpenJDK 64-Bit Server VM 17.0.16+8-Ubuntu-0ubuntu122.04.1 on Linux 6.8.0-79-generic
AMD Ryzen 9 7950X3D 16-Core Processor
Grouped HashAgg Exec: multiple group keys (cardinality 1024), single aggregate COUNT:  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
--------------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL Parquet - Spark (COUNT)                                                                    2811           2865          76          3.7         268.0       1.0X
SQL Parquet - Comet (COUNT)                                                                    1228           1236          11          8.5         117.1       2.3X

OpenJDK 64-Bit Server VM 17.0.16+8-Ubuntu-0ubuntu122.04.1 on Linux 6.8.0-79-generic
AMD Ryzen 9 7950X3D 16-Core Processor
Grouped HashAgg Exec: multiple group keys (cardinality 1048576), single aggregate COUNT:  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL Parquet - Spark (COUNT)                                                                       5837           5845          11          1.8         556.7       1.0X
SQL Parquet - Comet (COUNT)                                                                       4615           4727         158          2.3         440.2       1.3X


================================================================================================
Grouped Aggregate (single group key + multiple aggregates COUNT)
================================================================================================

OpenJDK 64-Bit Server VM 17.0.16+8-Ubuntu-0ubuntu122.04.1 on Linux 6.8.0-79-generic
AMD Ryzen 9 7950X3D 16-Core Processor
Grouped HashAgg Exec: single group key (cardinality 100), multiple aggregates COUNT:  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
-------------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL Parquet - Spark (COUNT)                                                                    307            320          27         34.2          29.3       1.0X
SQL Parquet - Comet (COUNT)                                                                    225            233           6         46.5          21.5       1.4X

OpenJDK 64-Bit Server VM 17.0.16+8-Ubuntu-0ubuntu122.04.1 on Linux 6.8.0-79-generic
AMD Ryzen 9 7950X3D 16-Core Processor
Grouped HashAgg Exec: single group key (cardinality 1024), multiple aggregates COUNT:  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
--------------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL Parquet - Spark (COUNT)                                                                     321            335          18         32.7          30.6       1.0X
SQL Parquet - Comet (COUNT)                                                                     240            253          10         43.7          22.9       1.3X

OpenJDK 64-Bit Server VM 17.0.16+8-Ubuntu-0ubuntu122.04.1 on Linux 6.8.0-79-generic
AMD Ryzen 9 7950X3D 16-Core Processor
Grouped HashAgg Exec: single group key (cardinality 1048576), multiple aggregates COUNT:  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL Parquet - Spark (COUNT)                                                                       2898           2926          40          3.6         276.4       1.0X
SQL Parquet - Comet (COUNT)                                                                       1440           1445           8          7.3         137.3       2.0X


================================================================================================
Grouped Aggregate (single group key + single aggregate COUNT on decimal)
================================================================================================

OpenJDK 64-Bit Server VM 17.0.16+8-Ubuntu-0ubuntu122.04.1 on Linux 6.8.0-79-generic
AMD Ryzen 9 7950X3D 16-Core Processor
Grouped HashAgg Exec: single group key (cardinality 100), single aggregate COUNT on decimal:  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL Parquet - Spark (COUNT)                                                                            295            309          25         35.5          28.2       1.0X
SQL Parquet - Comet (COUNT)                                                                            176            184           6         59.4          16.8       1.7X

OpenJDK 64-Bit Server VM 17.0.16+8-Ubuntu-0ubuntu122.04.1 on Linux 6.8.0-79-generic
AMD Ryzen 9 7950X3D 16-Core Processor
Grouped HashAgg Exec: single group key (cardinality 1024), single aggregate COUNT on decimal:  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL Parquet - Spark (COUNT)                                                                             308            311           4         34.0          29.4       1.0X
SQL Parquet - Comet (COUNT)                                                                             191            196           4         55.0          18.2       1.6X

OpenJDK 64-Bit Server VM 17.0.16+8-Ubuntu-0ubuntu122.04.1 on Linux 6.8.0-79-generic
AMD Ryzen 9 7950X3D 16-Core Processor
Grouped HashAgg Exec: single group key (cardinality 1048576), single aggregate COUNT on decimal:  Best Time(ms)   Avg Time(ms)   Stdev(ms)    Rate(M/s)   Per Row(ns)   Relative
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL Parquet - Spark (COUNT)                                                                               2473           2492          27          4.2         235.9       1.0X
SQL Parquet - Comet (COUNT)                                                                                989           1001          17         10.6          94.3       2.5X

codecov-commenter · 2025-09-16T17:11:42Z

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 57.52%. Comparing base (f09f8af) to head (a25f0a8).
⚠️ Report is 511 commits behind head on main.

Additional details and impacted files

@@             Coverage Diff              @@
##               main    #2407      +/-   ##
============================================
+ Coverage     56.12%   57.52%   +1.39%     
- Complexity      976     1296     +320     
============================================
  Files           119      147      +28     
  Lines         11743    13469    +1726     
  Branches       2251     2352     +101     
============================================
+ Hits           6591     7748    +1157     
- Misses         4012     4457     +445     
- Partials       1140     1264     +124

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andygrove · 2025-09-16T21:17:05Z

I ran TPC-H locally and saw no regression in performance

andygrove · 2025-09-16T21:19:29Z

-        benchmark.addCase(s"SQL Parquet - Comet (Scan) ($aggregateFunction)") { _ =>
-          withSQLConf(CometConf.COMET_ENABLED.key -> "true") {
-            spark.sql(query).noop()
-          }
-        }


It no longer makes sense to benchmark Comet with Scan vs Scan & Exec configurations, especially for aggregates. Comet scans won't accelerate aggregates.

mbutrovich

You know how I love a good negative line count. Thanks for following up on my comment in #2397. Glad to see we can rely on DF for this.

comphead

Thanks @andygrove it is nice removing unnecessary evaluations

andygrove · 2025-09-16T23:39:02Z

Merged. Thanks for the reviews @mbutrovich and @comphead

…LL, 1, 0))` (apache#2407)

andygrove added 4 commits September 16, 2025 08:59

refactor fuzz test

025d4bc

link to issue

6f0a12b

Use DF count_udaf

b2eec39

add test to CI

714e595

Merge remote-tracking branch 'apache/main' into use-df-count

9adad89

andygrove mentioned this pull request Sep 16, 2025

perf: Implement specialized aggregates for COUNT(*) and COUNT(expr) #2397

Closed

andygrove marked this pull request as ready for review September 16, 2025 20:56

andygrove requested review from comphead, mbutrovich and parthchandra September 16, 2025 20:58

andygrove added 2 commits September 16, 2025 15:17

update benchmark

ec0c9e2

update benchmark

a25f0a8

andygrove commented Sep 16, 2025

View reviewed changes

mbutrovich approved these changes Sep 16, 2025

View reviewed changes

comphead approved these changes Sep 16, 2025

View reviewed changes

andygrove merged commit 0e7c26b into apache:main Sep 16, 2025
136 of 137 checks passed

andygrove deleted the use-df-count branch September 16, 2025 23:38

comphead mentioned this pull request Sep 20, 2025

feat: do not fallback to Spark for COUNT(distinct) #2429

Merged

coderfender pushed a commit to coderfender/datafusion-comet that referenced this pull request Dec 13, 2025

perf: Use DataFusion's count_udaf instead of `SUM(IF(expr IS NOT NU…

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…LL, 1, 0))` (apache#2407)

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perf: Use DataFusion's `count_udaf` instead of `SUM(IF(expr IS NOT NULL, 1, 0))`#2407

perf: Use DataFusion's `count_udaf` instead of `SUM(IF(expr IS NOT NULL, 1, 0))`#2407
andygrove merged 7 commits intoapache:mainfrom
andygrove:use-df-count

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