feat: support col reference for percentiles by dd-annarose · Pull Request #25337 · apache/datafusion

dd-annarose · 2026-09-15T17:37:19Z

Which issue does this PR close?

Closes Support column reference as percentile arg for percentile_cont and approx_percentile_cont #24337.

Rationale for this change

When using a projection as the percentile argument to approx_percentile_cont or percentile_cont, planning fails because only literals are supported.

It makes sense to accept projections that are constant across all batches but not labelled as literals (although they practically are).

For example, this query cannot be planned, even though the percentile is constant:

SELECT
    approx_percentile_cont(y, m) AS median
FROM (
    SELECT t.x + 1 as y, 0.5 as m
    FROM (
        VALUES (10)
    ) AS t(x)
)

What changes are included in this PR?

Introduce PercentileParam and PercentileParamState to handle column references or projections for the percentile argument.

Resolution of percentile cannot always be done: for example, on an empty record batch, we won't be able to get the value from the columns. PercentileParamState makes sure the percentile resolution is both flexible enough to wait to be able to resolve the parameter AND applies the strict constraints that are required (constant Float32 or Float64).

The percentile is also included in state fields so that the merge_batch in the final Accumulator can process without any issues.

What is the testing strategy for this PR?

This new feature is covered by the sqllogictest cases added in aggregate.slt.

Unit tests have also been added to approx_percentile_cont.rs and percentile_cont.rs.

Are there any user-facing changes?

No breaking changes.

Benchark: ClickBench

Query	main	annarose_approx_percentile	Change
QQuery 0	0.73 ms	0.79 ms	1.08x slower
QQuery 1	8.10 ms	8.91 ms	1.10x slower
QQuery 2	27.90 ms	30.59 ms	1.10x slower
QQuery 3	23.27 ms	23.89 ms	no change
QQuery 4	157.25 ms	157.70 ms	no change
QQuery 5	197.65 ms	201.26 ms	no change
QQuery 6	0.72 ms	0.67 ms	+1.08x faster
QQuery 7	8.20 ms	8.28 ms	no change
QQuery 8	230.84 ms	215.32 ms	+1.07x faster
QQuery 9	296.27 ms	312.37 ms	1.05x slower
QQuery 10	49.12 ms	47.66 ms	no change
QQuery 11	58.86 ms	55.26 ms	+1.07x faster
QQuery 12	198.45 ms	192.95 ms	no change
QQuery 13	285.28 ms	280.02 ms	no change
QQuery 14	195.67 ms	204.80 ms	no change
QQuery 15	184.29 ms	180.74 ms	no change
QQuery 16	434.20 ms	457.81 ms	1.05x slower
QQuery 17	476.52 ms	427.84 ms	+1.11x faster
QQuery 18	912.71 ms	881.69 ms	no change
QQuery 19	18.14 ms	19.41 ms	1.07x slower
QQuery 20	456.87 ms	463.23 ms	no change
QQuery 21	468.67 ms	482.15 ms	no change
QQuery 22	892.28 ms	896.13 ms	no change
QQuery 23	2520.93 ms	2558.49 ms	no change
QQuery 24	34.14 ms	33.50 ms	no change
QQuery 25	99.14 ms	99.83 ms	no change
QQuery 26	35.25 ms	34.51 ms	no change
QQuery 27	467.74 ms	484.36 ms	no change
QQuery 28	1931.71 ms	1945.50 ms	no change
QQuery 29	29.16 ms	30.35 ms	no change
QQuery 30	214.69 ms	209.17 ms	no change
QQuery 31	196.43 ms	199.65 ms	no change
QQuery 32	583.78 ms	614.36 ms	1.05x slower
QQuery 33	1078.73 ms	1145.79 ms	1.06x slower
QQuery 34	1073.15 ms	1117.56 ms	no change
QQuery 35	182.87 ms	171.52 ms	+1.07x faster
QQuery 36	46.27 ms	47.18 ms	no change
QQuery 37	24.27 ms	24.03 ms	no change
QQuery 38	29.58 ms	29.76 ms	no change
QQuery 39	85.29 ms	86.14 ms	no change
QQuery 40	8.23 ms	8.41 ms	no change
QQuery 41	8.12 ms	8.47 ms	no change
QQuery 42	6.72 ms	6.81 ms	no change

Benchmark Summary
Total Time (main)	14238.19ms
Total Time (annarose_approx_percentile)	14404.87ms
Average Time (main)	331.12ms
Average Time (annarose_approx_percentile)	335.00ms
Queries Faster	5
Queries Slower	8
Queries with No Change	30
Queries with Failure	0

Memory profiling for clickbench_partitioned

this branch

Query	Time (ms)	Peak RSS	Peak Commit	Major Page Faults
0	5.43	84.0 MB	171.8 MB	0
1	11.45	119.6 MB	313.9 MB	0
2	27.44	240.8 MB	1536.1 MB	0
3	30.52	412.3 MB	1227.9 MB	0
4	173.88	2.8 GB	3.2 GB	0
5	193.60	2.5 GB	2.9 GB	0
6	3.36	93.0 MB	167.9 MB	0
7	10.66	128.1 MB	318.8 MB	0
8	219.80	3.4 GB	4.1 GB	0
9	268.65	2.4 GB	3.2 GB	0
10	45.84	780.3 MB	1809.8 MB	0
11	52.68	788.7 MB	1800.9 MB	0
12	183.80	2.5 GB	2.9 GB	0
13	266.55	3.0 GB	3.5 GB	0
14	191.93	2.4 GB	3.2 GB	0
15	185.03	3.0 GB	3.3 GB	0
16	422.42	6.4 GB	7.1 GB	0
17	404.75	6.1 GB	6.9 GB	0
18	861.29	12.2 GB	13.1 GB	0
19	19.20	362.3 MB	1118.0 MB	24
20	442.22	1171.1 MB	1429.2 MB	0
21	407.55	1836.8 MB	2.1 GB	0
22	763.73	2.5 GB	2.8 GB	0
23	2313.37	4.8 GB	5.5 GB	0
24	33.92	569.7 MB	959.2 MB	5
25	82.99	798.0 MB	1517.9 MB	0
26	35.10	599.1 MB	986.8 MB	0
27	392.34	1234.9 MB	1455.8 MB	0
28	1714.18	2.5 GB	2.7 GB	0
29	28.43	229.9 MB	1497.1 MB	0
30	191.47	2.2 GB	3.3 GB	0
31	182.56	2.8 GB	3.7 GB	0
32	1263.74	13.3 GB	16.2 GB	0
33	958.16	10.7 GB	10.9 GB	5
34	956.65	10.6 GB	10.9 GB	0
35	171.08	2.1 GB	2.6 GB	0
36	47.33	452.0 MB	800.8 MB	0
37	26.89	229.4 MB	544.9 MB	0
38	33.62	270.9 MB	503.8 MB	0
39	90.83	756.9 MB	1062.6 MB	0
40	11.41	208.3 MB	433.3 MB	0
41	11.47	170.3 MB	393.8 MB	0
42	10.48	142.8 MB	265.1 MB	0

main

Query	Time (ms)	Peak RSS	Peak Commit	Major Page Faults
0	4.76	94.7 MB	171.5 MB	0
1	11.22	120.7 MB	296.7 MB	0
2	32.05	244.2 MB	1533.8 MB	0
3	24.33	417.7 MB	1229.2 MB	0
4	175.85	2.8 GB	3.2 GB	0
5	207.07	2.5 GB	3.0 GB	0
6	3.46	94.3 MB	171.6 MB	0
7	11.08	129.4 MB	323.5 MB	0
8	223.08	3.4 GB	4.1 GB	0
9	288.63	2.4 GB	3.4 GB	0
10	48.79	792.1 MB	1767.0 MB	0
11	53.32	760.8 MB	1779.6 MB	0
12	189.17	2.6 GB	3.1 GB	0
13	274.96	3.0 GB	3.7 GB	0
14	202.74	2.6 GB	3.3 GB	0
15	208.83	3.0 GB	3.4 GB	0
16	576.37	6.3 GB	7.1 GB	0
17	623.87	6.5 GB	7.3 GB	0
18	1140.54	11.3 GB	13.1 GB	0
19	21.20	370.8 MB	1124.9 MB	26
20	507.91	1149.3 MB	1364.8 MB	0
21	479.85	1824.8 MB	2.1 GB	0
22	914.26	2.3 GB	2.7 GB	0
23	2757.47	4.6 GB	5.3 GB	0
24	41.85	591.0 MB	999.1 MB	0
25	91.00	763.3 MB	1500.8 MB	0
26	38.90	560.1 MB	980.6 MB	0
27	506.23	1319.5 MB	1550.4 MB	0
28	2119.47	2.6 GB	2.7 GB	0
29	34.79	213.7 MB	1267.2 MB	0
30	218.63	2.1 GB	3.1 GB	0
31	212.42	2.8 GB	3.7 GB	0
32	821.63	13.0 GB	16.1 GB	0
33	1162.42	10.5 GB	10.7 GB	14
34	1212.91	10.4 GB	10.6 GB	0
35	184.71	2.0 GB	2.5 GB	0
36	58.35	469.5 MB	845.9 MB	0
37	30.78	240.2 MB	545.1 MB	0
38	35.43	287.3 MB	485.4 MB	0
39	92.89	730.8 MB	1074.5 MB	0
40	11.87	204.7 MB	420.5 MB	0
41	11.43	171.2 MB	401.5 MB	0
42	10.57	146.6 MB	275.6 MB	0

github-actions · 2026-09-15T17:53:55Z

Thank you for opening this pull request!

Reviewer note: cargo-semver-checks reported the current version number is not SemVer-compatible with the changes in this pull request (compared against the base branch).

Details

     Cloning apache/main
    Building datafusion-functions-aggregate v55.1.0 (current)
       Built [  21.574s] (current)
     Parsing datafusion-functions-aggregate v55.1.0 (current)
      Parsed [   0.040s] (current)
    Building datafusion-functions-aggregate v55.1.0 (baseline)
       Built [  21.407s] (baseline)
     Parsing datafusion-functions-aggregate v55.1.0 (baseline)
      Parsed [   0.042s] (baseline)
    Checking datafusion-functions-aggregate v55.1.0 -> v55.1.0 (no change; assume patch)
     Checked [   0.142s] 229 checks: 228 pass, 1 fail, 0 warn, 31 skip

--- failure inherent_method_missing: pub method removed or renamed ---

Description:
A publicly-visible method or associated fn is no longer available under its prior name. It may have been renamed or removed entirely.
        ref: https://doc.rust-lang.org/cargo/reference/semver.html#item-remove
       impl: https://github.com/obi1kenobi/cargo-semver-checks/tree/v0.51.0/src/lints/inherent_method_missing.ron

Failed in:
  ApproxPercentileAccumulator::new_with_max_size, previously in file /home/runner/work/datafusion/datafusion/target/semver-checks/git-apache_main/aed9fa7af498a4f7de16022fefffc307fefd25b3/datafusion/functions-aggregate/src/approx_percentile_cont.rs:353

     Summary semver requires new major version: 1 major and 0 minor checks failed
    Finished [  45.024s] datafusion-functions-aggregate
    Building datafusion-sqllogictest v55.1.0 (current)
       Built [  65.621s] (current)
     Parsing datafusion-sqllogictest v55.1.0 (current)
      Parsed [   0.014s] (current)
    Building datafusion-sqllogictest v55.1.0 (baseline)
       Built [  63.058s] (baseline)
     Parsing datafusion-sqllogictest v55.1.0 (baseline)
      Parsed [   0.013s] (baseline)
    Checking datafusion-sqllogictest v55.1.0 -> v55.1.0 (no change; assume patch)
     Checked [   0.065s] 229 checks: 229 pass, 31 skip
     Summary no semver update required
    Finished [ 134.068s] datafusion-sqllogictest

codecov-commenter · 2026-09-15T18:12:44Z

Codecov Report

❌ Patch coverage is 88.29114% with 37 lines in your changes missing coverage. Please review.
✅ Project coverage is 82.93%. Comparing base (862843f) to head (97a173f).
⚠️ Report is 28 commits behind head on main.

Files with missing lines	Patch %	Lines
datafusion/functions-aggregate/src/utils.rs	82.69%	13 Missing and 5 partials ⚠️
...afusion/functions-aggregate/src/percentile_cont.rs	88.51%	4 Missing and 13 partials ⚠️
.../functions-aggregate/src/approx_percentile_cont.rs	95.65%	1 Missing and 1 partial ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main   #25337      +/-   ##
==========================================
+ Coverage   82.91%   82.93%   +0.02%     
==========================================
  Files        1155     1154       -1     
  Lines      458091   458258     +167     
  Branches   458091   458258     +167     
==========================================
+ Hits       379821   380069     +248     
+ Misses      55231    55148      -83     
- Partials    23039    23041       +2

☔ View full report in Codecov by Harness.
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alamb

Thanks @dd-annarose
Can we do this at planning time instead? that would likely be must faster as it wouldn't have to inspect the inputs.

In the example you showed

SELECT
    approx_percentile_cont(y, m) AS median
FROM (
    SELECT t.x + 1 as y, 0.5 as m
    FROM (
        VALUES (10)
    ) AS t(x)
)

I think the subquery could be flattened to

SELECT
    approx_percentile_cont(t.x + 1, 0.5) AS median
    FROM 
    VALUES (10)

( in fact I am surprised it isn't)

dd-annarose · 2026-09-16T08:34:44Z

@alamb We could, but we wouldn't support queries like this one (supported by Trino for example):

SELECT approx_percentile(x, m)
FROM (VALUES (10,0.1),(20,0.5),(30,0.9),(40,0.5)) AS t(x,m)

I don't have a Trino parity agenda, but this can be used more broadly when wanting to use a "real" column reference as percentile.

Happy to discuss!

dd-annarose · 2026-09-17T15:38:40Z

Also: this is supported by spark

asolimando

@dd-annarose thanks for working on this, I think it's good to support expressions beyond literals, as Postgres, Spark and Trino do. I left two comments, one minor potential perf improvement, and one blocking issue/error, the rest LGTM!

asolimando

LGTM!

dd-annarose · 2026-09-28T14:12:23Z

@Jefffrey @alamb does it make more sense now? happy to provide more context!

Adds a PercentileParam and PercentileParamState to accept column references or projections for the percentile argument. # Conflicts: # datafusion/functions-aggregate/src/percentile_cont.rs

replace non-deterministic metrics with <slt:ignore>

gabotechs · 2026-10-05T11:42:33Z

run benchmark clickbench_partitioned

adriangbot · 2026-10-05T11:45:38Z

🤖 Benchmark running (GKE) | trigger
Instance: c4a-highmem-16 (12 vCPU / 65 GiB) | Linux bench-c5993730557-3058-6slkh 6.12.94+ #1 SMP Fri Aug 21 08:00:16 UTC 2026 aarch64 GNU/Linux

CPU Details (lscpu)

Architecture:                            aarch64
CPU op-mode(s):                          64-bit
Byte Order:                              Little Endian
CPU(s):                                  16
On-line CPU(s) list:                     0-15
Vendor ID:                               ARM
Model name:                              Neoverse-V2
Model:                                   1
Thread(s) per core:                      1
Core(s) per cluster:                     16
Socket(s):                               -
Cluster(s):                              1
Stepping:                                r0p1
BogoMIPS:                                2000.00
Flags:                                   fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh rng bti
L1d cache:                               1 MiB (16 instances)
L1i cache:                               1 MiB (16 instances)
L2 cache:                                32 MiB (16 instances)
L3 cache:                                80 MiB (1 instance)
NUMA node(s):                            1
NUMA node0 CPU(s):                       0-15
Vulnerability Gather data sampling:      Not affected
Vulnerability Indirect target selection: Not affected
Vulnerability Itlb multihit:             Not affected
Vulnerability L1tf:                      Not affected
Vulnerability Mds:                       Not affected
Vulnerability Meltdown:                  Not affected
Vulnerability Mmio stale data:           Not affected
Vulnerability Reg file data sampling:    Not affected
Vulnerability Retbleed:                  Not affected
Vulnerability Spec rstack overflow:      Not affected
Vulnerability Spec store bypass:         Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:                Mitigation; __user pointer sanitization
Vulnerability Spectre v2:                Mitigation; CSV2, BHB
Vulnerability Srbds:                     Not affected
Vulnerability Tsa:                       Not affected
Vulnerability Tsx async abort:           Not affected
Vulnerability Vmscape:                   Not affected

Comparing annarose/approx_percentile (44a9b2b) to d040501 (merge-base) diff

Run configuration

run benchmark clickbench_partitioned

Results will be posted here when complete

File an issue against this benchmark runner

adriangbot · 2026-10-05T12:00:34Z

🤖 Benchmark completed (GKE) | trigger

Instance: c4a-highmem-16 (12 vCPU / 65 GiB)

Comparing annarose/approx_percentile (44a9b2b) to d040501 (merge-base) diff

Run configuration

run benchmark clickbench_partitioned

CPU Details (lscpu)

Architecture:                            aarch64
CPU op-mode(s):                          64-bit
Byte Order:                              Little Endian
CPU(s):                                  16
On-line CPU(s) list:                     0-15
Vendor ID:                               ARM
Model name:                              Neoverse-V2
Model:                                   1
Thread(s) per core:                      1
Core(s) per cluster:                     16
Socket(s):                               -
Cluster(s):                              1
Stepping:                                r0p1
BogoMIPS:                                2000.00
Flags:                                   fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh rng bti
L1d cache:                               1 MiB (16 instances)
L1i cache:                               1 MiB (16 instances)
L2 cache:                                32 MiB (16 instances)
L3 cache:                                80 MiB (1 instance)
NUMA node(s):                            1
NUMA node0 CPU(s):                       0-15
Vulnerability Gather data sampling:      Not affected
Vulnerability Indirect target selection: Not affected
Vulnerability Itlb multihit:             Not affected
Vulnerability L1tf:                      Not affected
Vulnerability Mds:                       Not affected
Vulnerability Meltdown:                  Not affected
Vulnerability Mmio stale data:           Not affected
Vulnerability Reg file data sampling:    Not affected
Vulnerability Retbleed:                  Not affected
Vulnerability Spec rstack overflow:      Not affected
Vulnerability Spec store bypass:         Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:                Mitigation; __user pointer sanitization
Vulnerability Spectre v2:                Mitigation; CSV2, BHB
Vulnerability Srbds:                     Not affected
Vulnerability Tsa:                       Not affected
Vulnerability Tsx async abort:           Not affected
Vulnerability Vmscape:                   Not affected

Details

Comparing HEAD and annarose_approx_percentile
--------------------
Benchmark clickbench_partitioned.json
--------------------
┏━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ Query     ┃       HEAD ┃ annarose_approx_percentile ┃        Change ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ QQuery 0  │    1.25 ms │                    1.23 ms │     no change │
│ QQuery 1  │   11.63 ms │                   11.73 ms │     no change │
│ QQuery 2  │   36.35 ms │                   36.73 ms │     no change │
│ QQuery 3  │   30.96 ms │                   31.85 ms │     no change │
│ QQuery 4  │  231.67 ms │                  236.76 ms │     no change │
│ QQuery 5  │  270.09 ms │                  273.28 ms │     no change │
│ QQuery 6  │    1.30 ms │                    1.27 ms │     no change │
│ QQuery 7  │   12.64 ms │                   12.75 ms │     no change │
│ QQuery 8  │  328.69 ms │                  329.59 ms │     no change │
│ QQuery 9  │  466.34 ms │                  470.37 ms │     no change │
│ QQuery 10 │   65.17 ms │                   63.71 ms │     no change │
│ QQuery 11 │   75.86 ms │                   75.02 ms │     no change │
│ QQuery 12 │  262.45 ms │                  264.52 ms │     no change │
│ QQuery 13 │  353.11 ms │                  367.19 ms │     no change │
│ QQuery 14 │  277.00 ms │                  278.92 ms │     no change │
│ QQuery 15 │  281.81 ms │                  286.09 ms │     no change │
│ QQuery 16 │  610.11 ms │                  617.44 ms │     no change │
│ QQuery 17 │  616.43 ms │                  629.67 ms │     no change │
│ QQuery 18 │ 1276.58 ms │                 1261.09 ms │     no change │
│ QQuery 19 │   27.38 ms │                   27.48 ms │     no change │
│ QQuery 20 │  515.48 ms │                  518.18 ms │     no change │
│ QQuery 21 │  512.22 ms │                  514.47 ms │     no change │
│ QQuery 22 │  995.86 ms │                 1002.17 ms │     no change │
│ QQuery 23 │ 3042.22 ms │                 3138.95 ms │     no change │
│ QQuery 24 │   40.65 ms │                   41.47 ms │     no change │
│ QQuery 25 │  105.24 ms │                  104.68 ms │     no change │
│ QQuery 26 │   41.09 ms │                   41.11 ms │     no change │
│ QQuery 27 │  513.20 ms │                  508.68 ms │     no change │
│ QQuery 28 │ 2908.79 ms │                 2878.27 ms │     no change │
│ QQuery 29 │   41.13 ms │                   41.63 ms │     no change │
│ QQuery 30 │  305.42 ms │                  301.71 ms │     no change │
│ QQuery 31 │  276.10 ms │                  275.67 ms │     no change │
│ QQuery 32 │ 1104.73 ms │                  976.69 ms │ +1.13x faster │
│ QQuery 33 │ 1593.01 ms │                 1545.86 ms │     no change │
│ QQuery 34 │ 1582.18 ms │                 1598.09 ms │     no change │
│ QQuery 35 │  296.53 ms │                  295.63 ms │     no change │
│ QQuery 36 │   67.24 ms │                   67.98 ms │     no change │
│ QQuery 37 │   35.69 ms │                   35.16 ms │     no change │
│ QQuery 38 │   44.38 ms │                   40.06 ms │ +1.11x faster │
│ QQuery 39 │  138.45 ms │                  134.94 ms │     no change │
│ QQuery 40 │   14.78 ms │                   14.33 ms │     no change │
│ QQuery 41 │   13.64 ms │                   13.67 ms │     no change │
│ QQuery 42 │   13.31 ms │                   13.04 ms │     no change │
└───────────┴────────────┴────────────────────────────┴───────────────┘
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓
┃ Benchmark Summary                         ┃            ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩
│ Total Time (HEAD)                         │ 19438.18ms │
│ Total Time (annarose_approx_percentile)   │ 19379.16ms │
│ Average Time (HEAD)                       │   452.05ms │
│ Average Time (annarose_approx_percentile) │   450.68ms │
│ Queries Faster                            │          2 │
│ Queries Slower                            │          0 │
│ Queries with No Change                    │         41 │
│ Queries with Failure                      │          0 │
└───────────────────────────────────────────┴────────────┘

Distribution per query (min / mean ±stddev / max):

Comparing HEAD and annarose_approx_percentile
--------------------
Benchmark clickbench_partitioned.json
--------------------
┏━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ Query     ┃                                   HEAD ┃             annarose_approx_percentile ┃        Change ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ QQuery 0  │           1.25 / 3.98 ±5.37 / 14.72 ms │           1.23 / 4.03 ±5.50 / 15.02 ms │     no change │
│ QQuery 1  │         11.63 / 11.73 ±0.10 / 11.91 ms │         11.73 / 11.86 ±0.08 / 11.94 ms │     no change │
│ QQuery 2  │         36.35 / 36.55 ±0.15 / 36.76 ms │         36.73 / 36.97 ±0.14 / 37.13 ms │     no change │
│ QQuery 3  │         30.96 / 31.80 ±1.05 / 33.82 ms │         31.85 / 32.51 ±0.68 / 33.81 ms │     no change │
│ QQuery 4  │      231.67 / 235.24 ±3.93 / 242.51 ms │      236.76 / 238.43 ±2.45 / 243.24 ms │     no change │
│ QQuery 5  │      270.09 / 271.89 ±1.67 / 274.58 ms │      273.28 / 277.86 ±3.10 / 282.34 ms │     no change │
│ QQuery 6  │            1.30 / 1.44 ±0.23 / 1.90 ms │            1.27 / 1.43 ±0.24 / 1.89 ms │     no change │
│ QQuery 7  │         12.64 / 12.76 ±0.12 / 12.95 ms │         12.75 / 12.93 ±0.14 / 13.10 ms │     no change │
│ QQuery 8  │      328.69 / 332.81 ±4.76 / 341.05 ms │      329.59 / 336.81 ±5.99 / 345.91 ms │     no change │
│ QQuery 9  │      466.34 / 472.81 ±4.89 / 480.71 ms │      470.37 / 480.10 ±6.81 / 489.86 ms │     no change │
│ QQuery 10 │         65.17 / 65.94 ±0.96 / 67.75 ms │         63.71 / 65.09 ±1.33 / 67.59 ms │     no change │
│ QQuery 11 │         75.86 / 76.33 ±0.38 / 76.89 ms │         75.02 / 75.69 ±0.91 / 77.42 ms │     no change │
│ QQuery 12 │      262.45 / 265.63 ±2.02 / 268.77 ms │      264.52 / 271.56 ±4.90 / 279.50 ms │     no change │
│ QQuery 13 │     353.11 / 375.13 ±19.08 / 408.32 ms │     367.19 / 375.94 ±10.67 / 396.25 ms │     no change │
│ QQuery 14 │      277.00 / 283.75 ±5.02 / 289.34 ms │      278.92 / 285.79 ±4.23 / 290.47 ms │     no change │
│ QQuery 15 │      281.81 / 290.57 ±7.06 / 300.45 ms │      286.09 / 290.81 ±4.28 / 298.42 ms │     no change │
│ QQuery 16 │      610.11 / 622.83 ±8.06 / 632.82 ms │      617.44 / 633.32 ±9.69 / 644.78 ms │     no change │
│ QQuery 17 │      616.43 / 628.82 ±8.71 / 640.43 ms │      629.67 / 639.66 ±8.38 / 650.94 ms │     no change │
│ QQuery 18 │  1276.58 / 1306.48 ±30.03 / 1356.12 ms │  1261.09 / 1291.43 ±26.11 / 1330.69 ms │     no change │
│ QQuery 19 │        27.38 / 35.16 ±15.03 / 65.21 ms │         27.48 / 28.16 ±0.62 / 29.21 ms │ +1.25x faster │
│ QQuery 20 │      515.48 / 524.27 ±8.88 / 540.65 ms │      518.18 / 523.91 ±6.82 / 537.00 ms │     no change │
│ QQuery 21 │      512.22 / 521.15 ±5.84 / 529.96 ms │      514.47 / 523.46 ±5.00 / 528.73 ms │     no change │
│ QQuery 22 │    995.86 / 1004.29 ±6.90 / 1010.88 ms │  1002.17 / 1021.39 ±18.75 / 1053.91 ms │     no change │
│ QQuery 23 │ 3042.22 / 3230.03 ±105.29 / 3356.72 ms │ 3138.95 / 3382.75 ±319.54 / 4007.22 ms │     no change │
│ QQuery 24 │      40.65 / 124.24 ±80.11 / 246.24 ms │         41.47 / 43.65 ±2.13 / 47.67 ms │ +2.85x faster │
│ QQuery 25 │     105.24 / 145.07 ±77.25 / 299.56 ms │      104.68 / 105.53 ±0.54 / 106.17 ms │ +1.37x faster │
│ QQuery 26 │         41.09 / 42.48 ±1.44 / 45.04 ms │         41.11 / 41.32 ±0.20 / 41.67 ms │     no change │
│ QQuery 27 │      513.20 / 519.40 ±5.71 / 527.56 ms │     508.68 / 534.81 ±22.52 / 576.49 ms │     no change │
│ QQuery 28 │  2908.79 / 2922.57 ±16.02 / 2952.02 ms │  2878.27 / 2934.14 ±54.45 / 3026.51 ms │     no change │
│ QQuery 29 │         41.13 / 44.13 ±5.13 / 54.37 ms │        41.63 / 53.23 ±22.74 / 98.70 ms │  1.21x slower │
│ QQuery 30 │      305.42 / 314.71 ±7.90 / 325.04 ms │      301.71 / 311.93 ±9.82 / 329.90 ms │     no change │
│ QQuery 31 │     276.10 / 290.83 ±10.92 / 307.97 ms │     275.67 / 295.26 ±11.32 / 306.47 ms │     no change │
│ QQuery 32 │  1104.73 / 1122.61 ±16.54 / 1146.91 ms │   976.69 / 1047.30 ±44.59 / 1090.57 ms │ +1.07x faster │
│ QQuery 33 │  1593.01 / 1634.21 ±61.92 / 1756.52 ms │  1545.86 / 1633.09 ±71.15 / 1731.17 ms │     no change │
│ QQuery 34 │  1582.18 / 1632.60 ±52.41 / 1729.22 ms │  1598.09 / 1627.74 ±22.77 / 1655.78 ms │     no change │
│ QQuery 35 │     296.53 / 322.38 ±28.98 / 378.80 ms │    295.63 / 410.11 ±203.72 / 817.24 ms │  1.27x slower │
│ QQuery 36 │         67.24 / 75.97 ±6.69 / 87.58 ms │         67.98 / 72.27 ±2.86 / 76.38 ms │     no change │
│ QQuery 37 │         35.69 / 41.57 ±4.44 / 46.57 ms │         35.16 / 35.75 ±0.58 / 36.86 ms │ +1.16x faster │
│ QQuery 38 │         44.38 / 47.21 ±2.79 / 52.37 ms │         40.06 / 42.01 ±1.60 / 44.40 ms │ +1.12x faster │
│ QQuery 39 │      138.45 / 151.57 ±9.60 / 167.57 ms │     134.94 / 155.97 ±21.97 / 195.31 ms │     no change │
│ QQuery 40 │         14.78 / 17.08 ±3.72 / 24.50 ms │         14.33 / 14.79 ±0.36 / 15.40 ms │ +1.16x faster │
│ QQuery 41 │         13.64 / 15.37 ±2.79 / 20.91 ms │         13.67 / 13.82 ±0.22 / 14.25 ms │ +1.11x faster │
│ QQuery 42 │         13.31 / 15.25 ±3.46 / 22.15 ms │         13.04 / 13.29 ±0.15 / 13.48 ms │ +1.15x faster │
└───────────┴────────────────────────────────────────┴────────────────────────────────────────┴───────────────┘
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓
┃ Benchmark Summary                         ┃            ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩
│ Total Time (HEAD)                         │ 20120.65ms │
│ Total Time (annarose_approx_percentile)   │ 20227.92ms │
│ Average Time (HEAD)                       │   467.92ms │
│ Average Time (annarose_approx_percentile) │   470.42ms │
│ Queries Faster                            │          9 │
│ Queries Slower                            │          2 │
│ Queries with No Change                    │         32 │
│ Queries with Failure                      │          0 │
└───────────────────────────────────────────┴────────────┘

Resource Usage

clickbench_partitioned — base (merge-base)

Metric	Value
Wall time	105.0s
Peak memory	17.1 GiB
Avg memory	5.6 GiB
CPU user	992.3s
CPU sys	96.5s
Peak spill	0 B

clickbench_partitioned — branch

Metric	Value
Wall time	105.0s
Peak memory	17.1 GiB
Avg memory	5.8 GiB
CPU user	995.4s
CPU sys	95.1s
Peak spill	0 B

File an issue against this benchmark runner

gabotechs · 2026-10-08T12:23:01Z

Also: this is supported by spark

Regarding this, I'm seeing that this is actually not supported by Spark. Did a quick test with a local Spark container running 4.0.1 and this is what I'm seeing:

Percentile argument	PR behavior	Spark 4.0.1
Literal or `0.25 + 0.25`	Accepted	Accepted
Projected literal, `SELECT …, 0.5 AS m`	Accepted	`NON_FOLDABLE_INPUT`
Column containing only `0.5`	Accepted	`NON_FOLDABLE_INPUT`
Column constant within each group	Accepted	`NON_FOLDABLE_INPUT`
Column with empty input	Returns `NULL`	`NON_FOLDABLE_INPUT`

In the doc you linked https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.approx_percentile.html#pyspark-sql-functions-approx-percentile, it looks like that Column is not an actual "column" as known in relational algebra, is just a Python class that can reference to a literal or an expression.

For reference here is the Spark code that rejects these kind of queries in case of a NON_FOLDABLE_INPUT.

Given that this is supported by Trino, and that it's still API compatible with Spark and Postgres, I'd still be in favor of merging this, however, I'm not comfortable just pulling this in without an extra pair of eyes from a PMC. cc @alamb as you reviewed this PR before.

dd-annarose · 2026-10-08T15:08:59Z

(sorry I closed the wrong PR 🤦🏻‍♀️)

gabotechs

Leaving here a +1, as on my side there's no more blockers here and I think it's worth pulling this in.

I'll still give a chance for other contributors to chime in.

martin-g · 2026-10-09T13:38:28Z

+        match array.data_type() {
+            DataType::Float64 | DataType::Float32 => {
+                let array = cast(array, &DataType::Float64)?;
+                Ok(downcast_value!(array, Float64Array).clone())


Is .clone() really needed here ?

operator cannot convert from &PrimitiveArray<_> to PrimitiveArray<_>

downcast_value!(array, Float64Array) returns a &Florat64Array

I could use to_owned but it's essentially cloning

martin-g · 2026-10-09T13:40:16Z


    fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
+        self.approx_percentile_cont_accumulator
+            .resolve_percentile(&values[2])?;


What guarantees that the passed values has at least three elements ?

values contains the arguments to this aggregate function.

The aggregate function's accumulator() also returns an error if there are not 3 or 4 arguments (approx_percentile_cont_with_weight requires three or four arguments: value, weight, percentile[, centroids]).

But I can add an assertion here if you'd prefer.

martin-g · 2026-10-09T13:43:51Z

+
+/// Percentile argument for `aggregate_fn_name` and its state.
+#[derive(Debug)]
+pub struct PercentileParam {


The API is strange - a pub struct with pub(crate) fields.
Since the struct is not exported in lib.rs it should be pub(crate).

I decided to keep it as pub and make PercentileParam::try_new pub too in order to preserve API contract for ApproxPercentileAccumulator's constructor.

added sqllogictests for inf and NaN

alamb · 2026-10-16T19:41:36Z

If @gabotechs is happy with this I think we can merge it -- I don't think I am likely going to have time to review it carefully

gabotechs · 2026-10-19T09:54:45Z

Sounds good, if @martin-g approves, we can merge this in

gabotechs · 2026-10-21T06:40:40Z

I see all @martin-g comments have been addressed, so I think we are good to pull this in. Please @martin-g, if you still have some follow up comments still feel free to post them here and @dd-annarose will resolve them in a follow up.

Thanks everyone!

- Closes apache#24337. When using a projection as the percentile argument to `approx_percentile_cont` or `percentile_cont`, planning fails because only literals are supported. It makes sense to accept projections that are constant across all batches but not labelled as literals (although they practically are). For example, this query cannot be planned, even though the percentile is constant: ``` SELECT approx_percentile_cont(y, m) AS median FROM ( SELECT t.x + 1 as y, 0.5 as m FROM ( VALUES (10) ) AS t(x) ) ```  Introduce `PercentileParam` and `PercentileParamState` to handle column references or projections for the percentile argument. Resolution of `percentile` cannot always be done: for example, on an empty record batch, we won't be able to get the value from the columns. `PercentileParamState` makes sure the percentile resolution is both flexible enough to wait to be able to resolve the parameter AND applies the strict constraints that are required (constant `Float32` or `Float64`). The percentile is also included in state fields so that the merge_batch in the final Accumulator can process without any issues. This new feature is covered by the `sqllogictest` cases added in `aggregate.slt`. Unit tests have also been added to `approx_percentile_cont.rs` and `percentile_cont.rs`. No breaking changes. | Query | main | annarose_approx_percentile | Change | | ---------- | ---------- | ---------- | ---------- | | QQuery 0 | 0.73 ms | 0.79 ms | 1.08x slower | | QQuery 1 | 8.10 ms | 8.91 ms | 1.10x slower | | QQuery 2 | 27.90 ms | 30.59 ms | 1.10x slower | | QQuery 3 | 23.27 ms | 23.89 ms | no change | | QQuery 4 | 157.25 ms | 157.70 ms | no change | | QQuery 5 | 197.65 ms | 201.26 ms | no change | | QQuery 6 | 0.72 ms | 0.67 ms | +1.08x faster | | QQuery 7 | 8.20 ms | 8.28 ms | no change | | QQuery 8 | 230.84 ms | 215.32 ms | +1.07x faster | | QQuery 9 | 296.27 ms | 312.37 ms | 1.05x slower | | QQuery 10 | 49.12 ms | 47.66 ms | no change | | QQuery 11 | 58.86 ms | 55.26 ms | +1.07x faster | | QQuery 12 | 198.45 ms | 192.95 ms | no change | | QQuery 13 | 285.28 ms | 280.02 ms | no change | | QQuery 14 | 195.67 ms | 204.80 ms | no change | | QQuery 15 | 184.29 ms | 180.74 ms | no change | | QQuery 16 | 434.20 ms | 457.81 ms | 1.05x slower | | QQuery 17 | 476.52 ms | 427.84 ms | +1.11x faster | | QQuery 18 | 912.71 ms | 881.69 ms | no change | | QQuery 19 | 18.14 ms | 19.41 ms | 1.07x slower | | QQuery 20 | 456.87 ms | 463.23 ms | no change | | QQuery 21 | 468.67 ms | 482.15 ms | no change | | QQuery 22 | 892.28 ms | 896.13 ms | no change | | QQuery 23 | 2520.93 ms | 2558.49 ms | no change | | QQuery 24 | 34.14 ms | 33.50 ms | no change | | QQuery 25 | 99.14 ms | 99.83 ms | no change | | QQuery 26 | 35.25 ms | 34.51 ms | no change | | QQuery 27 | 467.74 ms | 484.36 ms | no change | | QQuery 28 | 1931.71 ms | 1945.50 ms | no change | | QQuery 29 | 29.16 ms | 30.35 ms | no change | | QQuery 30 | 214.69 ms | 209.17 ms | no change | | QQuery 31 | 196.43 ms | 199.65 ms | no change | | QQuery 32 | 583.78 ms | 614.36 ms | 1.05x slower | | QQuery 33 | 1078.73 ms | 1145.79 ms | 1.06x slower | | QQuery 34 | 1073.15 ms | 1117.56 ms | no change | | QQuery 35 | 182.87 ms | 171.52 ms | +1.07x faster | | QQuery 36 | 46.27 ms | 47.18 ms | no change | | QQuery 37 | 24.27 ms | 24.03 ms | no change | | QQuery 38 | 29.58 ms | 29.76 ms | no change | | QQuery 39 | 85.29 ms | 86.14 ms | no change | | QQuery 40 | 8.23 ms | 8.41 ms | no change | | QQuery 41 | 8.12 ms | 8.47 ms | no change | | QQuery 42 | 6.72 ms | 6.81 ms | no change | | Benchmark Summary | | | ---- | ---- | | Total Time (main) | 14238.19ms | | Total Time (annarose_approx_percentile) | 14404.87ms | | Average Time (main) | 331.12ms | | Average Time (annarose_approx_percentile) | 335.00ms | | Queries Faster | 5 | | Queries Slower | 8 | | Queries with No Change | 30 | | Queries with Failure | 0 | |Query | Time (ms) | Peak RSS | Peak Commit | Major Page Faults| |--------|----------------|-------------|--------------|-------------| |0|5.43|84.0 MB|171.8 MB|0| |1|11.45|119.6 MB|313.9 MB|0| |2|27.44|240.8 MB|1536.1 MB|0| |3|30.52|412.3 MB|1227.9 MB|0| |4|173.88|2.8 GB|3.2 GB|0| |5|193.60|2.5 GB|2.9 GB|0| |6|3.36|93.0 MB|167.9 MB|0| |7|10.66|128.1 MB|318.8 MB|0| |8|219.80|3.4 GB|4.1 GB|0| |9|268.65|2.4 GB|3.2 GB|0| |10|45.84|780.3 MB|1809.8 MB|0| |11|52.68|788.7 MB|1800.9 MB|0| |12|183.80|2.5 GB|2.9 GB|0| |13|266.55|3.0 GB|3.5 GB|0| |14|191.93|2.4 GB|3.2 GB|0| |15|185.03|3.0 GB|3.3 GB|0| |16|422.42|6.4 GB|7.1 GB|0| |17|404.75|6.1 GB|6.9 GB|0| |18|861.29|12.2 GB|13.1 GB|0| |19|19.20|362.3 MB|1118.0 MB|24| |20|442.22|1171.1 MB|1429.2 MB|0| |21|407.55|1836.8 MB|2.1 GB|0| |22|763.73|2.5 GB|2.8 GB|0| |23|2313.37|4.8 GB|5.5 GB|0| |24|33.92|569.7 MB|959.2 MB|5| |25|82.99|798.0 MB|1517.9 MB|0| |26|35.10|599.1 MB|986.8 MB|0| |27|392.34|1234.9 MB|1455.8 MB|0| |28|1714.18|2.5 GB|2.7 GB|0| |29|28.43|229.9 MB|1497.1 MB|0| |30|191.47|2.2 GB|3.3 GB|0| |31|182.56|2.8 GB|3.7 GB|0| |32|1263.74|13.3 GB|16.2 GB|0| |33|958.16|10.7 GB|10.9 GB|5| |34|956.65|10.6 GB|10.9 GB|0| |35|171.08|2.1 GB|2.6 GB|0| |36|47.33|452.0 MB|800.8 MB|0| |37|26.89|229.4 MB|544.9 MB|0| |38|33.62|270.9 MB|503.8 MB|0| |39|90.83|756.9 MB|1062.6 MB|0| |40|11.41|208.3 MB|433.3 MB|0| |41|11.47|170.3 MB|393.8 MB|0| |42|10.48|142.8 MB|265.1 MB|0| |Query | Time (ms) | Peak RSS | Peak Commit |Major Page Faults| |----------|--------------|------------|----------------|------------| |0|4.76|94.7 MB|171.5 MB|0| |1|11.22|120.7 MB|296.7 MB|0| |2|32.05|244.2 MB|1533.8 MB|0| |3|24.33|417.7 MB|1229.2 MB|0| |4|175.85|2.8 GB|3.2 GB|0| |5|207.07|2.5 GB|3.0 GB|0| |6|3.46|94.3 MB|171.6 MB|0| |7|11.08|129.4 MB|323.5 MB|0| |8|223.08|3.4 GB|4.1 GB|0| |9|288.63|2.4 GB|3.4 GB|0| |10|48.79|792.1 MB|1767.0 MB|0| |11|53.32|760.8 MB|1779.6 MB|0| |12|189.17|2.6 GB|3.1 GB|0| |13|274.96|3.0 GB|3.7 GB|0| |14|202.74|2.6 GB|3.3 GB|0| |15|208.83|3.0 GB|3.4 GB|0| |16|576.37|6.3 GB|7.1 GB|0| |17|623.87|6.5 GB|7.3 GB|0| |18|1140.54|11.3 GB|13.1 GB|0| |19|21.20|370.8 MB|1124.9 MB|26| |20|507.91|1149.3 MB|1364.8 MB|0| |21|479.85|1824.8 MB|2.1 GB|0| |22|914.26|2.3 GB|2.7 GB|0| |23|2757.47|4.6 GB|5.3 GB|0| |24|41.85|591.0 MB|999.1 MB|0| |25|91.00|763.3 MB|1500.8 MB|0| |26|38.90|560.1 MB|980.6 MB|0| |27|506.23|1319.5 MB|1550.4 MB|0| |28|2119.47|2.6 GB|2.7 GB|0| |29|34.79|213.7 MB|1267.2 MB|0| |30|218.63|2.1 GB|3.1 GB|0| |31|212.42|2.8 GB|3.7 GB|0| |32|821.63|13.0 GB|16.1 GB|0| |33|1162.42|10.5 GB|10.7 GB|14| |34|1212.91|10.4 GB|10.6 GB|0| |35|184.71|2.0 GB|2.5 GB|0| |36|58.35|469.5 MB|845.9 MB|0| |37|30.78|240.2 MB|545.1 MB|0| |38|35.43|287.3 MB|485.4 MB|0| |39|92.89|730.8 MB|1074.5 MB|0| |40|11.87|204.7 MB|420.5 MB|0| |41|11.43|171.2 MB|401.5 MB|0| |42|10.57|146.6 MB|275.6 MB|0| (cherry picked from commit 9504942)

feat: support col reference for percentiles (apache#25337)

github-actions Bot added sqllogictest SQL Logic Tests (.slt) functions Changes to functions implementation labels Sep 15, 2026

github-actions Bot added the auto detected api change Auto detected API change label Sep 15, 2026

alamb reviewed Sep 15, 2026

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asolimando reviewed Sep 23, 2026

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Comment thread datafusion/functions-aggregate/src/percentile_cont.rs Resolved

Comment thread datafusion/functions-aggregate/src/approx_percentile_cont.rs Resolved

dd-annarose force-pushed the annarose/approx_percentile branch 2 times, most recently from 147bbb8 to e778c2f Compare September 25, 2026 09:54

asolimando approved these changes Sep 25, 2026

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gabotechs reviewed Oct 1, 2026

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dd-annarose added 5 commits October 5, 2026 12:07

feat: support col reference for percentiles

a343a6e

Adds a PercentileParam and PercentileParamState to accept column references or projections for the percentile argument. # Conflicts: # datafusion/functions-aggregate/src/percentile_cont.rs

address comment and add test

7a403ca

fix benches for aggregate-functions

d4ce46c

fix: fix aggregate_memory_spill sqllogictest

3f96719

replace non-deterministic metrics with <slt:ignore>

revert aggregate_memory_spill.slt

f904f3f

github-actions Bot removed execution Related to the execution crate proto Related to proto crate datasource Changes to the datasource crate ffi Changes to the ffi crate physical-plan Changes to the physical-plan crate spark Changes to datafusion-spark crate labels Oct 5, 2026

dd-annarose requested a review from gabotechs October 5, 2026 14:54

add sqllogictests and support for group accumulation

a1f030b

dd-annarose closed this Oct 8, 2026

dd-annarose reopened this Oct 8, 2026

gabotechs approved these changes Oct 9, 2026

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martin-g reviewed Oct 9, 2026

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dd-annarose added 3 commits October 9, 2026 16:49

revert changes to aggregate_memory_spill.slt

98fd0c5

cleaner code

ef39c25

added sqllogictests for inf and NaN

retrigger CI

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dd-annarose requested review from alamb and martin-g October 16, 2026 08:39

Merge branch 'main' into annarose/approx_percentile

97a173f

dd-annarose force-pushed the annarose/approx_percentile branch from 3bd5b5f to 97a173f Compare October 20, 2026 12:27

gabotechs added this pull request to the merge queue Oct 21, 2026

Merged via the queue into apache:main with commit 9504942 Oct 21, 2026
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github-actions Bot added the v56.0.0 label Oct 21, 2026

dd-annarose added a commit to DataDog/datafusion that referenced this pull request Oct 22, 2026

Merge pull request #190 from DataDog/annarose/approx-percentile

68678e2

feat: support col reference for percentiles (apache#25337)

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Benchark: ClickBench

Memory profiling for clickbench_partitioned

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