perf: improve performance of `array_repeat` function #20049

lyne7-sc · 2026-01-28T15:35:15Z

Which issue does this PR close?

Closes #.

Rationale for this change

The current array_repeat implementation built intermediate arrays row by row using MutableArrayData + concat. This caused unnecessary allocations and per-row overhead.

This PR replaces it with a vectorized implementation based on offsets + take, which constructs the output in a single pass and reduces intermediate memory usage.

What changes are included in this PR?

Reimplemented general_repeat and general_list_repeat using take, eliminating per-row materialization.

Benchmarks

group                                               after                                   before
-----                                               -----                                   ------
array_repeat_boolean/repeat_50_count/100            1.00     18.1±0.59µs        ? ?/sec     5.92    106.8±3.29µs        ? ?/sec
array_repeat_boolean/repeat_50_count/1000           1.00    100.0±8.00µs        ? ?/sec     9.34   934.2±20.43µs        ? ?/sec
array_repeat_boolean/repeat_50_count/10000          1.00   882.5±18.07µs        ? ?/sec     10.45     9.2±0.16ms        ? ?/sec
array_repeat_boolean/repeat_5_count/100             1.00     10.3±0.58µs        ? ?/sec     6.82     70.6±2.74µs        ? ?/sec
array_repeat_boolean/repeat_5_count/1000            1.00     20.5±1.05µs        ? ?/sec     28.07  574.6±20.67µs        ? ?/sec
array_repeat_boolean/repeat_5_count/10000           1.00    119.1±6.41µs        ? ?/sec     47.08     5.6±0.12ms        ? ?/sec
array_repeat_float64/repeat_50_count/100            1.00     15.0±0.34µs        ? ?/sec     6.47     96.9±4.63µs        ? ?/sec
array_repeat_float64/repeat_50_count/1000           1.00     68.6±2.91µs        ? ?/sec     12.23  839.5±29.00µs        ? ?/sec
array_repeat_float64/repeat_50_count/10000          1.00   700.7±29.21µs        ? ?/sec     12.21     8.6±0.21ms        ? ?/sec
array_repeat_float64/repeat_5_count/100             1.00      9.7±0.27µs        ? ?/sec     7.12     69.2±1.75µs        ? ?/sec
array_repeat_float64/repeat_5_count/1000            1.00     18.2±0.81µs        ? ?/sec     30.75  558.7±19.02µs        ? ?/sec
array_repeat_float64/repeat_5_count/10000           1.00     98.8±8.05µs        ? ?/sec     55.35     5.5±0.23ms        ? ?/sec
array_repeat_int64/repeat_50_count/100              1.00     15.5±0.70µs        ? ?/sec     6.46     99.8±2.94µs        ? ?/sec
array_repeat_int64/repeat_50_count/1000             1.00     69.3±3.29µs        ? ?/sec     12.42  860.6±14.99µs        ? ?/sec
array_repeat_int64/repeat_50_count/10000            1.00   672.0±20.81µs        ? ?/sec     12.54     8.4±0.14ms        ? ?/sec
array_repeat_int64/repeat_5_count/100               1.00      9.6±0.51µs        ? ?/sec     6.03     57.7±1.94µs        ? ?/sec
array_repeat_int64/repeat_5_count/1000              1.00     17.9±0.73µs        ? ?/sec     32.14  574.2±22.44µs        ? ?/sec
array_repeat_int64/repeat_5_count/10000             1.00     99.2±6.90µs        ? ?/sec     55.65     5.5±0.20ms        ? ?/sec
array_repeat_nested_int64/repeat_50_count/100       1.00     53.6±2.21µs        ? ?/sec     2.67    143.0±5.55µs        ? ?/sec
array_repeat_nested_int64/repeat_50_count/1000      1.00   474.7±30.74µs        ? ?/sec     2.95  1398.8±40.50µs        ? ?/sec
array_repeat_nested_int64/repeat_50_count/10000     1.00     14.3±0.41ms        ? ?/sec     1.39     19.9±2.98ms        ? ?/sec
array_repeat_nested_int64/repeat_5_count/100        1.00     14.2±0.49µs        ? ?/sec     6.62     93.8±3.66µs        ? ?/sec
array_repeat_nested_int64/repeat_5_count/1000       1.00     57.1±1.81µs        ? ?/sec     14.09  803.8±18.81µs        ? ?/sec
array_repeat_nested_int64/repeat_5_count/10000      1.00   509.5±27.43µs        ? ?/sec     18.27     9.3±0.36ms        ? ?/sec
array_repeat_nested_string/repeat_50_count/100      1.00    138.6±5.27µs        ? ?/sec    1.60   221.4±10.37µs        ? ?/sec
array_repeat_nested_string/repeat_50_count/1000     1.00  1300.5±49.34µs        ? ?/sec    1.70      2.2±0.05ms        ? ?/sec
array_repeat_nested_string/repeat_50_count/10000    1.00     28.6±1.21ms        ? ?/sec    1.06     30.3±1.91ms        ? ?/sec
array_repeat_nested_string/repeat_5_count/100       1.00     24.2±1.61µs        ? ?/sec    4.37    106.1±3.95µs        ? ?/sec
array_repeat_nested_string/repeat_5_count/1000      1.00    144.5±4.22µs        ? ?/sec    7.04  1016.5±39.20µs        ? ?/sec
array_repeat_nested_string/repeat_5_count/10000     1.00  1471.1±60.22µs        ? ?/sec    8.11     11.9±0.60ms        ? ?/sec
array_repeat_string/repeat_50_count/100             1.00     30.9±2.19µs        ? ?/sec     4.52    139.8±5.38µs        ? ?/sec
array_repeat_string/repeat_50_count/1000            1.00    231.5±4.96µs        ? ?/sec     5.25  1214.5±23.72µs        ? ?/sec
array_repeat_string/repeat_50_count/10000           1.00      4.0±0.12ms        ? ?/sec     3.18     12.9±0.49ms        ? ?/sec
array_repeat_string/repeat_5_count/100              1.00     11.5±0.35µs        ? ?/sec     6.47     74.5±1.81µs        ? ?/sec
array_repeat_string/repeat_5_count/1000             1.00     35.6±1.21µs        ? ?/sec     16.66  593.5±14.59µs        ? ?/sec
array_repeat_string/repeat_5_count/10000            1.00   284.3±26.10µs        ? ?/sec     21.21     6.0±0.14ms        ? ?/sec

Are these changes tested?

Yes. Existing SLT tests pass without modification.

Are there any user-facing changes?

No.

Jefffrey · 2026-01-29T08:23:43Z

datafusion/functions-nested/src/repeat.rs

+    let mut outer_offsets = Vec::with_capacity(counts.len() + 1);
+    outer_offsets.push(O::zero());
+    let mut running_offset = 0usize;
+    for &count in counts.iter() {


Can use OffsetBuffer::from_lengths here I believe?

Would using OffsetBuffer::from_lengths cause an extra loop over the lengths array internally?
I'm a bit concerned this could introduce some performance overhead.

Here we already have to iterate over counts, which is equivalent to what from_lengths is doing I believe?

Oh, I misread that, the outer offsets can indeed be replaced with from_lengths, which is clearer. Thanks!

Jefffrey · 2026-01-29T08:31:57Z

datafusion/functions-nested/src/repeat.rs

-    let data_type = list_array.data_type();
-    let value_type = list_array.value_type();
-    let mut new_values = vec![];
+    let counts = count_array.values();


What happens if an element of count_array is null? It looks like we still access the underlying primitive?

will produce an empty array. This function seems to assume count[i] >= 0 and doesn’t handle count[i] being null. This also confused me, but I kept the original behavior since I’m not sure whether existing users rely on null count being treated as empty array.

We might need a followup issue if this is the existing behaviour; we can't rely on null slots being 0 value (potential bug), moreover I feel we should be consistent with null semantics (usually a null input would return null 🤔)

I agree. I’ve opened a follow-up issue to track this #20075.

Since this could potentially introduce a user-facing behavioral change around null semantics, I’d prefer to keep this PR focused on the performance improvement. I can address the null-handling semantics separately in a follow-up PR.

lyne7-sc and others added 5 commits January 28, 2026 23:08

perf array_repeat

ada1809

cargo fmt

03dee1a

Merge branch 'apache:main' into perf/array_repeat

e184578

nit

edefff4

fmt

2f097e2

Jefffrey reviewed Jan 29, 2026

View reviewed changes

lyne7-sc and others added 2 commits January 29, 2026 22:56

Merge branch 'apache:main' into perf/array_repeat

6b590ad

count null slt

84a312a

github-actions bot added the sqllogictest SQL Logic Tests (.slt) label Jan 29, 2026

lyne7-sc and others added 2 commits January 30, 2026 21:28

Merge branch 'apache:main' into perf/array_repeat

c87d8b0

use from_length

a8eafe6

lyne7-sc mentioned this pull request Jan 30, 2026

array_repeat function does not handle null values in count array #20075

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Jefffrey approved these changes Jan 30, 2026

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perf: improve performance of `array_repeat` function #20049

perf: improve performance of `array_repeat` function #20049

lyne7-sc commented Jan 28, 2026

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Jefffrey Jan 29, 2026

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lyne7-sc commented Jan 28, 2026

Which issue does this PR close?

Rationale for this change

What changes are included in this PR?

Benchmarks

Are these changes tested?

Are there any user-facing changes?

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perf: improve performance of `array_repeat` function #20049

perf: improve performance of `array_repeat` function #20049