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[SPARK-51001][SQL] Refine arrayEquals #49568
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LGTM |
I think I might make a JIRA for this, just because it is touching an important method. Just for completeness. |
This is a trivial change to replace the loop index from `int` to `long`. Surprisingly, microbenchmark shows more than double performance uplift. Analysis -------- The hot loop of `arrayEquals` method is simplifed as below. Loop index `i` is defined as `int`, it's compared with `length`, which is a `long`, to determine if the loop should end. ``` public static boolean arrayEquals( Object leftBase, long leftOffset, Object rightBase, long rightOffset, final long length) { ...... int i = 0; while (i <= length - 8) { if (Platform.getLong(leftBase, leftOffset + i) != Platform.getLong(rightBase, rightOffset + i)) { return false; } i += 8; } ...... } ``` Strictly speaking, there's a code bug here. If `length` is greater than 2^31 + 8, this loop will never end because `i` as a 32 bit integer is at most 2^31 - 1. But compiler must consider this behaviour as intentional and generate code strictly match the logic. It prevents compiler from generating optimal code. Defining loop index `i` as `long` corrects this issue. Besides more accurate code logic, JIT is able to optimize this code much more aggressively. From microbenchmark, this trivial change improves performance significantly on both Arm and x86 platforms. Benchmark --------- Source code: https://gist.github.com/cyb70289/258e261f388e22f47e4d961431786d1a Result on Arm Neoverse N2: Benchmark Mode Cnt Score Error Units ArrayEqualsBenchmark.arrayEqualsInt avgt 10 674.313 ± 0.213 ns/op ArrayEqualsBenchmark.arrayEqualsLong avgt 10 313.563 ± 2.338 ns/op Result on Intel Cascake Lake: Benchmark Mode Cnt Score Error Units ArrayEqualsBenchmark.arrayEqualsInt avgt 10 1130.695 ± 0.168 ns/op ArrayEqualsBenchmark.arrayEqualsLong avgt 10 461.979 ± 0.097 ns/op Deep dive --------- Dive deep to the machine code level, we can see why the big gap. Listed below are arm64 assembly generated by Openjdk-17 C2 compiler. For `int i`, the machine code is similar to source code, no deep optimization. Safepoint polling is expensive in this short loop. ``` // jit c2 machine code snippet 0x0000ffff81ba8904: mov w15, wzr // int i = 0 0x0000ffff81ba8908: nop 0x0000ffff81ba890c: nop loop: 0x0000ffff81ba8910: ldr x10, [x13, w15, sxtw] // Platform.getLong(leftBase, leftOffset + i) 0x0000ffff81ba8914: ldr x14, [x12, w15, sxtw] // Platform.getLong(rightBase, rightOffset + i) 0x0000ffff81ba8918: cmp x10, x14 0x0000ffff81ba891c: b.ne 0x0000ffff81ba899c // return false if not equal 0x0000ffff81ba8920: ldr x14, [x28, apache#848] // x14 -> safepoint 0x0000ffff81ba8924: add w15, w15, #0x8 // i += 8 0x0000ffff81ba8928: ldr wzr, [x14] // safepoint polling 0x0000ffff81ba892c: sxtw x10, w15 // extend i to long 0x0000ffff81ba8930: cmp x10, x11 0x0000ffff81ba8934: b.le 0x0000ffff81ba8910 // if (i <= length - 8) goto loop ``` For `long i`, JIT is able to do much more aggressive optimization. E.g, below code snippet unrolls the loop by four. Safepoint polling does not impact much in this long loop. ``` // jit c2 machine code snippet unrolled_loop: 0x0000ffff91de6fe0: sxtw x10, w7 0x0000ffff91de6fe4: add x23, x22, x10 0x0000ffff91de6fe8: add x24, x21, x10 0x0000ffff91de6fec: ldr x13, [x23] // unroll-1 0x0000ffff91de6ff0: ldr x14, [x24] 0x0000ffff91de6ff4: cmp x13, x14 0x0000ffff91de6ff8: b.ne 0x0000ffff91de70a8 0x0000ffff91de6ffc: ldr x13, [x23, apache#8] // unroll-2 0x0000ffff91de7000: ldr x14, [x24, apache#8] 0x0000ffff91de7004: cmp x13, x14 0x0000ffff91de7008: b.ne 0x0000ffff91de70b4 0x0000ffff91de700c: ldr x13, [x23, apache#16] // unroll-3 0x0000ffff91de7010: ldr x14, [x24, apache#16] 0x0000ffff91de7014: cmp x13, x14 0x0000ffff91de7018: b.ne 0x0000ffff91de70a4 0x0000ffff91de701c: ldr x13, [x23, apache#24] // unroll-4 0x0000ffff91de7020: ldr x14, [x24, apache#24] 0x0000ffff91de7024: cmp x13, x14 0x0000ffff91de7028: b.ne 0x0000ffff91de70b0 0x0000ffff91de702c: add w7, w7, #0x20 0x0000ffff91de7030: cmp w7, w11 0x0000ffff91de7034: b.lt 0x0000ffff91de6fe0 ```
Thanks @srowen , I've created a JIRA card. |
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Could anyone else review too and merge? I'm having trouble merging.
Nevermind I got it |
This is a trivial change to replace the loop index from
int
tolong
. Surprisingly, microbenchmark shows more than double performance uplift.Analysis
The hot loop of
arrayEquals
method is simplifed as below. Loop indexi
is defined asint
, it's compared withlength
, which is along
, to determine if the loop should end.Strictly speaking, there's a code bug here. If
length
is greater than 2^31 + 8, this loop will never end becausei
as a 32 bit integer is at most 2^31 - 1. But compiler must consider this behaviour as intentional and generate code strictly match the logic. It prevents compiler from generating optimal code.Defining loop index
i
aslong
corrects this issue. Besides more accurate code logic, JIT is able to optimize this code much more aggressively. From microbenchmark, this trivial change improves performance significantly on both Arm and x86 platforms.Benchmark
Source code:
https://gist.github.com/cyb70289/258e261f388e22f47e4d961431786d1a
Result on Arm Neoverse N2:
Result on Intel Cascake Lake:
Deep dive
Dive deep to the machine code level, we can see why the big gap. Listed below are arm64 assembly generated by Openjdk-17 C2 compiler.
For
int i
, the machine code is similar to source code, no deep optimization. Safepoint polling is expensive in this short loop.For
long i
, JIT is able to do much more aggressive optimization. E.g, below code snippet unrolls the loop by four.What changes were proposed in this pull request?
A trivial change to replace loop index
i
of methodarrayEquals
fromint
tolong
.Why are the changes needed?
To improve performance and fix a possible bug.
Does this PR introduce any user-facing change?
No.
How was this patch tested?
Existing unit tests.
Was this patch authored or co-authored using generative AI tooling?
No.