Re-gen date-time benchmarks #16
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MaxGekk
commented
May 19, 2020
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| OpenJDK 64-Bit Server VM 1.8.0_252-8u252-b09-1~18.04-b09 on Linux 4.15.0-1063-aws | ||
| Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz | ||
| to_timestamp: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative | ||
| ------------------------------------------------------------------------------------------------------------------------ | ||
| to_timestamp wholestage off 1838 1842 5 0.5 1838.1 1.0X | ||
| to_timestamp wholestage on 1952 1971 11 0.5 1952.2 0.9X | ||
| to_timestamp wholestage off 2678 2694 24 0.4 2677.8 1.0X |
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@cloud-fan Here is a perf regression.
cloud-fan
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Apr 24, 2023
…onnect ### What changes were proposed in this pull request? Implement Arrow-optimized Python UDFs in Spark Connect. Please see apache#39384 for motivation and performance improvements of Arrow-optimized Python UDFs. ### Why are the changes needed? Parity with vanilla PySpark. ### Does this PR introduce _any_ user-facing change? Yes. In Spark Connect Python Client, users can: 1. Set `useArrow` parameter True to enable Arrow optimization for a specific Python UDF. ```sh >>> df = spark.range(2) >>> df.select(udf(lambda x : x + 1, useArrow=True)('id')).show() +------------+ |<lambda>(id)| +------------+ | 1| | 2| +------------+ # ArrowEvalPython indicates Arrow optimization >>> df.select(udf(lambda x : x + 1, useArrow=True)('id')).explain() == Physical Plan == *(2) Project [pythonUDF0#18 AS <lambda>(id)#16] +- ArrowEvalPython [<lambda>(id#14L)#15], [pythonUDF0#18], 200 +- *(1) Range (0, 2, step=1, splits=1) ``` 2. Enable `spark.sql.execution.pythonUDF.arrow.enabled` Spark Conf to make all Python UDFs Arrow-optimized. ```sh >>> spark.conf.set("spark.sql.execution.pythonUDF.arrow.enabled", True) >>> df.select(udf(lambda x : x + 1)('id')).show() +------------+ |<lambda>(id)| +------------+ | 1| | 2| +------------+ # ArrowEvalPython indicates Arrow optimization >>> df.select(udf(lambda x : x + 1)('id')).explain() == Physical Plan == *(2) Project [pythonUDF0#30 AS <lambda>(id)apache#28] +- ArrowEvalPython [<lambda>(id#26L)apache#27], [pythonUDF0#30], 200 +- *(1) Range (0, 2, step=1, splits=1) ``` ### How was this patch tested? Parity unit tests. Closes apache#40725 from xinrong-meng/connect_arrow_py_udf. Authored-by: Xinrong Meng <xinrong@apache.org> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
cloud-fan
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Feb 6, 2025
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.
```
// 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, #8] // unroll-2
0x0000ffff91de7000: ldr x14, [x24, #8]
0x0000ffff91de7004: cmp x13, x14
0x0000ffff91de7008: b.ne 0x0000ffff91de70b4
0x0000ffff91de700c: ldr x13, [x23, #16] // unroll-3
0x0000ffff91de7010: ldr x14, [x24, #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
```
### What changes were proposed in this pull request?
A trivial change to replace loop index `i` of method `arrayEquals` from `int` to `long`.
### 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.
Closes apache#49568 from cyb70289/arrayEquals.
Authored-by: Yibo Cai <cyb70289@gmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
cloud-fan
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Jul 29, 2025
…ingBuilder` ### What changes were proposed in this pull request? This PR aims to improve `toString` by `JEP-280` instead of `ToStringBuilder`. In addition, `Scalastyle` and `Checkstyle` rules are added to prevent a future regression. ### Why are the changes needed? Since Java 9, `String Concatenation` has been handled better by default. | ID | DESCRIPTION | | - | - | | JEP-280 | [Indify String Concatenation](https://openjdk.org/jeps/280) | For example, this PR improves `OpenBlocks` like the following. Both Java source code and byte code are simplified a lot by utilizing JEP-280 properly. **CODE CHANGE** ```java - return new ToStringBuilder(this, ToStringStyle.SHORT_PREFIX_STYLE) - .append("appId", appId) - .append("execId", execId) - .append("blockIds", Arrays.toString(blockIds)) - .toString(); + return "OpenBlocks[appId=" + appId + ",execId=" + execId + ",blockIds=" + + Arrays.toString(blockIds) + "]"; ``` **BEFORE** ``` public java.lang.String toString(); Code: 0: new apache#39 // class org/apache/commons/lang3/builder/ToStringBuilder 3: dup 4: aload_0 5: getstatic apache#41 // Field org/apache/commons/lang3/builder/ToStringStyle.SHORT_PREFIX_STYLE:Lorg/apache/commons/lang3/builder/ToStringStyle; 8: invokespecial apache#47 // Method org/apache/commons/lang3/builder/ToStringBuilder."<init>":(Ljava/lang/Object;Lorg/apache/commons/lang3/builder/ToStringStyle;)V 11: ldc apache#50 // String appId 13: aload_0 14: getfield #7 // Field appId:Ljava/lang/String; 17: invokevirtual apache#51 // Method org/apache/commons/lang3/builder/ToStringBuilder.append:(Ljava/lang/String;Ljava/lang/Object;)Lorg/apache/commons/lang3/builder/ToStringBuilder; 20: ldc apache#55 // String execId 22: aload_0 23: getfield #13 // Field execId:Ljava/lang/String; 26: invokevirtual apache#51 // Method org/apache/commons/lang3/builder/ToStringBuilder.append:(Ljava/lang/String;Ljava/lang/Object;)Lorg/apache/commons/lang3/builder/ToStringBuilder; 29: ldc apache#56 // String blockIds 31: aload_0 32: getfield #16 // Field blockIds:[Ljava/lang/String; 35: invokestatic apache#57 // Method java/util/Arrays.toString:([Ljava/lang/Object;)Ljava/lang/String; 38: invokevirtual apache#51 // Method org/apache/commons/lang3/builder/ToStringBuilder.append:(Ljava/lang/String;Ljava/lang/Object;)Lorg/apache/commons/lang3/builder/ToStringBuilder; 41: invokevirtual apache#61 // Method org/apache/commons/lang3/builder/ToStringBuilder.toString:()Ljava/lang/String; 44: areturn ``` **AFTER** ``` public java.lang.String toString(); Code: 0: aload_0 1: getfield #7 // Field appId:Ljava/lang/String; 4: aload_0 5: getfield #13 // Field execId:Ljava/lang/String; 8: aload_0 9: getfield #16 // Field blockIds:[Ljava/lang/String; 12: invokestatic apache#39 // Method java/util/Arrays.toString:([Ljava/lang/Object;)Ljava/lang/String; 15: invokedynamic apache#43, 0 // InvokeDynamic #0:makeConcatWithConstants:(Ljava/lang/String;Ljava/lang/String;Ljava/lang/String;)Ljava/lang/String; 20: areturn ``` ### Does this PR introduce _any_ user-facing change? No. This is an `toString` implementation improvement. ### How was this patch tested? Pass the CIs. ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#51572 from dongjoon-hyun/SPARK-52880. Authored-by: Dongjoon Hyun <dongjoon@apache.org> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
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What changes were proposed in this pull request?
Regenerated the following benchmarks:
How was this patch tested?
By running the benchmark in the environment: