RFR: 8302204: Optimize BigDecimal.divide
Sergey Kuksenko
skuksenko at openjdk.org
Mon Feb 13 03:56:26 UTC 2023
On Fri, 10 Feb 2023 10:00:05 GMT, Xiaowei Lu <duke at openjdk.org> wrote:
> [JDK-8269667](https://bugs.openjdk.org/browse/JDK-8269667) has uncovered the poor performance of BigDecimal.divide under certain circumstance.
>
> We confront similar situations when benchmarking Spark3 on TPC-DS test kit. According to the flame-graph below, it is StripZeros that spends most of the time of BigDecimal.divide. Hence we propose this patch to optimize stripping zeros.
> 
>
> Currently, createAndStripZerosToMatchScale() is performed linearly. That is, the target value is parsed from back to front, each time stripping out single ‘0’. To optimize, we can adopt the method of binary search. That is, each time we try to strip out ${scale/2} ‘0’s.
>
> The performance looks good. Therotically, time complexity of our method is O(log n), while the current one is O(n). In practice, benchmarks on Spark3 show that 1/3 less time (102s->68s) is spent on TPC-DS query4. We also runs Jtreg and JCK to check correctness, and it seems fine.
>
> More about environment:
> we run Spark3.3.0 on Openjdk11, but it seems jdk version doesn’t have much impact on BigDecimal. Spark cluster consists of a main node and 2 core nodes, each has 4cores, 16g memory and 4x500GB storage.
As for TPC-DS
[AUTO-RESULT] QueryTotal=1968s vs [AUTO-RESULT] QueryTotal=1934s
that gives ~1.7% of performance difference.
Are you sure that this small diff is a real diff, but not run-to-run variance?
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PR: https://git.openjdk.org/jdk/pull/12509
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