Since there might be concerns about the performance degration that might
caused by switching to use strictMath, here is some simple performance info:
https://bugs.openjdk.java.net/browse/JDK-8210416  , we can see that the
perf difference between Math and StrictMath is actually very very small. And
there are also some discussions about it in the spark PR:
https://github.com/apache/spark/pull/25279  So it shouldn't be a problem.

On Mon, Apr 27, 2020 at 10:46 AM Zhenyu Zheng <[email protected]>
wrote:

> Hi Hive,
>
> We have tested and put up a patch for this:
> https://issues.apache.org/jira/browse/HIVE-23133 it is done pretty much
> the same as in Spark:
> https://github.com/apache/spark/pull/25279 , it could be a very good fix
> for running Hive across different platforms.
>
> BR,
>
> On Fri, Apr 3, 2020 at 3:18 PM Zhenyu Zheng <[email protected]>
> wrote:
>
>> Hi Hive,
>>
>> Currently, we have set up an ARM CI to test out how Hive works on ARM
>> platform:
>>
>> https://builds.apache.org/view/H-L/view/Hive/job/Hive-linux-ARM-trunk/
>>
>> Among the failures, we have observed that some numeric operations can
>> have different result across hardware archs, such as:
>>
>>
>> https://builds.apache.org/view/H-L/view/Hive/job/Hive-linux-ARM-trunk/25/testReport/org.apache.hadoop.hive.cli/TestCliDriver/testCliDriver_vector_decimal_udf2_/
>>
>>
>> https://builds.apache.org/view/H-L/view/Hive/job/Hive-linux-ARM-trunk/25/testReport/org.apache.hadoop.hive.cli/TestSparkCliDriver/testCliDriver_subquery_select_/
>>
>>
>> https://builds.apache.org/view/H-L/view/Hive/job/Hive-linux-ARM-trunk/25/testReport/org.apache.hadoop.hive.cli/TestSparkCliDriver/testCliDriver_vectorized_math_funcs_/
>>
>> we can see that the calculation results of log, exp, cos, toRadians etc
>> is slitly different than the .out file results that we are
>>
>> comparing(they are tested and wrote on X86 machines), this is because of
>> we use Math Library
>> <https://docs.oracle.com/javase/6/docs/api/java/lang/Math.html> for
>> these kind of calculations.
>>
>> and according to the illustration
>> <https://docs.oracle.com/javase/6/docs/api/java/lang/Math.html>:
>>
>> *Unlike some of the numeric methods of class StrictMath, all
>> implementations of the equivalent functions of class Math are not*
>> *defined to return the bit-for-bit same results. This relaxation permits
>> better-performing implementations where strict reproducibility*
>> *is not required.*
>>
>> *By default many of the Math methods simply call the equivalent method in
>> StrictMath for their implementation.*
>> *Code generators are encouraged to use platform-specific native libraries
>> or microprocessor instructions, where available,*
>> *to provide higher-performance implementations of Math methods.*
>>
>> so the result will have difference across hardware archs.
>>
>> On the other hand, JAVA provided another library StrictMath
>> <https://docs.oracle.com/javase/6/docs/api/java/lang/StrictMath.html>
>> that will not have this kind of problem as according to its' reference
>> <https://docs.oracle.com/javase/6/docs/api/java/lang/StrictMath.html>:
>>
>> *To help ensure portability of Java programs, the definitions of some of
>> the numeric functions in this package require that they produce*
>> *the same results as certain published algorithms.*
>>
>> So in order to fix the above mentioned problem, we have to consider
>> switch to use StrictMath instead of Math.
>>
>> I have also reported an issue about this
>> https://issues.apache.org/jira/browse/HIVE-23133 so comments and
>> suggestions are welcome.
>>
>>
>> BR,
>>
>> Zhenyu Zheng
>>
>>
>>
>

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