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Posted to reviews@spark.apache.org by 10110346 <gi...@git.apache.org> on 2017/05/31 06:39:04 UTC
[GitHub] spark pull request #18156: [SPARK-20933][SQL]when the input parameter is flo...
GitHub user 10110346 opened a pull request:
https://github.com/apache/spark/pull/18156
[SPARK-20933][SQL]when the input parameter is float type，the ’round ’ or ‘bround’ function can't work well
## What changes were proposed in this pull request?
spark-sql>select round(cast(3.1415 as float), 3);
spark-sql>3.141
For this case, the result we expected is 3.142
spark-sql>select bround(cast(3.1415 as float), 3);
spark-sql>3.141
For this case, the result we expected is 3.142
## How was this patch tested?
add unit test
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/10110346/spark wip-lx-0526
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/18156.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #18156
----
commit ea2a8ce9fa8f8f70847c08d732a0397e4ca473e2
Author: liuxian <li...@zte.com.cn>
Date: 2017-05-31T06:19:39Z
when the input parameter is float type，the ’round ’ and ‘bround’
function can't work well
----
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[GitHub] spark issue #18156: [SPARK-20933][SQL]when the input parameter is float type...
Posted by 10110346 <gi...@git.apache.org>.
Github user 10110346 commented on the issue:
https://github.com/apache/spark/pull/18156
maybe i have understood,thanks @srowen
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[GitHub] spark issue #18156: [SPARK-20933][SQL]when the input parameter is float type...
Posted by 10110346 <gi...@git.apache.org>.
Github user 10110346 commented on the issue:
https://github.com/apache/spark/pull/18156
I don't understand why the value of 3.1415f is actually something like 3.14149999...
From the user's point of view, i think 3.142 maybe more reasonable.
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[GitHub] spark pull request #18156: [SPARK-20933][SQL]when the input parameter is flo...
Posted by 10110346 <gi...@git.apache.org>.
Github user 10110346 closed the pull request at:
https://github.com/apache/spark/pull/18156
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[GitHub] spark issue #18156: [SPARK-20933][SQL]when the input parameter is float type...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/18156
No, that's not how floating-point works. Even 0.1 as a double isn't exactly 0.1.
No, converting to double from float does not lose precision, but this is beside the point.
3.1415 as a double is also not exactly 3.1415. I don't understand what you're trying to point out; of course the narrowing conversion from 3.1415d to float matches 3.1415f. This doesn't change the fact that the rounding answer is correct here. I think you are thinking of the case where you specified 3.1415 as a decimal type.
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[GitHub] spark issue #18156: [SPARK-20933][SQL]when the input parameter is float type...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/18156
Although I agree that 3.1415 should round to 3.141 in both cases, the value of 3.1415f is not quite the same as 3.1415. It's actually something like 3.14149999... The behavior is correct, therefore. You should find that rounding 3.1415 as a double or string gives the answer you're expecting.
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[GitHub] spark issue #18156: [SPARK-20933][SQL]when the input parameter is float type...
Posted by srowen <gi...@git.apache.org>.
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/18156
Try evaluating 3.1415f < 3.1415. It is true. Floating point representation is inexact and in your example you explicitly choose the inexact representation
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[GitHub] spark issue #18156: [SPARK-20933][SQL]when the input parameter is float type...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18156
Can one of the admins verify this patch?
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[GitHub] spark issue #18156: [SPARK-20933][SQL]when the input parameter is float type...
Posted by 10110346 <gi...@git.apache.org>.
Github user 10110346 commented on the issue:
https://github.com/apache/spark/pull/18156
Yes,Floating point representation is inexact .But I think if the length of Floating point value is less than 7, it should be exact.
Evaluating 3.1415f < 3.1415, firstly, 3.1415f will be converted to Double,this step will lead to the precision loss.
Try evaluating 3.1415f == 3.1415.toFloat. It is true.
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