[SPARK-24957][SQL][BACKPORT-2.2] Average with decimal followed by aggregation returns wrong result #21949
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
@mgaido91, thanks! I am a bot who has found some folks who might be able to help with the review:@rxin, @marmbrus and @gatorsmile |
Contributor
Author
|
cc @cloud-fan |
|
Test build #93900 has finished for PR 21949 at commit
|
asfgit
pushed a commit
that referenced
this pull request
Aug 1, 2018
…regation returns wrong result ## What changes were proposed in this pull request? When we do an average, the result is computed dividing the sum of the values by their count. In the case the result is a DecimalType, the way we are casting/managing the precision and scale is not really optimized and it is not coherent with what we do normally. In particular, a problem can happen when the Divide operand returns a result which contains a precision and scale different by the ones which are expected as output of the Divide operand. In the case reported in the JIRA, for instance, the result of the Divide operand is a Decimal(38, 36), while the output data type for Divide is 38, 22. This is not an issue when the Divide is followed by a CheckOverflow or a Cast to the right data type, as these operations return a decimal with the defined precision and scale. Despite in the Average operator we do have a Cast, this may be bypassed if the result of Divide is the same type which it is casted to, hence the issue reported in the JIRA may arise. The PR proposes to use the normal rules/handling of the arithmetic operators with Decimal data type, so we both reuse the existing code (having a single logic for operations between decimals) and we fix this problem as the result is always guarded by CheckOverflow. ## How was this patch tested? added UT Author: Marco Gaido <[email protected]> Closes #21949 from mgaido91/SPARK-24957_2.2.
Member
|
Thanks! Merged to 2.2. Could you close this PR? |
Contributor
Author
|
Thanks, closed. |
Willymontaz
pushed a commit
to criteo-forks/spark
that referenced
this pull request
Sep 26, 2019
…regation returns wrong result ## What changes were proposed in this pull request? When we do an average, the result is computed dividing the sum of the values by their count. In the case the result is a DecimalType, the way we are casting/managing the precision and scale is not really optimized and it is not coherent with what we do normally. In particular, a problem can happen when the Divide operand returns a result which contains a precision and scale different by the ones which are expected as output of the Divide operand. In the case reported in the JIRA, for instance, the result of the Divide operand is a Decimal(38, 36), while the output data type for Divide is 38, 22. This is not an issue when the Divide is followed by a CheckOverflow or a Cast to the right data type, as these operations return a decimal with the defined precision and scale. Despite in the Average operator we do have a Cast, this may be bypassed if the result of Divide is the same type which it is casted to, hence the issue reported in the JIRA may arise. The PR proposes to use the normal rules/handling of the arithmetic operators with Decimal data type, so we both reuse the existing code (having a single logic for operations between decimals) and we fix this problem as the result is always guarded by CheckOverflow. ## How was this patch tested? added UT Author: Marco Gaido <[email protected]> Closes apache#21949 from mgaido91/SPARK-24957_2.2.
Willymontaz
pushed a commit
to criteo-forks/spark
that referenced
this pull request
Sep 27, 2019
…regation returns wrong result ## What changes were proposed in this pull request? When we do an average, the result is computed dividing the sum of the values by their count. In the case the result is a DecimalType, the way we are casting/managing the precision and scale is not really optimized and it is not coherent with what we do normally. In particular, a problem can happen when the Divide operand returns a result which contains a precision and scale different by the ones which are expected as output of the Divide operand. In the case reported in the JIRA, for instance, the result of the Divide operand is a Decimal(38, 36), while the output data type for Divide is 38, 22. This is not an issue when the Divide is followed by a CheckOverflow or a Cast to the right data type, as these operations return a decimal with the defined precision and scale. Despite in the Average operator we do have a Cast, this may be bypassed if the result of Divide is the same type which it is casted to, hence the issue reported in the JIRA may arise. The PR proposes to use the normal rules/handling of the arithmetic operators with Decimal data type, so we both reuse the existing code (having a single logic for operations between decimals) and we fix this problem as the result is always guarded by CheckOverflow. ## How was this patch tested? added UT Author: Marco Gaido <[email protected]> Closes apache#21949 from mgaido91/SPARK-24957_2.2.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
4 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
What changes were proposed in this pull request?
When we do an average, the result is computed dividing the sum of the values by their count. In the case the result is a DecimalType, the way we are casting/managing the precision and scale is not really optimized and it is not coherent with what we do normally.
In particular, a problem can happen when the Divide operand returns a result which contains a precision and scale different by the ones which are expected as output of the Divide operand. In the case reported in the JIRA, for instance, the result of the Divide operand is a Decimal(38, 36), while the output data type for Divide is 38, 22. This is not an issue when the Divide is followed by a CheckOverflow or a Cast to the right data type, as these operations return a decimal with the defined precision and scale. Despite in the Average operator we do have a Cast, this may be bypassed if the result of Divide is the same type which it is casted to, hence the issue reported in the JIRA may arise.
The PR proposes to use the normal rules/handling of the arithmetic operators with Decimal data type, so we both reuse the existing code (having a single logic for operations between decimals) and we fix this problem as the result is always guarded by CheckOverflow.
How was this patch tested?
added UT