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[GitHub] [spark] gengliangwang opened a new pull request, #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
gengliangwang opened a new pull request, #38513:
URL: https://github.com/apache/spark/pull/38513
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This is a follow-up of https://github.com/apache/spark/pull/38379. On second thought, if the canonicalized `Add` has a different type, casting it as the original data type can still match more semantically equivalent `Add`s
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A better solution for the issue https://issues.apache.org/jira/browse/SPARK-40903. We can avoid regressions on marking on certain semantically equivalent `Add`s as not equivalent.
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[GitHub] [spark] cloud-fan commented on pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on PR #38513:
URL: https://github.com/apache/spark/pull/38513#issuecomment-1306748021
We should not change query semantics after reordering, as this is canonicalization. It's hard to convince people that different result types still guarantee the same query semantic.
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[GitHub] [spark] gengliangwang commented on pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on PR #38513:
URL: https://github.com/apache/spark/pull/38513#issuecomment-1306246938
> Adding cast only hides the bug
The issue of SPARK-40903 is due to Spark calculating the data type of decimal Add conservatively. What do you mean by "bug"?
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[GitHub] [spark] gengliangwang commented on pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on PR #38513:
URL: https://github.com/apache/spark/pull/38513#issuecomment-1304002389
cc @cloud-fan @srielau @ulysses-you @peter-toth
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[GitHub] [spark] gengliangwang commented on a diff in pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on code in PR #38513:
URL: https://github.com/apache/spark/pull/38513#discussion_r1015000035
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -481,12 +481,12 @@ case class Add(
// TODO: do not reorder consecutive `Add`s with different `evalMode`
val reorderResult =
orderCommutative({ case Add(l, r, _) => Seq(l, r) }).reduce(Add(_, _, evalMode))
- if (resolved && reorderResult.resolved && reorderResult.dataType == dataType) {
- reorderResult
+ if (resolved && reorderResult.resolved && reorderResult.dataType != dataType) {
Review Comment:
@ulysses-you the current code seems fine. If there is a new data type in the future, we can still avoid the issue.
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[GitHub] [spark] cloud-fan commented on pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on PR #38513:
URL: https://github.com/apache/spark/pull/38513#issuecomment-1305100077
I think canonicalization should not change the data type in the first place. Adding cast only hides the bug. What's worse, it doesn't help with the goal of canonicalization: match plans/expressions that are semantically equal, due to the extra cast.
Can we be stricter on when we can reorder? e.g. add an allowlist and only reorder under certain cases, e.g. integral add with ansi off.
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[GitHub] [spark] gengliangwang closed pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
Posted by GitBox <gi...@apache.org>.
gengliangwang closed pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
URL: https://github.com/apache/spark/pull/38513
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[GitHub] [spark] gengliangwang commented on a diff in pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on code in PR #38513:
URL: https://github.com/apache/spark/pull/38513#discussion_r1014999188
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -481,12 +481,12 @@ case class Add(
// TODO: do not reorder consecutive `Add`s with different `evalMode`
val reorderResult =
orderCommutative({ case Add(l, r, _) => Seq(l, r) }).reduce(Add(_, _, evalMode))
- if (resolved && reorderResult.resolved && reorderResult.dataType == dataType) {
- reorderResult
+ if (resolved && reorderResult.resolved && reorderResult.dataType != dataType) {
+ // SPARK-40903: Append cast for the canonicalization of decimal Add if the result data type is
+ // changed. Otherwise, it may cause data checking error within ComplexTypeMergingExpression.
+ Cast(reorderResult, dataType)
Review Comment:
Yes, the cast is better after seconds thought.
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[GitHub] [spark] gengliangwang commented on pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on PR #38513:
URL: https://github.com/apache/spark/pull/38513#issuecomment-1308060566
It's true that having a cast in the canonicalized expression is hacky. I am closing this one and keeping the solution as it is in https://github.com/apache/spark/pull/38379
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[GitHub] [spark] peter-toth commented on a diff in pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
Posted by GitBox <gi...@apache.org>.
peter-toth commented on code in PR #38513:
URL: https://github.com/apache/spark/pull/38513#discussion_r1014619447
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -481,12 +481,12 @@ case class Add(
// TODO: do not reorder consecutive `Add`s with different `evalMode`
val reorderResult =
orderCommutative({ case Add(l, r, _) => Seq(l, r) }).reduce(Add(_, _, evalMode))
- if (resolved && reorderResult.resolved && reorderResult.dataType == dataType) {
- reorderResult
+ if (resolved && reorderResult.resolved && reorderResult.dataType != dataType) {
+ // SPARK-40903: Append cast for the canonicalization of decimal Add if the result data type is
+ // changed. Otherwise, it may cause data checking error within ComplexTypeMergingExpression.
+ Cast(reorderResult, dataType)
Review Comment:
This seems to be the same idea that has come up previously: https://github.com/apache/spark/pull/38379#discussion_r1004195334 but my concerns (https://github.com/apache/spark/pull/38379#discussion_r1004215562) were wrong, so LGTM.
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[GitHub] [spark] ulysses-you commented on a diff in pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
Posted by GitBox <gi...@apache.org>.
ulysses-you commented on code in PR #38513:
URL: https://github.com/apache/spark/pull/38513#discussion_r1015003195
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -481,12 +481,12 @@ case class Add(
// TODO: do not reorder consecutive `Add`s with different `evalMode`
val reorderResult =
orderCommutative({ case Add(l, r, _) => Seq(l, r) }).reduce(Add(_, _, evalMode))
- if (resolved && reorderResult.resolved && reorderResult.dataType == dataType) {
- reorderResult
+ if (resolved && reorderResult.resolved && reorderResult.dataType != dataType) {
Review Comment:
I'm not worry about new data types, just want to avoid unnecessary logic for some unrelated data types like integer, float ..
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[GitHub] [spark] ulysses-you commented on a diff in pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
Posted by GitBox <gi...@apache.org>.
ulysses-you commented on code in PR #38513:
URL: https://github.com/apache/spark/pull/38513#discussion_r1014959493
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -481,12 +481,12 @@ case class Add(
// TODO: do not reorder consecutive `Add`s with different `evalMode`
val reorderResult =
orderCommutative({ case Add(l, r, _) => Seq(l, r) }).reduce(Add(_, _, evalMode))
- if (resolved && reorderResult.resolved && reorderResult.dataType == dataType) {
- reorderResult
+ if (resolved && reorderResult.resolved && reorderResult.dataType != dataType) {
Review Comment:
for safe, can we do this for decimal type only ? e.g
```scala
left match {
case _: DecimalType if resolved && reorderResult.resolved && reorderResult.dataType != dataType =>
Cast(reorderResult, dataType)
case _ => reorderResult
}
```
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[GitHub] [spark] peter-toth commented on a diff in pull request #38513: [SPARK-40903][SQL][FOLLOWUP] Cast canonicalized Add as its original data type if necessary
Posted by GitBox <gi...@apache.org>.
peter-toth commented on code in PR #38513:
URL: https://github.com/apache/spark/pull/38513#discussion_r1014619447
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala:
##########
@@ -481,12 +481,12 @@ case class Add(
// TODO: do not reorder consecutive `Add`s with different `evalMode`
val reorderResult =
orderCommutative({ case Add(l, r, _) => Seq(l, r) }).reduce(Add(_, _, evalMode))
- if (resolved && reorderResult.resolved && reorderResult.dataType == dataType) {
- reorderResult
+ if (resolved && reorderResult.resolved && reorderResult.dataType != dataType) {
+ // SPARK-40903: Append cast for the canonicalization of decimal Add if the result data type is
+ // changed. Otherwise, it may cause data checking error within ComplexTypeMergingExpression.
+ Cast(reorderResult, dataType)
Review Comment:
This seems to be the same idea that came up previously: https://github.com/apache/spark/pull/38379#discussion_r1004195334 but my concerns (https://github.com/apache/spark/pull/38379#discussion_r1004215562) were wrong, so LGTM.
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