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[GitHub] [spark] sigmod opened a new pull request #32280: [WIP][SPARK-35078] Support tree traversal pruning in expression rules
sigmod opened a new pull request #32280:
URL: https://github.com/apache/spark/pull/32280
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[GitHub] [spark] gengliangwang commented on pull request #32280: [SPARK-35078][SQL] Add tree traversal pruning in expression rules
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on pull request #32280:
URL: https://github.com/apache/spark/pull/32280#issuecomment-825495849
Thanks, merging to master
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URL: https://github.com/apache/spark/pull/32280#issuecomment-825274305
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[GitHub] [spark] sigmod commented on pull request #32280: [SPARK-35078][SQL] Add tree traversal pruning in expression rules
Posted by GitBox <gi...@apache.org>.
sigmod commented on pull request #32280:
URL: https://github.com/apache/spark/pull/32280#issuecomment-825308281
@hvanhovell @gengliangwang @maryannxue @dbaliafroozeh this PR is ready for review. Let me know if I missed anything.
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[GitHub] [spark] gengliangwang commented on a change in pull request #32280: [SPARK-35078][SQL] Add tree traversal pruning in expression rules
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on a change in pull request #32280:
URL: https://github.com/apache/spark/pull/32280#discussion_r618936104
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/expressions.scala
##########
@@ -740,8 +751,10 @@ object NullPropagation extends Rule[LogicalPlan] {
case _ => false
}
- def apply(plan: LogicalPlan): LogicalPlan = plan transform {
- case q: LogicalPlan => q transformExpressionsUp {
+ def apply(plan: LogicalPlan): LogicalPlan = plan.transformWithPruning(
+ _.containsAnyPattern(NULL_CHECK, NULL_LITERAL, COUNT, CAST), ruleId) {
Review comment:
OK. I think now developers need to spend extra effort on choosing the Bits here. And there seems no good solution for avoiding regressions except for asking developers to add more unit tests.
Do you have any idea to improve the framework for this?
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[GitHub] [spark] sigmod commented on a change in pull request #32280: [SPARK-35078][SQL] Add tree traversal pruning in expression rules
Posted by GitBox <gi...@apache.org>.
sigmod commented on a change in pull request #32280:
URL: https://github.com/apache/spark/pull/32280#discussion_r618930570
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/expressions.scala
##########
@@ -740,8 +751,10 @@ object NullPropagation extends Rule[LogicalPlan] {
case _ => false
}
- def apply(plan: LogicalPlan): LogicalPlan = plan transform {
- case q: LogicalPlan => q transformExpressionsUp {
+ def apply(plan: LogicalPlan): LogicalPlan = plan.transformWithPruning(
+ _.containsAnyPattern(NULL_CHECK, NULL_LITERAL, COUNT, CAST), ruleId) {
Review comment:
I tried to capture the first case:
case e @ WindowExpression(Cast(Literal(0L, _), _, _), _)
I'm not sure why this pattern is related to NullPropagation, but that seems a separate issue.
I updated the condition to be more restrictive since CAST may be common in certain queries:
t.containsAnyPattern(NULL_CHECK, NULL_LITERAL, COUNT)
|| t.containsAllPatterns(WINDOW_EXPRESSION, CAST, LITERAL)
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[GitHub] [spark] gengliangwang commented on a change in pull request #32280: [SPARK-35078][SQL] Add tree traversal pruning in expression rules
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on a change in pull request #32280:
URL: https://github.com/apache/spark/pull/32280#discussion_r618925238
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
##########
@@ -29,7 +29,7 @@ import org.apache.spark.sql.catalyst.plans._
import org.apache.spark.sql.catalyst.plans.physical.{HashPartitioning, Partitioning, RangePartitioning, RoundRobinPartitioning, SinglePartition}
import org.apache.spark.sql.catalyst.trees.TreeNodeTag
import org.apache.spark.sql.catalyst.trees.TreePattern.{
- INNER_LIKE_JOIN, JOIN, LEFT_SEMI_OR_ANTI_JOIN, NATURAL_LIKE_JOIN, OUTER_JOIN, TreePattern
+ FILTER, INNER_LIKE_JOIN, JOIN, LEFT_SEMI_OR_ANTI_JOIN, NATURAL_LIKE_JOIN, OUTER_JOIN, TreePattern
Review comment:
nit:
import org.apache.spark.sql.catalyst.trees.TreePattern._
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[GitHub] [spark] sigmod commented on a change in pull request #32280: [SPARK-35078][SQL] Add tree traversal pruning in expression rules
Posted by GitBox <gi...@apache.org>.
sigmod commented on a change in pull request #32280:
URL: https://github.com/apache/spark/pull/32280#discussion_r618930030
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
##########
@@ -29,7 +29,7 @@ import org.apache.spark.sql.catalyst.plans._
import org.apache.spark.sql.catalyst.plans.physical.{HashPartitioning, Partitioning, RangePartitioning, RoundRobinPartitioning, SinglePartition}
import org.apache.spark.sql.catalyst.trees.TreeNodeTag
import org.apache.spark.sql.catalyst.trees.TreePattern.{
- INNER_LIKE_JOIN, JOIN, LEFT_SEMI_OR_ANTI_JOIN, NATURAL_LIKE_JOIN, OUTER_JOIN, TreePattern
+ FILTER, INNER_LIKE_JOIN, JOIN, LEFT_SEMI_OR_ANTI_JOIN, NATURAL_LIKE_JOIN, OUTER_JOIN, TreePattern
Review comment:
Done.
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[GitHub] [spark] sigmod commented on a change in pull request #32280: [SPARK-35078][SQL] Add tree traversal pruning in expression rules
Posted by GitBox <gi...@apache.org>.
sigmod commented on a change in pull request #32280:
URL: https://github.com/apache/spark/pull/32280#discussion_r618944025
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/expressions.scala
##########
@@ -740,8 +751,10 @@ object NullPropagation extends Rule[LogicalPlan] {
case _ => false
}
- def apply(plan: LogicalPlan): LogicalPlan = plan transform {
- case q: LogicalPlan => q transformExpressionsUp {
+ def apply(plan: LogicalPlan): LogicalPlan = plan.transformWithPruning(
+ _.containsAnyPattern(NULL_CHECK, NULL_LITERAL, COUNT, CAST), ruleId) {
Review comment:
>> seems no good solution for avoiding regressions except for asking developers to add more unit tests
- For an existing rule that we're adding this pruning, yes, we need to be careful, particularly when a rule has complex case patterns, although many rules are simple and intuitive.
- For a new rule or a new case branch in an existing rule, it seems that the regression risk doesn't change much? if a case pattern branch is not covered by unit tests, there's also a regression risk even without bits pruning, e.g., the case pattern could be wrong too.
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[GitHub] [spark] sigmod commented on a change in pull request #32280: [SPARK-35078][SQL] Add tree traversal pruning in expression rules
Posted by GitBox <gi...@apache.org>.
sigmod commented on a change in pull request #32280:
URL: https://github.com/apache/spark/pull/32280#discussion_r618930570
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/expressions.scala
##########
@@ -740,8 +751,10 @@ object NullPropagation extends Rule[LogicalPlan] {
case _ => false
}
- def apply(plan: LogicalPlan): LogicalPlan = plan transform {
- case q: LogicalPlan => q transformExpressionsUp {
+ def apply(plan: LogicalPlan): LogicalPlan = plan.transformWithPruning(
+ _.containsAnyPattern(NULL_CHECK, NULL_LITERAL, COUNT, CAST), ruleId) {
Review comment:
I tried to capture the first case:
case e @ WindowExpression(Cast(Literal(0L, _), _, _), _)
I'm not sure why this pattern is related to NullPropagation, but it probably deserve a separate change.
I updated the condition to be more restrictive since CAST may be common in certain queries:
t.containsAnyPattern(NULL_CHECK, NULL_LITERAL, COUNT)
|| t.containsAllPatterns(WINDOW_EXPRESSION, CAST, LITERAL)
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* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] [spark] sigmod commented on a change in pull request #32280: [SPARK-35078][SQL] Add tree traversal pruning in expression rules
Posted by GitBox <gi...@apache.org>.
sigmod commented on a change in pull request #32280:
URL: https://github.com/apache/spark/pull/32280#discussion_r618930570
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/expressions.scala
##########
@@ -740,8 +751,10 @@ object NullPropagation extends Rule[LogicalPlan] {
case _ => false
}
- def apply(plan: LogicalPlan): LogicalPlan = plan transform {
- case q: LogicalPlan => q transformExpressionsUp {
+ def apply(plan: LogicalPlan): LogicalPlan = plan.transformWithPruning(
+ _.containsAnyPattern(NULL_CHECK, NULL_LITERAL, COUNT, CAST), ruleId) {
Review comment:
I tried to capture the first case:
case e @ WindowExpression(Cast(Literal(0L, _), _, _), _)
I'm not sure why this pattern is related to NullPropagation, but it probably deserves a separate change.
I updated the condition to be more restrictive since CAST may be common in certain queries:
t.containsAnyPattern(NULL_CHECK, NULL_LITERAL, COUNT)
|| t.containsAllPatterns(WINDOW_EXPRESSION, CAST, LITERAL)
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[GitHub] [spark] gengliangwang commented on pull request #32280: [SPARK-35078][SQL] Add tree traversal pruning in expression rules
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gengliangwang commented on pull request #32280:
URL: https://github.com/apache/spark/pull/32280#issuecomment-825387938
@sigmod could you resolve the conflicts?
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[GitHub] [spark] gengliangwang commented on a change in pull request #32280: [SPARK-35078][SQL] Add tree traversal pruning in expression rules
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on a change in pull request #32280:
URL: https://github.com/apache/spark/pull/32280#discussion_r618924916
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/expressions.scala
##########
@@ -740,8 +751,10 @@ object NullPropagation extends Rule[LogicalPlan] {
case _ => false
}
- def apply(plan: LogicalPlan): LogicalPlan = plan transform {
- case q: LogicalPlan => q transformExpressionsUp {
+ def apply(plan: LogicalPlan): LogicalPlan = plan.transformWithPruning(
+ _.containsAnyPattern(NULL_CHECK, NULL_LITERAL, COUNT, CAST), ruleId) {
Review comment:
Why do we need `CAST` here?
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