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[GitHub] [spark] gengliangwang opened a new pull request #29075: [SPARK-32284][SQL] Avoid pushing down too many predicated in partition pruning
gengliangwang opened a new pull request #29075:
URL: https://github.com/apache/spark/pull/29075
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After https://github.com/apache/spark/pull/28805, the pushed down predicates for partition pruning can be very long.
For example, the following partition filter:
```
(p0 = '1' AND p1 = '1') OR (p0 = '2' AND p1 = '2') OR (p0 = '3' AND p1 = '3') OR (p0 = '4' AND p1 = '4') OR (p0 = '5' AND p1 = '5') OR (p0 = '6' AND p1 = '6') OR (p0 = '7' AND p1 = '7') OR (p0 = '8' AND p1 = '8') OR (p0 = '9' AND p1 = '9') OR (p0 = '10' AND p1 = '10') OR (p0 = '11' AND p1 = '11') OR (p0 = '12' AND p1 = '12') OR (p0 = '13' AND p1 = '13') OR (p0 = '14' AND p1 = '14') OR (p0 = '15' AND p1 = '15') OR (p0 = '16' AND p1 = '16') OR (p0 = '17' AND p1 = '17') OR (p0 = '18' AND p1 = '18') OR (p0 = '19' AND p1 = '19') OR (p0 = '20' AND p1 = '20')
```
will be converted into a long query(130K characters) in Hive metastore, and there will be error:
```
javax.jdo.JDOException: Exception thrown when executing query : SELECT DISTINCT 'org.apache.hadoop.hive.metastore.model.MPartition' AS NUCLEUS_TYPE,A0.CREATE_TIME,A0.LAST_ACCESS_TIME,A0.PART_NAME,A0.PART_ID,A0.PART_NAME AS NUCORDER0 FROM PARTITIONS A0 LEFT OUTER JOIN TBLS B0 ON A0.TBL_ID = B0.TBL_ID LEFT OUTER JOIN DBS C0 ON B0.DB_ID = C0.DB_ID WHERE B0.TBL_NAME = ? AND C0."NAME" = ? AND ((((((A0.PART_NAME LIKE '%/p1=1' ESCAPE '\' ) OR (A0.PART_NAME LIKE '%/p1=2' ESCAPE '\' )) OR (A0.PART_NAME LIKE '%/p1=3' ESCAPE '\' )) OR ((A0.PART_NAME LIKE '%/p1=4' ESCAPE '\' ) O ...
```
To avoid it:
1. We should push down the convertible original queries as they are, instead of converting all predicates into CNF
2. We can skip grouping expressions so that we can stop the CNF conversion when the predicates becoming too long.
### Why are the changes needed?
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Avoid potential regressions in partition pruning.
### Does this PR introduce _any_ user-facing change?
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No
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Unit test
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[GitHub] [spark] maropu commented on a change in pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
maropu commented on a change in pull request #29075:
URL: https://github.com/apache/spark/pull/29075#discussion_r453388615
##########
File path: sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/PruneHiveTablePartitions.scala
##########
@@ -103,7 +110,7 @@ private[sql] class PruneHiveTablePartitions(session: SparkSession)
override def apply(plan: LogicalPlan): LogicalPlan = plan resolveOperators {
case op @ PhysicalOperation(projections, filters, relation: HiveTableRelation)
if filters.nonEmpty && relation.isPartitioned && relation.prunedPartitions.isEmpty =>
- val predicates = CNFWithGroupExpressionsByReference(filters.reduceLeft(And))
+ val predicates = CNFConversion(filters.reduceLeft(And))
Review comment:
nit: `conjunctiveNormalForm(filters.reduceLeft(And), identity)`?
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Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #29075:
URL: https://github.com/apache/spark/pull/29075#issuecomment-657393239
**[Test build #125746 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/125746/testReport)** for PR 29075 at commit [`df08390`](https://github.com/apache/spark/commit/df083906f2d9938d77b4b41878271af1826b5220).
* This patch **fails due to an unknown error code, -9**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] [spark] gengliangwang commented on a change in pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on a change in pull request #29075:
URL: https://github.com/apache/spark/pull/29075#discussion_r453408669
##########
File path: sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/PruneHiveTablePartitions.scala
##########
@@ -54,9 +55,15 @@ private[sql] class PruneHiveTablePartitions(session: SparkSession)
val normalizedFilters = DataSourceStrategy.normalizeExprs(
filters.filter(f => f.deterministic && !SubqueryExpression.hasSubquery(f)), relation.output)
val partitionColumnSet = AttributeSet(relation.partitionCols)
- ExpressionSet(normalizedFilters.filter { f =>
+ val (partitionFilters, remainingFilters) = normalizedFilters.partition { f =>
!f.references.isEmpty && f.references.subsetOf(partitionColumnSet)
- })
+ }
+ // Try extracting more convertible partition filters from the remaining filters by converting
+ // them into CNF.
+ val remainingFilterInCnf = remainingFilters.flatMap(CNFConversion)
+ val extraPartitionFilters = remainingFilterInCnf.filter(f =>
+ !f.references.isEmpty && f.references.subsetOf(partitionColumnSet))
+ ExpressionSet(partitionFilters ++ extraPartitionFilters)
Review comment:
The `filters` here is already processed with `splitConjunctivePredicates` in `PhysicalOperation.unapply`. That's why the original code before #28805 doesn't call `splitConjunctivePredicates` either.
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Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/29075#issuecomment-657423860
**[Test build #125758 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/125758/testReport)** for PR 29075 at commit [`6fe106c`](https://github.com/apache/spark/commit/6fe106ce84e83641d66d572c45050b25761bbf3d).
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[GitHub] [spark] maropu commented on a change in pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
maropu commented on a change in pull request #29075:
URL: https://github.com/apache/spark/pull/29075#discussion_r453999940
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PruneFileSourcePartitions.scala
##########
@@ -53,11 +53,17 @@ private[sql] object PruneFileSourcePartitions
val partitionColumns =
relation.resolve(partitionSchema, sparkSession.sessionState.analyzer.resolver)
val partitionSet = AttributeSet(partitionColumns)
- val (partitionFilters, dataFilters) = normalizedFilters.partition(f =>
+ val (partitionFilters, remainingFilters) = normalizedFilters.partition(f =>
f.references.subsetOf(partitionSet)
)
- (ExpressionSet(partitionFilters), dataFilters)
+ // Try extracting more convertible partition filters from the remaining filters by converting
+ // them into CNF.
+ val remainingFilterInCnf = remainingFilters.flatMap(CNFConversion)
+ val extraPartitionFilters =
+ remainingFilterInCnf.filter(f => f.references.subsetOf(partitionSet))
+
+ (ExpressionSet(partitionFilters ++ extraPartitionFilters), remainingFilters)
Review comment:
okay.
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[GitHub] [spark] gengliangwang commented on pull request #29075: [SPARK-32284][SQL] Avoid pushing down too many predicated in partition pruning
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on pull request #29075:
URL: https://github.com/apache/spark/pull/29075#issuecomment-657222077
cc @AngersZhuuuu @cloud-fan
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[GitHub] [spark] gengliangwang commented on a change in pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on a change in pull request #29075:
URL: https://github.com/apache/spark/pull/29075#discussion_r453409529
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PruneFileSourcePartitions.scala
##########
@@ -53,11 +53,17 @@ private[sql] object PruneFileSourcePartitions
val partitionColumns =
relation.resolve(partitionSchema, sparkSession.sessionState.analyzer.resolver)
val partitionSet = AttributeSet(partitionColumns)
- val (partitionFilters, dataFilters) = normalizedFilters.partition(f =>
+ val (partitionFilters, remainingFilters) = normalizedFilters.partition(f =>
f.references.subsetOf(partitionSet)
)
- (ExpressionSet(partitionFilters), dataFilters)
+ // Try extracting more convertible partition filters from the remaining filters by converting
+ // them into CNF.
+ val remainingFilterInCnf = remainingFilters.flatMap(CNFConversion)
+ val extraPartitionFilters =
+ remainingFilterInCnf.filter(f => f.references.subsetOf(partitionSet))
+
+ (ExpressionSet(partitionFilters ++ extraPartitionFilters), remainingFilters)
Review comment:
In that way, `otherFilters` can be very long, which leads to a longer codegen... I am avoiding that on purpose. Let me add comment here.
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[GitHub] [spark] dongjoon-hyun edited a comment on pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
dongjoon-hyun edited a comment on pull request #29075:
URL: https://github.com/apache/spark/pull/29075#issuecomment-657275435
Thank you for updating, @gengliangwang . Shall we adjust this test case name accordingly together?
```
test("SPARK-32284: Avoid pushing down too many predicates in partition pruning") {
```
BTW, in the test case, since `20` looks like reasonably a small number in the Spark world. Could you use more functional word to describe the change? For example, this PR is not limiting based on the number of predicate like `10 is possible, but 20 is not allowed`. Apache Spark still will hit the HMS issue when we have a long long SQL query with `too many predicates` after this PR. So, this PR doesn't fix `Avoid pushing down too many predicates in partition pruning`. Instead, this PR looks like mitigating the regression due to the previous improvement PR.
```
We should push down the convertible original queries as they are, instead of converting all predicates into CNF
We can skip grouping expressions so that we can stop the CNF conversion when the predicates becoming too long.
```
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[GitHub] [spark] maropu commented on a change in pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
maropu commented on a change in pull request #29075:
URL: https://github.com/apache/spark/pull/29075#discussion_r454001849
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala
##########
@@ -207,13 +207,15 @@ trait PredicateHelper extends Logging {
* CNF can explode exponentially in the size of the input expression when converting [[Or]]
* clauses. Use a configuration [[SQLConf.MAX_CNF_NODE_COUNT]] to prevent such cases.
*
- * @param condition to be converted into CNF.
+ * @param condition Condition to be converted into CNF.
+ * @param groupExpsFunc A method for grouping intermediate results so that the final result can be
+ * shorter.
Review comment:
`A method to group expressions for reducing the size of pushed down predicates and corresponding codegen`?
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[GitHub] [spark] dongjoon-hyun commented on pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
dongjoon-hyun commented on pull request #29075:
URL: https://github.com/apache/spark/pull/29075#issuecomment-657275435
Thank you for updating, @gengliangwang . Shall we adjust this test case name accordingly together?
```
test("SPARK-32284: Avoid pushing down too many predicates in partition pruning") {
```
BTW, in the test case, since `20` looks reasonably a small number in the Spark world. Could you use more functional word to describe the change? For example, this PR is not limiting based on the number of predicate like `10 is possible, but 20 is not allowed`. Apache Spark still will hit the HMS issue when we have a long long SQL query with `too many predicates` after this PR. So, this PR doesn't fix `Avoid pushing down too many predicates in partition pruning`. Instead, this PR looks like mitigating the regression due to the previous improvement PR.
```
We should push down the convertible original queries as they are, instead of converting all predicates into CNF
We can skip grouping expressions so that we can stop the CNF conversion when the predicates becoming too long.
```
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URL: https://github.com/apache/spark/pull/29075#issuecomment-657580499
**[Test build #125758 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/125758/testReport)** for PR 29075 at commit [`6fe106c`](https://github.com/apache/spark/commit/6fe106ce84e83641d66d572c45050b25761bbf3d).
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[GitHub] [spark] maropu commented on a change in pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
maropu commented on a change in pull request #29075:
URL: https://github.com/apache/spark/pull/29075#discussion_r453391118
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PruneFileSourcePartitions.scala
##########
@@ -53,11 +53,17 @@ private[sql] object PruneFileSourcePartitions
val partitionColumns =
relation.resolve(partitionSchema, sparkSession.sessionState.analyzer.resolver)
val partitionSet = AttributeSet(partitionColumns)
- val (partitionFilters, dataFilters) = normalizedFilters.partition(f =>
+ val (partitionFilters, remainingFilters) = normalizedFilters.partition(f =>
f.references.subsetOf(partitionSet)
)
- (ExpressionSet(partitionFilters), dataFilters)
+ // Try extracting more convertible partition filters from the remaining filters by converting
+ // them into CNF.
+ val remainingFilterInCnf = remainingFilters.flatMap(CNFConversion)
+ val extraPartitionFilters =
+ remainingFilterInCnf.filter(f => f.references.subsetOf(partitionSet))
+
+ (ExpressionSet(partitionFilters ++ extraPartitionFilters), remainingFilters)
Review comment:
```
val (extraPartitionFilters, otherFilters) = remainingFilterInCnf.partition(f =>
f.references.subsetOf(partitionSet)
)
(ExpressionSet(partitionFilters ++ extraPartitionFilters), otherFilters)
```
?
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[GitHub] [spark] gengliangwang commented on pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on pull request #29075:
URL: https://github.com/apache/spark/pull/29075#issuecomment-657250180
@dongjoon-hyun Thanks for the suggestion. I have updated the title.
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Posted by GitBox <gi...@apache.org>.
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[GitHub] [spark] SparkQA commented on pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #29075:
URL: https://github.com/apache/spark/pull/29075#issuecomment-657258446
**[Test build #125715 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/125715/testReport)** for PR 29075 at commit [`ccba836`](https://github.com/apache/spark/commit/ccba8360f2815d1445816e75e33a9c2f41f1072e).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] [spark] AngersZhuuuu commented on a change in pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
AngersZhuuuu commented on a change in pull request #29075:
URL: https://github.com/apache/spark/pull/29075#discussion_r453392851
##########
File path: sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/PruneHiveTablePartitions.scala
##########
@@ -27,6 +27,7 @@ import org.apache.spark.sql.catalyst.planning.PhysicalOperation
import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, Project}
import org.apache.spark.sql.catalyst.rules.Rule
import org.apache.spark.sql.execution.datasources.DataSourceStrategy
+import org.apache.spark.sql.execution.datasources.PruneFileSourcePartitions.CNFConversion
import org.apache.spark.sql.internal.SQLConf
Review comment:
This import is not necessary.
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[GitHub] [spark] AngersZhuuuu commented on a change in pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
AngersZhuuuu commented on a change in pull request #29075:
URL: https://github.com/apache/spark/pull/29075#discussion_r453394363
##########
File path: sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/PruneHiveTablePartitions.scala
##########
@@ -54,9 +55,15 @@ private[sql] class PruneHiveTablePartitions(session: SparkSession)
val normalizedFilters = DataSourceStrategy.normalizeExprs(
filters.filter(f => f.deterministic && !SubqueryExpression.hasSubquery(f)), relation.output)
val partitionColumnSet = AttributeSet(relation.partitionCols)
- ExpressionSet(normalizedFilters.filter { f =>
+ val (partitionFilters, remainingFilters) = normalizedFilters.partition { f =>
!f.references.isEmpty && f.references.subsetOf(partitionColumnSet)
- })
+ }
+ // Try extracting more convertible partition filters from the remaining filters by converting
+ // them into CNF.
+ val remainingFilterInCnf = remainingFilters.flatMap(CNFConversion)
+ val extraPartitionFilters = remainingFilterInCnf.filter(f =>
+ !f.references.isEmpty && f.references.subsetOf(partitionColumnSet))
+ ExpressionSet(partitionFilters ++ extraPartitionFilters)
Review comment:
I am confused that seems CNFConversion won't change references, You don't need to call a `splitConjunctivePredicates` to each expr in `remainingFilterInCnf` to extract more predicate?
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[GitHub] [spark] maropu commented on a change in pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
maropu commented on a change in pull request #29075:
URL: https://github.com/apache/spark/pull/29075#discussion_r454001849
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala
##########
@@ -207,13 +207,15 @@ trait PredicateHelper extends Logging {
* CNF can explode exponentially in the size of the input expression when converting [[Or]]
* clauses. Use a configuration [[SQLConf.MAX_CNF_NODE_COUNT]] to prevent such cases.
*
- * @param condition to be converted into CNF.
+ * @param condition Condition to be converted into CNF.
+ * @param groupExpsFunc A method for grouping intermediate results so that the final result can be
+ * shorter.
Review comment:
nit: `A method to group expressions for reducing the size of pushed down predicates and corresponding codegen`?
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[GitHub] [spark] gengliangwang commented on pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on pull request #29075:
URL: https://github.com/apache/spark/pull/29075#issuecomment-658631580
https://github.com/apache/spark/pull/29101 is a better solution to me. Close this one now.
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[GitHub] [spark] gengliangwang closed pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning
Posted by GitBox <gi...@apache.org>.
gengliangwang closed pull request #29075:
URL: https://github.com/apache/spark/pull/29075
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