[SPARK-31705][SQL] Push more possible predicates through Join via CNF…

… conversion

### What changes were proposed in this pull request?

This PR add a new rule to support push predicate through join by rewriting join condition to CNF(conjunctive normal form). The following example is the steps of this rule:

1. Prepare Table:

```sql
CREATE TABLE x(a INT);
CREATE TABLE y(b INT);
...
SELECT * FROM x JOIN y ON ((a < 0 and a > b) or a > 10);
```

2. Convert the join condition to CNF:
```
(a < 0 or a > 10) and (a > b or a > 10)
```

3. Split conjunctive predicates

Predicates
---|
(a < 0 or a > 10)
(a > b or a > 10)

4. Push predicate

Table | Predicate
--- | ---
x | (a < 0 or a > 10)

### Why are the changes needed?
Improve query performance. PostgreSQL, [Impala](https://issues.apache.org/jira/browse/IMPALA-9183) and Hive support this feature.

### Does this PR introduce _any_ user-facing change?
No.

### How was this patch tested?
Unit test and benchmark test.

SQL | Before this PR | After this PR
--- | --- | ---
TPCDS 5T Q13 | 84s | 21s
TPCDS 5T q85 | 66s | 34s
TPCH 1T q19 | 37s | 32s

Closes #28733 from gengliangwang/cnf.

Lead-authored-by: Gengliang Wang <[email protected]>
Co-authored-by: Yuming Wang <[email protected]>
Signed-off-by: Gengliang Wang <[email protected]>

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala

@@ -18,7 +18,9 @@
 package org.apache.spark.sql.catalyst.expressions
 
 import scala.collection.immutable.TreeSet
+import scala.collection.mutable
 
+import org.apache.spark.internal.Logging
 import org.apache.spark.sql.catalyst.CatalystTypeConverters.convertToScala
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.catalyst.analysis.TypeCheckResult
@@ -95,7 +97,7 @@ object Predicate extends CodeGeneratorWithInterpretedFallback[Expression, BasePr
   }
 }
 
-trait PredicateHelper {
+trait PredicateHelper extends Logging {
   protected def splitConjunctivePredicates(condition: Expression): Seq[Expression] = {
     condition match {
       case And(cond1, cond2) =>
@@ -198,6 +200,98 @@ trait PredicateHelper {
     case e: Unevaluable => false
     case e => e.children.forall(canEvaluateWithinJoin)
   }
+
+  /**
+   * Convert an expression into conjunctive normal form.
+   * Definition and algorithm: https://en.wikipedia.org/wiki/Conjunctive_normal_form
+   * 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.
+   * @return the CNF result as sequence of disjunctive expressions. If the number of expressions
+   *         exceeds threshold on converting `Or`, `Seq.empty` is returned.
+   */
+  def conjunctiveNormalForm(condition: Expression): Seq[Expression] = {
+    val postOrderNodes = postOrderTraversal(condition)
+    val resultStack = new mutable.Stack[Seq[Expression]]
+    val maxCnfNodeCount = SQLConf.get.maxCnfNodeCount
+    // Bottom up approach to get CNF of sub-expressions
+    while (postOrderNodes.nonEmpty) {
+      val cnf = postOrderNodes.pop() match {
+        case _: And =>
+          val right = resultStack.pop()
+          val left = resultStack.pop()
+          left ++ right
+        case _: Or =>
+          // For each side, there is no need to expand predicates of the same references.
+          // So here we can aggregate predicates of the same qualifier as one single predicate,
+          // for reducing the size of pushed down predicates and corresponding codegen.
+          val right = groupExpressionsByQualifier(resultStack.pop())
+          val left = groupExpressionsByQualifier(resultStack.pop())
+          // Stop the loop whenever the result exceeds the `maxCnfNodeCount`
+          if (left.size * right.size > maxCnfNodeCount) {
+            logInfo(s"As the result size exceeds the threshold $maxCnfNodeCount. " +
+              "The CNF conversion is skipped and returning Seq.empty now. To avoid this, you can " +
+              s"raise the limit ${SQLConf.MAX_CNF_NODE_COUNT.key}.")
+            return Seq.empty
+          } else {
+            for { x <- left; y <- right } yield Or(x, y)
+          }
+        case other => other :: Nil
+      }
+      resultStack.push(cnf)
+    }
+    if (resultStack.length != 1) {
+      logWarning("The length of CNF conversion result stack is supposed to be 1. There might " +
+        "be something wrong with CNF conversion.")
+      return Seq.empty
+    }
+    resultStack.top
+  }
+
+  private def groupExpressionsByQualifier(expressions: Seq[Expression]): Seq[Expression] = {
+    expressions.groupBy(_.references.map(_.qualifier)).map(_._2.reduceLeft(And)).toSeq
+  }
+
+  /**
+   * Iterative post order traversal over a binary tree built by And/Or clauses with two stacks.
+   * For example, a condition `(a And b) Or c`, the postorder traversal is
+   * (`a`,`b`, `And`, `c`, `Or`).
+   * Following is the complete algorithm. After step 2, we get the postorder traversal in
+   * the second stack.
+   * 1. Push root to first stack.
+   * 2. Loop while first stack is not empty
+   *    2.1 Pop a node from first stack and push it to second stack
+   *    2.2 Push the children of the popped node to first stack
+   *
+   * @param condition to be traversed as binary tree
+   * @return sub-expressions in post order traversal as a stack.
+   *         The first element of result stack is the leftmost node.
+   */
+  private def postOrderTraversal(condition: Expression): mutable.Stack[Expression] = {
+    val stack = new mutable.Stack[Expression]
+    val result = new mutable.Stack[Expression]
+    stack.push(condition)
+    while (stack.nonEmpty) {
+      val node = stack.pop()
+      node match {
+        case Not(a And b) => stack.push(Or(Not(a), Not(b)))
+        case Not(a Or b) => stack.push(And(Not(a), Not(b)))
+        case Not(Not(a)) => stack.push(a)
+        case a And b =>
+          result.push(node)
+          stack.push(a)
+          stack.push(b)
+        case a Or b =>
+          result.push(node)
+          stack.push(a)
+          stack.push(b)
+        case _ =>
+          result.push(node)
+      }
+    }
+    result
+  }
 }
 
 @ExpressionDescription(

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala

@@ -51,7 +51,8 @@ abstract class Optimizer(catalogManager: CatalogManager)
   override protected val blacklistedOnceBatches: Set[String] =
     Set(
       "PartitionPruning",
-      "Extract Python UDFs")
+      "Extract Python UDFs",
+      "Push CNF predicate through join")
 
   protected def fixedPoint =
     FixedPoint(
@@ -118,7 +119,11 @@ abstract class Optimizer(catalogManager: CatalogManager)
       Batch("Infer Filters", Once,
         InferFiltersFromConstraints) ::
       Batch("Operator Optimization after Inferring Filters", fixedPoint,
-        rulesWithoutInferFiltersFromConstraints: _*) :: Nil
+        rulesWithoutInferFiltersFromConstraints: _*) ::
+      // Set strategy to Once to avoid pushing filter every time because we do not change the
+      // join condition.
+      Batch("Push CNF predicate through join", Once,
+        PushCNFPredicateThroughJoin) :: Nil
     }
 
     val batches = (Batch("Eliminate Distinct", Once, EliminateDistinct) ::

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/PushCNFPredicateThroughJoin.scala

@@ -0,0 +1,62 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst.optimizer
+
+import org.apache.spark.sql.catalyst.expressions.{And, PredicateHelper}
+import org.apache.spark.sql.catalyst.plans._
+import org.apache.spark.sql.catalyst.plans.logical.{Filter, Join, LogicalPlan}
+import org.apache.spark.sql.catalyst.rules.Rule
+
+/**
+ * Try converting join condition to conjunctive normal form expression so that more predicates may
+ * be able to be pushed down.
+ * To avoid expanding the join condition, the join condition will be kept in the original form even
+ * when predicate pushdown happens.
+ */
+object PushCNFPredicateThroughJoin extends Rule[LogicalPlan] with PredicateHelper {
+  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
+    case j @ Join(left, right, joinType, Some(joinCondition), hint) =>
+      val predicates = conjunctiveNormalForm(joinCondition)
+      if (predicates.isEmpty) {
+        j
+      } else {
+        val pushDownCandidates = predicates.filter(_.deterministic)
+        lazy val leftFilterConditions =
+          pushDownCandidates.filter(_.references.subsetOf(left.outputSet))
+        lazy val rightFilterConditions =
+          pushDownCandidates.filter(_.references.subsetOf(right.outputSet))
+
+        lazy val newLeft =
+          leftFilterConditions.reduceLeftOption(And).map(Filter(_, left)).getOrElse(left)
+        lazy val newRight =
+          rightFilterConditions.reduceLeftOption(And).map(Filter(_, right)).getOrElse(right)
+
+        joinType match {
+          case _: InnerLike | LeftSemi =>
+            Join(newLeft, newRight, joinType, Some(joinCondition), hint)
+          case RightOuter =>
+            Join(newLeft, right, RightOuter, Some(joinCondition), hint)
+          case LeftOuter | LeftAnti | ExistenceJoin(_) =>
+            Join(left, newRight, joinType, Some(joinCondition), hint)
+          case FullOuter => j
+          case NaturalJoin(_) => sys.error("Untransformed NaturalJoin node")
+          case UsingJoin(_, _) => sys.error("Untransformed Using join node")
+        }
+      }
+  }
+}

sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala

@@ -545,6 +545,19 @@ object SQLConf {
     .booleanConf
     .createWithDefault(true)
 
+  val MAX_CNF_NODE_COUNT =
+    buildConf("spark.sql.optimizer.maxCNFNodeCount")
+      .internal()
+      .doc("Specifies the maximum allowable number of conjuncts in the result of CNF " +
+        "conversion. If the conversion exceeds the threshold, an empty sequence is returned. " +
+        "For example, CNF conversion of (a && b) || (c && d) generates " +
+        "four conjuncts (a || c) && (a || d) && (b || c) && (b || d).")
+      .version("3.1.0")
+      .intConf
+      .checkValue(_ >= 0,
+        "The depth of the maximum rewriting conjunction normal form must be positive.")
+      .createWithDefault(128)
+
   val ESCAPED_STRING_LITERALS = buildConf("spark.sql.parser.escapedStringLiterals")
     .internal()
     .doc("When true, string literals (including regex patterns) remain escaped in our SQL " +
@@ -2874,6 +2887,8 @@ class SQLConf extends Serializable with Logging {
 
   def constraintPropagationEnabled: Boolean = getConf(CONSTRAINT_PROPAGATION_ENABLED)
 
+  def maxCnfNodeCount: Int = getConf(MAX_CNF_NODE_COUNT)
+
   def escapedStringLiterals: Boolean = getConf(ESCAPED_STRING_LITERALS)
 
   def fileCompressionFactor: Double = getConf(FILE_COMPRESSION_FACTOR)

sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ConjunctiveNormalFormPredicateSuite.scala

@@ -0,0 +1,128 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst.expressions
+
+import org.apache.spark.SparkFunSuite
+import org.apache.spark.sql.catalyst.dsl.expressions._
+import org.apache.spark.sql.catalyst.plans.PlanTest
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.types.BooleanType
+
+class ConjunctiveNormalFormPredicateSuite extends SparkFunSuite with PredicateHelper with PlanTest {
+  private val a = AttributeReference("A", BooleanType)(exprId = ExprId(1)).withQualifier(Seq("ta"))
+  private val b = AttributeReference("B", BooleanType)(exprId = ExprId(2)).withQualifier(Seq("tb"))
+  private val c = AttributeReference("C", BooleanType)(exprId = ExprId(3)).withQualifier(Seq("tc"))
+  private val d = AttributeReference("D", BooleanType)(exprId = ExprId(4)).withQualifier(Seq("td"))
+  private val e = AttributeReference("E", BooleanType)(exprId = ExprId(5)).withQualifier(Seq("te"))
+  private val f = AttributeReference("F", BooleanType)(exprId = ExprId(6)).withQualifier(Seq("tf"))
+  private val g = AttributeReference("G", BooleanType)(exprId = ExprId(7)).withQualifier(Seq("tg"))
+  private val h = AttributeReference("H", BooleanType)(exprId = ExprId(8)).withQualifier(Seq("th"))
+  private val i = AttributeReference("I", BooleanType)(exprId = ExprId(9)).withQualifier(Seq("ti"))
+  private val j = AttributeReference("J", BooleanType)(exprId = ExprId(10)).withQualifier(Seq("tj"))
+  private val a1 =
+    AttributeReference("a1", BooleanType)(exprId = ExprId(11)).withQualifier(Seq("ta"))
+  private val a2 =
+    AttributeReference("a2", BooleanType)(exprId = ExprId(12)).withQualifier(Seq("ta"))
+  private val b1 =
+    AttributeReference("b1", BooleanType)(exprId = ExprId(12)).withQualifier(Seq("tb"))
+
+  // Check CNF conversion with expected expression, assuming the input has non-empty result.
+  private def checkCondition(input: Expression, expected: Expression): Unit = {
+    val cnf = conjunctiveNormalForm(input)
+    assert(cnf.nonEmpty)
+    val result = cnf.reduceLeft(And)
+    assert(result.semanticEquals(expected))
+  }
+
+  test("Keep non-predicated expressions") {
+    checkCondition(a, a)
+    checkCondition(Literal(1), Literal(1))
+  }
+
+  test("Conversion of Not") {
+    checkCondition(!a, !a)
+    checkCondition(!(!a), a)
+    checkCondition(!(!(a && b)), a && b)
+    checkCondition(!(!(a || b)), a || b)
+    checkCondition(!(a || b), !a && !b)
+    checkCondition(!(a && b), !a || !b)
+  }
+
+  test("Conversion of And") {
+    checkCondition(a && b, a && b)
+    checkCondition(a && b && c, a && b && c)
+    checkCondition(a && (b || c), a && (b || c))
+    checkCondition((a || b) && c, (a || b) && c)
+    checkCondition(a && b && c && d, a && b && c && d)
+  }
+
+  test("Conversion of Or") {
+    checkCondition(a || b, a || b)
+    checkCondition(a || b || c, a || b || c)
+    checkCondition(a || b || c || d, a || b || c || d)
+    checkCondition((a && b) || c, (a || c) && (b || c))
+    checkCondition((a && b) || (c && d), (a || c) && (a || d) && (b || c) && (b || d))
+  }
+
+  test("More complex cases") {
+    checkCondition(a && !(b || c), a && !b && !c)
+    checkCondition((a && b) || !(c && d), (a || !c || !d) && (b || !c || !d))
+    checkCondition(a || b || c && d, (a || b || c) && (a || b || d))
+    checkCondition(a || (b && c || d), (a || b || d) && (a || c || d))
+    checkCondition(a && !(b && c || d && e), a && (!b || !c) && (!d || !e))
+    checkCondition(((a && b) || c) || (d || e), (a || c || d || e) && (b || c || d || e))
+
+    checkCondition(
+      (a && b && c) || (d && e && f),
+      (a || d) && (a || e) && (a || f) && (b || d) && (b || e) && (b || f) &&
+      (c || d) && (c || e) && (c || f)
+    )
+  }
+
+  test("Aggregate predicate of same qualifiers to avoid expanding") {
+    checkCondition(((a && b && a1) || c), ((a && a1) || c) && (b ||c))
+    checkCondition(((a && a1 && b) || c), ((a && a1) || c) && (b ||c))
+    checkCondition(((b && d && a && a1) || c), ((a && a1) || c) && (b ||c) && (d || c))
+    checkCondition(((b && a2 && d && a && a1) || c), ((a2 && a && a1) || c) && (b ||c) && (d || c))
+    checkCondition(((b && d && a && a1 && b1) || c),
+      ((a && a1) || c) && ((b && b1) ||c) && (d || c))
+    checkCondition((a && a1) || (b && b1), (a && a1) || (b && b1))
+    checkCondition((a && a1 && c) || (b && b1), ((a && a1) || (b && b1)) && (c || (b && b1)))
+  }
+
+  test("Return Seq.empty when exceeding MAX_CNF_NODE_COUNT") {
+    // The following expression contains 36 conjunctive sub-expressions in CNF
+    val input = (a && b && c) || (d && e && f) || (g && h && i && j)
+    // The following expression contains 9 conjunctive sub-expressions in CNF
+    val input2 = (a && b && c) || (d && e && f)
+    Seq(8, 9, 10, 35, 36, 37).foreach { maxCount =>
+      withSQLConf(SQLConf.MAX_CNF_NODE_COUNT.key -> maxCount.toString) {
+        if (maxCount < 36) {
+          assert(conjunctiveNormalForm(input).isEmpty)
+        } else {
+          assert(conjunctiveNormalForm(input).nonEmpty)
+        }
+        if (maxCount < 9) {
+          assert(conjunctiveNormalForm(input2).isEmpty)
+        } else {
+          assert(conjunctiveNormalForm(input2).nonEmpty)
+        }
+      }
+    }
+  }
+}