[SPARK-12218][SQL] Invalid splitting of nested AND expressions in Dat…

…a Source filter API

JIRA: https://issues.apache.org/jira/browse/SPARK-12218

When creating filters for Parquet/ORC, we should not push nested AND expressions partially.

Author: Yin Huai <[email protected]>

Closes #10362 from yhuai/SPARK-12218.

(cherry picked from commit 41ee7c5)
Signed-off-by: Yin Huai <[email protected]>

Conflicts:
	sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilters.scala

@@ -264,7 +264,17 @@ private[sql] object ParquetFilters {
         makeGtEq.lift(dataTypeOf(name)).map(_(name, value))
 
       case sources.And(lhs, rhs) =>
-        (createFilter(schema, lhs) ++ createFilter(schema, rhs)).reduceOption(FilterApi.and)
+        // At here, it is not safe to just convert one side if we do not understand the
+        // other side. Here is an example used to explain the reason.
+        // Let's say we have NOT(a = 2 AND b in ('1')) and we do not understand how to
+        // convert b in ('1'). If we only convert a = 2, we will end up with a filter
+        // NOT(a = 2), which will generate wrong results.
+        // Pushing one side of AND down is only safe to do at the top level.
+        // You can see ParquetRelation's initializeLocalJobFunc method as an example.
+        for {
+          lhsFilter <- createFilter(schema, lhs)
+          rhsFilter <- createFilter(schema, rhs)
+        } yield FilterApi.and(lhsFilter, rhsFilter)
 
       case sources.Or(lhs, rhs) =>
         for {

sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala

@@ -336,4 +336,23 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex
       }
     }
   }
+
+  test("SPARK-12218: 'Not' is included in Parquet filter pushdown") {
+    import testImplicits._
+
+    withSQLConf(SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED.key -> "true") {
+      withTempPath { dir =>
+        val path = s"${dir.getCanonicalPath}/table1"
+        (1 to 5).map(i => (i, (i % 2).toString)).toDF("a", "b").write.parquet(path)
+
+        checkAnswer(
+          sqlContext.read.parquet(path).where("not (a = 2) or not(b in ('1'))"),
+          (1 to 5).map(i => Row(i, (i % 2).toString)))
+
+        checkAnswer(
+          sqlContext.read.parquet(path).where("not (a = 2 and b in ('1'))"),
+          (1 to 5).map(i => Row(i, (i % 2).toString)))
+      }
+    }
+  }
 }

sql/hive/src/main/scala/org/apache/spark/sql/hive/orc/OrcFilters.scala

@@ -74,22 +74,20 @@ private[orc] object OrcFilters extends Logging {
 
     expression match {
       case And(left, right) =>
-        val tryLeft = buildSearchArgument(left, newBuilder)
-        val tryRight = buildSearchArgument(right, newBuilder)
-
-        val conjunction = for {
-          _ <- tryLeft
-          _ <- tryRight
+        // At here, it is not safe to just convert one side if we do not understand the
+        // other side. Here is an example used to explain the reason.
+        // Let's say we have NOT(a = 2 AND b in ('1')) and we do not understand how to
+        // convert b in ('1'). If we only convert a = 2, we will end up with a filter
+        // NOT(a = 2), which will generate wrong results.
+        // Pushing one side of AND down is only safe to do at the top level.
+        // You can see ParquetRelation's initializeLocalJobFunc method as an example.
+        for {
+          _ <- buildSearchArgument(left, newBuilder)
+          _ <- buildSearchArgument(right, newBuilder)
           lhs <- buildSearchArgument(left, builder.startAnd())
           rhs <- buildSearchArgument(right, lhs)
         } yield rhs.end()
 
-        // For filter `left AND right`, we can still push down `left` even if `right` is not
-        // convertible, and vice versa.
-        conjunction
-          .orElse(tryLeft.flatMap(_ => buildSearchArgument(left, builder)))
-          .orElse(tryRight.flatMap(_ => buildSearchArgument(right, builder)))
-
       case Or(left, right) =>
         for {
           _ <- buildSearchArgument(left, newBuilder)

sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcHadoopFsRelationSuite.scala

@@ -20,6 +20,7 @@ package org.apache.spark.sql.hive.orc
 import org.apache.hadoop.fs.Path
 
 import org.apache.spark.deploy.SparkHadoopUtil
+import org.apache.spark.sql.{Row, SQLConf}
 import org.apache.spark.sql.sources.HadoopFsRelationTest
 import org.apache.spark.sql.types._
 
@@ -61,4 +62,23 @@ class OrcHadoopFsRelationSuite extends HadoopFsRelationTest {
           "dataSchema" -> dataSchemaWithPartition.json)).format(dataSourceName).load())
     }
   }
+
+  test("SPARK-12218: 'Not' is included in ORC filter pushdown") {
+    import testImplicits._
+
+    withSQLConf(SQLConf.ORC_FILTER_PUSHDOWN_ENABLED.key -> "true") {
+      withTempPath { dir =>
+        val path = s"${dir.getCanonicalPath}/table1"
+        (1 to 5).map(i => (i, (i % 2).toString)).toDF("a", "b").write.orc(path)
+
+        checkAnswer(
+          sqlContext.read.orc(path).where("not (a = 2) or not(b in ('1'))"),
+          (1 to 5).map(i => Row(i, (i % 2).toString)))
+
+        checkAnswer(
+          sqlContext.read.orc(path).where("not (a = 2 and b in ('1'))"),
+          (1 to 5).map(i => Row(i, (i % 2).toString)))
+      }
+    }
+  }
 }