Filter nulls for left semi and left anti join to work around cudf (NV…

…IDIA#1664)

Signed-off-by: Alessandro Bellina <abellina@nvidia.com>

sql-plugin/src/main/scala/org/apache/spark/sql/rapids/execution/GpuHashJoin.scala

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
+ * Copyright (c) 2020-2021, NVIDIA CORPORATION. All rights reserved.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -16,14 +16,13 @@
 package org.apache.spark.sql.rapids.execution
 
 import ai.rapids.cudf.{NvtxColor, Table}
-import com.nvidia.spark.rapids.{CoalesceGoal, GpuBindReferences, GpuBoundReference, GpuBuildLeft, GpuBuildRight, GpuBuildSide, GpuColumnVector, GpuExec, GpuExpression, GpuFilter, GpuIsNotNull, GpuProjectExec, NvtxWithMetrics, RapidsMeta, RequireSingleBatch}
+import com.nvidia.spark.rapids.{CoalesceGoal, GpuBindReferences, GpuBuildLeft, GpuBuildRight, GpuBuildSide, GpuColumnVector, GpuExec, GpuExpression, GpuFilter, GpuIsNotNull, GpuProjectExec, NvtxWithMetrics, RapidsMeta, RequireSingleBatch}
 
 import org.apache.spark.TaskContext
 import org.apache.spark.sql.catalyst.expressions.{Attribute, Expression}
 import org.apache.spark.sql.catalyst.plans.{ExistenceJoin, FullOuter, InnerLike, JoinType, LeftAnti, LeftExistence, LeftOuter, LeftSemi, RightOuter}
 import org.apache.spark.sql.execution.SparkPlan
 import org.apache.spark.sql.execution.metric.SQLMetric
-import org.apache.spark.sql.rapids.GpuAnd
 import org.apache.spark.sql.vectorized.{ColumnarBatch, ColumnVector}
 
 object GpuHashJoin {
@@ -232,16 +231,23 @@ trait GpuHashJoin extends GpuExec {
       GpuColumnVector.from(cb)
     }
 
-    val nvtxRange = new NvtxWithMetrics("hash join", NvtxColor.ORANGE, joinTime)
-    val joined = try {
-      buildSide match {
-        case GpuBuildLeft => doJoinLeftRight(builtTable, streamedTable)
-        case GpuBuildRight => doJoinLeftRight(streamedTable, builtTable)
+    val joined =
+      withResource(new NvtxWithMetrics("hash join", NvtxColor.ORANGE, joinTime)) { _ =>
+        // `doJoinLeftRight` closes the right table if the last argument (`closeRightTable`)
+        // is true, but never closes the left table.
+        buildSide match {
+          case GpuBuildLeft =>
+            // tell `doJoinLeftRight` it is ok to close the `streamedTable`, this can help
+            // in order to close temporary/intermediary data after a filter in some scenarios.
+            doJoinLeftRight(builtTable, streamedTable, true)
+          case GpuBuildRight =>
+            // tell `doJoinLeftRight` to not close `builtTable`, as it is owned by our caller,
+            // here we close the left table as that one is never closed by `doJoinLeftRight`.
+            withResource(streamedTable) { _ =>
+              doJoinLeftRight(streamedTable, builtTable, false)
+            }
+        }
       }
-    } finally {
-      streamedTable.close()
-      nvtxRange.close()
-    }
 
     numJoinOutputRows += joined.numRows()
 
@@ -262,23 +268,79 @@ trait GpuHashJoin extends GpuExec {
     }
   }
 
-  private[this] def doJoinLeftRight(leftTable: Table, rightTable: Table): ColumnarBatch = {
-    val joinedTable = joinType match {
-      case LeftOuter => leftTable.onColumns(joinKeyIndices: _*)
-          .leftJoin(rightTable.onColumns(joinKeyIndices: _*), false)
-      case RightOuter => rightTable.onColumns(joinKeyIndices: _*)
-          .leftJoin(leftTable.onColumns(joinKeyIndices: _*), false)
-      case _: InnerLike => leftTable.onColumns(joinKeyIndices: _*)
-          .innerJoin(rightTable.onColumns(joinKeyIndices: _*), false)
-      case LeftSemi => leftTable.onColumns(joinKeyIndices: _*)
-          .leftSemiJoin(rightTable.onColumns(joinKeyIndices: _*), false)
-      case LeftAnti => leftTable.onColumns(joinKeyIndices: _*)
-          .leftAntiJoin(rightTable.onColumns(joinKeyIndices: _*), false)
-      case FullOuter => leftTable.onColumns(joinKeyIndices: _*)
-          .fullJoin(rightTable.onColumns(joinKeyIndices: _*), false)
-      case _ => throw new NotImplementedError(s"Joint Type ${joinType.getClass} is not currently" +
-          s" supported")
+  // This is a work around added in response to https://github.com/NVIDIA/spark-rapids/issues/1643.
+  // to deal with slowness arising from many nulls in the build-side of the join. The work around
+  // should be removed when https://github.com/rapidsai/cudf/issues/7300 is addressed.
+  private[this] def filterNulls(table: Table, joinKeyIndices: Range, closeTable: Boolean): Table = {
+    var mask: ai.rapids.cudf.ColumnVector = null
+    try {
+      joinKeyIndices.indices.foreach { c =>
+        mask = withResource(table.getColumn(c).isNotNull) { nn =>
+          if (mask == null) {
+            nn.incRefCount()
+          } else {
+            withResource(mask) { _ =>
+              mask.and(nn)
+            }
+          }
+        }
+      }
+      table.filter(mask)
+    } finally {
+      if (mask != null) {
+        mask.close()
+      }
+
+      // in some cases, we cannot close the table since it was the build table and is
+      // reused.
+      if (closeTable) {
+        table.close()
+      }
+    }
+  }
+
+  private[this] def doJoinLeftRight(
+      leftTable: Table, rightTable: Table, closeRightTable: Boolean): ColumnarBatch = {
+
+    def withRightTable(body: Table => Table): Table = {
+      val builtAnyNullable =
+        (joinType == LeftSemi || joinType == LeftAnti) && gpuBuildKeys.exists(_.nullable)
+
+      if (builtAnyNullable) {
+        withResource(filterNulls(rightTable, joinKeyIndices, closeRightTable)) { filtered =>
+          body(filtered)
+        }
+      } else {
+        try {
+          body(rightTable)
+        } finally {
+          if (closeRightTable) {
+            rightTable.close()
+          }
+        }
+      }
+    }
+
+    val joinedTable = withRightTable { rt =>
+      joinType match {
+        case LeftOuter => leftTable.onColumns(joinKeyIndices: _*)
+            .leftJoin(rt.onColumns(joinKeyIndices: _*), false)
+        case RightOuter => rt.onColumns(joinKeyIndices: _*)
+            .leftJoin(leftTable.onColumns(joinKeyIndices: _*), false)
+        case _: InnerLike => leftTable.onColumns(joinKeyIndices: _*)
+            .innerJoin(rt.onColumns(joinKeyIndices: _*), false)
+        case LeftSemi => leftTable.onColumns(joinKeyIndices: _*)
+            .leftSemiJoin(rt.onColumns(joinKeyIndices: _*), false)
+        case LeftAnti => leftTable.onColumns(joinKeyIndices: _*)
+            .leftAntiJoin(rt.onColumns(joinKeyIndices: _*), false)
+        case FullOuter => leftTable.onColumns(joinKeyIndices: _*)
+            .fullJoin(rt.onColumns(joinKeyIndices: _*), false)
+        case _ =>
+          throw new NotImplementedError(s"Joint Type ${joinType.getClass} is not currently" +
+              s" supported")
+      }
     }
+
     try {
       val result = joinIndices.zip(output).map { case (joinIndex, outAttr) =>
         GpuColumnVector.from(joinedTable.getColumn(joinIndex).incRefCount(), outAttr.dataType)
@@ -289,5 +351,4 @@ trait GpuHashJoin extends GpuExec {
       joinedTable.close()
     }
   }
-
 }