Support explode outer

docs/configs.md

@@ -162,7 +162,7 @@ Name | SQL Function(s) | Description | Default Value | Notes
 <a name="sql.expression.EqualNullSafe"></a>spark.rapids.sql.expression.EqualNullSafe|`<=>`|Check if the values are equal including nulls <=>|true|None|
 <a name="sql.expression.EqualTo"></a>spark.rapids.sql.expression.EqualTo|`=`, `==`|Check if the values are equal|true|None|
 <a name="sql.expression.Exp"></a>spark.rapids.sql.expression.Exp|`exp`|Euler's number e raised to a power|true|None|
-<a name="sql.expression.Explode"></a>spark.rapids.sql.expression.Explode|`explode`, `explode_outer`|Given an input array produces a sequence of rows for each value in the array. Explode with outer Generate is not supported under GPU runtime.|true|None|
+<a name="sql.expression.Explode"></a>spark.rapids.sql.expression.Explode|`explode`, `explode_outer`|Given an input array produces a sequence of rows for each value in the array.|true|None|
 <a name="sql.expression.Expm1"></a>spark.rapids.sql.expression.Expm1|`expm1`|Euler's number e raised to a power minus 1|true|None|
 <a name="sql.expression.Floor"></a>spark.rapids.sql.expression.Floor|`floor`|Floor of a number|true|None|
 <a name="sql.expression.FromUnixTime"></a>spark.rapids.sql.expression.FromUnixTime|`from_unixtime`|Get the string from a unix timestamp|true|None|
@@ -213,7 +213,7 @@ Name | SQL Function(s) | Description | Default Value | Notes
 <a name="sql.expression.Not"></a>spark.rapids.sql.expression.Not|`!`, `not`|Boolean not operator|true|None|
 <a name="sql.expression.Or"></a>spark.rapids.sql.expression.Or|`or`|Logical OR|true|None|
 <a name="sql.expression.Pmod"></a>spark.rapids.sql.expression.Pmod|`pmod`|Pmod|true|None|
-<a name="sql.expression.PosExplode"></a>spark.rapids.sql.expression.PosExplode|`posexplode_outer`, `posexplode`|Given an input array produces a sequence of rows for each value in the array. PosExplode with outer Generate is not supported under GPU runtime.|true|None|
+<a name="sql.expression.PosExplode"></a>spark.rapids.sql.expression.PosExplode|`posexplode_outer`, `posexplode`|Given an input array produces a sequence of rows for each value in the array.|true|None|
 <a name="sql.expression.Pow"></a>spark.rapids.sql.expression.Pow|`pow`, `power`|lhs ^ rhs|true|None|
 <a name="sql.expression.PromotePrecision"></a>spark.rapids.sql.expression.PromotePrecision| |PromotePrecision before arithmetic operations between DecimalType data|true|None|
 <a name="sql.expression.PythonUDF"></a>spark.rapids.sql.expression.PythonUDF| |UDF run in an external python process. Does not actually run on the GPU, but the transfer of data to/from it can be accelerated.|true|None|

docs/supported_ops.md

@@ -5660,7 +5660,7 @@ Accelerator support is described below.
 <tr>
 <td rowSpan="2">Explode</td>
 <td rowSpan="2">`explode`, `explode_outer`</td>
-<td rowSpan="2">Given an input array produces a sequence of rows for each value in the array. Explode with outer Generate is not supported under GPU runtime.</td>
+<td rowSpan="2">Given an input array produces a sequence of rows for each value in the array.</td>
 <td rowSpan="2">None</td>
 <td rowSpan="2">project</td>
 <td>input</td>
@@ -11050,7 +11050,7 @@ Accelerator support is described below.
 <tr>
 <td rowSpan="2">PosExplode</td>
 <td rowSpan="2">`posexplode_outer`, `posexplode`</td>
-<td rowSpan="2">Given an input array produces a sequence of rows for each value in the array. PosExplode with outer Generate is not supported under GPU runtime.</td>
+<td rowSpan="2">Given an input array produces a sequence of rows for each value in the array.</td>
 <td rowSpan="2">None</td>
 <td rowSpan="2">project</td>
 <td>input</td>

integration_tests/src/main/python/generate_expr_test.py

@@ -69,6 +69,26 @@ def test_explode_nested_array_data(spark_tmp_path, data_gen):
             'a', 'explode(b) as c').selectExpr('a', 'explode(c)'),
         conf=conf_to_enforce_split_input)
 
+#sort locally because of https://github.com/NVIDIA/spark-rapids/issues/84
+# After 3.1.0 is the min spark version we can drop this
+@ignore_order(local=True)
+@pytest.mark.parametrize('data_gen', all_gen, ids=idfn)
+def test_explode_outer_array_data(spark_tmp_path, data_gen):
+    data_gen = [int_gen, ArrayGen(data_gen)]
+    assert_gpu_and_cpu_are_equal_collect(
+        lambda spark: two_col_df(spark, *data_gen).selectExpr('a', 'explode_outer(b)'),
+        conf=conf_to_enforce_split_input)
+
+#sort locally because of https://github.com/NVIDIA/spark-rapids/issues/84
+# After 3.1.0 is the min spark version we can drop this
+@ignore_order(local=True)
+@pytest.mark.parametrize('data_gen', all_gen, ids=idfn)
+def test_explode_outer_nested_array_data(spark_tmp_path, data_gen):
+    data_gen = [int_gen, ArrayGen(ArrayGen(data_gen))]
+    assert_gpu_and_cpu_are_equal_collect(
+        lambda spark: two_col_df(spark, *data_gen).selectExpr(
+            'a', 'explode_outer(b) as c').selectExpr('a', 'explode_outer(c)'),
+        conf=conf_to_enforce_split_input)
 
 #sort locally because of https://github.com/NVIDIA/spark-rapids/issues/84
 # After 3.1.0 is the min spark version we can drop this
@@ -108,3 +128,25 @@ def test_posexplode_nested_array_data(spark_tmp_path, data_gen):
         lambda spark: two_col_df(spark, *data_gen).selectExpr(
             'a', 'posexplode(b) as (pos, c)').selectExpr('a', 'pos', 'posexplode(c)'),
         conf=conf_to_enforce_split_input)
+
+#sort locally because of https://github.com/NVIDIA/spark-rapids/issues/84
+# After 3.1.0 is the min spark version we can drop this
+@ignore_order(local=True)
+@pytest.mark.parametrize('data_gen', all_gen, ids=idfn)
+def test_posexplode_outer_array_data(spark_tmp_path, data_gen):
+    data_gen = [int_gen, ArrayGen(data_gen)]
+    assert_gpu_and_cpu_are_equal_collect(
+        lambda spark: two_col_df(spark, *data_gen).selectExpr('a', 'posexplode_outer(b)'),
+        conf=conf_to_enforce_split_input)
+
+#sort locally because of https://github.com/NVIDIA/spark-rapids/issues/84
+# After 3.1.0 is the min spark version we can drop this
+@ignore_order(local=True)
+@pytest.mark.parametrize('data_gen', all_gen, ids=idfn)
+def test_posexplode_nested_outer_array_data(spark_tmp_path, data_gen):
+    data_gen = [int_gen, ArrayGen(ArrayGen(data_gen))]
+    assert_gpu_and_cpu_are_equal_collect(
+        lambda spark: two_col_df(spark, *data_gen).selectExpr(
+            'a', 'posexplode_outer(b) as (pos, c)').selectExpr(
+            'a', 'pos', 'posexplode_outer(c)'),
+        conf=conf_to_enforce_split_input)

sql-plugin/src/main/scala/com/nvidia/spark/rapids/GpuGenerateExec.scala

@@ -342,8 +342,10 @@ case class GpuExplode(child: Expression) extends GpuExplodeBase {
     require(inputBatch.numCols() - 1 == generatorOffset,
       "Internal Error GpuExplode supports one and only one input attribute.")
     val schema = resultSchema(GpuColumnVector.extractTypes(inputBatch), generatorOffset)
+    val explodeFun = (t: Table) =>
+      if (outer) t.explodeOuter(generatorOffset) else t.explode(generatorOffset)
     withResource(GpuColumnVector.from(inputBatch)) { table =>
-      withResource(table.explode(generatorOffset)) { exploded =>
+      withResource(explodeFun(table)) { exploded =>
         GpuColumnVector.from(exploded, schema)
       }
     }
@@ -362,8 +364,10 @@ case class GpuPosExplode(child: Expression) extends GpuExplodeBase {
       "Internal Error GpuPosExplode supports one and only one input attribute.")
     val schema = resultSchema(
       GpuColumnVector.extractTypes(inputBatch), generatorOffset, includePos = true)
+    val explodePosFun = (t: Table) =>
+      if (outer) t.explodeOuterPosition(generatorOffset) else t.explodePosition(generatorOffset)
     withResource(GpuColumnVector.from(inputBatch)) { table =>
-      withResource(table.explodePosition(generatorOffset)) { exploded =>
+      withResource(explodePosFun(table)) { exploded =>
         GpuColumnVector.from(exploded, schema)
       }
     }

sql-plugin/src/main/scala/com/nvidia/spark/rapids/GpuOverrides.scala

@@ -2471,8 +2471,7 @@ object GpuOverrides {
           GpuMakeDecimal(child, a.precision, a.scale, a.nullOnOverflow)
       }),
     expr[Explode](
-      "Given an input array produces a sequence of rows for each value in the array. "
-        + "Explode with outer Generate is not supported under GPU runtime." ,
+      "Given an input array produces a sequence of rows for each value in the array.",
       ExprChecks.unaryProject(
         // Here is a walk-around representation, since multi-level nested type is not supported yet.
         // related issue: https://github.com/NVIDIA/spark-rapids/issues/1901
@@ -2483,11 +2482,11 @@ object GpuOverrides {
           TypeSig.commonCudfTypes + TypeSig.DECIMAL + TypeSig.NULL + TypeSig.ARRAY),
         (TypeSig.ARRAY + TypeSig.MAP).nested(TypeSig.all)),
       (a, conf, p, r) => new GeneratorExprMeta[Explode](a, conf, p, r) {
+        override val supportOuter: Boolean = true
         override def convertToGpu(): GpuExpression = GpuExplode(childExprs.head.convertToGpu())
       }),
     expr[PosExplode](
-      "Given an input array produces a sequence of rows for each value in the array. "
-        + "PosExplode with outer Generate is not supported under GPU runtime." ,
+      "Given an input array produces a sequence of rows for each value in the array.",
       ExprChecks.unaryProject(
         // Here is a walk-around representation, since multi-level nested type is not supported yet.
         // related issue: https://github.com/NVIDIA/spark-rapids/issues/1901
@@ -2499,6 +2498,7 @@ object GpuOverrides {
         TypeSig.ARRAY.nested(
           TypeSig.commonCudfTypes + TypeSig.DECIMAL + TypeSig.NULL + TypeSig.ARRAY)),
       (a, conf, p, r) => new GeneratorExprMeta[PosExplode](a, conf, p, r) {
+        override val supportOuter: Boolean = true
         override def convertToGpu(): GpuExpression = GpuPosExplode(childExprs.head.convertToGpu())
       }),
     expr[CollectList](