Feat: support array_except function

native/core/src/execution/planner.rs

@@ -68,6 +68,7 @@ use datafusion_functions_nested::array_has::array_has_any_udf;
 use datafusion_functions_nested::concat::ArrayAppend;
 use datafusion_functions_nested::remove::array_remove_all_udf;
 use datafusion_functions_nested::set_ops::array_intersect_udf;
+use datafusion_functions_nested::except::array_except_udf;
 use datafusion_functions_nested::string::array_to_string_udf;
 use datafusion_physical_expr::aggregate::{AggregateExprBuilder, AggregateFunctionExpr};
 
@@ -829,6 +830,22 @@ impl PhysicalPlanner {
                 ));
                 Ok(array_has_any_expr)
             }
+            ExprStruct::ArrayExcept(expr) => {
+                let left_expr =
+                    self.create_expr(expr.left.as_ref().unwrap(), Arc::clone(&input_schema))?;
+                let right_expr =
+                    self.create_expr(expr.right.as_ref().unwrap(), Arc::clone(&input_schema))?;
+                let return_type = left_expr.data_type(&input_schema)?;
+                let args = vec![Arc::clone(&left_expr), right_expr];
+
+                let array_except_expr = Arc::new(ScalarFunctionExpr::new(
+                    "array_except",
+                    array_except_udf(),
+                    args,
+                    return_type,
+                ));
+                Ok(array_except_expr)
+            }
             expr => Err(ExecutionError::GeneralError(format!(
                 "Not implemented: {:?}",
                 expr

native/proto/src/proto/expr.proto

@@ -89,6 +89,7 @@ message Expr {
     BinaryExpr array_intersect = 62;
     ArrayJoin array_join = 63;
     BinaryExpr arrays_overlap = 64;
+    BinaryExpr array_except = 65;
   }
 }
 

spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala

@@ -2387,6 +2387,8 @@ object QueryPlanSerde extends Logging with ShimQueryPlanSerde with CometExprShim
       case _: ArrayIntersect => convert(CometArrayIntersect)
       case _: ArrayJoin => convert(CometArrayJoin)
       case _: ArraysOverlap => convert(CometArraysOverlap)
+      case _ if expr.prettyName == "array_except" =>
+        convert(CometArrayExcept)
       case _ =>
         withInfo(expr, s"${expr.prettyName} is not supported", expr.children: _*)
         None

spark/src/main/scala/org/apache/comet/serde/arrays.scala

@@ -126,6 +126,21 @@ object CometArraysOverlap extends CometExpressionSerde with IncompatExpr {
   }
 }
 
+object CometArrayExcept extends CometExpressionSerde with CometExprShim {
+  override def convert(
+      expr: Expression,
+      inputs: Seq[Attribute],
+      binding: Boolean): Option[ExprOuterClass.Expr] = {
+    createBinaryExpr(
+      expr,
+      expr.children(0),
+      expr.children(1),
+      inputs,
+      binding,
+      (builder, binaryExpr) => builder.setArrayExcept(binaryExpr))
+  }
+}
+
 object CometArrayJoin extends CometExpressionSerde with IncompatExpr {
   override def convert(
       expr: Expression,

spark/src/test/scala/org/apache/comet/CometArrayExpressionSuite.scala

@@ -292,4 +292,89 @@ class CometArrayExpressionSuite extends CometTestBase with AdaptiveSparkPlanHelp
     }
   }
 
+  test("array_except - basic test (only integer values)") {
+    withSQLConf(CometConf.COMET_EXPR_ALLOW_INCOMPATIBLE.key -> "true") {
+      Seq(true, false).foreach { dictionaryEnabled =>
+        withTempDir { dir =>
+          val path = new Path(dir.toURI.toString, "test.parquet")
+          makeParquetFileAllTypes(path, dictionaryEnabled, 10000)
+          spark.read.parquet(path.toString).createOrReplaceTempView("t1")
+
+          checkSparkAnswerAndOperator(
+            sql("SELECT array_except(array(_2, _3, _4), array(_3, _4)) from t1"))
+          checkSparkAnswerAndOperator(sql("SELECT array_except(array(_18), array(_19)) from t1"))
+          checkSparkAnswerAndOperator(spark.sql(
+            "SELECT array_except((CASE WHEN _2 = _3 THEN array(_2, _3, _4) END), array(_4)) FROM t1"))
+        }
+      }
+    }
+  }
+
+  test("array_except - test all types (native Parquet reader)") {
+    withTempDir { dir =>
+      val path = new Path(dir.toURI.toString, "test.parquet")
+      val filename = path.toString
+      val random = new Random(42)
+      withSQLConf(CometConf.COMET_ENABLED.key -> "false") {
+        ParquetGenerator.makeParquetFile(
+          random,
+          spark,
+          filename,
+          100,
+          DataGenOptions(
+            allowNull = true,
+            generateNegativeZero = true,
+            generateArray = false,
+            generateStruct = false,
+            generateMap = false))
+      }
+      val table = spark.read.parquet(filename)
+      table.createOrReplaceTempView("t1")
+      // test with array of each column
+      for (fieldName <- table.schema.fieldNames) {
+        sql(s"SELECT array($fieldName, $fieldName) as a, array($fieldName) as b FROM t1")
+          .createOrReplaceTempView("t2")
+        val df = sql("SELECT array_except(a, b) FROM t2")
+        checkSparkAnswerAndOperator(df)
+      }
+    }
+  }
+
+  test("array_except - test all types (convert from Parquet)") {
+    withTempDir { dir =>
+      val path = new Path(dir.toURI.toString, "test.parquet")
+      val filename = path.toString
+      val random = new Random(42)
+      withSQLConf(CometConf.COMET_ENABLED.key -> "false") {
+        val options = DataGenOptions(
+          allowNull = true,
+          generateNegativeZero = true,
+          generateArray = true,
+          generateStruct = true,
+          generateMap = false)
+        ParquetGenerator.makeParquetFile(random, spark, filename, 100, options)
+      }
+      withSQLConf(
+        CometConf.COMET_NATIVE_SCAN_ENABLED.key -> "false",
+        CometConf.COMET_SPARK_TO_ARROW_ENABLED.key -> "true",
+        CometConf.COMET_CONVERT_FROM_PARQUET_ENABLED.key -> "true") {
+        val table = spark.read.parquet(filename)
+        table.createOrReplaceTempView("t1")
+        // test with array of each column
+        for (field <- table.schema.fields) {
+          val fieldName = field.name
+          sql(s"SELECT array($fieldName, $fieldName) as a, array($fieldName) as b FROM t1")
+            .createOrReplaceTempView("t2")
+          val df = sql("SELECT array_except(a, b) FROM t2")
+          field.dataType match {
+            case _: StructType =>
+            // skip due to https://github.com/apache/datafusion-comet/issues/1314
+            case _ =>
+              checkSparkAnswer(df)
+          }
+        }
+      }
+    }
+  }
+
 }