[SPARK][VARIANT] Add minimal support for variant type in delta-spark (#…

…2923)

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#### Which Delta project/connector is this regarding?
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- [x] Spark
- [ ] Standalone
- [ ] Flink
- [ ] Kernel
- [ ] Other (fill in here)

## Description

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- Describe what this PR changes.
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Adds the variant table feature to minimally implement the variant type
as described in the RFC in #2867.

Also disables using variant columns as partition columns.

## How was this patch tested?

Added some UTs. More UTs will be merged in followup PRs

tested against both spark 3.5 and 4.0 snapshot with
```
build/sbt -DsparkVersion=latest spark/'testOnly org.apache.spark.sql.delta.DeltaVariantSuite'
build/sbt -DsparkVersion=master spark/'testOnly org.apache.spark.sql.delta.DeltaVariantSuite'
```


## Does this PR introduce _any_ user-facing changes?

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no

spark/src/main/scala-spark-3.5/shims/VariantShims.scala

@@ -0,0 +1,26 @@
+/*
+ * Copyright (2024) The Delta Lake Project Authors.
+ *
+ * Licensed 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.types
+
+object VariantShims {
+
+  /**
+   * Spark's variant type is implemented for Spark 4.0 and is not implemented in Spark 3.5. Thus,
+   * any Spark 3.5 DataType cannot be a variant type.
+   */
+  def isVariantType(dt: DataType): Boolean = false
+}

spark/src/main/scala-spark-master/shims/VariantShims.scala

@@ -0,0 +1,23 @@
+/*
+ * Copyright (2021) The Delta Lake Project Authors.
+ *
+ * Licensed 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.types
+
+object VariantShims {
+
+  /** Spark's variant type is only implemented in Spark 4.0 and above. */
+  def isVariantType(dt: DataType): Boolean = dt.isInstanceOf[VariantType]
+}

spark/src/main/scala/org/apache/spark/sql/delta/TableFeature.scala

@@ -339,7 +339,8 @@ object TableFeature {
       VacuumProtocolCheckTableFeature,
       V2CheckpointTableFeature,
       RowTrackingFeature,
-      InCommitTimestampTableFeature)
+      InCommitTimestampTableFeature,
+      VariantTypeTableFeature)
     if (DeltaUtils.isTesting) {
       features ++= Set(
         TestLegacyWriterFeature,
@@ -502,6 +503,14 @@ object TimestampNTZTableFeature extends ReaderWriterFeature(name = "timestampNtz
   }
 }
 
+object VariantTypeTableFeature extends ReaderWriterFeature(name = "variantType-dev")
+    with FeatureAutomaticallyEnabledByMetadata {
+  override def metadataRequiresFeatureToBeEnabled(
+      metadata: Metadata, spark: SparkSession): Boolean = {
+    SchemaUtils.checkForVariantTypeColumnsRecursively(metadata.schema)
+  }
+}
+
 object DeletionVectorsTableFeature
   extends ReaderWriterFeature(name = "deletionVectors")
   with FeatureAutomaticallyEnabledByMetadata {

spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaUtils.scala

@@ -1271,6 +1271,14 @@ def normalizeColumnNamesInDataType(
     SchemaUtils.typeExistsRecursively(schema)(_.isInstanceOf[TimestampNTZType])
   }
 
+
+  /**
+   * Returns 'true' if any VariantType exists in the table schema.
+   */
+  def checkForVariantTypeColumnsRecursively(schema: StructType): Boolean = {
+    SchemaUtils.typeExistsRecursively(schema)(VariantShims.isVariantType(_))
+  }
+
   /**
    * Find the unsupported data types in a `DataType` recursively. Add the unsupported data types to
    * the provided `unsupportedDataTypes` buffer.
@@ -1303,6 +1311,7 @@ def normalizeColumnNamesInDataType(
     case DateType =>
     case TimestampType =>
     case TimestampNTZType =>
+    case dt if VariantShims.isVariantType(dt) =>
     case BinaryType =>
     case _: DecimalType =>
     case a: ArrayType =>

spark/src/main/scala/org/apache/spark/sql/delta/util/PartitionUtils.scala

@@ -605,7 +605,8 @@ private[delta] object PartitionUtils {
 
     partitionColumnsSchema(schema, partitionColumns, caseSensitive).foreach {
       field => field.dataType match {
-        case _: AtomicType => // OK
+        // Variant types are not orderable and thus cannot be partition columns.
+        case a: AtomicType if !VariantShims.isVariantType(a) => // OK
         case _ => throw DeltaErrors.cannotUseDataTypeForPartitionColumnError(field)
       }
     }

spark/src/test/scala-spark-master/org/apache/spark/sql/delta/DeltaVariantSuite.scala

@@ -0,0 +1,129 @@
+/*
+ * Copyright (2021) The Delta Lake Project Authors.
+ *
+ * Licensed 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.delta
+
+import org.apache.spark.sql.delta.actions.Protocol
+import org.apache.spark.sql.delta.actions.TableFeatureProtocolUtils
+import org.apache.spark.sql.delta.test.DeltaSQLCommandTest
+
+import org.apache.spark.SparkThrowable
+import org.apache.spark.sql.{AnalysisException, QueryTest, Row}
+import org.apache.spark.sql.catalyst.TableIdentifier
+import org.apache.spark.sql.test.SharedSparkSession
+import org.apache.spark.sql.types.StructType
+
+class DeltaVariantSuite
+    extends QueryTest
+    with SharedSparkSession
+    with DeltaSQLCommandTest {
+
+  private def getProtocolForTable(table: String): Protocol = {
+    val deltaLog = DeltaLog.forTable(spark, TableIdentifier(table))
+    deltaLog.unsafeVolatileSnapshot.protocol
+  }
+
+  test("create a new table with Variant, higher protocol and feature should be picked.") {
+    withTable("tbl") {
+      sql("CREATE TABLE tbl(s STRING, v VARIANT) USING DELTA")
+      sql("INSERT INTO tbl (SELECT 'foo', parse_json(cast(id + 99 as string)) FROM range(1))")
+      assert(spark.table("tbl").selectExpr("v::int").head == Row(99))
+      assert(
+        getProtocolForTable("tbl") ==
+        VariantTypeTableFeature.minProtocolVersion.withFeature(VariantTypeTableFeature)
+      )
+    }
+  }
+
+  test("creating a table without Variant should use the usual minimum protocol") {
+    withTable("tbl") {
+      sql("CREATE TABLE tbl(s STRING, i INTEGER) USING DELTA")
+      assert(getProtocolForTable("tbl") == Protocol(1, 2))
+
+      val deltaLog = DeltaLog.forTable(spark, TableIdentifier("tbl"))
+      assert(
+        !deltaLog.unsafeVolatileSnapshot.protocol.isFeatureSupported(VariantTypeTableFeature),
+        s"Table tbl contains VariantTypeFeature descriptor when its not supposed to"
+      )
+    }
+  }
+
+  test("add a new Variant column should upgrade to the correct protocol versions") {
+    withTable("tbl") {
+      sql("CREATE TABLE tbl(s STRING) USING delta")
+      assert(getProtocolForTable("tbl") == Protocol(1, 2))
+
+      // Should throw error
+      val e = intercept[SparkThrowable] {
+        sql("ALTER TABLE tbl ADD COLUMN v VARIANT")
+      }
+      // capture the existing protocol here.
+      // we will check the error message later in this test as we need to compare the
+      // expected schema and protocol
+      val deltaLog = DeltaLog.forTable(spark, TableIdentifier("tbl"))
+      val currentProtocol = deltaLog.unsafeVolatileSnapshot.protocol
+      val currentFeatures = currentProtocol.implicitlyAndExplicitlySupportedFeatures
+        .map(_.name)
+        .toSeq
+        .sorted
+        .mkString(", ")
+
+      // add table feature
+      sql(
+        s"ALTER TABLE tbl " +
+        s"SET TBLPROPERTIES('delta.feature.variantType-dev' = 'supported')"
+      )
+
+      sql("ALTER TABLE tbl ADD COLUMN v VARIANT")
+
+      // check previously thrown error message
+      checkError(
+        e,
+        errorClass = "DELTA_FEATURES_REQUIRE_MANUAL_ENABLEMENT",
+        parameters = Map(
+          "unsupportedFeatures" -> VariantTypeTableFeature.name,
+          "supportedFeatures" -> currentFeatures
+        )
+      )
+
+      sql("INSERT INTO tbl (SELECT 'foo', parse_json(cast(id + 99 as string)) FROM range(1))")
+      assert(spark.table("tbl").selectExpr("v::int").head == Row(99))
+
+      assert(
+        getProtocolForTable("tbl") ==
+        VariantTypeTableFeature.minProtocolVersion
+          .withFeature(VariantTypeTableFeature)
+          .withFeature(InvariantsTableFeature)
+          .withFeature(AppendOnlyTableFeature)
+      )
+    }
+  }
+
+  test("VariantType may not be used as a partition column") {
+    withTable("delta_test") {
+      checkError(
+        exception = intercept[AnalysisException] {
+          sql(
+            """CREATE TABLE delta_test(s STRING, v VARIANT)
+              |USING delta
+              |PARTITIONED BY (v)""".stripMargin)
+        },
+        errorClass = "INVALID_PARTITION_COLUMN_DATA_TYPE",
+        parameters = Map("type" -> "\"VARIANT\"")
+      )
+    }
+  }
+}