[Spark][3.2] Fix replacing clustered table with non-clustered table (#…

…3195)

## Description
Fix replacing clustered table with non-clustered table, by creating a
domain metadata with empty clustering columns.

Cherry-picked from 59f8c64

## How was this patch tested?
New unit tests

spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala

@@ -255,7 +255,8 @@ case class CreateDeltaTableCommand(
       // exists (replacing table), otherwise it is handled inside WriteIntoDelta (creating table).
       if (!isV1Writer && isReplace && txn.readVersion > -1L) {
         val newDomainMetadata = Seq.empty[DomainMetadata] ++
-          ClusteredTableUtils.getDomainMetadataOptional(table, txn)
+          ClusteredTableUtils.getDomainMetadataFromTransaction(
+            ClusteredTableUtils.getClusterBySpecOptional(table), txn)
         // Ensure to remove any domain metadata for REPLACE TABLE.
         val newActions = taggedCommitData.actions ++
           DomainMetadataUtils.handleDomainMetadataForReplaceTable(
@@ -337,7 +338,8 @@ case class CreateDeltaTableCommand(
         protocol.foreach { protocol =>
           txn.updateProtocol(protocol)
         }
-        ClusteredTableUtils.getDomainMetadataOptional(table, txn).toSeq
+        ClusteredTableUtils.getDomainMetadataFromTransaction(
+          ClusteredTableUtils.getClusterBySpecOptional(table), txn).toSeq
       } else {
         verifyTableMetadata(txn, tableWithLocation)
         Nil
@@ -381,7 +383,8 @@ case class CreateDeltaTableCommand(
         actionsToCommit = removes ++
           DomainMetadataUtils.handleDomainMetadataForReplaceTable(
             txn.snapshot.domainMetadata,
-            ClusteredTableUtils.getDomainMetadataOptional(table, txn).toSeq)
+            ClusteredTableUtils.getDomainMetadataFromTransaction(
+              ClusteredTableUtils.getClusterBySpecOptional(table), txn).toSeq)
         actionsToCommit
     }
 

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

@@ -181,7 +181,7 @@ trait ImplicitMetadataOperation extends DeltaLogging {
       clusterBySpecOpt: Option[ClusterBySpec] = None): Seq[DomainMetadata] = {
     if (canUpdateMetadata && (!txn.deltaLog.tableExists || isReplacingTable)) {
       val newDomainMetadata = Seq.empty[DomainMetadata] ++
-        ClusteredTableUtils.getDomainMetadataOptional(clusterBySpecOpt, txn)
+        ClusteredTableUtils.getDomainMetadataFromTransaction(clusterBySpecOpt, txn)
       if (!txn.deltaLog.tableExists) {
         newDomainMetadata
       } else {

spark/src/main/scala/org/apache/spark/sql/delta/skipping/clustering/ClusteredTableUtils.scala

@@ -130,17 +130,29 @@ trait ClusteredTableUtilsBase extends DeltaLogging {
   }
 
   /**
-   * Create an optional [[DomainMetadata]] action to store clustering columns.
+   * Returns [[DomainMetadata]] action to store clustering columns.
+   * If clusterBySpecOpt is not empty (clustering columns are specified by CLUSTER BY), it creates
+   * the domain metadata based on the clustering columns.
+   * Otherwise (CLUSTER BY is not specified for REPLACE TABLE), it creates the domain metadata
+   * with empty clustering columns if a clustering domain exists.
+   *
+   * This is used for CREATE TABLE and REPLACE TABLE.
    */
-  def getDomainMetadataOptional(
+  def getDomainMetadataFromTransaction(
       clusterBySpecOpt: Option[ClusterBySpec],
-      txn: OptimisticTransaction): Option[DomainMetadata] = {
+      txn: OptimisticTransaction): Seq[DomainMetadata] = {
     clusterBySpecOpt.map { clusterBy =>
       ClusteredTableUtils.validateClusteringColumnsInStatsSchema(
         txn.protocol, txn.metadata, clusterBy)
       val clusteringColumns =
         clusterBy.columnNames.map(_.toString).map(ClusteringColumn(txn.metadata.schema, _))
-      createDomainMetadata(clusteringColumns)
+       Some(createDomainMetadata(clusteringColumns)).toSeq
+    }.getOrElse {
+      if (txn.snapshot.domainMetadata.exists(_.domain == ClusteringMetadataDomain.domainName)) {
+        Some(createDomainMetadata(Seq.empty)).toSeq
+      } else {
+        None.toSeq
+      }
     }
   }
 
@@ -151,15 +163,6 @@ trait ClusteredTableUtilsBase extends DeltaLogging {
     ClusteringMetadataDomain.fromClusteringColumns(clusteringColumns).toDomainMetadata
   }
 
-  /**
-   * Create a [[ClusteringMetadataDomain]] with the given CatalogTable's clustering column property.
-   */
-  def getDomainMetadataOptional(
-      table: CatalogTable,
-      txn: OptimisticTransaction): Option[DomainMetadata] = {
-    getDomainMetadataOptional(getClusterBySpecOptional(table), txn)
-  }
-
   /**
    * Extract [[ClusteringColumn]]s from a given snapshot. Return None if the clustering domain
    * metadata is missing.

spark/src/test/scala/org/apache/spark/sql/delta/skipping/ClusteredTableTestUtils.scala

@@ -61,7 +61,7 @@ trait ClusteredTableTestUtilsBase extends SparkFunSuite with SharedSparkSession
     }
     val expectedClusteringColumns = logicalColumnNames.map(ClusteringColumn(snapshot.schema, _))
     val actualClusteringColumns =
-      ClusteredTableUtils.getClusteringColumnsOptional(snapshot).getOrElse(Seq.empty)
+      ClusteredTableUtils.getClusteringColumnsOptional(snapshot).orNull
     assert(expectedClusteringColumns == actualClusteringColumns)
   }
 
@@ -152,6 +152,8 @@ trait ClusteredTableTestUtilsBase extends SparkFunSuite with SharedSparkSession
         } else {
           assertClusterByNotExist()
         }
+      case "WRITE" =>
+        doAssert(!lastOperationParameters.contains(CLUSTERING_PARAMETER_KEY))
       case _ =>
         // Other operations are not tested yet. If the test fails here, please check the expected
         // behavior and add the operation to the appropriate case.
@@ -212,7 +214,8 @@ trait ClusteredTableTestUtilsBase extends SparkFunSuite with SharedSparkSession
 
   def verifyClusteringColumns(
       tableIdentifier: TableIdentifier,
-      expectedLogicalClusteringColumns: String): Unit = {
+      expectedLogicalClusteringColumns: String
+    ): Unit = {
     val (_, snapshot) = DeltaLog.forTableWithSnapshot(spark, tableIdentifier)
     verifyClusteringColumnsInternal(
       snapshot,
@@ -235,12 +238,15 @@ trait ClusteredTableTestUtilsBase extends SparkFunSuite with SharedSparkSession
   def verifyClusteringColumnsInternal(
       snapshot: Snapshot,
       tableNameOrPath: String,
-      expectedLogicalClusteringColumns: String): Unit = {
+      expectedLogicalClusteringColumns: String
+    ): Unit = {
     assert(ClusteredTableUtils.isSupported(snapshot.protocol) === true)
     verifyClusteringColumnsInDomainMetadata(snapshot, expectedLogicalClusteringColumns)
 
     // Verify Delta history operation parameters' clusterBy
-    verifyDescribeHistoryOperationParameters(tableNameOrPath)
+    verifyDescribeHistoryOperationParameters(
+      tableNameOrPath
+    )
   }
 }
 

spark/src/test/scala/org/apache/spark/sql/delta/skipping/clustering/ClusteredTableDDLSuite.scala

@@ -398,6 +398,66 @@ trait ClusteredTableCreateOrReplaceDDLSuiteBase
     }
   }
 
+  test("Replace clustered table with non-clustered table") {
+    import testImplicits._
+    withTable(sourceTable) {
+      sql(s"CREATE TABLE $sourceTable(i int, s string) USING delta")
+      spark.range(1000)
+        .map(i => (i.intValue(), "string col"))
+        .toDF("i", "s")
+        .write
+        .format("delta")
+        .mode("append")
+        .saveAsTable(sourceTable)
+
+      // Validate REPLACE TABLE (AS SELECT).
+      Seq("REPLACE", "CREATE OR REPLACE").foreach { clause =>
+        withClusteredTable(testTable, "a int", "a") {
+          verifyClusteringColumns(TableIdentifier(testTable), "a")
+
+          Seq(true, false).foreach { isRTAS =>
+            val testQuery = if (isRTAS) {
+              s"$clause TABLE $testTable USING delta AS SELECT * FROM $sourceTable"
+            } else {
+              sql(s"$clause TABLE $testTable (i int, s string) USING delta")
+              s"INSERT INTO $testTable SELECT * FROM $sourceTable"
+            }
+            sql(testQuery)
+            // Note that clustering table feature are still retained after REPLACE TABLE.
+            verifyClusteringColumns(TableIdentifier(testTable), "")
+          }
+        }
+      }
+    }
+  }
+
+  test("Replace clustered table with non-clustered table - dataframe writer") {
+    import testImplicits._
+    withTable(sourceTable) {
+      sql(s"CREATE TABLE $sourceTable(i int, s string) USING delta")
+      spark.range(1000)
+        .map(i => (i.intValue(), "string col"))
+        .toDF("i", "s")
+        .write
+        .format("delta")
+        .mode("append")
+        .saveAsTable(sourceTable)
+
+      withClusteredTable(testTable, "a int", "a") {
+        verifyClusteringColumns(TableIdentifier(testTable), "a")
+
+        spark.table(sourceTable)
+          .write
+          .format("delta")
+          .mode("overwrite")
+          .option("overwriteSchema", "true")
+          .saveAsTable(testTable)
+        // Note that clustering table feature are still retained after REPLACE TABLE.
+        verifyClusteringColumns(TableIdentifier(testTable), "")
+      }
+    }
+  }
+
   protected def withTempDirIfNecessary(f: Option[String] => Unit): Unit = {
     if (isPathBased) {
       withTempDir { dir =>