[SPARK-18346][SQL] TRUNCATE TABLE should fail if no partition is matched for the given non-partial partition spec

sql/core/src/main/scala/org/apache/spark/sql/execution/command/tables.scala

@@ -30,13 +30,13 @@ import org.apache.hadoop.fs.Path
 
 import org.apache.spark.sql.{AnalysisException, Row, SparkSession}
 import org.apache.spark.sql.catalyst.TableIdentifier
+import org.apache.spark.sql.catalyst.analysis.NoSuchPartitionException
 import org.apache.spark.sql.catalyst.catalog._
 import org.apache.spark.sql.catalyst.catalog.CatalogTableType._
 import org.apache.spark.sql.catalyst.catalog.CatalogTypes.TablePartitionSpec
 import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference}
 import org.apache.spark.sql.catalyst.util.quoteIdentifier
 import org.apache.spark.sql.execution.datasources.PartitioningUtils
-import org.apache.spark.sql.internal.StaticSQLConf.CATALOG_IMPLEMENTATION
 import org.apache.spark.sql.types._
 import org.apache.spark.util.Utils
 
@@ -324,38 +324,47 @@ case class TruncateTableCommand(
   override def run(spark: SparkSession): Seq[Row] = {
     val catalog = spark.sessionState.catalog
     val table = catalog.getTableMetadata(tableName)
-    val tableIdentwithDB = table.identifier.quotedString
+    val tableIdentWithDB = table.identifier.quotedString
 
     if (table.tableType == CatalogTableType.EXTERNAL) {
       throw new AnalysisException(
-        s"Operation not allowed: TRUNCATE TABLE on external tables: $tableIdentwithDB")
+        s"Operation not allowed: TRUNCATE TABLE on external tables: $tableIdentWithDB")
     }
     if (table.tableType == CatalogTableType.VIEW) {
       throw new AnalysisException(
-        s"Operation not allowed: TRUNCATE TABLE on views: $tableIdentwithDB")
+        s"Operation not allowed: TRUNCATE TABLE on views: $tableIdentWithDB")
     }
     if (table.partitionColumnNames.isEmpty && partitionSpec.isDefined) {
       throw new AnalysisException(
         s"Operation not allowed: TRUNCATE TABLE ... PARTITION is not supported " +
-        s"for tables that are not partitioned: $tableIdentwithDB")
+        s"for tables that are not partitioned: $tableIdentWithDB")
     }
     if (partitionSpec.isDefined) {
       DDLUtils.verifyPartitionProviderIsHive(spark, table, "TRUNCATE TABLE ... PARTITION")
     }
+
+    val partCols = table.partitionColumnNames
     val locations =
-      if (table.partitionColumnNames.isEmpty) {
+      if (partCols.isEmpty) {
         Seq(table.storage.locationUri)
       } else {
-        // Here we diverge from Hive when the given partition spec contains all partition columns
-        // but no partition is matched: Hive will throw an exception and we just do nothing.
         val normalizedSpec = partitionSpec.map { spec =>
           PartitioningUtils.normalizePartitionSpec(
             spec,
-            table.partitionColumnNames,
+            partCols,
             table.identifier.quotedString,
             spark.sessionState.conf.resolver)
         }
-        catalog.listPartitions(table.identifier, normalizedSpec).map(_.storage.locationUri)
+        val partLocations =
+          catalog.listPartitions(table.identifier, normalizedSpec).map(_.storage.locationUri)
+
+        // Fail if the partition spec is fully specified (not partial) and the partition does not
+        // exist.
+        for (spec <- partitionSpec if partLocations.isEmpty && spec.size == partCols.length) {
+          throw new NoSuchPartitionException(table.database, table.identifier.table, spec)
+        }
+
+        partLocations
       }
     val hadoopConf = spark.sessionState.newHadoopConf()
     locations.foreach { location =>
@@ -368,7 +377,7 @@ case class TruncateTableCommand(
         } catch {
           case NonFatal(e) =>
             throw new AnalysisException(
-              s"Failed to truncate table $tableIdentwithDB when removing data of the path: $path " +
+              s"Failed to truncate table $tableIdentWithDB when removing data of the path: $path " +
                 s"because of ${e.toString}")
         }
       }
@@ -381,7 +390,7 @@ case class TruncateTableCommand(
       spark.sharedState.cacheManager.uncacheQuery(spark.table(table.identifier))
     } catch {
       case NonFatal(e) =>
-        log.warn(s"Exception when attempting to uncache table $tableIdentwithDB", e)
+        log.warn(s"Exception when attempting to uncache table $tableIdentWithDB", e)
     }
     Seq.empty[Row]
   }

sql/core/src/test/scala/org/apache/spark/sql/execution/command/DDLSuite.scala

@@ -1673,11 +1673,10 @@ class DDLSuite extends QueryTest with SharedSQLContext with BeforeAndAfterEach {
       sql("TRUNCATE TABLE partTable PARTITION (width=100)")
       assert(spark.table("partTable").count() == data.count())
 
-      // do nothing if no partition is matched for the given non-partial partition spec
-      // TODO: This behaviour is different from Hive, we should decide whether we need to follow
-      // Hive's behaviour or stick with our existing behaviour later.
-      sql("TRUNCATE TABLE partTable PARTITION (width=100, length=100)")
-      assert(spark.table("partTable").count() == data.count())
+      // throw exception if no partition is matched for the given non-partial partition spec.
+      intercept[NoSuchPartitionException] {
+        sql("TRUNCATE TABLE partTable PARTITION (width=100, length=100)")
+      }
 
       // throw exception if the column in partition spec is not a partition column.
       val e = intercept[AnalysisException] {

sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala

@@ -23,11 +23,10 @@ import org.apache.hadoop.fs.Path
 import org.scalatest.BeforeAndAfterEach
 
 import org.apache.spark.sql.{AnalysisException, QueryTest, Row, SaveMode}
-import org.apache.spark.sql.catalyst.analysis.TableAlreadyExistsException
+import org.apache.spark.sql.catalyst.analysis.{NoSuchPartitionException, TableAlreadyExistsException}
 import org.apache.spark.sql.catalyst.catalog.{CatalogDatabase, CatalogTable, CatalogTableType}
 import org.apache.spark.sql.catalyst.TableIdentifier
 import org.apache.spark.sql.execution.command.DDLUtils
-import org.apache.spark.sql.execution.datasources.CaseInsensitiveMap
 import org.apache.spark.sql.hive.HiveExternalCatalog
 import org.apache.spark.sql.hive.test.TestHiveSingleton
 import org.apache.spark.sql.internal.SQLConf
@@ -1149,11 +1148,10 @@ class HiveDDLSuite
       sql("TRUNCATE TABLE partTable PARTITION (width=100)")
       assert(spark.table("partTable").count() == data.count())
 
-      // do nothing if no partition is matched for the given non-partial partition spec
-      // TODO: This behaviour is different from Hive, we should decide whether we need to follow
-      // Hive's behaviour or stick with our existing behaviour later.
-      sql("TRUNCATE TABLE partTable PARTITION (width=100, length=100)")
-      assert(spark.table("partTable").count() == data.count())
+      // throw exception if no partition is matched for the given non-partial partition spec.
+      intercept[NoSuchPartitionException] {
+        sql("TRUNCATE TABLE partTable PARTITION (width=100, length=100)")
+      }
 
       // throw exception if the column in partition spec is not a partition column.
       val e = intercept[AnalysisException] {