Repository: spark
Updated Branches:
  refs/heads/master 1462b1766 -> a5925c163


http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
 
b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
index d5969b5..31ef090 100644
--- 
a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
+++ 
b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java
@@ -244,7 +244,7 @@ public class VectorizedColumnReader {
     return new SchemaColumnConvertNotSupportedException(
       Arrays.toString(descriptor.getPath()),
       descriptor.getType().toString(),
-      column.dataType().toString());
+      column.dataType().catalogString());
   }
 
   /**

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala
index c6449cd..b068493 100644
--- 
a/sql/core/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala
+++ 
b/sql/core/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala
@@ -452,7 +452,7 @@ class RelationalGroupedDataset protected[sql](
     require(expr.evalType == PythonEvalType.SQL_GROUPED_MAP_PANDAS_UDF,
       "Must pass a grouped map udf")
     require(expr.dataType.isInstanceOf[StructType],
-      "The returnType of the udf must be a StructType")
+      s"The returnType of the udf must be a ${StructType.simpleString}")
 
     val groupingNamedExpressions = groupingExprs.map {
       case ne: NamedExpression => ne

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowUtils.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowUtils.scala 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowUtils.scala
index 93c8127..533097a 100644
--- 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowUtils.scala
+++ 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowUtils.scala
@@ -47,11 +47,13 @@ object ArrowUtils {
     case DateType => new ArrowType.Date(DateUnit.DAY)
     case TimestampType =>
       if (timeZoneId == null) {
-        throw new UnsupportedOperationException("TimestampType must supply 
timeZoneId parameter")
+        throw new UnsupportedOperationException(
+          s"${TimestampType.catalogString} must supply timeZoneId parameter")
       } else {
         new ArrowType.Timestamp(TimeUnit.MICROSECOND, timeZoneId)
       }
-    case _ => throw new UnsupportedOperationException(s"Unsupported data type: 
${dt.simpleString}")
+    case _ =>
+      throw new UnsupportedOperationException(s"Unsupported data type: 
${dt.catalogString}")
   }
 
   def fromArrowType(dt: ArrowType): DataType = dt match {

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowWriter.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowWriter.scala
 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowWriter.scala
index 66888fc..3de6ea8 100644
--- 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowWriter.scala
+++ 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowWriter.scala
@@ -68,7 +68,7 @@ object ArrowWriter {
         }
         new StructWriter(vector, children.toArray)
       case (dt, _) =>
-        throw new UnsupportedOperationException(s"Unsupported data type: 
${dt.simpleString}")
+        throw new UnsupportedOperationException(s"Unsupported data type: 
${dt.catalogString}")
     }
   }
 }

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/ColumnType.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/ColumnType.scala
 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/ColumnType.scala
index e9b150f..542a10f 100644
--- 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/ColumnType.scala
+++ 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/ColumnType.scala
@@ -717,7 +717,7 @@ private[columnar] object ColumnType {
       case struct: StructType => STRUCT(struct)
       case udt: UserDefinedType[_] => apply(udt.sqlType)
       case other =>
-        throw new Exception(s"Unsupported type: ${other.simpleString}")
+        throw new Exception(s"Unsupported type: ${other.catalogString}")
     }
   }
 }

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceUtils.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceUtils.scala
 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceUtils.scala
index 82e9919..cccd6c0 100644
--- 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceUtils.scala
+++ 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceUtils.scala
@@ -45,7 +45,7 @@ object DataSourceUtils {
     schema.foreach { field =>
       if (!format.supportDataType(field.dataType, isReadPath)) {
         throw new AnalysisException(
-          s"$format data source does not support 
${field.dataType.simpleString} data type.")
+          s"$format data source does not support 
${field.dataType.catalogString} data type.")
       }
     }
   }

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
index b81737e..6cc7922 100644
--- 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
+++ 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
@@ -175,7 +175,7 @@ object JdbcUtils extends Logging {
 
   private def getJdbcType(dt: DataType, dialect: JdbcDialect): JdbcType = {
     dialect.getJDBCType(dt).orElse(getCommonJDBCType(dt)).getOrElse(
-      throw new IllegalArgumentException(s"Can't get JDBC type for 
${dt.simpleString}"))
+      throw new IllegalArgumentException(s"Can't get JDBC type for 
${dt.catalogString}"))
   }
 
   /**
@@ -480,7 +480,7 @@ object JdbcUtils extends Logging {
 
         case LongType if metadata.contains("binarylong") =>
           throw new IllegalArgumentException(s"Unsupported array element " +
-            s"type ${dt.simpleString} based on binary")
+            s"type ${dt.catalogString} based on binary")
 
         case ArrayType(_, _) =>
           throw new IllegalArgumentException("Nested arrays unsupported")
@@ -494,7 +494,7 @@ object JdbcUtils extends Logging {
           array => new 
GenericArrayData(elementConversion.apply(array.getArray)))
         row.update(pos, array)
 
-    case _ => throw new IllegalArgumentException(s"Unsupported type 
${dt.simpleString}")
+    case _ => throw new IllegalArgumentException(s"Unsupported type 
${dt.catalogString}")
   }
 
   private def nullSafeConvert[T](input: T, f: T => Any): Any = {

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcFilters.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcFilters.scala
 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcFilters.scala
index 4f44ae4..c4c3b30 100644
--- 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcFilters.scala
+++ 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcFilters.scala
@@ -98,7 +98,7 @@ private[orc] object OrcFilters {
     case DateType => PredicateLeaf.Type.DATE
     case TimestampType => PredicateLeaf.Type.TIMESTAMP
     case _: DecimalType => PredicateLeaf.Type.DECIMAL
-    case _ => throw new UnsupportedOperationException(s"DataType: $dataType")
+    case _ => throw new UnsupportedOperationException(s"DataType: 
${dataType.catalogString}")
   }
 
   /**

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcUtils.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcUtils.scala
 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcUtils.scala
index 460194b..b404cfa 100644
--- 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcUtils.scala
+++ 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcUtils.scala
@@ -104,7 +104,7 @@ object OrcUtils extends Logging {
         // This is a ORC file written by Hive, no field names in the physical 
schema, assume the
         // physical schema maps to the data scheme by index.
         assert(orcFieldNames.length <= dataSchema.length, "The given data 
schema " +
-          s"${dataSchema.simpleString} has less fields than the actual ORC 
physical schema, " +
+          s"${dataSchema.catalogString} has less fields than the actual ORC 
physical schema, " +
           "no idea which columns were dropped, fail to read.")
         Some(requiredSchema.fieldNames.map { name =>
           val index = dataSchema.fieldIndex(name)

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaConverter.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaConverter.scala
 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaConverter.scala
index c61be07..70f42f2 100644
--- 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaConverter.scala
+++ 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaConverter.scala
@@ -555,7 +555,7 @@ class SparkToParquetSchemaConverter(
         convertField(field.copy(dataType = udt.sqlType))
 
       case _ =>
-        throw new AnalysisException(s"Unsupported data type $field.dataType")
+        throw new AnalysisException(s"Unsupported data type 
${field.dataType.catalogString}")
     }
   }
 }

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala
 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala
index cab0025..dfcf6c1 100644
--- 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala
+++ 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala
@@ -281,7 +281,7 @@ case class PreprocessTableCreation(sparkSession: 
SparkSession) extends Rule[Logi
 
     schema.filter(f => 
normalizedPartitionCols.contains(f.name)).map(_.dataType).foreach {
       case _: AtomicType => // OK
-      case other => failAnalysis(s"Cannot use ${other.simpleString} for 
partition column")
+      case other => failAnalysis(s"Cannot use ${other.catalogString} for 
partition column")
     }
 
     normalizedPartitionCols
@@ -307,7 +307,7 @@ case class PreprocessTableCreation(sparkSession: 
SparkSession) extends Rule[Logi
 
         
normalizedBucketSpec.sortColumnNames.map(schema(_)).map(_.dataType).foreach {
           case dt if RowOrdering.isOrderable(dt) => // OK
-          case other => failAnalysis(s"Cannot use ${other.simpleString} for 
sorting column")
+          case other => failAnalysis(s"Cannot use ${other.catalogString} for 
sorting column")
         }
 
         Some(normalizedBucketSpec)

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
index 685d584..bea652c 100644
--- 
a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
+++ 
b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
@@ -157,7 +157,7 @@ object StatFunctions extends Logging {
     cols.map(name => (name, df.schema.fields.find(_.name == name))).foreach { 
case (name, data) =>
       require(data.nonEmpty, s"Couldn't find column with name $name")
       require(data.get.dataType.isInstanceOf[NumericType], s"Currently 
$functionName calculation " +
-        s"for columns with dataType ${data.get.dataType} not supported.")
+        s"for columns with dataType ${data.get.dataType.catalogString} not 
supported.")
     }
     val columns = cols.map(n => Column(Cast(Column(n).expr, DoubleType)))
     df.select(columns: _*).queryExecution.toRdd.treeAggregate(new 
CovarianceCounter)(

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/test/resources/sql-tests/results/json-functions.sql.out
----------------------------------------------------------------------
diff --git 
a/sql/core/src/test/resources/sql-tests/results/json-functions.sql.out 
b/sql/core/src/test/resources/sql-tests/results/json-functions.sql.out
index 3d49323..827931d 100644
--- a/sql/core/src/test/resources/sql-tests/results/json-functions.sql.out
+++ b/sql/core/src/test/resources/sql-tests/results/json-functions.sql.out
@@ -120,7 +120,7 @@ select to_json(named_struct('a', 1, 'b', 2), map('mode', 1))
 struct<>
 -- !query 11 output
 org.apache.spark.sql.AnalysisException
-A type of keys and values in map() must be string, but got 
MapType(StringType,IntegerType,false);; line 1 pos 7
+A type of keys and values in map() must be string, but got map<string,int>;; 
line 1 pos 7
 
 
 -- !query 12
@@ -216,7 +216,7 @@ select from_json('{"a":1}', 'a INT', map('mode', 1))
 struct<>
 -- !query 20 output
 org.apache.spark.sql.AnalysisException
-A type of keys and values in map() must be string, but got 
MapType(StringType,IntegerType,false);; line 1 pos 7
+A type of keys and values in map() must be string, but got map<string,int>;; 
line 1 pos 7
 
 
 -- !query 21

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/test/resources/sql-tests/results/literals.sql.out
----------------------------------------------------------------------
diff --git a/sql/core/src/test/resources/sql-tests/results/literals.sql.out 
b/sql/core/src/test/resources/sql-tests/results/literals.sql.out
index b8c91dc..7f30161 100644
--- a/sql/core/src/test/resources/sql-tests/results/literals.sql.out
+++ b/sql/core/src/test/resources/sql-tests/results/literals.sql.out
@@ -147,7 +147,7 @@ struct<>
 -- !query 15 output
 org.apache.spark.sql.catalyst.parser.ParseException
 
-DecimalType can only support precision up to 38
+decimal can only support precision up to 38
 == SQL ==
 select 1234567890123456789012345678901234567890
 
@@ -159,7 +159,7 @@ struct<>
 -- !query 16 output
 org.apache.spark.sql.catalyst.parser.ParseException
 
-DecimalType can only support precision up to 38
+decimal can only support precision up to 38
 == SQL ==
 select 1234567890123456789012345678901234567890.0
 
@@ -379,7 +379,7 @@ struct<>
 -- !query 39 output
 org.apache.spark.sql.catalyst.parser.ParseException
 
-DecimalType can only support precision up to 38(line 1, pos 7)
+decimal can only support precision up to 38(line 1, pos 7)
 
 == SQL ==
 select 1.20E-38BD

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala 
b/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
index a7ce952..9f9af89 100644
--- 
a/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
+++ 
b/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
@@ -312,14 +312,14 @@ class FileBasedDataSourceSuite extends QueryTest with 
SharedSQLContext with Befo
         Seq((1, new UDT.MyDenseVector(Array(0.25, 2.25, 4.25)))).toDF("id", 
"vectors")
           .write.mode("overwrite").csv(csvDir)
       }.getMessage
-      assert(msg.contains("CSV data source does not support mydensevector data 
type"))
+      assert(msg.contains("CSV data source does not support array<double> data 
type"))
 
       msg = intercept[AnalysisException] {
         val schema = StructType(StructField("a", new UDT.MyDenseVectorUDT(), 
true) :: Nil)
         spark.range(1).write.mode("overwrite").csv(csvDir)
         spark.read.schema(schema).csv(csvDir).collect()
       }.getMessage
-      assert(msg.contains("CSV data source does not support mydensevector data 
type."))
+      assert(msg.contains("CSV data source does not support array<double> data 
type."))
     }
   }
 
@@ -339,7 +339,7 @@ class FileBasedDataSourceSuite extends QueryTest with 
SharedSQLContext with Befo
           sql("select 
testType()").write.format(format).mode("overwrite").save(tempDir)
         }.getMessage
         assert(msg.toLowerCase(Locale.ROOT)
-          .contains(s"$format data source does not support interval data 
type."))
+          .contains(s"$format data source does not support calendarinterval 
data type."))
       }
 
       // read path
@@ -358,7 +358,7 @@ class FileBasedDataSourceSuite extends QueryTest with 
SharedSQLContext with Befo
           spark.read.schema(schema).format(format).load(tempDir).collect()
         }.getMessage
         assert(msg.toLowerCase(Locale.ROOT)
-          .contains(s"$format data source does not support interval data 
type."))
+          .contains(s"$format data source does not support calendarinterval 
data type."))
       }
     }
   }

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala
----------------------------------------------------------------------
diff --git 
a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala
 
b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala
index 9d3dfae..368e52c 100644
--- 
a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala
+++ 
b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala
@@ -430,9 +430,9 @@ class ParquetSchemaSuite extends ParquetSchemaTest {
       val col = 
spark.read.parquet(file).schema.fields.filter(_.name.equals("a"))
       assert(col.length == 1)
       if (col(0).dataType == StringType) {
-        assert(errMsg.contains("Column: [a], Expected: IntegerType, Found: 
BINARY"))
+        assert(errMsg.contains("Column: [a], Expected: int, Found: BINARY"))
       } else {
-        assert(errMsg.endsWith("Column: [a], Expected: StringType, Found: 
INT32"))
+        assert(errMsg.endsWith("Column: [a], Expected: string, Found: INT32"))
       }
     }
   }

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveExternalCatalog.scala
----------------------------------------------------------------------
diff --git 
a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveExternalCatalog.scala 
b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveExternalCatalog.scala
index 7f28fc4..5cc1047 100644
--- 
a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveExternalCatalog.scala
+++ 
b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveExternalCatalog.scala
@@ -785,9 +785,9 @@ private[spark] class HiveExternalCatalog(conf: SparkConf, 
hadoopConf: Configurat
         // schema we read back is different(ignore case and nullability) from 
the one in table
         // properties which was written when creating table, we should respect 
the table schema
         // from hive.
-        logWarning(s"The table schema given by Hive 
metastore(${table.schema.simpleString}) is " +
+        logWarning(s"The table schema given by Hive 
metastore(${table.schema.catalogString}) is " +
           "different from the schema when this table was created by Spark SQL" 
+
-          s"(${schemaFromTableProps.simpleString}). We have to fall back to 
the table schema " +
+          s"(${schemaFromTableProps.catalogString}). We have to fall back to 
the table schema " +
           "from Hive metastore which is not case preserving.")
         hiveTable.copy(schemaPreservesCase = false)
       }

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScanExec.scala
----------------------------------------------------------------------
diff --git 
a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScanExec.scala
 
b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScanExec.scala
index 7dcaf17..6052486 100644
--- 
a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScanExec.scala
+++ 
b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScanExec.scala
@@ -78,9 +78,9 @@ case class HiveTableScanExec(
   // Bind all partition key attribute references in the partition pruning 
predicate for later
   // evaluation.
   private lazy val boundPruningPred = 
partitionPruningPred.reduceLeftOption(And).map { pred =>
-    require(
-      pred.dataType == BooleanType,
-      s"Data type of predicate $pred must be BooleanType rather than 
${pred.dataType}.")
+    require(pred.dataType == BooleanType,
+      s"Data type of predicate $pred must be ${BooleanType.catalogString} 
rather than " +
+        s"${pred.dataType.catalogString}.")
 
     BindReferences.bindReference(pred, relation.partitionCols)
   }

http://git-wip-us.apache.org/repos/asf/spark/blob/a5925c16/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/HiveOrcSourceSuite.scala
----------------------------------------------------------------------
diff --git 
a/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/HiveOrcSourceSuite.scala
 
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/HiveOrcSourceSuite.scala
index fb4957e..d84f9a3 100644
--- 
a/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/HiveOrcSourceSuite.scala
+++ 
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/HiveOrcSourceSuite.scala
@@ -155,7 +155,7 @@ class HiveOrcSourceSuite extends OrcSuite with 
TestHiveSingleton {
         spark.udf.register("testType", () => new IntervalData())
         sql("select testType()").write.mode("overwrite").orc(orcDir)
       }.getMessage
-      assert(msg.contains("ORC data source does not support interval data 
type."))
+      assert(msg.contains("ORC data source does not support calendarinterval 
data type."))
 
       // read path
       msg = intercept[AnalysisException] {
@@ -170,7 +170,7 @@ class HiveOrcSourceSuite extends OrcSuite with 
TestHiveSingleton {
         spark.range(1).write.mode("overwrite").orc(orcDir)
         spark.read.schema(schema).orc(orcDir).collect()
       }.getMessage
-      assert(msg.contains("ORC data source does not support interval data 
type."))
+      assert(msg.contains("ORC data source does not support calendarinterval 
data type."))
     }
   }
 }


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