diff options
Diffstat (limited to 'sql/core')
3 files changed, 26 insertions, 8 deletions
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVFileFormat.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVFileFormat.scala index 1bf57882ce..9a118fe5a2 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVFileFormat.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVFileFormat.scala @@ -186,13 +186,18 @@ class CSVFileFormat extends TextBasedFileFormat with DataSourceRegister { } private def verifySchema(schema: StructType): Unit = { - schema.foreach { field => - field.dataType match { - case _: ArrayType | _: MapType | _: StructType => - throw new UnsupportedOperationException( - s"CSV data source does not support ${field.dataType.simpleString} data type.") + def verifyType(dataType: DataType): Unit = dataType match { + case ByteType | ShortType | IntegerType | LongType | FloatType | + DoubleType | BooleanType | _: DecimalType | TimestampType | + DateType | StringType => + + case udt: UserDefinedType[_] => verifyType(udt.sqlType) + case _ => - } + throw new UnsupportedOperationException( + s"CSV data source does not support ${dataType.simpleString} data type.") } + + schema.foreach(field => verifyType(field.dataType)) } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVInferSchema.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVInferSchema.scala index f1b4c11878..1ca6eff1b8 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVInferSchema.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVInferSchema.scala @@ -290,6 +290,7 @@ private[csv] object CSVTypeCast { DateTimeUtils.millisToDays(DateTimeUtils.stringToTime(datum).getTime) } case _: StringType => UTF8String.fromString(datum) + case udt: UserDefinedType[_] => castTo(datum, udt.sqlType, nullable, options) case _ => throw new RuntimeException(s"Unsupported type: ${castType.typeName}") } } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala index 2befad6d72..1930862118 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala @@ -27,8 +27,7 @@ import org.apache.hadoop.io.SequenceFile.CompressionType import org.apache.hadoop.io.compress.GzipCodec import org.apache.spark.SparkException -import org.apache.spark.sql.{DataFrame, QueryTest, Row} -import org.apache.spark.sql.catalyst.util.DateTimeUtils +import org.apache.spark.sql.{DataFrame, QueryTest, Row, UDT} import org.apache.spark.sql.test.{SharedSQLContext, SQLTestUtils} import org.apache.spark.sql.types._ @@ -681,6 +680,19 @@ class CSVSuite extends QueryTest with SharedSQLContext with SQLTestUtils { Seq((1, Array("Tesla", "Chevy", "Ford"))).toDF("id", "brands").write.csv(csvDir) }.getMessage assert(msg.contains("CSV data source does not support array<string> data type")) + + msg = intercept[UnsupportedOperationException] { + Seq((1, new UDT.MyDenseVector(Array(0.25, 2.25, 4.25)))).toDF("id", "vectors") + .write.csv(csvDir) + }.getMessage + assert(msg.contains("CSV data source does not support array<double> data type")) + + msg = intercept[SparkException] { + val schema = StructType(StructField("a", new UDT.MyDenseVectorUDT(), true) :: Nil) + spark.range(1).write.csv(csvDir) + spark.read.schema(schema).csv(csvDir).collect() + }.getCause.getMessage + assert(msg.contains("Unsupported type: array")) } } |