Github user maropu commented on a diff in the pull request:
https://github.com/apache/spark/pull/21389#discussion_r198355370
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceUtils.scala
---
@@ -0,0 +1,101 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You 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.execution.datasources
+
+import org.apache.spark.sql.execution.datasources.csv.CSVFileFormat
+import org.apache.spark.sql.execution.datasources.json.JsonFileFormat
+import org.apache.spark.sql.execution.datasources.orc.OrcFileFormat
+import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat
+import org.apache.spark.sql.types._
+
+
+object DataSourceUtils {
+
+ /**
+ * Verify if the schema is supported in datasource in write path.
+ */
+ def verifyWriteSchema(format: FileFormat, schema: StructType): Unit = {
+ verifySchema(format, schema, isReadPath = false)
+ }
+
+ /**
+ * Verify if the schema is supported in datasource in read path.
+ */
+ def verifyReadSchema(format: FileFormat, schema: StructType): Unit = {
+ verifySchema(format, schema, isReadPath = true)
+ }
+
+ /**
+ * Verify if the schema is supported in datasource. This verification
should be done
+ * in a driver side, e.g., `prepareWrite`, `buildReader`, and
`buildReaderWithPartitionValues`
+ * in `FileFormat`.
+ *
+ * Unsupported data types of csv, json, orc, and parquet are as follows;
+ * csv -> R/W: Interval, Null, Array, Map, Struct
+ * json -> W: Interval
+ * orc -> W: Interval, Null
+ * parquet -> R/W: Interval, Null
+ */
+ private def verifySchema(format: FileFormat, schema: StructType,
isReadPath: Boolean): Unit = {
+ def throwUnsupportedException(dataType: DataType): Unit = {
+ throw new UnsupportedOperationException(
+ s"$format data source does not support ${dataType.simpleString}
data type.")
+ }
+
+ def verifyType(dataType: DataType): Unit = dataType match {
+ case BooleanType | ByteType | ShortType | IntegerType | LongType |
FloatType | DoubleType |
+ StringType | BinaryType | DateType | TimestampType | _:
DecimalType =>
+
+ case _: CalendarIntervalType | _: StructType | _: ArrayType | _:
MapType
+ if format.isInstanceOf[CSVFileFormat] =>
+ throwUnsupportedException(dataType)
+
+ case st: StructType => st.foreach { f => verifyType(f.dataType) }
+
+ case ArrayType(elementType, _) => verifyType(elementType)
+
+ case MapType(keyType, valueType, _) =>
+ verifyType(keyType)
+ verifyType(valueType)
+
+ // JSON and ORC don't support an Interval type, but we pass it in
read pass
+ // for back-compatibility.
+ case _: CalendarIntervalType if isReadPath &&
--- End diff --
Thanks for the comment. Based on the suggestion, I modified code. Could you
check again?
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