Github user gengliangwang commented on a diff in the pull request: https://github.com/apache/spark/pull/21389#discussion_r198340297 --- 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 -- If `isReadPath` is `false`, we should always throw exception. So we can simplify all the handling of `CalendarIntervalType` as following: ``` case _: CalendarIntervalType if !isReadPath => throwUnsupportedException(dataType) case _: CalendarIntervalType if format.isInstanceOf[JsonFileFormat] | format.isInstanceOf[OrcFileFormat] => throwUnsupportedException(dataType) ```
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