Github user JoshRosen commented on a diff in the pull request: https://github.com/apache/spark/pull/8026#discussion_r42584058 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala --- @@ -544,11 +544,35 @@ abstract class HadoopFsRelation private[sql](maybePartitionSpec: Option[Partitio } private def discoverPartitions(): PartitionSpec = { - val typeInference = sqlContext.conf.partitionColumnTypeInferenceEnabled() // We use leaf dirs containing data files to discover the schema. val leafDirs = fileStatusCache.leafDirToChildrenFiles.keys.toSeq - PartitioningUtils.parsePartitions(leafDirs, PartitioningUtils.DEFAULT_PARTITION_NAME, - typeInference) + userDefinedPartitionColumns match { + case Some(schema) => + val spec = PartitioningUtils.parsePartitions( + leafDirs, PartitioningUtils.DEFAULT_PARTITION_NAME, false) + + // Without auto inference, all of value in the `row` should be null or in StringType, + // we need to cast into the data type that user specified. + def castPartitionValueWithGivenSchema(row: InternalRow, schema: StructType) + : InternalRow = { + InternalRow((0 until row.numFields) map { i => + Cast(Literal.create(row.getString(i), StringType), schema.fields(i).dataType).eval() + }: _*) + } + + assert(schema.length == spec.partitionColumns.length && + schema.fieldNames.sameElements(spec.partitionColumns.fieldNames), + s"Auto infer partition column is not match with user specified, " + + s"expect $schema, but got ${spec.partitionColumns}}") + + PartitionSpec(schema, spec.partitions.map { part => + part.copy(values = castPartitionValueWithGivenSchema(part.values, schema)) + }) + case None => + val typeInference = sqlContext.conf.partitionColumnTypeInferenceEnabled() --- End diff -- You could just inline this call on line 574 and save one variable declaration.
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