Github user JoshRosen commented on a diff in the pull request: https://github.com/apache/spark/pull/8026#discussion_r42583944 --- 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, " + --- End diff -- The wording of this error message might be slightly confusing to users since this branch is explicitly _disabling_ inference. I think that it might be slightly clearer to say something like "Actual partitioning column names did not match user-specified partitioning schema; expected ... but got ...", since as far as I know the inference is really only done for the types of the columns, not their names.
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