Github user liancheng commented on a diff in the pull request:
https://github.com/apache/spark/pull/8509#discussion_r38760022
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/CatalystReadSupport.scala
---
@@ -160,4 +101,168 @@ private[parquet] object CatalystReadSupport {
val SPARK_ROW_REQUESTED_SCHEMA =
"org.apache.spark.sql.parquet.row.requested_schema"
val SPARK_METADATA_KEY = "org.apache.spark.sql.parquet.row.metadata"
+
+ /**
+ * Tailors `parquetSchema` according to `catalystSchema` by removing
column paths don't exist
+ * in `catalystSchema`, and adding those only exist in `catalystSchema`.
+ */
+ def clipParquetSchema(parquetSchema: MessageType, catalystSchema:
StructType): MessageType = {
+ val clippedParquetFields =
clipParquetGroupFields(parquetSchema.asGroupType(), catalystSchema)
+ Types.buildMessage().addFields(clippedParquetFields: _*).named("root")
+ }
+
+ private def clipParquetType(parquetType: Type, catalystType: DataType):
Type = {
+ catalystType match {
+ case t: ArrayType if !isPrimitiveCatalystType(t.elementType) =>
+ // Only clips array types with nested type as element type.
+ clipParquetListType(parquetType.asGroupType(), t.elementType)
+
+ case t: MapType if !isPrimitiveCatalystType(t.valueType) =>
+ // Only clips map types with nested type as value type.
+ clipParquetMapType(parquetType.asGroupType(), t.keyType,
t.valueType)
+
+ case t: StructType =>
+ clipParquetGroup(parquetType.asGroupType(), t)
+
+ case _ =>
+ parquetType
+ }
+ }
+
+ /**
+ * Whether a Catalyst [[DataType]] is primitive. Primitive [[DataType]]
is not equivalent to
+ * [[AtomicType]]. For example, [[CalendarIntervalType]] is primitive,
but it's not an
+ * [[AtomicType]].
+ */
+ private def isPrimitiveCatalystType(dataType: DataType): Boolean = {
+ dataType match {
+ case _: ArrayType | _: MapType | _: StructType => false
+ case _ => true
+ }
+ }
+
+ /**
+ * Clips a Parquet [[GroupType]] which corresponds to a Catalyst
[[ArrayType]]. The element type
+ * of the [[ArrayType]] should also be a nested type, namely an
[[ArrayType]], a [[MapType]], or a
+ * [[StructType]].
+ */
+ private def clipParquetListType(parquetList: GroupType, elementType:
DataType): Type = {
+ // Precondition of this method, should only be called for lists with
nested element types.
+ assert(!isPrimitiveCatalystType(elementType))
+
+ // Unannotated repeated group should be interpreted as required list
of required element, so
+ // list element type is just the group itself. Clip it.
+ if (parquetList.getOriginalType == null &&
parquetList.isRepetition(Repetition.REPEATED)) {
+ clipParquetType(parquetList, elementType)
+ } else {
+ assert(
+ parquetList.getOriginalType == OriginalType.LIST,
+ "Invalid Parquet schema. " +
+ "Original type of annotated Parquet lists must be LIST: " +
+ parquetList.toString)
+
+ assert(
+ parquetList.getFieldCount == 1 &&
parquetList.getType(0).isRepetition(Repetition.REPEATED),
+ "Invalid Parquet schema. " +
+ "LIST-annotated group should only have exactly one repeated
field: " +
+ parquetList)
+
+ // Precondition of this method, should only be called for lists with
nested element types.
+ assert(!parquetList.getType(0).isPrimitive)
+
+ val repeatedGroup = parquetList.getType(0).asGroupType()
+
+ // If the repeated field is a group with multiple fields, or the
repeated field is a group
+ // with one field and is named either "array" or uses the
LIST-annotated group's name with
+ // "_tuple" appended then the repeated type is the element type and
elements are required.
+ // Build a new LIST-annotated group with clipped `repeatedGroup` as
element type and the
+ // only field.
+ if (
+ repeatedGroup.getFieldCount > 1 ||
--- End diff --
This case corresponds to the 2nd rule of LIST backwards-compatibility rules
defined here:
https://github.com/apache/parquet-format/blob/master/LogicalTypes.md#backward-compatibility-rules
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