Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/19651#discussion_r150367382
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcDeserializer.scala
---
@@ -0,0 +1,206 @@
+/*
+ * 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.orc
+
+import scala.collection.JavaConverters._
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.hadoop.io._
+import org.apache.orc.mapred.{OrcList, OrcMap, OrcStruct, OrcTimestamp}
+import org.apache.orc.storage.serde2.io.{DateWritable, HiveDecimalWritable}
+
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.SpecificInternalRow
+import org.apache.spark.sql.catalyst.util._
+import org.apache.spark.sql.types._
+import org.apache.spark.unsafe.types.UTF8String
+
+private[orc] class OrcDeserializer(
+ dataSchema: StructType,
+ requiredSchema: StructType,
+ maybeMissingSchema: Option[StructType]) {
+
+ private[this] val mutableRow = new
SpecificInternalRow(requiredSchema.map(_.dataType))
+
+ private[this] val unwrappers = requiredSchema.fields.map(f =>
unwrapperFor(f.dataType))
+
+ def deserialize(writable: OrcStruct): InternalRow = {
+ convertOrcStructToInternalRow(writable, dataSchema, requiredSchema,
+ maybeMissingSchema, Some(unwrappers), Some(mutableRow))
+ }
+
+ /**
+ * Convert Apache ORC OrcStruct to Apache Spark InternalRow.
+ * If internalRow is not None, fill into it. Otherwise, create a
SpecificInternalRow and use it.
+ */
+ private[this] def convertOrcStructToInternalRow(
+ orcStruct: OrcStruct,
+ dataSchema: StructType,
+ requiredSchema: StructType,
+ missingSchema: Option[StructType] = None,
+ valueUnwrappers: Option[Seq[(Any, InternalRow, Int) => Unit]] = None,
+ internalRow: Option[InternalRow] = None): InternalRow = {
+ val mutableRow = internalRow.getOrElse(new
SpecificInternalRow(requiredSchema.map(_.dataType)))
+ val unwrappers =
+
valueUnwrappers.getOrElse(requiredSchema.fields.map(_.dataType).map(unwrapperFor).toSeq)
+ var i = 0
+ val len = requiredSchema.length
+ val names = orcStruct.getSchema.getFieldNames
+ while (i < len) {
+ val name = requiredSchema(i).name
+ val writable = if (missingSchema.isEmpty ||
missingSchema.get.getFieldIndex(name).isEmpty) {
--- End diff --
Can we strictly follow the style in `OrcFileFormat.unwrapOrcStructs`? i.e.
no method like `convertOrcStructToInternalRow`, top-level columns and struct
fields are handled with different while loops.
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