Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/19651#discussion_r150368108
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcSerializer.scala
---
@@ -0,0 +1,163 @@
+/*
+ * 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 org.apache.hadoop.io._
+import org.apache.orc.mapred.{OrcList, OrcMap, OrcStruct, OrcTimestamp}
+import org.apache.orc.storage.common.`type`.HiveDecimal
+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.execution.datasources.orc.OrcUtils.getTypeDescription
+import org.apache.spark.sql.types._
+import org.apache.spark.unsafe.types.UTF8String
+
+private[orc] class OrcSerializer(dataSchema: StructType) {
+
+ private[this] lazy val orcStruct: OrcStruct =
+ createOrcValue(dataSchema).asInstanceOf[OrcStruct]
+
+ private[this] val writableWrappers =
+ dataSchema.fields.map(f => getWritableWrapper(f.dataType))
+
+ def serialize(row: InternalRow): OrcStruct = {
+ convertInternalRowToOrcStruct(row, dataSchema, Some(writableWrappers),
Some(orcStruct))
+ }
+
+ /**
+ * Return a Orc value object for the given Spark schema.
+ */
+ private[this] def createOrcValue(dataType: DataType) =
+ OrcStruct.createValue(getTypeDescription(dataType))
+
+ /**
+ * Convert Apache Spark InternalRow to Apache ORC OrcStruct.
+ */
+ private[this] def convertInternalRowToOrcStruct(
+ row: InternalRow,
+ schema: StructType,
+ valueWrappers: Option[Seq[Any => Any]] = None,
+ struct: Option[OrcStruct] = None): OrcStruct = {
+ val wrappers =
+
valueWrappers.getOrElse(schema.fields.map(_.dataType).map(getWritableWrapper).toSeq)
+ val orcStruct =
struct.getOrElse(createOrcValue(schema).asInstanceOf[OrcStruct])
+
+ for (schemaIndex <- 0 until schema.length) {
+ val fieldType = schema(schemaIndex).dataType
+ if (row.isNullAt(schemaIndex)) {
+ orcStruct.setFieldValue(schemaIndex, null)
+ } else {
+ val field = row.get(schemaIndex, fieldType)
+ val fieldValue =
wrappers(schemaIndex)(field).asInstanceOf[WritableComparable[_]]
+ orcStruct.setFieldValue(schemaIndex, fieldValue)
+ }
+ }
+ orcStruct
+ }
+
+ private[this] def withNullSafe(f: Any => Any): Any => Any = {
+ input => if (input == null) null else f(input)
+ }
+
+ /**
+ * Builds a WritableComparable-return function ahead of time according
to DataType
+ * to avoid pattern matching and branching costs per row.
+ */
+ private[this] def getWritableWrapper(dataType: DataType): Any => Any =
dataType match {
+ case NullType => _ => null
+
+ case BooleanType => withNullSafe(o => new
BooleanWritable(o.asInstanceOf[Boolean]))
+
+ case ByteType => withNullSafe(o => new
ByteWritable(o.asInstanceOf[Byte]))
--- End diff --
we can apply the same technology: pass `SpecializedGetters` as a parameter
to avoid boxing.
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