Github user aarondav commented on a diff in the pull request:
https://github.com/apache/spark/pull/5279#discussion_r27939459
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ReflectionConverters.scala
---
@@ -0,0 +1,263 @@
+/*
+ * 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.catalyst
+
+import java.util.{Map => JavaMap}
+
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.types._
+
+/**
+ * Functions to convert Scala types to Catalyst types and vice versa.
+ */
+object ReflectionConverters {
+ // The Predef.Map is scala.collection.immutable.Map.
+ // Since the map values can be mutable, we explicitly import
scala.collection.Map at here.
+ import scala.collection.Map
+
+ /**
+ * Converts Scala objects to catalyst rows / types.
+ * Note: This is always called after schemaFor has been called.
+ * This ordering is important for UDT registration.
+ */
+ def convertToCatalyst(a: Any, dataType: DataType): Any = (a, dataType)
match {
+ // Check UDT first since UDTs can override other types
+ case (obj, udt: UserDefinedType[_]) => udt.serialize(obj)
+ case (o: Option[_], _) => o.map(convertToCatalyst(_, dataType)).orNull
+ case (s: Seq[_], arrayType: ArrayType) => s.map(convertToCatalyst(_,
arrayType.elementType))
+ case (s: Array[_], arrayType: ArrayType) =>
+ s.toSeq.map(convertToCatalyst(_, arrayType.elementType))
+ case (m: Map[_, _], mapType: MapType) => m.map { case (k, v) =>
+ convertToCatalyst(k, mapType.keyType) -> convertToCatalyst(v,
mapType.valueType)
+ }
+ case (jmap: JavaMap[_, _], mapType: MapType) =>
+ val iter = jmap.entrySet.iterator
+ var listOfEntries: List[(Any, Any)] = List()
+ while (iter.hasNext) {
+ val entry = iter.next()
+ listOfEntries :+= (convertToCatalyst(entry.getKey,
mapType.keyType),
+ convertToCatalyst(entry.getValue, mapType.valueType))
+ }
+ listOfEntries.toMap
+ case (p: Product, structType: StructType) =>
+ val ar = new Array[Any](structType.size)
+ val iter = p.productIterator
+ var idx = 0
+ while (idx < structType.size) {
+ ar(idx) = convertToCatalyst(iter.next(),
structType.fields(idx).dataType)
+ idx += 1
+ }
+ new GenericRowWithSchema(ar, structType)
+ case (d: BigDecimal, _) => Decimal(d)
+ case (d: java.math.BigDecimal, _) => Decimal(d)
+ case (d: java.sql.Date, _) => DateUtils.fromJavaDate(d)
+ case (r: Row, structType: StructType) =>
+ val converters = structType.fields.map {
+ f => (item: Any) => convertToCatalyst(item, f.dataType)
+ }
+ convertRowWithConverters(r, structType, converters)
+ case (other, _) => other
+ }
+
+ /**
+ * Creates a converter function that will convert Scala objects to the
specified catalyst type.
+ */
+ private[sql] def createCatalystConverter(dataType: DataType): Any => Any
= {
+ def extractOption(item: Any): Any = item match {
+ case s: Some[_] => s.get
+ case None => null
+ case other => other
+ }
+
+ dataType match {
+ // Check UDT first since UDTs can override other types
+ case udt: UserDefinedType[_] =>
+ (item) => {
+ if (item == None) null else udt.serialize(extractOption(item))
+ }
+
+ case arrayType: ArrayType =>
+ val elementConverter =
createCatalystConverter(arrayType.elementType)
+ (item: Any) => {
+ extractOption(item) match {
+ case a: Array[_] => a.toSeq.map(elementConverter)
+ case s: Seq[_] => s.map(elementConverter)
+ case null => null
+ }
+ }
+
+ case mapType: MapType =>
+ val keyConverter = createCatalystConverter(mapType.keyType)
+ val valueConverter = createCatalystConverter(mapType.valueType)
+ (item: Any) => {
+ extractOption(item) match {
+ case m: Map[_, _] =>
+ m.map { case (k, v) =>
+ keyConverter(k) -> valueConverter(v)
+ }
+
+ case jmap: JavaMap[_, _] =>
+ val iter = jmap.entrySet.iterator
+ var listOfEntries: List[(Any, Any)] = List()
+ while (iter.hasNext) {
+ val entry = iter.next()
+ listOfEntries :+= (keyConverter(entry.getKey),
valueConverter(entry.getValue))
+ }
+ listOfEntries.toMap
+
+ case null => null
+ }
+ }
+
+ case structType: StructType =>
+ val converters = new Array[Any => Any](structType.length)
+ val iter = structType.fields.iterator
+ var idx = 0
+ while (iter.hasNext) {
+ converters(idx) = createCatalystConverter(iter.next().dataType)
+ idx += 1
+ }
+ (item: Any) => {
+ extractOption(item) match {
+ case r: Row => convertRowWithConverters(r, structType,
converters)
+
+ case p: Product =>
+ val ar = new Array[Any](structType.size)
+ val iter = p.productIterator
+ var idx = 0
+ while (idx < structType.size) {
+ ar(idx) = converters(idx)(iter.next())
+ idx += 1
+ }
+ new GenericRowWithSchema(ar, structType)
+
+ case null => null
+ }
+ }
+
+ case _ =>
+ (item: Any) => extractOption(item) match {
+ case d: BigDecimal => Decimal(d)
+ case d: java.math.BigDecimal => Decimal(d)
+ case d: java.sql.Date => DateUtils.fromJavaDate(d)
+ case other => other
+ }
+ }
+ }
+
+ /** Converts Catalyst types used internally in rows to standard Scala
types */
+ def convertToScala(a: Any, dataType: DataType): Any = (a, dataType)
match {
+ // Check UDT first since UDTs can override other types
+ case (d, udt: UserDefinedType[_]) => udt.deserialize(d)
+ case (s: Seq[_], arrayType: ArrayType) => s.map(convertToScala(_,
arrayType.elementType))
+ case (m: Map[_, _], mapType: MapType) => m.map { case (k, v) =>
+ convertToScala(k, mapType.keyType) -> convertToScala(v,
mapType.valueType)
+ }
+ case (r: Row, s: StructType) => convertRowToScala(r, s)
+ case (d: Decimal, _: DecimalType) => d.toJavaBigDecimal
+ case (i: Int, DateType) => DateUtils.toJavaDate(i)
+ case (other, _) => other
+ }
+
+ /**
+ * Creates a converter function that will convert Catalyst types to
Scala type.
+ */
+ private[sql] def createScalaConverter(dataType: DataType): Any => Any =
dataType match {
+ // Check UDT first since UDTs can override other types
+ case udt: UserDefinedType[_] =>
+ (item: Any) => if (item == null) null else udt.deserialize(item)
+
+ case arrayType: ArrayType =>
+ val elementConverter = createScalaConverter(arrayType.elementType)
+ (item: Any) => if (item == null) null else
item.asInstanceOf[Seq[_]].map(elementConverter)
+
+ case mapType: MapType =>
+ val keyConverter = createScalaConverter(mapType.keyType)
+ val valueConverter = createScalaConverter(mapType.valueType)
+ (item: Any) => if (item == null) {
+ null
+ } else {
+ item.asInstanceOf[Map[_, _]].map { case (k, v) =>
+ keyConverter(k) -> valueConverter(v)
+ }
+ }
+
+ case s: StructType =>
+ val converters = createScalaConvertersForStruct(s)
--- End diff --
This implementation is so clear that I would actually just inline it:
`s.fields.map(f => createScalaConverter(f.dataType))`
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