Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/15821#discussion_r112376037
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/ArrowConverters.scala ---
@@ -0,0 +1,432 @@
+/*
+* 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
+
+import java.io.ByteArrayOutputStream
+import java.nio.ByteBuffer
+import java.nio.channels.{Channels, SeekableByteChannel}
+
+import scala.collection.JavaConverters._
+
+import io.netty.buffer.ArrowBuf
+import org.apache.arrow.memory.{BaseAllocator, RootAllocator}
+import org.apache.arrow.vector._
+import org.apache.arrow.vector.BaseValueVector.BaseMutator
+import org.apache.arrow.vector.file.{ArrowReader, ArrowWriter}
+import org.apache.arrow.vector.schema.{ArrowFieldNode, ArrowRecordBatch}
+import org.apache.arrow.vector.types.{FloatingPointPrecision, TimeUnit}
+import org.apache.arrow.vector.types.pojo.{ArrowType, Field, Schema}
+
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.types._
+import org.apache.spark.util.Utils
+
+
+/**
+ * ArrowReader requires a seekable byte channel.
+ * TODO: This is available in arrow-vector now with ARROW-615, to be
included in 0.2.1 release
+ */
+private[sql] class ByteArrayReadableSeekableByteChannel(var byteArray:
Array[Byte])
+ extends SeekableByteChannel {
+ var _position: Long = 0L
+
+ override def isOpen: Boolean = {
+ byteArray != null
+ }
+
+ override def close(): Unit = {
+ byteArray = null
+ }
+
+ override def read(dst: ByteBuffer): Int = {
+ val remainingBuf = byteArray.length - _position
+ val length = Math.min(dst.remaining(), remainingBuf).toInt
+ dst.put(byteArray, _position.toInt, length)
+ _position += length
+ length
+ }
+
+ override def position(): Long = _position
+
+ override def position(newPosition: Long): SeekableByteChannel = {
+ _position = newPosition.toLong
+ this
+ }
+
+ override def size: Long = {
+ byteArray.length.toLong
+ }
+
+ override def write(src: ByteBuffer): Int = {
+ throw new UnsupportedOperationException("Read Only")
+ }
+
+ override def truncate(size: Long): SeekableByteChannel = {
+ throw new UnsupportedOperationException("Read Only")
+ }
+}
+
+/**
+ * Intermediate data structure returned from Arrow conversions
+ */
+private[sql] abstract class ArrowPayload extends Iterator[ArrowRecordBatch]
+
+/**
+ * Build a payload from existing ArrowRecordBatches
+ */
+private[sql] class ArrowStaticPayload(batches: ArrowRecordBatch*) extends
ArrowPayload {
+ private val iter = batches.iterator
+ override def next(): ArrowRecordBatch = iter.next()
+ override def hasNext: Boolean = iter.hasNext
+}
+
+/**
+ * Class that wraps an Arrow RootAllocator used in conversion
+ */
+private[sql] class ArrowConverters {
+ private val _allocator = new RootAllocator(Long.MaxValue)
+
+ private[sql] def allocator: RootAllocator = _allocator
+
+ /**
+ * Iterate over the rows and convert to an ArrowPayload, using
RootAllocator from this class
+ */
+ def interalRowIterToPayload(rowIter: Iterator[InternalRow], schema:
StructType): ArrowPayload = {
+ val batch = ArrowConverters.internalRowIterToArrowBatch(rowIter,
schema, _allocator)
+ new ArrowStaticPayload(batch)
+ }
+
+ /**
+ * Read an Array of Arrow Record batches as byte Arrays into an
ArrowPayload, using
+ * RootAllocator from this class
+ */
+ def readPayloadByteArrays(payloadByteArrays: Array[Array[Byte]]):
ArrowPayload = {
+ val batches =
scala.collection.mutable.ArrayBuffer.empty[ArrowRecordBatch]
+ var i = 0
+ while (i < payloadByteArrays.length) {
+ val payloadBytes = payloadByteArrays(i)
+ val in = new ByteArrayReadableSeekableByteChannel(payloadBytes)
+ val reader = new ArrowReader(in, _allocator)
+ val footer = reader.readFooter()
+ val batchBlocks = footer.getRecordBatches.asScala.toArray
+ batchBlocks.foreach(block => batches +=
reader.readRecordBatch(block))
+ i += 1
+ }
+ new ArrowStaticPayload(batches: _*)
+ }
+
+ /**
+ * Call when done using this converter, will close RootAllocator so any
ArrowBuffers should be
+ * closed first
+ */
+ def close(): Unit = {
+ _allocator.close()
+ }
+}
+
+private[sql] object ArrowConverters {
+
+ /**
+ * Map a Spark Dataset type to ArrowType.
+ */
+ private[sql] def sparkTypeToArrowType(dataType: DataType): ArrowType = {
+ dataType match {
+ case BooleanType => ArrowType.Bool.INSTANCE
+ case ShortType => new ArrowType.Int(8 * ShortType.defaultSize, true)
+ case IntegerType => new ArrowType.Int(8 * IntegerType.defaultSize,
true)
+ case LongType => new ArrowType.Int(8 * LongType.defaultSize, true)
+ case FloatType => new
ArrowType.FloatingPoint(FloatingPointPrecision.SINGLE)
+ case DoubleType => new
ArrowType.FloatingPoint(FloatingPointPrecision.DOUBLE)
+ case ByteType => new ArrowType.Int(8, true)
+ case StringType => ArrowType.Utf8.INSTANCE
+ case BinaryType => ArrowType.Binary.INSTANCE
+ // TODO: Enable Date and Timestamp type with Arrow 0.3
+ // case DateType => ArrowType.Date.INSTANCE
+ // case TimestampType => new
ArrowType.Timestamp(TimeUnit.MILLISECOND)
+ case _ => throw new UnsupportedOperationException(s"Unsupported data
type: $dataType")
+ }
+ }
+
+ /**
+ * Iterate over InternalRows and convert to an ArrowRecordBatch.
+ */
+ private def internalRowIterToArrowBatch(
+ rowIter: Iterator[InternalRow],
+ schema: StructType,
+ allocator: RootAllocator): ArrowRecordBatch = {
+
+ val columnWriters = schema.fields.zipWithIndex.map { case (field,
ordinal) =>
+ ColumnWriter(ordinal, allocator, field.dataType)
+ .init()
+ }
+
+ val writerLength = columnWriters.length
+ while (rowIter.hasNext) {
+ val row = rowIter.next()
+ var i = 0
+ while (i < writerLength) {
+ columnWriters(i).write(row)
+ i += 1
+ }
+ }
+
+ val (fieldNodes, bufferArrays) = columnWriters.map(_.finish()).unzip
+ val buffers = bufferArrays.flatten
+
+ val rowLength = if (fieldNodes.nonEmpty) fieldNodes.head.getLength
else 0
+ val recordBatch = new ArrowRecordBatch(rowLength,
+ fieldNodes.toList.asJava, buffers.toList.asJava)
+
+ buffers.foreach(_.release())
+ recordBatch
+ }
+
+ /**
+ * Convert a Spark Dataset schema to Arrow schema.
+ */
+ private[sql] def schemaToArrowSchema(schema: StructType): Schema = {
+ val arrowFields = schema.fields.map { f =>
+ new Field(f.name, f.nullable, sparkTypeToArrowType(f.dataType),
List.empty[Field].asJava)
+ }
+ new Schema(arrowFields.toList.asJava)
+ }
+
+ /**
+ * Write an ArrowPayload to a byte array
+ */
+ private[sql] def payloadToByteArray(payload: ArrowPayload, schema:
StructType): Array[Byte] = {
+ val arrowSchema = ArrowConverters.schemaToArrowSchema(schema)
+ val out = new ByteArrayOutputStream()
+ val writer = new ArrowWriter(Channels.newChannel(out), arrowSchema)
+
+ // Iterate over payload batches to write each one, ensure all batches
get closed
+ var batch: ArrowRecordBatch = null
+ Utils.tryWithSafeFinallyAndFailureCallbacks {
+ while (payload.hasNext) {
+ batch = payload.next()
+ writer.writeRecordBatch(batch)
+ batch.close()
+ }
+ }(catchBlock = {
+ Option(batch).foreach(_.close())
+ payload.foreach(_.close())
+ }, finallyBlock = writer.close())
+
+ out.toByteArray
+ }
+}
+
+private[sql] trait ColumnWriter {
+ def init(): this.type
+ def write(row: InternalRow): Unit
+
+ /**
+ * Clear the column writer and return the ArrowFieldNode and ArrowBuf.
+ * This should be called only once after all the data is written.
+ */
+ def finish(): (ArrowFieldNode, Array[ArrowBuf])
+}
+
+/**
+ * Base class for flat arrow column writer, i.e., column without children.
+ */
+private[sql] abstract class PrimitiveColumnWriter(
+ val ordinal: Int,
+ val allocator: BaseAllocator)
+ extends ColumnWriter {
+ def valueVector: BaseDataValueVector
+ def valueMutator: BaseMutator
+
+ def setNull(): Unit
+ def setValue(row: InternalRow): Unit
+
+ protected var count = 0
+ protected var nullCount = 0
+
+ override def init(): this.type = {
+ valueVector.allocateNew()
+ this
+ }
+
+ override def write(row: InternalRow): Unit = {
+ if (row.isNullAt(ordinal)) {
+ setNull()
+ nullCount += 1
+ } else {
+ setValue(row)
+ }
+ count += 1
+ }
+
+ override def finish(): (ArrowFieldNode, Array[ArrowBuf]) = {
+ valueMutator.setValueCount(count)
+ val fieldNode = new ArrowFieldNode(count, nullCount)
+ val valueBuffers = valueVector.getBuffers(true)
+ (fieldNode, valueBuffers)
+ }
+}
+
+private[sql] class BooleanColumnWriter(ordinal: Int, allocator:
BaseAllocator)
+ extends PrimitiveColumnWriter(ordinal, allocator) {
+ private def bool2int(b: Boolean): Int = if (b) 1 else 0
--- End diff --
just inline this
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