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/*
* 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.ml.python
import java.io.OutputStream
import java.nio.{ByteBuffer, ByteOrder}
import java.util.{ArrayList => JArrayList}
import scala.collection.JavaConverters._
import net.razorvine.pickle._
import org.apache.spark.api.java.JavaRDD
import org.apache.spark.api.python.SerDeUtil
import org.apache.spark.ml.linalg._
import org.apache.spark.mllib.api.python.SerDeBase
import org.apache.spark.rdd.RDD
/**
* SerDe utility functions for pyspark.ml.
*/
private[spark] object MLSerDe extends SerDeBase with Serializable {
override val PYSPARK_PACKAGE = "pyspark.ml"
// Pickler for DenseVector
private[python] class DenseVectorPickler extends BasePickler[DenseVector] {
def saveState(obj: Object, out: OutputStream, pickler: Pickler): Unit = {
val vector: DenseVector = obj.asInstanceOf[DenseVector]
val bytes = new Array[Byte](8 * vector.size)
val bb = ByteBuffer.wrap(bytes)
bb.order(ByteOrder.nativeOrder())
val db = bb.asDoubleBuffer()
db.put(vector.values)
out.write(Opcodes.BINSTRING)
out.write(PickleUtils.integer_to_bytes(bytes.length))
out.write(bytes)
out.write(Opcodes.TUPLE1)
}
def construct(args: Array[Object]): Object = {
if (args.length != 1) {
throw new PickleException("length of args should be 1")
}
val bytes = getBytes(args(0))
val bb = ByteBuffer.wrap(bytes, 0, bytes.length)
bb.order(ByteOrder.nativeOrder())
val db = bb.asDoubleBuffer()
val ans = new Array[Double](bytes.length / 8)
db.get(ans)
Vectors.dense(ans)
}
}
// Pickler for DenseMatrix
private[python] class DenseMatrixPickler extends BasePickler[DenseMatrix] {
def saveState(obj: Object, out: OutputStream, pickler: Pickler): Unit = {
val m: DenseMatrix = obj.asInstanceOf[DenseMatrix]
val bytes = new Array[Byte](8 * m.values.length)
val order = ByteOrder.nativeOrder()
val isTransposed = if (m.isTransposed) 1 else 0
ByteBuffer.wrap(bytes).order(order).asDoubleBuffer().put(m.values)
out.write(Opcodes.MARK)
out.write(Opcodes.BININT)
out.write(PickleUtils.integer_to_bytes(m.numRows))
out.write(Opcodes.BININT)
out.write(PickleUtils.integer_to_bytes(m.numCols))
out.write(Opcodes.BINSTRING)
out.write(PickleUtils.integer_to_bytes(bytes.length))
out.write(bytes)
out.write(Opcodes.BININT)
out.write(PickleUtils.integer_to_bytes(isTransposed))
out.write(Opcodes.TUPLE)
}
def construct(args: Array[Object]): Object = {
if (args.length != 4) {
throw new PickleException("length of args should be 4")
}
val bytes = getBytes(args(2))
val n = bytes.length / 8
val values = new Array[Double](n)
val order = ByteOrder.nativeOrder()
ByteBuffer.wrap(bytes).order(order).asDoubleBuffer().get(values)
val isTransposed = args(3).asInstanceOf[Int] == 1
new DenseMatrix(args(0).asInstanceOf[Int], args(1).asInstanceOf[Int], values, isTransposed)
}
}
// Pickler for SparseMatrix
private[python] class SparseMatrixPickler extends BasePickler[SparseMatrix] {
def saveState(obj: Object, out: OutputStream, pickler: Pickler): Unit = {
val s = obj.asInstanceOf[SparseMatrix]
val order = ByteOrder.nativeOrder()
val colPtrsBytes = new Array[Byte](4 * s.colPtrs.length)
val indicesBytes = new Array[Byte](4 * s.rowIndices.length)
val valuesBytes = new Array[Byte](8 * s.values.length)
val isTransposed = if (s.isTransposed) 1 else 0
ByteBuffer.wrap(colPtrsBytes).order(order).asIntBuffer().put(s.colPtrs)
ByteBuffer.wrap(indicesBytes).order(order).asIntBuffer().put(s.rowIndices)
ByteBuffer.wrap(valuesBytes).order(order).asDoubleBuffer().put(s.values)
out.write(Opcodes.MARK)
out.write(Opcodes.BININT)
out.write(PickleUtils.integer_to_bytes(s.numRows))
out.write(Opcodes.BININT)
out.write(PickleUtils.integer_to_bytes(s.numCols))
out.write(Opcodes.BINSTRING)
out.write(PickleUtils.integer_to_bytes(colPtrsBytes.length))
out.write(colPtrsBytes)
out.write(Opcodes.BINSTRING)
out.write(PickleUtils.integer_to_bytes(indicesBytes.length))
out.write(indicesBytes)
out.write(Opcodes.BINSTRING)
out.write(PickleUtils.integer_to_bytes(valuesBytes.length))
out.write(valuesBytes)
out.write(Opcodes.BININT)
out.write(PickleUtils.integer_to_bytes(isTransposed))
out.write(Opcodes.TUPLE)
}
def construct(args: Array[Object]): Object = {
if (args.length != 6) {
throw new PickleException("length of args should be 6")
}
val order = ByteOrder.nativeOrder()
val colPtrsBytes = getBytes(args(2))
val indicesBytes = getBytes(args(3))
val valuesBytes = getBytes(args(4))
val colPtrs = new Array[Int](colPtrsBytes.length / 4)
val rowIndices = new Array[Int](indicesBytes.length / 4)
val values = new Array[Double](valuesBytes.length / 8)
ByteBuffer.wrap(colPtrsBytes).order(order).asIntBuffer().get(colPtrs)
ByteBuffer.wrap(indicesBytes).order(order).asIntBuffer().get(rowIndices)
ByteBuffer.wrap(valuesBytes).order(order).asDoubleBuffer().get(values)
val isTransposed = args(5).asInstanceOf[Int] == 1
new SparseMatrix(
args(0).asInstanceOf[Int], args(1).asInstanceOf[Int], colPtrs, rowIndices, values,
isTransposed)
}
}
// Pickler for SparseVector
private[python] class SparseVectorPickler extends BasePickler[SparseVector] {
def saveState(obj: Object, out: OutputStream, pickler: Pickler): Unit = {
val v: SparseVector = obj.asInstanceOf[SparseVector]
val n = v.indices.length
val indiceBytes = new Array[Byte](4 * n)
val order = ByteOrder.nativeOrder()
ByteBuffer.wrap(indiceBytes).order(order).asIntBuffer().put(v.indices)
val valueBytes = new Array[Byte](8 * n)
ByteBuffer.wrap(valueBytes).order(order).asDoubleBuffer().put(v.values)
out.write(Opcodes.BININT)
out.write(PickleUtils.integer_to_bytes(v.size))
out.write(Opcodes.BINSTRING)
out.write(PickleUtils.integer_to_bytes(indiceBytes.length))
out.write(indiceBytes)
out.write(Opcodes.BINSTRING)
out.write(PickleUtils.integer_to_bytes(valueBytes.length))
out.write(valueBytes)
out.write(Opcodes.TUPLE3)
}
def construct(args: Array[Object]): Object = {
if (args.length != 3) {
throw new PickleException("length of args should be 3")
}
val size = args(0).asInstanceOf[Int]
val indiceBytes = getBytes(args(1))
val valueBytes = getBytes(args(2))
val n = indiceBytes.length / 4
val indices = new Array[Int](n)
val values = new Array[Double](n)
if (n > 0) {
val order = ByteOrder.nativeOrder()
ByteBuffer.wrap(indiceBytes).order(order).asIntBuffer().get(indices)
ByteBuffer.wrap(valueBytes).order(order).asDoubleBuffer().get(values)
}
new SparseVector(size, indices, values)
}
}
var initialized = false
// This should be called before trying to serialize any above classes
// In cluster mode, this should be put in the closure
override def initialize(): Unit = {
SerDeUtil.initialize()
synchronized {
if (!initialized) {
new DenseVectorPickler().register()
new DenseMatrixPickler().register()
new SparseMatrixPickler().register()
new SparseVectorPickler().register()
initialized = true
}
}
}
// will not called in Executor automatically
initialize()
}
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