org.apache.spark.sql.execution.python.ArrowPythonRunner.scala Maven / Gradle / Ivy

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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.sql.execution.python

import java.io._
import java.net._

import org.apache.arrow.vector.VectorSchemaRoot
import org.apache.arrow.vector.ipc.ArrowStreamWriter

import org.apache.spark._
import org.apache.spark.api.python._
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.execution.arrow.ArrowWriter
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types._
import org.apache.spark.sql.util.ArrowUtils
import org.apache.spark.sql.vectorized.ColumnarBatch
import org.apache.spark.util.Utils

/**
 * Similar to `PythonUDFRunner`, but exchange data with Python worker via Arrow stream.
 */
class ArrowPythonRunner(
    funcs: Seq[ChainedPythonFunctions],
    evalType: Int,
    argOffsets: Array[Array[Int]],
    schema: StructType,
    timeZoneId: String,
    conf: Map[String, String])
  extends BasePythonRunner[Iterator[InternalRow], ColumnarBatch](funcs, evalType, argOffsets)
  with PythonArrowOutput {

  override val bufferSize: Int = SQLConf.get.pandasUDFBufferSize
  require(
    bufferSize >= 4,
    "Pandas execution requires more than 4 bytes. Please set higher buffer. " +
      s"Please change '${SQLConf.PANDAS_UDF_BUFFER_SIZE.key}'.")

  protected override def newWriterThread(
      env: SparkEnv,
      worker: Socket,
      inputIterator: Iterator[Iterator[InternalRow]],
      partitionIndex: Int,
      context: TaskContext): WriterThread = {
    new WriterThread(env, worker, inputIterator, partitionIndex, context) {

      protected override def writeCommand(dataOut: DataOutputStream): Unit = {

        // Write config for the worker as a number of key -> value pairs of strings
        dataOut.writeInt(conf.size)
        for ((k, v) <- conf) {
          PythonRDD.writeUTF(k, dataOut)
          PythonRDD.writeUTF(v, dataOut)
        }

        PythonUDFRunner.writeUDFs(dataOut, funcs, argOffsets)
      }

      protected override def writeIteratorToStream(dataOut: DataOutputStream): Unit = {
        val arrowSchema = ArrowUtils.toArrowSchema(schema, timeZoneId)
        val allocator = ArrowUtils.rootAllocator.newChildAllocator(
          s"stdout writer for $pythonExec", 0, Long.MaxValue)
        val root = VectorSchemaRoot.create(arrowSchema, allocator)

        Utils.tryWithSafeFinally {
          val arrowWriter = ArrowWriter.create(root)
          val writer = new ArrowStreamWriter(root, null, dataOut)
          writer.start()

          while (inputIterator.hasNext) {
            val nextBatch = inputIterator.next()

            while (nextBatch.hasNext) {
              arrowWriter.write(nextBatch.next())
            }

            arrowWriter.finish()
            writer.writeBatch()
            arrowWriter.reset()
          }
          // end writes footer to the output stream and doesn't clean any resources.
          // It could throw exception if the output stream is closed, so it should be
          // in the try block.
          writer.end()
        } {
          // If we close root and allocator in TaskCompletionListener, there could be a race
          // condition where the writer thread keeps writing to the VectorSchemaRoot while
          // it's being closed by the TaskCompletion listener.
          // Closing root and allocator here is cleaner because root and allocator is owned
          // by the writer thread and is only visible to the writer thread.
          //
          // If the writer thread is interrupted by TaskCompletionListener, it should either
          // (1) in the try block, in which case it will get an InterruptedException when
          // performing io, and goes into the finally block or (2) in the finally block,
          // in which case it will ignore the interruption and close the resources.
          root.close()
          allocator.close()
        }
      }
    }
  }

}