[DO-NOT-MERGE] Prototype: runtime profiling of Python workers #52679
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| Original file line number | Diff line number | Diff line change |
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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. | ||
| */ | ||
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| package org.apache.spark.sql.execution.streaming.sources | ||
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| import java.io.DataInputStream | ||
| import java.nio.channels.Channels | ||
| import java.util.concurrent.atomic.AtomicBoolean | ||
| import javax.annotation.concurrent.GuardedBy | ||
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| import scala.collection.mutable.ListBuffer | ||
| import scala.jdk.CollectionConverters._ | ||
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| import net.razorvine.pickle.Unpickler | ||
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| import org.apache.spark.SparkEnv | ||
| import org.apache.spark.internal.Logging | ||
| import org.apache.spark.sql.catalyst.{CatalystTypeConverters, InternalRow} | ||
| import org.apache.spark.sql.connector.read.{InputPartition, PartitionReader, PartitionReaderFactory} | ||
| import org.apache.spark.sql.connector.read.streaming.{MicroBatchStream, Offset} | ||
| import org.apache.spark.sql.execution.streaming.runtime.LongOffset | ||
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| class PythonProfileMicroBatchStream | ||
| extends MicroBatchStream with Logging { | ||
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| @GuardedBy("this") | ||
| private var readThread: Thread = null | ||
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| @GuardedBy("this") | ||
| private val batches = new ListBuffer[java.util.List[java.util.Map[String, String]]] | ||
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| @GuardedBy("this") | ||
| private var currentOffset: LongOffset = LongOffset(-1L) | ||
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| @GuardedBy("this") | ||
| private var lastOffsetCommitted: LongOffset = LongOffset(-1L) | ||
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| private val initialized: AtomicBoolean = new AtomicBoolean(false) | ||
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| private def initialize(): Unit = synchronized { | ||
| readThread = new Thread(s"PythonProfileMicroBatchStream") { | ||
| setDaemon(true) | ||
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| override def run(): Unit = { | ||
| val unpickler = new Unpickler | ||
| val extraChannel = SparkEnv.get.pythonWorkers.values | ||
| .head.getAllDaemonWorkers.map(_._1.extraChannel).head | ||
| extraChannel.foreach { s => | ||
| val inputStream = new DataInputStream(Channels.newInputStream(s)) | ||
| while (true) { | ||
| val len = inputStream.readInt() | ||
| val buf = new Array[Byte](len) | ||
| var totalRead = 0 | ||
| while (totalRead < len) { | ||
| val readNow = inputStream.read(buf, totalRead, len - totalRead) | ||
| assert(readNow != -1) | ||
| totalRead += readNow | ||
| } | ||
| currentOffset += 1 | ||
| batches.append( | ||
| unpickler.loads(buf).asInstanceOf[java.util.List[java.util.Map[String, String]]]) | ||
| } | ||
| } | ||
| } | ||
| } | ||
| readThread.start() | ||
| } | ||
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| override def initialOffset(): Offset = LongOffset(-1L) | ||
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| override def latestOffset(): Offset = currentOffset | ||
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| override def deserializeOffset(json: String): Offset = { | ||
| LongOffset(json.toLong) | ||
| } | ||
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| override def planInputPartitions(start: Offset, end: Offset): Array[InputPartition] = { | ||
| val startOrdinal = start.asInstanceOf[LongOffset].offset.toInt + 1 | ||
| val endOrdinal = end.asInstanceOf[LongOffset].offset.toInt + 1 | ||
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| val rawList = synchronized { | ||
| if (initialized.compareAndSet(false, true)) { | ||
| initialize() | ||
| } | ||
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| val sliceStart = startOrdinal - lastOffsetCommitted.offset.toInt - 1 | ||
| val sliceEnd = endOrdinal - lastOffsetCommitted.offset.toInt - 1 | ||
| batches.slice(sliceStart, sliceEnd) | ||
| } | ||
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| Array(PythonProfileInputPartition(rawList)) | ||
| } | ||
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| override def createReaderFactory(): PartitionReaderFactory = | ||
| (partition: InputPartition) => { | ||
| val stats = partition.asInstanceOf[PythonProfileInputPartition].stats | ||
| new PartitionReader[InternalRow] { | ||
| private var currentIdx = -1 | ||
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| override def next(): Boolean = { | ||
| currentIdx += 1 | ||
| currentIdx < stats.size | ||
| } | ||
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| override def get(): InternalRow = { | ||
| InternalRow.fromSeq( | ||
| CatalystTypeConverters.convertToCatalyst( | ||
| stats(currentIdx).asScala.toSeq.map(_.asScala)) :: Nil) | ||
| } | ||
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| override def close(): Unit = {} | ||
| } | ||
| } | ||
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| override def commit(end: Offset): Unit = synchronized { | ||
| val newOffset = end.asInstanceOf[LongOffset] | ||
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| val offsetDiff = (newOffset.offset - lastOffsetCommitted.offset).toInt | ||
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| if (offsetDiff < 0) { | ||
| throw new IllegalStateException( | ||
| s"Offsets committed out of order: $lastOffsetCommitted followed by $end") | ||
| } | ||
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| batches.dropInPlace(offsetDiff) | ||
| lastOffsetCommitted = newOffset | ||
| } | ||
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| override def toString: String = s"PythonProfile" | ||
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| override def stop(): Unit = { } | ||
| } | ||
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| case class PythonProfileInputPartition( | ||
| stats: ListBuffer[java.util.List[java.util.Map[String, String]]]) extends InputPartition |
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obviously make configurable later