Github user zecevicp commented on a diff in the pull request: https://github.com/apache/spark/pull/21109#discussion_r193763364 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/InMemoryUnsafeRowQueue.scala --- @@ -0,0 +1,183 @@ +/* + * 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 + +import java.util.ConcurrentModificationException + +import scala.collection.mutable +import scala.collection.mutable.ArrayBuffer + +import org.apache.spark.{SparkEnv, TaskContext} +import org.apache.spark.memory.TaskMemoryManager +import org.apache.spark.serializer.SerializerManager +import org.apache.spark.sql.catalyst.expressions.UnsafeRow +import org.apache.spark.sql.execution.ExternalAppendOnlyUnsafeRowArray.DefaultInitialSizeOfInMemoryBuffer +import org.apache.spark.storage.BlockManager + +/** + * An append-only array for [[UnsafeRow]]s that strictly keeps content in an in-memory array + * until [[numRowsInMemoryBufferThreshold]] is reached post which it will switch to a mode which + * would flush to disk after [[numRowsSpillThreshold]] is met (or before if there is + * excessive memory consumption). Setting these threshold involves following trade-offs: + * + * - If [[numRowsInMemoryBufferThreshold]] is too high, the in-memory array may occupy more memory + * than is available, resulting in OOM. + * - If [[numRowsSpillThreshold]] is too low, data will be spilled frequently and lead to + * excessive disk writes. This may lead to a performance regression compared to the normal case + * of using an [[ArrayBuffer]] or [[Array]]. + */ +private[sql] class InMemoryUnsafeRowQueue( + taskMemoryManager: TaskMemoryManager, + blockManager: BlockManager, + serializerManager: SerializerManager, + taskContext: TaskContext, + initialSize: Int, + pageSizeBytes: Long, + numRowsInMemoryBufferThreshold: Int, + numRowsSpillThreshold: Int) + extends ExternalAppendOnlyUnsafeRowArray(taskMemoryManager, + blockManager, + serializerManager, + taskContext, + initialSize, + pageSizeBytes, + numRowsInMemoryBufferThreshold, + numRowsSpillThreshold) { + + def this(numRowsInMemoryBufferThreshold: Int, numRowsSpillThreshold: Int) { + this( + TaskContext.get().taskMemoryManager(), + SparkEnv.get.blockManager, + SparkEnv.get.serializerManager, + TaskContext.get(), + 1024, + SparkEnv.get.memoryManager.pageSizeBytes, + numRowsInMemoryBufferThreshold, + numRowsSpillThreshold) + } + + private val initialSizeOfInMemoryBuffer = + Math.min(DefaultInitialSizeOfInMemoryBuffer, numRowsInMemoryBufferThreshold) + + private val inMemoryQueue = if (initialSizeOfInMemoryBuffer > 0) { + new mutable.Queue[UnsafeRow]() + } else { + null + } + +// private var spillableArray: UnsafeExternalSorter = _ --- End diff -- No, it's not. Thank you
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