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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
import java.util.ConcurrentModificationException
import scala.collection.mutable.ArrayBuffer
import org.apache.spark.{SparkEnv, TaskContext}
import org.apache.spark.internal.Logging
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
import org.apache.spark.util.collection.unsafe.sort.{UnsafeExternalSorter, UnsafeSorterIterator}
/**
* 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 ExternalAppendOnlyUnsafeRowArray(
taskMemoryManager: TaskMemoryManager,
blockManager: BlockManager,
serializerManager: SerializerManager,
taskContext: TaskContext,
initialSize: Int,
pageSizeBytes: Long,
numRowsInMemoryBufferThreshold: Int,
numRowsSpillThreshold: Int) extends Logging {
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 inMemoryBuffer = if (initialSizeOfInMemoryBuffer > 0) {
new ArrayBuffer[UnsafeRow](initialSizeOfInMemoryBuffer)
} else {
null
}
private var spillableArray: UnsafeExternalSorter = _
private var numRows = 0
// A counter to keep track of total modifications done to this array since its creation.
// This helps to invalidate iterators when there are changes done to the backing array.
private var modificationsCount: Long = 0
private var numFieldsPerRow = 0
def length: Int = numRows
def isEmpty: Boolean = numRows == 0
/**
* Clears up resources (eg. memory) held by the backing storage
*/
def clear(): Unit = {
if (spillableArray != null) {
// The last `spillableArray` of this task will be cleaned up via task completion listener
// inside `UnsafeExternalSorter`
spillableArray.cleanupResources()
spillableArray = null
} else if (inMemoryBuffer != null) {
inMemoryBuffer.clear()
}
numFieldsPerRow = 0
numRows = 0
modificationsCount += 1
}
def add(unsafeRow: UnsafeRow): Unit = {
if (numRows < numRowsInMemoryBufferThreshold) {
inMemoryBuffer += unsafeRow.copy()
} else {
if (spillableArray == null) {
logInfo(s"Reached spill threshold of $numRowsInMemoryBufferThreshold rows, switching to " +
s"${classOf[UnsafeExternalSorter].getName}")
// We will not sort the rows, so prefixComparator and recordComparator are null
spillableArray = UnsafeExternalSorter.create(
taskMemoryManager,
blockManager,
serializerManager,
taskContext,
null,
null,
initialSize,
pageSizeBytes,
numRowsSpillThreshold,
false)
// populate with existing in-memory buffered rows
if (inMemoryBuffer != null) {
inMemoryBuffer.foreach(existingUnsafeRow =>
spillableArray.insertRecord(
existingUnsafeRow.getBaseObject,
existingUnsafeRow.getBaseOffset,
existingUnsafeRow.getSizeInBytes,
0,
false)
)
inMemoryBuffer.clear()
}
numFieldsPerRow = unsafeRow.numFields()
}
spillableArray.insertRecord(
unsafeRow.getBaseObject,
unsafeRow.getBaseOffset,
unsafeRow.getSizeInBytes,
0,
false)
}
numRows += 1
modificationsCount += 1
}
/**
* Creates an [[Iterator]] for the current rows in the array starting from a user provided index
*
* If there are subsequent [[add()]] or [[clear()]] calls made on this array after creation of
* the iterator, then the iterator is invalidated thus saving clients from thinking that they
* have read all the data while there were new rows added to this array.
*/
def generateIterator(startIndex: Int): Iterator[UnsafeRow] = {
if (startIndex < 0 || (numRows > 0 && startIndex > numRows)) {
throw new ArrayIndexOutOfBoundsException(
"Invalid `startIndex` provided for generating iterator over the array. " +
s"Total elements: $numRows, requested `startIndex`: $startIndex")
}
if (spillableArray == null) {
new InMemoryBufferIterator(startIndex)
} else {
new SpillableArrayIterator(spillableArray.getIterator(startIndex), numFieldsPerRow)
}
}
def generateIterator(): Iterator[UnsafeRow] = generateIterator(startIndex = 0)
private[this]
abstract class ExternalAppendOnlyUnsafeRowArrayIterator extends Iterator[UnsafeRow] {
private val expectedModificationsCount = modificationsCount
protected def isModified(): Boolean = expectedModificationsCount != modificationsCount
protected def throwExceptionIfModified(): Unit = {
if (expectedModificationsCount != modificationsCount) {
throw new ConcurrentModificationException(
s"The backing ${classOf[ExternalAppendOnlyUnsafeRowArray].getName} has been modified " +
s"since the creation of this Iterator")
}
}
}
private[this] class InMemoryBufferIterator(startIndex: Int)
extends ExternalAppendOnlyUnsafeRowArrayIterator {
private var currentIndex = startIndex
override def hasNext(): Boolean = !isModified() && currentIndex < numRows
override def next(): UnsafeRow = {
throwExceptionIfModified()
val result = inMemoryBuffer(currentIndex)
currentIndex += 1
result
}
}
private[this] class SpillableArrayIterator(
iterator: UnsafeSorterIterator,
numFieldPerRow: Int)
extends ExternalAppendOnlyUnsafeRowArrayIterator {
private val currentRow = new UnsafeRow(numFieldPerRow)
override def hasNext(): Boolean = !isModified() && iterator.hasNext
override def next(): UnsafeRow = {
throwExceptionIfModified()
iterator.loadNext()
currentRow.pointTo(iterator.getBaseObject, iterator.getBaseOffset, iterator.getRecordLength)
currentRow
}
}
}
private[sql] object ExternalAppendOnlyUnsafeRowArray {
val DefaultInitialSizeOfInMemoryBuffer = 128
}
