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https://issues.apache.org/jira/browse/SPARK-19908?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16091168#comment-16091168
]
Bojan Babic commented on SPARK-19908:
-------------------------------------
[~skp33] got the same error while running RowMatrix transpose.
{code}
def buildRow(rowWithIndexes: Iterable[(Long, Double)]):
org.apache.spark.mllib.linalg.Vector = {
val resArr = new Array[Double](rowWithIndexes.size)
rowWithIndexes.foreach{case (index, value) =>
resArr(index.toInt) = value
}
Vectors.dense(resArr)
}
def rowToTransposedTriplet(row: org.apache.spark.mllib.linalg.Vector, rowIndex:
Long): Array[(Long, (Long, Double))] = {
val indexedRow = row.toArray.zipWithIndex
indexedRow.map{case (value, colIndex) => (colIndex.toLong, (rowIndex,
value))}
}
def transposeRowMatrix(m: RowMatrix): RowMatrix = {
// cache in case flatMap fails
val transposedTripletRDD = m.rows.zipWithIndex.map{case (row, rowIndex) =>
rowToTransposedTriplet(row, rowIndex)}.cache()
val transposedRowsRDD = transposedTripletRDD.flatMap(x => x) // now we have
triplets (newRowIndex, (newColIndex, value))
.groupByKey
.sortByKey().map(_._2) // sort rows and remove row indexes
.map(buildRow) // restore order of elements in each row and remove column
indexes
new RowMatrix(transposedRowsRDD)
}
val mat_transposed = transposeRowMatrix(mat)
{code}
matrix is medium size 40Kx260K
> Direct buffer memory OOM should not cause stage retries.
> --------------------------------------------------------
>
> Key: SPARK-19908
> URL: https://issues.apache.org/jira/browse/SPARK-19908
> Project: Spark
> Issue Type: Bug
> Components: Shuffle
> Affects Versions: 2.1.0
> Reporter: Zhan Zhang
> Priority: Minor
>
> Currently if there is java.lang.OutOfMemoryError: Direct buffer memory, the
> exception will be changed to FetchFailedException, causing stage retries.
> org.apache.spark.shuffle.FetchFailedException: Direct buffer memory
> at
> org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:357)
> at
> org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:332)
> at
> org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:54)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at
> org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32)
> at
> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:40)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.sort_addToSorter$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
> at
> org.apache.spark.sql.execution.RowIteratorFromScala.advanceNext(RowIterator.scala:83)
> at
> org.apache.spark.sql.execution.joins.SortMergeJoinScanner.advancedStreamed(SortMergeJoinExec.scala:731)
> at
> org.apache.spark.sql.execution.joins.SortMergeJoinScanner.findNextOuterJoinRows(SortMergeJoinExec.scala:692)
> at
> org.apache.spark.sql.execution.joins.OneSideOuterIterator.advanceStream(SortMergeJoinExec.scala:854)
> at
> org.apache.spark.sql.execution.joins.OneSideOuterIterator.advanceNext(SortMergeJoinExec.scala:887)
> at
> org.apache.spark.sql.execution.RowIteratorToScala.hasNext(RowIterator.scala:68)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at
> org.apache.spark.shuffle.sort.UnsafeShuffleWriter.write(UnsafeShuffleWriter.java:161)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
> at org.apache.spark.scheduler.Task.run(Task.scala:86)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:278)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: java.lang.OutOfMemoryError: Direct buffer memory
> at java.nio.Bits.reserveMemory(Bits.java:658)
> at java.nio.DirectByteBuffer.<init>(DirectByteBuffer.java:123)
> at java.nio.ByteBuffer.allocateDirect(ByteBuffer.java:311)
> at io.netty.buffer.PoolArena$DirectArena.newChunk(PoolArena.java:645)
> at io.netty.buffer.PoolArena.allocateNormal(PoolArena.java:228)
> at io.netty.buffer.PoolArena.allocate(PoolArena.java:212)
> at io.netty.buffer.PoolArena.allocate(PoolArena.java:132)
> at
> io.netty.buffer.PooledByteBufAllocator.newDirectBuffer(PooledByteBufAllocator.java:271)
> at
> io.netty.buffer.AbstractByteBufAllocator.directBuffer(AbstractByteBufAllocator.java:155)
> at
> io.netty.buffer.AbstractByteBufAllocator.directBuffer(AbstractByteBufAllocator.java:146)
> at
> io.netty.buffer.AbstractByteBufAllocator.ioBuffer(AbstractByteBufAllocator.java:107)
> at
> io.netty.channel.AdaptiveRecvByteBufAllocator$HandleImpl.allocate(AdaptiveRecvByteBufAllocator.java:104)
> at
> io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:117)
> at
> io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511)
> at
> io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
> at
> io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
> at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
> at
> io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
> ... 1 more
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