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Original file line number Diff line number Diff line change
Expand Up @@ -44,28 +44,33 @@ class FileStreamSink(

private val basePath = new Path(path)
private val logPath = new Path(basePath, FileStreamSink.metadataDir)
private val fileLog = new HDFSMetadataLog[Seq[String]](sqlContext, logPath.toUri.toString)
private val fileLog = new FileStreamSinkLog(sqlContext, logPath.toUri.toString)
private val fs = basePath.getFileSystem(sqlContext.sparkContext.hadoopConfiguration)

override def addBatch(batchId: Long, data: DataFrame): Unit = {
if (fileLog.get(batchId).isDefined) {
if (batchId <= fileLog.getLatest().map(_._1).getOrElse(-1L)) {
logInfo(s"Skipping already committed batch $batchId")
} else {
val files = writeFiles(data)
val files = fs.listStatus(writeFiles(data)).map { f =>
SinkFileStatus(
path = f.getPath.toUri.toString,
size = f.getLen,
isDir = f.isDirectory,
modificationTime = f.getModificationTime,
blockReplication = f.getReplication,
blockSize = f.getBlockSize,
action = FileStreamSinkLog.ADD_ACTION)
}
if (fileLog.add(batchId, files)) {
logInfo(s"Committed batch $batchId")
} else {
logWarning(s"Race while writing batch $batchId")
throw new IllegalStateException(s"Race while writing batch $batchId")
}
}
}

/** Writes the [[DataFrame]] to a UUID-named dir, returning the list of files paths. */
private def writeFiles(data: DataFrame): Seq[String] = {
val ctx = sqlContext
val outputDir = path
val format = fileFormat
val schema = data.schema

private def writeFiles(data: DataFrame): Array[Path] = {
val file = new Path(basePath, UUID.randomUUID().toString).toUri.toString
data.write.parquet(file)
sqlContext.read
Expand All @@ -74,7 +79,6 @@ class FileStreamSink(
.inputFiles
.map(new Path(_))
.filterNot(_.getName.startsWith("_"))
.map(_.toUri.toString)
}

override def toString: String = s"FileSink[$path]"
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,278 @@
/*
* 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.streaming

import java.io.IOException
import java.nio.charset.StandardCharsets.UTF_8

import org.apache.hadoop.fs.{FileStatus, Path, PathFilter}
import org.json4s.NoTypeHints
import org.json4s.jackson.Serialization
import org.json4s.jackson.Serialization.{read, write}

import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.internal.SQLConf

/**
* The status of a file outputted by [[FileStreamSink]]. A file is visible only if it appears in
* the sink log and its action is not "delete".
*
* @param path the file path.
* @param size the file size.
* @param isDir whether this file is a directory.
* @param modificationTime the file last modification time.
* @param blockReplication the block replication.
* @param blockSize the block size.
* @param action the file action. Must be either "add" or "delete".
*/
case class SinkFileStatus(
path: String,
size: Long,
isDir: Boolean,
modificationTime: Long,
blockReplication: Int,
blockSize: Long,
action: String) {

def toFileStatus: FileStatus = {
new FileStatus(size, isDir, blockReplication, blockSize, modificationTime, new Path(path))
}
}

/**
* A special log for [[FileStreamSink]]. It will write one log file for each batch. The first line
* of the log file is the version number, and there are multiple JSON lines following. Each JSON
* line is a JSON format of [[SinkFileStatus]].
*
* As reading from many small files is usually pretty slow, [[FileStreamSinkLog]] will compact log
* files every "spark.sql.sink.file.log.compactLen" batches into a big file. When doing a
* compaction, it will read all old log files and merge them with the new batch. During the
* compaction, it will also delete the files that are deleted (marked by [[SinkFileStatus.action]]).
* When the reader uses `allFiles` to list all files, this method only returns the visible files
* (drops the deleted files).
*/
class FileStreamSinkLog(sqlContext: SQLContext, path: String)
extends HDFSMetadataLog[Seq[SinkFileStatus]](sqlContext, path) {

import FileStreamSinkLog._

private implicit val formats = Serialization.formats(NoTypeHints)

/**
* If we delete the old files after compaction at once, there is a race condition in S3: other
* processes may see the old files are deleted but still cannot see the compaction file using
* "list". The `allFiles` handles this by looking for the next compaction file directly, however,
* a live lock may happen if the compaction happens too frequently: one processing keeps deleting
* old files while another one keeps retrying. Setting a reasonable cleanup delay could avoid it.
*/
private val fileCleanupDelayMs = sqlContext.getConf(SQLConf.FILE_SINK_LOG_CLEANUP_DELAY)
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all AWS S3 endpoints now implement create consistency: if a new object is created, then a GET made directly on it will return that object.

what can take time to appear is the aggregate file in an ls of the parent "directory" —that's really a wild card match on the path. If the processes can determine the final name of the compaction file, they can look for that file directly (getFileStatus() should suffice, open() even better). If the compact file isn't found, they can look for the non-aggregate files. All that should be required is the aggregate file fully written (with a close() at the end of output operation which doesn't discard any raised exception), before deleting the original files. Adding a minor delay is a low-harm feature, but having a direct check for the aggregate file is something which should be done first

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@steveloughran thanks for pointing out it. I updated the codes. Now it will try to access the next compaction/aggregate file directly. However, a cleanup delay is still helpful to avoid a live lock.


private val isDeletingExpiredLog = sqlContext.getConf(SQLConf.FILE_SINK_LOG_DELETION)

private val compactInterval = sqlContext.getConf(SQLConf.FILE_SINK_LOG_COMPACT_INTERVAL)
require(compactInterval > 0,
s"Please set ${SQLConf.FILE_SINK_LOG_COMPACT_INTERVAL.key} (was $compactInterval) " +
"to a positive value.")

override def batchIdToPath(batchId: Long): Path = {
if (isCompactionBatch(batchId, compactInterval)) {
new Path(metadataPath, s"$batchId$COMPACT_FILE_SUFFIX")
} else {
new Path(metadataPath, batchId.toString)
}
}

override def pathToBatchId(path: Path): Long = {
getBatchIdFromFileName(path.getName)
}

override def isBatchFile(path: Path): Boolean = {
try {
getBatchIdFromFileName(path.getName)
true
} catch {
case _: NumberFormatException => false
}
}

override def serialize(logData: Seq[SinkFileStatus]): Array[Byte] = {
(VERSION +: logData.map(write(_))).mkString("\n").getBytes(UTF_8)
}

override def deserialize(bytes: Array[Byte]): Seq[SinkFileStatus] = {
val lines = new String(bytes, UTF_8).split("\n")
if (lines.length == 0) {
throw new IllegalStateException("Incomplete log file")
}
val version = lines(0)
if (version != VERSION) {
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Should this be 'version > VERSION' ?

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Should this be 'version > VERSION' ?

It doesn't matter now. This is the first version. We will update the logic here when we add a new format in future.

throw new IllegalStateException(s"Unknown log version: ${version}")
}
lines.toSeq.slice(1, lines.length).map(read[SinkFileStatus](_))
}

override def add(batchId: Long, logs: Seq[SinkFileStatus]): Boolean = {
if (isCompactionBatch(batchId, compactInterval)) {
compact(batchId, logs)
} else {
super.add(batchId, logs)
}
}

/**
* Returns all files except the deleted ones.
*/
def allFiles(): Array[SinkFileStatus] = {
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Can you make this allSinkFile() so that its not ambiguous with the log files?

var latestId = getLatest().map(_._1).getOrElse(-1L)
// There is a race condition when `FileStreamSink` is deleting old files and `StreamFileCatalog`
// is calling this method. This loop will retry the reading to deal with the
// race condition.
while (true) {
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nit: can you explain the loop?

if (latestId >= 0) {
val startId = getAllValidBatches(latestId, compactInterval)(0)
try {
val logs = get(Some(startId), Some(latestId)).flatMap(_._2)
return compactLogs(logs).toArray
} catch {
case e: IOException =>
// Another process using `FileStreamSink` may delete the batch files when
// `StreamFileCatalog` are reading. However, it only happens when a compaction is
// deleting old files. If so, let's try the next compaction batch and we should find it.
// Otherwise, this is a real IO issue and we should throw it.
latestId = nextCompactionBatchId(latestId, compactInterval)
get(latestId).getOrElse {
throw e
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Maybe include latestId in the exception message

}
}
} else {
return Array.empty
}
}
Array.empty
}

/**
* Compacts all logs before `batchId` plus the provided `logs`, and writes them into the
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nit: compact all sink files before ...

* corresponding `batchId` file. It will delete expired files as well if enabled.
*/
private def compact(batchId: Long, logs: Seq[SinkFileStatus]): Boolean = {
val validBatches = getValidBatchesBeforeCompactionBatch(batchId, compactInterval)
val allLogs = validBatches.flatMap(batchId => get(batchId)).flatten ++ logs
if (super.add(batchId, compactLogs(allLogs))) {
if (isDeletingExpiredLog) {
deleteExpiredLog(batchId)
}
true
} else {
// Return false as there is another writer.
false
}
}

/**
* Since all logs before `compactionBatchId` are compacted and written into the
* `compactionBatchId` log file, they can be removed. However, due to the eventual consistency of
* S3, the compaction file may not be seen by other processes at once. So we only delete files
* created `fileCleanupDelayMs` milliseconds ago.
*/
private def deleteExpiredLog(compactionBatchId: Long): Unit = {
val expiredTime = System.currentTimeMillis() - fileCleanupDelayMs
fileManager.list(metadataPath, new PathFilter {
override def accept(path: Path): Boolean = {
try {
val batchId = getBatchIdFromFileName(path.getName)
batchId < compactionBatchId
} catch {
case _: NumberFormatException =>
false
}
}
}).foreach { f =>
if (f.getModificationTime <= expiredTime) {
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What happens in file systems where getModificationTime is not reported, or reported as 0. Then this would always delete all the files.

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I made a mistake about getModificationTime. Only the directory's getModificationTime in S3 returns 0. File's getModificationTime returns the correct value. See https://issues.apache.org/jira/browse/HADOOP-12837

I also verified that in S3 by myself.

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Note that granularity of modification time can be 1s (azure)

fileManager.delete(f.getPath)
}
}
}
}

object FileStreamSinkLog {
val VERSION = "v1"
val COMPACT_FILE_SUFFIX = ".compact"
val DELETE_ACTION = "delete"
val ADD_ACTION = "add"

def getBatchIdFromFileName(fileName: String): Long = {
fileName.stripSuffix(COMPACT_FILE_SUFFIX).toLong
}

/**
* Returns if this is a compaction batch. FileStreamSinkLog will compact old logs every
* `compactInterval` commits.
*
* E.g., if `compactInterval` is 3, then 2, 5, 8, ... are all compaction batches.
*/
def isCompactionBatch(batchId: Long, compactInterval: Int): Boolean = {
(batchId + 1) % compactInterval == 0
}

/**
* Returns all valid batches before the specified `compactionBatchId`. They contain all logs we
* need to do a new compaction.
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nit: Can you put an example like the isCompletionBatch

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Added.

*
* E.g., if `compactInterval` is 3 and `compactionBatchId` is 5, this method should returns
* `Seq(2, 3, 4)` (Note: it includes the previous compaction batch 2).
*/
def getValidBatchesBeforeCompactionBatch(
compactionBatchId: Long,
compactInterval: Int): Seq[Long] = {
assert(isCompactionBatch(compactionBatchId, compactInterval),
s"$compactionBatchId is not a compaction batch")
(math.max(0, compactionBatchId - compactInterval)) until compactionBatchId
}

/**
* Returns all necessary logs before `batchId` (inclusive). If `batchId` is a compaction, just
* return itself. Otherwise, it will find the previous compaction batch and return all batches
* between it and `batchId`.
*/
def getAllValidBatches(batchId: Long, compactInterval: Long): Seq[Long] = {
assert(batchId >= 0)
val start = math.max(0, (batchId + 1) / compactInterval * compactInterval - 1)
start to batchId
}

/**
* Removes all deleted files from logs. It assumes once one file is deleted, it won't be added to
* the log in future.
*/
def compactLogs(logs: Seq[SinkFileStatus]): Seq[SinkFileStatus] = {
val deletedFiles = logs.filter(_.action == DELETE_ACTION).map(_.path).toSet
if (deletedFiles.isEmpty) {
logs
} else {
logs.filter(f => !deletedFiles.contains(f.path))
}
}

/**
* Returns the next compaction batch id after `batchId`.
*/
def nextCompactionBatchId(batchId: Long, compactInterval: Long): Long = {
(batchId + compactInterval + 1) / compactInterval * compactInterval - 1
}
}
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