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Original file line number Diff line number Diff line change
@@ -0,0 +1,245 @@
/*
* 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 scala.reflect.ClassTag

import org.apache.hadoop.fs.{Path, PathFilter}

import org.apache.spark.sql.SparkSession

/**
* An abstract class for compactible metadata logs. It will write one log file for each batch.
* The first line of the log file is the version number, and there are multiple serialized
* metadata lines following.
*
* As reading from many small files is usually pretty slow, also too many
* small files in one folder will mess the FS, [[CompactibleFileStreamLog]] will
* compact log files every 10 batches by default into a big file. When
* doing a compaction, it will read all old log files and merge them with the new batch.
*/
abstract class CompactibleFileStreamLog[T: ClassTag](
metadataLogVersion: String,
sparkSession: SparkSession,
path: String)
extends HDFSMetadataLog[Array[T]](sparkSession, path) {

import CompactibleFileStreamLog._

/**
* 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.
*/
protected def fileCleanupDelayMs: Long

protected def isDeletingExpiredLog: Boolean

protected def compactInterval: Int

/**
* Serialize the data into encoded string.
*/
protected def serializeData(t: T): String

/**
* Deserialize the string into data object.
*/
protected def deserializeData(encodedString: String): T

/**
* Filter out the obsolete logs.
*/
def compactLogs(logs: Seq[T]): Seq[T]

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: Array[T]): Array[Byte] = {
(metadataLogVersion +: logData.map(serializeData)).mkString("\n").getBytes(UTF_8)
}

override def deserialize(bytes: Array[Byte]): Array[T] = {
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 != metadataLogVersion) {
throw new IllegalStateException(s"Unknown log version: ${version}")
}
lines.slice(1, lines.length).map(deserializeData)
}

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

/**
* Compacts all logs before `batchId` plus the provided `logs`, and writes them into the
* corresponding `batchId` file. It will delete expired files as well if enabled.
*/
private def compact(batchId: Long, logs: Array[T]): Boolean = {
val validBatches = getValidBatchesBeforeCompactionBatch(batchId, compactInterval)
val allLogs = validBatches.flatMap(batchId => super.get(batchId)).flatten ++ logs
if (super.add(batchId, compactLogs(allLogs).toArray)) {
if (isDeletingExpiredLog) {
deleteExpiredLog(batchId)
}
true
} else {
// Return false as there is another writer.
false
}
}

/**
* Returns all files except the deleted ones.
*/
def allFiles(): Array[T] = {
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) {
if (latestId >= 0) {
try {
val logs =
getAllValidBatches(latestId, compactInterval).flatMap(id => super.get(id)).flatten
return compactLogs(logs).toArray
} catch {
case e: IOException =>
// Another process using `CompactibleFileStreamLog` 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)
super.get(latestId).getOrElse {
throw e
}
}
} else {
return Array.empty
}
}
Array.empty
}

/**
* 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) {
fileManager.delete(f.getPath)
}
}
}
}

object CompactibleFileStreamLog {
val COMPACT_FILE_SUFFIX = ".compact"

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.
*
* 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
}

/**
* Returns the next compaction batch id after `batchId`.
*/
def nextCompactionBatchId(batchId: Long, compactInterval: Long): Long = {
(batchId + compactInterval + 1) / compactInterval * compactInterval - 1
}
}
Original file line number Diff line number Diff line change
Expand Up @@ -56,7 +56,8 @@ class FileStreamSink(

private val basePath = new Path(path)
private val logPath = new Path(basePath, FileStreamSink.metadataDir)
private val fileLog = new FileStreamSinkLog(sparkSession, logPath.toUri.toString)
private val fileLog =
new FileStreamSinkLog(FileStreamSinkLog.VERSION, sparkSession, logPath.toUri.toString)
private val hadoopConf = sparkSession.sessionState.newHadoopConf()
private val fs = basePath.getFileSystem(hadoopConf)

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