本文深入剖析了Kafka中的日志管理系统，包括LogManager、Log、LogSegment等核心组件的功能与实现细节，以及消息的读写流程。
LogManager
LogManager会管理broker上所有的logs（在一个log目录下），一个topic的一个partition对应于一个log（一个log子目录）
首先loadLogs会加载每个partition所对应的log对象， 然后提供createLog，getLog，deleteLog之类的管理接口
并且会创建些后台线程来进行，cleanup，flush，checkpoint生成之类的工作
/**
* The entry point to the kafka log management subsystem. The log manager is responsible for log creation, retrieval, and cleaning.
* All read and write operations are delegated to the individual log instances.
*
* The log manager maintains logs in one or more directories. New logs are created in the data directory
* with the fewest logs. No attempt is made to move partitions after the fact or balance based on
* size or I/O rate.
*
* A background thread handles log retention by periodically truncating excess log segments.
*/
@threadsafe
class LogManager(val logDirs: Array[File],
val topicConfigs: Map[String, LogConfig],
val defaultConfig: LogConfig,
val cleanerConfig: CleanerConfig,
val flushCheckMs: Long,
val flushCheckpointMs: Long,
val retentionCheckMs: Long,
scheduler: Scheduler,
private val time: Time) extends Logging {
//kafka.utils.Pool，对ConcurrentHashMap的封装
private val logs = new Pool[TopicAndPartition, Log]() //一个topic的partition对应于一个log
/**
* Recover and load all logs in the given data directories
*/
private def loadLogs(dirs: Seq[File]) {
for(dir <- dirs) {
val recoveryPoints = this.recoveryPointCheckpoints(dir).read //载入recoveryPoints
/* load the logs */
val subDirs = dir.listFiles()
if(subDirs != null) {
for(dir <- subDirs) { //将每个子目录load成log，子目录中的文件就是segment文件
if(dir.isDirectory) {
val topicPartition = Log.parseTopicPartitionName(dir.getName) //从目录名可以解析出topic和partition名
val config = topicConfigs.getOrElse(topicPartition.topic, defaultConfig)
val log = new Log(dir,
config,
recoveryPoints.getOrElse(topicPartition, 0L),
scheduler,
time)
val previous = this.logs.put(topicPartition, log)
}
}
cleanShutDownFile.delete()
}
}
}
/**
* Create a log for the given topic and the given partition
* If the log already exists, just return a copy of the existing log
*/
def createLog(topicAndPartition: TopicAndPartition, config: LogConfig): Log = {
logCreationOrDeletionLock synchronized {
var log = logs.get(topicAndPartition)
// check if the log has already been created in another thread
if(log != null)
return log
// if not, create it
val dataDir = nextLogDir()
val dir = new File(dataDir, topicAndPartition.topic + "-" + topicAndPartition.partition) //创建log目录
dir.mkdirs()
log = new Log(dir, //创建log对象
config,
recoveryPoint = 0L,
scheduler,
time)
logs.put(topicAndPartition, log)
log
}
}
//从checkpoint文件load各个log的RecoveryPoint
private val recoveryPointCheckpoints = logDirs.map(dir => (dir, new OffsetCheckpoint(new File(dir, RecoveryPointCheckpointFile)))).toMap
//生成所有logs的RecoveryPoint的checkpoint文件
/**
* Write out the current recovery point for all logs to a text file in the log directory
* to avoid recovering the whole log on startup.
*/
def checkpointRecoveryPointOffsets() {
val recoveryPointsByDir = this.logsByTopicPartition.groupBy(_._2.dir.getParent.toString)
for(dir <- logDirs) {
val recoveryPoints = recoveryPointsByDir.get(dir.toString)
if(recoveryPoints.isDefined)
this.recoveryPointCheckpoints(dir).write(recoveryPoints.get.mapValues(_.recoveryPoint))
}
}
}
Log
Log只是对于LogSegments的封装，包含loadSegments，append（到active segment），read（需要定位到相应的segment）
/**
* An append-only log for storing messages.
*
* The log is a sequence of LogSegments, each with a base offset denoting the first message in the segment.
*
* New log segments are created according to a configurable policy that controls the size in bytes or time interval
* for a given segment.
*
* @param dir The directory in which log segments are created.
* @param config The log configuration settings
* @param recoveryPoint The offset at which to begin recovery--i.e. the first offset which has not been flushed to disk
* @param scheduler The thread pool scheduler used for background actions
* @param time The time instance used for checking the clock
*
*/
@threadsafe
class Log(val dir: File,
@volatile var config: LogConfig,
@volatile var recoveryPoint: Long = 0L,
val scheduler: Scheduler,
time: Time = SystemTime) extends Logging with KafkaMetricsGroup {
//使用ConcurrentSkipListMap来保存segments信息（startoffset，logSegment），按startoffset排序
/* the actual segments of the log */
private val segments: ConcurrentNavigableMap[java.lang.Long, LogSegment] = new ConcurrentSkipListMap[java.lang.Long, LogSegment]
loadSegments()
/* Calculate the offset of the next message */
private val nextOffset: AtomicLong = new AtomicLong(activeSegment.nextOffset())
/**
* The active segment that is currently taking appends
*/
def activeSegment = segments.lastEntry.getValue //最新的segment就是active
/* Load the log segments from the log files on disk */
private def loadSegments() {
// create the log directory if it doesn't exist
dir.mkdirs()
// first do a pass through the files in the log directory and remove any temporary files
// and complete any interrupted swap operations
// ......为load做准备，清除临时文件和一些swap操作
// now do a second pass and load all the .log and .index files，真正开始load segment
for(file <- dir.listFiles if file.isFile) {
val filename = file.getName
if(filename.endsWith(IndexFileSuffix)) { //清理无效的index文件，无配对的log文件
// if it is an index file, make sure it has a corresponding .log file
val logFile = new File(file.getAbsolutePath.replace(IndexFileSuffix, LogFileSuffix))
if(!logFile.exists) {
warn("Found an orphaned index file, %s, with no corresponding log file.".format(file.getAbsolutePath))
file.delete()
}
} else if(filename.endsWith(LogFileSuffix)) { //对于log文件，生成LogSegment对象完成load
// if its a log file, load the corresponding log segment
val start = filename.substring(0, filename.length - LogFileSuffix.length).toLong
val hasIndex = Log.indexFilename(dir, start).exists
val segment = new LogSegment(dir = dir,
startOffset = start,
indexIntervalBytes = config.indexInterval,
maxIndexSize = config.maxIndexSize,
time = time)
if(!hasIndex) { //对于没有index文件的，需要rebuild index文件
error("Could not find index file corresponding to log file %s, rebuilding index...".format(segment.log.file.getAbsolutePath))
segment.recover(config.maxMessageSize)
}
segments.put(start, segment)
}
}
}
/** Struct to hold various quantities we compute about each message set before appending to the log
* @param firstOffset The first offset in the message set
* @param lastOffset The last offset in the message set
* @param codec The codec used in the message set
* @param offsetsMonotonic Are the offsets in this message set monotonically increasing
*/
case class LogAppendInfo(var firstOffset: Long, var lastOffset: Long, codec: CompressionCodec, shallowCount: Int, offsetsMonotonic: Boolean)
/**
* Append this message set to the active segment of the log, rolling over to a fresh segment if necessary.
*
* This method will generally be responsible for assigning offsets to the messages,
* however if the assignOffsets=false flag is passed we will only check that the existing offsets are valid.
*
* @param messages The message set to append
* @param assignOffsets Should the log assign offsets to this message set or blindly apply what it is given
*
* @throws KafkaStorageException If the append fails due to an I/O error.
*
* @return Information about the appended messages including the first and last offset.
*/
def append(messages: ByteBufferMessageSet, assignOffsets: Boolean = true): LogAppendInfo = {
val appendInfo = analyzeAndValidateMessageSet(messages) //分析ByteBufferMessageSet，生成LogAppendInfo
try {
// they are valid, insert them in the log
lock synchronized {
appendInfo.firstOffset = nextOffset.get //nextOffset作为append的起始点
// maybe roll the log if this segment is full
val segment = maybeRoll() //是否需要产生新的segment
// now append to the log
segment.append(appendInfo.firstOffset, validMessages) //append
// increment the log end offset
nextOffset.set(appendInfo.lastOffset + 1) //递增nextOffset
if(unflushedMessages >= config.flushInterval)
flush() //定期flush
appendInfo
}
} catch {
case e: IOException => throw new KafkaStorageException("I/O exception in append to log '%s'".format(name), e)
}
}
/**
* Read messages from the log
* @param startOffset The offset to begin reading at
* @param maxLength The maximum number of bytes to read
* @param maxOffset -The offset to read up to, exclusive. (i.e. the first offset NOT included in the resulting message set).
*
* @throws OffsetOutOfRangeException If startOffset is beyond the log end offset or before the base offset of the first segment.
* @return The messages read
*/
def read(startOffset: Long, maxLength: Int, maxOffset: Option[Long] = None): MessageSet = {
// check if the offset is valid and in range
val next = nextOffset.get
if(startOffset == next)
return MessageSet.Empty
var entry = segments.floorEntry(startOffset) //floorEntry会找出小于startOffset，并最接近的那个segment
// do the read on the segment with a base offset less than the target offset
// but if that segment doesn't contain any messages with an offset greater than that
// continue to read from successive segments until we get some messages or we reach the end of the log
while(entry != null) {
val messages = entry.getValue.read(startOffset, maxOffset, maxLength) //从该segment中读出数据
if(messages == null)
entry = segments.higherEntry(entry.getKey) //如果没有读到，去下个segment中读
else
return messages
}
// okay we are beyond the end of the last segment but less than the log end offset
MessageSet.Empty
}
}
LogSegment
Segment是个逻辑概念，为了防止log文件过大， 将log分成许多的LogSegments
Segment又分为两部分，MessageSet文件和Index文件，分别命名为[base_offset].log和[base_offset].index
base_offset就是该Segment的起始offset，比前一个segment里面的offset都要大
Segment提供对于MessageSet的读写接口
写，需要间隔的更新index文件，应该为了尽量减小index的size，所以只是当写入数据大于indexIntervalBytes时，才增加一条索引
读，由于user传入的是逻辑offest，需要先转化为物理地址才能从文件中读到数据，如何转化参考下面
同时index文件是可以根据MessageSet文件重新rebuild的
/**
* A segment of the log. Each segment has two components: a log and an index. The log is a FileMessageSet containing
* the actual messages. The index is an OffsetIndex that maps from logical offsets to physical file positions. Each
* segment has a base offset which is an offset <= the least offset of any message in this segment and > any offset in
* any previous segment.
*
* A segment with a base offset of [base_offset] would be stored in two files, a [base_offset].index and a [base_offset].log file.
*
* @param log The message set containing log entries
* @param index The offset index
* @param baseOffset A lower bound on the offsets in this segment
* @param indexIntervalBytes The approximate number of bytes between entries in the index
* @param time The time instance
*/
@nonthreadsafe
class LogSegment(val log: FileMessageSet,
val index: OffsetIndex,
val baseOffset: Long,
val indexIntervalBytes: Int,
time: Time) extends Logging {
/**
* Append the given messages starting with the given offset. Add
* an entry to the index if needed.
*
* It is assumed this method is being called from within a lock.
*
* @param offset The first offset in the message set.
* @param messages The messages to append.
*/
@nonthreadsafe
def append(offset: Long, messages: ByteBufferMessageSet) {
if (messages.sizeInBytes > 0) {
// append an entry to the index (if needed)
if(bytesSinceLastIndexEntry > indexIntervalBytes) { //仅index部分message
index.append(offset, log.sizeInBytes()) //写index文件
this.bytesSinceLastIndexEntry = 0
}
// append the messages
log.append(messages) //写messageset文件
this.bytesSinceLastIndexEntry += messages.sizeInBytes
}
}
/**
* Read a message set from this segment beginning with the first offset >= startOffset. The message set will include
* no more than maxSize bytes and will end before maxOffset if a maxOffset is specified.
*
* @param startOffset A lower bound on the first offset to include in the message set we read
* @param maxSize The maximum number of bytes to include in the message set we read
* @param maxOffset An optional maximum offset for the message set we read
*
* @return The message set read or null if the startOffset is larger than the largest offset in this log.
*/
@threadsafe
def read(startOffset: Long, maxOffset: Option[Long], maxSize: Int): MessageSet = {
val logSize = log.sizeInBytes // this may change, need to save a consistent copy
val startPosition = translateOffset(startOffset)
// calculate the length of the message set to read based on whether or not they gave us a maxOffset
val length =
maxOffset match {
case None =>
// no max offset, just use the max size they gave unmolested
maxSize
case Some(offset) => {
// there is a max offset, translate it to a file position and use that to calculate the max read size
if(offset < startOffset)
throw new IllegalArgumentException("Attempt to read with a maximum offset (%d) less than the start offset (%d).".format(offset, startOffset))
val mapping = translateOffset(offset, startPosition.position)
val endPosition =
if(mapping == null)
logSize // the max offset is off the end of the log, use the end of the file
else
mapping.position
min(endPosition - startPosition.position, maxSize)
}
}
log.read(startPosition.position, length) //读出messageset
}
/**
* Run recovery on the given segment. This will rebuild the index from the log file and lop off any invalid bytes from the end of the log and index.
*
* @param maxMessageSize A bound the memory allocation in the case of a corrupt message size--we will assume any message larger than this
* is corrupt.
*
* @return The number of bytes truncated from the log
*/
@nonthreadsafe
def recover(maxMessageSize: Int): Int = {...}
}
FileMessageSet
Segment中实际存放log message的文件，通过FileChannel可以读写文件
1: /**
2: * An on-disk message set. An optional start and end position can be applied to the message set
3: * which will allow slicing a subset of the file.
4: * @param file The file name for the underlying log data
5: * @param channel the underlying file channel used
6: * @param start A lower bound on the absolute position in the file from which the message set begins
7: * @param end The upper bound on the absolute position in the file at which the message set ends
8: * @param isSlice Should the start and end parameters be used for slicing?
9: */
10: @nonthreadsafe
11: class FileMessageSet private[kafka](@volatile var file: File,
12: private[log] val channel: FileChannel,
13: private[log] val start: Int,
14: private[log] val end: Int,
15: isSlice: Boolean) extends MessageSet with Logging {...}
OffsetIndex
Segment的index文件， 这是0.8后加上的，之前message直接使用物理offset标识
新版本中还是改成了使用逻辑offset，让物理地址对用户透明， 这样就需要一个index来匹配逻辑offset和物理地址
index考虑到效率，最好放在内存中，但是考虑到size问题， 所以使用MappedByteBuffer（参考，Java RandomAccessFile用法 ）
注释里面说，
Index是sparse的，不保证每个message在index都有索引的entry
Index由entry组成，每个entry为8-byte，逻辑offset4-byte，物理地址4-byte
并且逻辑offset是基于base offset的相对offset，否则无法保证只使用4-byte
1: /**
2: * An index that maps offsets to physical file locations for a particular log segment. This index may be sparse:
3: * that is it may not hold an entry for all messages in the log.
4: *
5: * The index is stored in a file that is pre-allocated to hold a fixed maximum number of 8-byte entries.
6: *
7: * The index supports lookups against a memory-map of this file. These lookups are done using a simple binary search variant
8: * to locate the offset/location pair for the greatest offset less than or equal to the target offset.
9: *
10: * Index files can be opened in two ways: either as an empty, mutable index that allows appends or
11: * an immutable read-only index file that has previously been populated. The makeReadOnly method will turn a mutable file into an
12: * immutable one and truncate off any extra bytes. This is done when the index file is rolled over.
13: *
14: * No attempt is made to checksum the contents of this file, in the event of a crash it is rebuilt.
15: *
16: * The file format is a series of entries. The physical format is a 4 byte "relative" offset and a 4 byte file location for the
17: * message with that offset. The offset stored is relative to the base offset of the index file. So, for example,
18: * if the base offset was 50, then the offset 55 would be stored as 5. Using relative offsets in this way let's us use
19: * only 4 bytes for the offset.
20: *
21: * The frequency of entries is up to the user of this class.
22: *
23: * All external APIs translate from relative offsets to full offsets, so users of this class do not interact with the internal
24: * storage format.
25: */
26: class OffsetIndex(@volatile var file: File, val baseOffset: Long, val maxIndexSize: Int = -1) extends Logging {
27: private val lock = new ReentrantLock //操作index文件需要加锁
28:
29: /* initialize the memory mapping for this index */
30: private var mmap: MappedByteBuffer = //使用MappedByteBuffer来操作index文件以应对大文件
31: {
32: val newlyCreated = file.createNewFile()
33: val raf = new RandomAccessFile(file, "rw")
34: val len = raf.length()
35: val idx = raf.getChannel.map(FileChannel.MapMode.READ_WRITE, 0, len)
36: }
37:
38: //通过byte偏移从buffer中读出某个entry的内容，offset和physical地址
39: /* return the nth offset relative to the base offset */
40: private def relativeOffset(buffer: ByteBuffer, n: Int): Int = buffer.getInt(n * 8)
41: /* return the nth physical position */
42: private def physical(buffer: ByteBuffer, n: Int): Int = buffer.getInt(n * 8 + 4)
43:
44: //通过二分查找找到targetOffset或最接近的offset（less than）
45: /**
46: * Find the largest offset less than or equal to the given targetOffset
47: * and return a pair holding this offset and it's corresponding physical file position.
48: *
49: * @param targetOffset The offset to look up.
50: *
51: * @return The offset found and the corresponding file position for this offset.
52: * If the target offset is smaller than the least entry in the index (or the index is empty),
53: * the pair (baseOffset, 0) is returned.
54: */
55: def lookup(targetOffset: Long): OffsetPosition = {...}
56:
57: /**
58: * Get the nth offset mapping from the index
59: * @param n The entry number in the index
60: * @return The offset/position pair at that entry
61: */
62: def entry(n: Int): OffsetPosition = {
63: maybeLock(lock) {
64: if(n >= entries)
65: throw new IllegalArgumentException("Attempt to fetch the %dth entry from an index of size %d.".format(n, entries))
66: val idx = mmap.duplicate
67: OffsetPosition(relativeOffset(idx, n), physical(idx, n))
68: }
69: }
70:
71: /**
72: * Append an entry for the given offset/location pair to the index. This entry must have a larger offset than all subsequent entries.
73: */
74: def append(offset: Long, position: Int) {
75: inLock(lock) {
76: require(!isFull, "Attempt to append to a full index (size = " + size + ").")
77: if (size.get == 0 || offset > lastOffset) {
78: debug("Adding index entry %d => %d to %s.".format(offset, position, file.getName))
79: this.mmap.putInt((offset - baseOffset).toInt)
80: this.mmap.putInt(position)
81: this.size.incrementAndGet()
82: this.lastOffset = offset
83: require(entries * 8 == mmap.position, entries + " entries but file position in index is " + mmap.position + ".")
84: } else {
85: throw new InvalidOffsetException("Attempt to append an offset (%d) to position %d no larger than the last offset appended (%d) to %s."
86: .format(offset, entries, lastOffset, file.getAbsolutePath))
87: }
88: }
89: }
具体看看如何从逻辑offset转化为物理地址的？
0.8中增加了逻辑offset，那么就需要做逻辑offset和物理地址间的转化
简单的方法，直接用hashmap，cache所有offset，问题就是这样空间耗费比较大
所以kafka的方式，是分段索引，用offset通过二分查找中index中找出段的起始地址，然后再去file里面遍历找出精确的地址， 时间换空间的设计
1. LogSegment.translateOffset
首先是从index文件中找到近似的物理地址
前面说了，index中从效率考虑并不会为每个offset建立索引entry，只会分段建立offset索引， 所以从index中直接可以找到精确物理地址的概率不大，但是可以找到最接近的那个物理地址
如果你觉得index的粒度比较粗，可以直接给出开始查找的startingFilePosition
所以精确的物理地址需要到MessageSet文件里面去继续找
/**
* Find the physical file position for the first message with offset >= the requested offset.
*
* The lowerBound argument is an optimization that can be used if we already know a valid starting position
* in the file higher than the greast-lower-bound from the index.
*
* @param offset The offset we want to translate
* @param startingFilePosition A lower bound on the file position from which to begin the search. This is purely an optimization and
* when omitted, the search will begin at the position in the offset index.
*
* @return The position in the log storing the message with the least offset >= the requested offset or null if no message meets this criteria.
*/
@threadsafe
private[log] def translateOffset(offset: Long, startingFilePosition: Int = 0): OffsetPosition = {
val mapping = index.lookup(offset) //从index查出近似物理地址
log.searchFor(offset, max(mapping.position, startingFilePosition))
}
2. FileMessageSet.searchFor
在messageSet中，message的构成是，overhead（MessageSize+Offset）和message
而searchFor的逻辑是从startingPosition开始， 逐条遍历各个message，并从overhead中取出offset进行比较，直到找到target offset为止
/**
* Search forward for the file position of the last offset that is greater than or equal to the target offset
* and return its physical position. If no such offsets are found, return null.
* @param targetOffset The offset to search for.
* @param startingPosition The starting position in the file to begin searching from.
*/
def searchFor(targetOffset: Long, startingPosition: Int): OffsetPosition = {
var position = startingPosition
val buffer = ByteBuffer.allocate(MessageSet.LogOverhead) // LogOverhead = MessageSizeLength + OffsetLength
val size = sizeInBytes()
while(position + MessageSet.LogOverhead < size) { //从postion开始逐条遍历
buffer.rewind()
channel.read(buffer, position)
buffer.rewind()
val offset = buffer.getLong()
if(offset >= targetOffset) //判断是否找到offset
return OffsetPosition(offset, position)
val messageSize = buffer.getInt()
position += MessageSet.LogOverhead + messageSize //递进到下个message
}
null
}
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