日志重播分析

 

Hbase的日志重播分为启动时的日志重播与rs下线时的日志重播操作。

 

通过hbase.master.distributed.log.replay来控制日志的split是在region的reopen前执行还是reopen后执行

 

如果是true表示在reopen后执行,否则相反

 

 

Rs下线时的日志重播分析

 

master监听下线

 

master通过RegionServerTracker监听rs在zk上的节点，当节点被删除时(rs下线)。触发nodeDeleted

 

publicvoidnodeDeleted(String path) {

 

if (path.startsWith(watcher.rsZNode)) {

 

解析出zk中rs路径下的rs名称，并解析成ServerName实例。

 

String serverName = ZKUtil.getNodeName(path);

 

....................此处部分日志打印信息没有显示

 

ServerName sn = ServerName.parseServerName(serverName);

 

如果下线的rs在ServerManager的onlineServers中已经不包含，不做处理，

 

if (!serverManager.isServerOnline(sn)) {

 

....................此处部分日志打印信息没有显示

 

return;

 

}

 

从RegionServerTracker.onlineServers列表中移出此rs

 

remove(sn);

 

执行ServerManager.expireServer进行下线处理

 

this.serverManager.expireServer(sn);

 

}

 

}

 

执行ServerManager.expireServer进行下线处理

 

publicsynchronizedvoidexpireServer(final ServerName serverName) {

 

....................此处部分代码没有显示

 

 

 

把rs添加到deadservers列表中。

 

this.deadservers.add(serverName);

 

从onlineServers列表中移出此rs

 

this.onlineServers.remove(serverName);

 

synchronized (onlineServers) {

 

onlineServers.notifyAll();

 

}

 

从rsAdmins(对rs进行RPC调用的接口实现类)容器中移出此rs

 

this.rsAdmins.remove(serverName);

 

....................此处部分代码没有显示

 

 

 

检查此rs中是否包含meta的region，如果是，执行MetaServerShutdownHandler.否则执行ServerShutdownHandler

 

booleancarryingMeta = services.getAssignmentManager().isCarryingMeta(serverName);

 

if (carryingMeta) {

 

this.services.getExecutorService().submit(newMetaServerShutdownHandler(this.master,

 

this.services, this.deadservers, serverName));

 

} else {

 

this.services.getExecutorService().submit(newServerShutdownHandler(this.master,

 

this.services, this.deadservers, serverName, true));

 

}

 

....................此处部分日志打印没有显示

 

}

 

 

MetaServerShutdownHandler.process方法处理流程:

 

 

 

publicvoidprocess() throws IOException {

 

booleangotException = true;

 

try {

 

AssignmentManager am = this.services.getAssignmentManager();

 

try {

 

检查是否需要做hlog的split，生成此实例时，shouldSplitHlog的值为true

 

if (this.shouldSplitHlog) {

 

LOG.info("Splitting hbase:meta logs for " + serverName);

 

 

 

检查hbase.master.distributed.log.replay配置是否设置为true,默认值为false

 

if (this.distributedLogReplay) {

 

 

 

先对meta region执行prepareLogReplay处理。

 

见MasterFileSystem.prepareLogReplay分析

 

Set<HRegionInfo> regions = newHashSet<HRegionInfo>();

 

regions.add(HRegionInfo.FIRST_META_REGIONINFO);

 

this.services.getMasterFileSystem().prepareLogReplay(serverName, regions);

 

} else {

 

 

 

否则在没有配置distributedLogReplay时，执行splitMetaLog对rs的日志进行split,等待split完成

 

见MasterFileSystem.splitMetaLog分析

 

this.services.getMasterFileSystem().splitMetaLog(serverName);

 

}

 

 

 

从AssignmentManager.RegionStates.lastAssignments中移出meta region的分配。

 

am.getRegionStates().logSplit(HRegionInfo.FIRST_META_REGIONINFO);

 

}

 

} catch (IOException ioe) {

 

....................此处部分代码没有显示

 

}

 

 

 

// Assign meta if we were carrying it.

 

// Check again: region may be assigned to other where because of RIT

 

// timeout

 

检查此server上还没有完成region open操作(regionInTransition还在)如果包含有meta region,

 

if (am.isCarryingMeta(serverName)) {

 

LOG.info("Server " + serverName + " was carrying META. Trying to assign.");

 

更新RegionStates中此region的状态为offline

 

从regionsInTransition中移出此region,

 

从serverHoldings中移出此server中meta region的分配信息

 

从regionAssignments中移出此meta region的分配信息

 

从regionsToReopen中移出此meta region

 

从regionPlans中移出此meta region

 

am.regionOffline(HRegionInfo.FIRST_META_REGIONINFO);

 

等待meta region的分配,

 

通过hbase.catalog.verification.retries配置meta region分配的重试次数,默认10次

 

通过hbase.catalog.verification.timeout配置每次分配重试的间隔时间,默认1000ms

 

verifyAndAssignMetaWithRetries();

 

 

 

如果meta在zk中的地址过期数据被删除,重新执行meta的分配,并等待meta分配完成

 

} elseif (!this.services.getCatalogTracker().isMetaLocationAvailable()) {

 

// the meta location as per master is null. This could happen in case when meta assignment

 

// in previous run failed, while meta znode has been updated to null. We should try to

 

// assign the meta again.

 

如果meta region在zk中的地址没有注册的数据,执行meta region的分配,并等待分配结束

 

通过hbase.catalog.verification.retries配置meta region分配的重试次数,默认10次

 

通过hbase.catalog.verification.timeout配置每次分配重试的间隔时间,默认1000ms

 

verifyAndAssignMetaWithRetries();

 

} else {

 

LOG.info("META has been assigned to otherwhere, skip assigning.");

 

}

 

 

 

try {

 

如果distributedLogReplay配置为true,等待region replay的regionintranstion事务完成

 

也就是RegionStates.regionsInTransition中不在包含此meta region的regionintransition

 

region replay的等待超时通过hbase.master.log.replay.wait.region.timeout配置，默认为15000ms

 

如果在超时的时间内没有完成regionintransition时，此方法返回false

 

if (this.shouldSplitHlog && this.distributedLogReplay) {

 

if (!am.waitOnRegionToClearRegionsInTransition(HRegionInfo.FIRST_META_REGIONINFO,

 

regionAssignmentWaitTimeout)) {

 

....................此处部分代码没有显示

 

}

 

 

 

执行log split,并等待split完成,如果是distributedLogReplay时，

 

此时region assign已经完成,开始splt log

 

见MasterFileSystem.splitMetaLog分析

 

this.services.getMasterFileSystem().splitMetaLog(serverName);

 

}

 

} catch (Exception ex) {

 

....................此处部分代码没有显示

 

}

 

 

 

gotException = false;

 

} finally {

 

if (gotException){

 

// If we had an exception, this.deadServers.finish will be skipped in super.process()

 

this.deadServers.finish(serverName);

 

}

 

}

 

执行此rs中非meta region的日志重播与region assign，

 

见ServerShutdownHandler.process方法处理流程

 

super.process();

 

}

 

 

 

 

 

MasterFileSystem.prepareLogReplay分析

 

 

 

此方法在hbase.master.distributed.log.replay配置为true时,分执行此操作

 

 

 

public void prepareLogReplay(ServerName serverName, Set<HRegionInfo> regions) throws IOException {

 

一些必要的检查,检查是否设置有日志的分布式replay模式,要进行分布式日志的region列表是否为空

 

if (!this.distributedLogReplay) {

 

return;

 

}

 

// mark regions in recovering state

 

if (regions == null || regions.isEmpty()) {

 

return;

 

}

 

try {

 

通过SplitLogManager.markRegionsRecoveringInZK在/hbase/recovering-regions中添加region路径

 

this.splitLogManager.markRegionsRecoveringInZK(serverName, regions);

 

} catch (KeeperExceptione) {

 

thrownewIOException(e);

 

}

 

}

 

 

 

执行distributedLogReplay

 

void markRegionsRecoveringInZK(final ServerName serverName, Set<HRegionInfo> userRegions)

 

throws KeeperException {

 

一些必要的检查,检查是否设置有日志的分布式replay模式,要进行分布式日志的region列表是否为空

 

if (userRegions == null || !this.distributedLogReplay) {

 

return;

 

}

 

 

 

try {

 

this.recoveringRegionLock.lock();

 

// mark that we're creating recovering znodes

 

更新SplitLogManager中最后一次recoveringnode的时间为当前时间

 

this.lastRecoveringNodeCreationTime = EnvironmentEdgeManager.currentTimeMillis();

 

 

 

开始迭代执行要replay的每一个region,如果是meta region,此时只有一个迭代

 

for (HRegionInfo region : userRegions) {

 

String regionEncodeName = region.getEncodedName();

 

得到hbase.splitlog.zk.retries配置的在zk中创建子路径的最大重试次数,默认为3

 

longretries = this.zkretries;

 

 

 

do {

 

在zookeeper.znode.recovering.regions配置的路径下生成一个通过region name为名称的子路径

 

默认为/hbase/recovering-regions/region-name

 

String nodePath = ZKUtil.joinZNode(watcher.recoveringRegionsZNode, regionEncodeName);

 

longlastRecordedFlushedSequenceId = -1;

 

try {

 

得到region中的最大的seqid,此seqid在ServerManager.flushedSequenceIdByRegion中存储,

 

记录着region中flush的最大的seqid

 

longlastSequenceId = this.master.getServerManager().getLastFlushedSequenceId(

 

regionEncodeName.getBytes());

 

....................此处部分代码没有显示

 

 

 

 

 

检查在zk中的recovering-regions中是否已经包含此region,

 

byte[] data = ZKUtil.getData(this.watcher, nodePath);

 

if (data == null) {

 

如果recovering-regions中还不包含此region的replay信息,

 

把region的最后一次flush的seqid写入到replay路径下

 

ZKUtil.createSetData(this.watcher, nodePath,

 

ZKUtil.positionToByteArray(lastSequenceId));

 

} else {

 

如果recovering-regions中已经包含有此region的replay信息,

 

得到上一次region的recovering的seqid,

 

如果上一次的seqid小于当前region的最后一次flush的seqid,更新zk中此region的replay的seqid为最新的seqid

 

否则不做修改(上一次flush的seqid比记录的flush的seqid更加的新)

 

lastRecordedFlushedSequenceId = SplitLogManager.parseLastFlushedSequenceIdFrom(data);

 

if (lastRecordedFlushedSequenceId < lastSequenceId) {

 

// update last flushed sequence id in the region level

 

ZKUtil.setData(this.watcher, nodePath, ZKUtil.positionToByteArray(lastSequenceId));

 

}

 

}

 

// go one level deeper with server name

 

在recovering-regions/region-name下生成当前下线的server子路径

 

nodePath = ZKUtil.joinZNode(nodePath, serverName.getServerName());

 

如果当前region的flush的seqid小于上一次的recovering中replay的seqid,

 

(上一次flush的seqid比记录的flush的seqid更加的新),更新region的last flush seqid为上一次的seqid

 

if (lastSequenceId <= lastRecordedFlushedSequenceId) {

 

// the newly assigned RS failed even before any flush to the region

 

lastSequenceId = lastRecordedFlushedSequenceId;

 

}

 

 

 

在/hbase/recovering-regions/region-name/server-name路径下记录最后一次flush的seqid.

 

ZKUtil.createSetData(this.watcher, nodePath,

 

ZKUtil.regionSequenceIdsToByteArray(lastSequenceId, null));

 

 

 

....................此处部分代码没有显示

 

break;

 

} catch (KeeperExceptione) {

 

....................此处部分代码没有显示

 

}

 

} while ((--retries) > 0 && (!this.stopper.isStopped()));

 

}

 

} finally {

 

this.recoveringRegionLock.unlock();

 

}

 

}

 

 

 

 

 

MasterFileSystem.splitMetaLog分析

 

splitMetaLog传入需要执行split操作的server(下线的server),方法去调用splitLog方法，

 

由于此时只针对meta region的hlog时行split,因此在splitLog方法时传入META_FILTER来区分是否meta split

 

 

 

public void splitLog(final Set<ServerName> serverNames, PathFilter filter) throws IOException {

 

longsplitTime = 0, splitLogSize = 0;

 

从/hbase/WALs的日志路径下得到通过下线的servers命名的所有日志路径,老版本中.logs目录

 

如：/hbase/WALs/server-name1

 

并把下线的server路径名称更新为/hbase/WALs/server-name1-splitting路径

 

List<Path> logDirs = getLogDirs(serverNames);

 

把下线的所有rs server添加到SplitLogManager.deadWorkers中，

 

等待SplitLogManager.TimeoutMonitor线程定期去处理,

 

见SplitLogManager.TimeoutMonitor线程分析

 

splitLogManager.handleDeadWorkers(serverNames);

 

splitTime = EnvironmentEdgeManager.currentTimeMillis();

 

执行hlog split操作，见SplitLogManager.splitLogDistributed分析

 

splitLogSize = splitLogManager.splitLogDistributed(serverNames, logDirs, filter);

 

splitTime = EnvironmentEdgeManager.currentTimeMillis() - splitTime;

 

 

 

....................此处部分代码没有显示,监控信息

 

}

 

 

 

 

 

MasterFileSystem.splitLog分析

 

splitLog传入需要执行split操作的server(下线的server),方法去调用splitLog方法，

 

由于此时只针对非meta region的hlog时行split,

 

因此在splitLog方法时传入NON_META_FILTER来区分是否非meta split

 

 

 

public void splitLog(final Set<ServerName> serverNames, PathFilter filter) throws IOException {

 

longsplitTime = 0, splitLogSize = 0;

 

从/hbase/WALs的日志路径下得到通过下线的servers命名的所有日志路径,老版本中.logs目录

 

如：/hbase/WALs/server-name1

 

并把下线的server路径名称更新为/hbase/WALs/server-name1-splitting路径

 

List<Path> logDirs = getLogDirs(serverNames);

 

把下线的所有rs server添加到SplitLogManager.deadWorkers中，

 

等待SplitLogManager.TimeoutMonitor线程定期去处理,

 

见SplitLogManager.TimeoutMonitor线程分析

 

splitLogManager.handleDeadWorkers(serverNames);

 

splitTime = EnvironmentEdgeManager.currentTimeMillis();

 

执行hlog split操作，见SplitLogManager.splitLogDistributed分析

 

splitLogSize = splitLogManager.splitLogDistributed(serverNames, logDirs, filter);

 

splitTime = EnvironmentEdgeManager.currentTimeMillis() - splitTime;

 

 

 

....................此处部分代码没有显示,监控信息

 

}

 

 

 

 

 

 

 

SplitLogManager.splitLogDistributed分析

 

 

 

此方法主要用于对server hlog根据region进行split操作，生成split task，并等待split完成。

 

public long splitLogDistributed(final Set<ServerName> serverNames, final List<Path> logDirs,

 

PathFilterfilter) throws IOException {

 

 

 

....................此处部分代码没有显示,监控信息,日志信息

 

 

 

得到/hbase/WALs/server-name-splitting下的所有日志文件,

 

如果传入的filter为META_FILTER,那么只获取.meta的hlog文件,否则获取全部hlog文件

 

 

 

FileStatus[] logfiles = getFileList(logDirs, filter);

 

 

 

....................此处部分代码没有显示,监控信息,日志信息

 

 

 

longtotalSize = 0;

 

TaskBatch batch = newTaskBatch();

 

Boolean isMetaRecovery = (filter == null) ? null : false;

 

for (FileStatus lf : logfiles) {

 

 

 

....................此处部分代码没有显示,监控信息,日志信息

 

 

 

totalSize += lf.getLen();

 

得到日志文件路径去掉/hbase的部分名称，如/WALs/server-name-splitting/aaa.meta

 

 

 

String pathToLog = FSUtils.removeRootPath(lf.getPath(), conf);

 

 

 

1.把hlog的全路径去掉/hbase部分通过URLEncoder.encode进行转码(/会被转换成%2F)

 

2.把hlog的全路径添加到zookeeper.znode.splitlog配置的路径下默认为splitWAL，作为其子路径存在。

 

3.在SplitLogManager.tasks中添加一个Task实例,key为2中zk生成的path，value为生成的Task实例,

 

设置Task的status为IN_PROGRESS，并把task的batch实例为上面生成的TaskBatch实例(batch),

 

把batch中的installed加一，表示增加一个批量执行的Task

 

4.根据hbase.splitlog.zk.retries配置的zk重试次数,默认为3，

 

生成SplitLogTask实例，设置其originServer为master的ServerName

 

设置其state为ZooKeeperProtos.SplitLogTask.State.UNASSIGNED

 

在zk中注册此地址,并把SplitLogTask写入到此zk的路径下。

 

5.regionserver中监听zk的splitWAL的路径，

 

见regionserver中处理splitlog

 

6.master中通过SplitLogManager.nodeDataChanged来监听rs中SplitLogTask的状态修改。

 

见SplitLogManager.nodeDataChanged分析

 

 

 

if (!enqueueSplitTask(pathToLog, batch)) {

 

thrownewIOException("duplicate log split scheduled for " + lf.getPath());

 

}

 

}

 

 

 

等待split操作完成,

 

a.batch中所有的Task.status为TerminationStatus.IN_PROGRESS的task个数为0

 

b.splitWAL路径下的所有子路径的个数为0

 

c.每次迭代都需要等待batch被nodeDataChanged或者其它地方对batch进行notify

 

 

 

waitForSplittingCompletion(batch, status);

 

// remove recovering regions from ZK

 

if (filter == MasterFileSystem.META_FILTER/* reference comparison */) {

 

....................此处部分代码没有显示,日志信息

 

isMetaRecovery = true;

 

}

 

 

 

删除zk的recovering-regions下对应的region路径下传入的servers子路径

 

(如果region下所有的servers子路径不存在,直接删除region子路径)

 

如果isMetaRecovery等于true表示只删除meta region的recovering路径

 

this.removeRecoveringRegionsFromZK(serverNames, isMetaRecovery);

 

 

 

如果有日志split出现错误,直接throw IOException

 

if (batch.done != batch.installed) {

 

batch.isDead = true;

 

....................此处部分代码没有显示,日志信息

 

thrownewIOException(msg);

 

}

 

for(Path logDir: logDirs){

 

status.setStatus("Cleaning up log directory...");

 

try {

 

删除WALs目录下对应的server-name-splitting的日志文件。

 

if (fs.exists(logDir) && !fs.delete(logDir, false)) {

 

LOG.warn("Unable to delete log src dir. Ignoring. " + logDir);

 

}

 

} catch (IOException ioe) {

 

....................此处部分代码没有显示,日志信息

 

}

 

SplitLogCounters.tot_mgr_log_split_batch_success.incrementAndGet();

 

}

 

....................此处部分代码没有显示,监控信息,日志信息

 

returntotalSize;

 

}

 

 

 

 

 

ServerShutdownHandler.process方法处理流程:

 

ServerShutdownHandler的处理流程主要对非meta region的下线处理，region的重新分配,日志split

 

 

 

 

 

public void process() throws IOException {

 

booleanhasLogReplayWork = false;

 

final ServerName serverName = this.serverName;

 

try {

 

....................此处部分代码没有显示

 

 

 

AssignmentManager am = services.getAssignmentManager();

 

if (isCarryingMeta() // hbase:meta

 

|| !am.isFailoverCleanupDone()) {

 

this.services.getServerManager().processDeadServer(serverName, this.shouldSplitHlog);

 

return;

 

}

 

 

 

....................此处部分代码没有显示

 

 

 

NavigableMap<HRegionInfo, Result> hris = null;

 

while (!this.server.isStopped()) {

 

try {

 

从meta表中进行scan,扫描出当前下线的regionserver中所有的user region 列表。

 

this.server.getCatalogTracker().waitForMeta();

 

hris = MetaReader.getServerUserRegions(this.server.getCatalogTracker(),

 

this.serverName);

 

break;

 

} catch (InterruptedException e) {

 

Thread.currentThread().interrupt();

 

thrownewIOException("Interrupted", e)

 

} catch (IOException ioe) {

 

....................此处部分代码没有显示

 

}

 

}

 

if (this.server.isStopped()) {

 

thrownewIOException("Server is stopped");

 

}

 

 

 

try {

 

shouldSplitHlog在ServerShutdownHandler实例生成时默认为true

 

if (this.shouldSplitHlog) {

 

LOG.info("Splitting logs for " + serverName + " before assignment.");

 

 

 

检查hbase.master.distributed.log.replay配置是否设置为true,默认值为false

 

 

 

if (this.distributedLogReplay) {

 

LOG.info("Mark regions in recovery before assignment.");

 

Set<ServerName> serverNames = newHashSet<ServerName>();

 

serverNames.add(serverName);

 

如果设置有distributedLogReplay，执行log split的预处理,

 

见MasterFileSystem.prepareLogReplay分析

 

this.services.getMasterFileSystem().prepareLogReplay(serverNames);

 

} else {

 

如果没有设置distributedLogReplay，执行log split,并等待split完成

 

见MasterFileSystem.splitLog分析

 

this.services.getMasterFileSystem().splitLog(serverName);

 

}

 

从RegionStates.lastAssignments中移出此server对应的所有region分配信息

 

从RegionStates.processedServers中移出超出时间限制的

 

通过hbase.master.maximum.logsplit.keeptime配置的时间的server,默认为7200000ms(2 hour)

 

am.getRegionStates().logSplit(serverName);

 

} else {

 

LOG.info("Skipping log splitting for " + serverName);

 

}

 

} catch (IOException ioe) {

 

resubmit(serverName, ioe);

 

}

 

....................此处部分代码没有显示

 

 

 

1.从AssignmentManager.regionPlans中移出包含此server的region plan,

 

2.从regionStates.serverHoldings中得到此server所有的region assign,

 

如果region的状态为online/splitting/merging,把region的状态设置为offline

 

并从regionsInTransition与regionAssignments移出这些个region.

 

如果region的状态为splitting/merging时，删除region在zk中region-in-transition的注册信息

 

3.从regionsInTransition中找到所有此server中transition的

 

状态为PENDING_OPEN/OPENING/FAILED_OPEN/FAILED_CLOSE/OFFLINE的region,并返回

 

4.根据3返回的在regionsInTransition中的region,删除region在zk中region-in-transition的注册信息

 

zk中的路径通过zookeeper.znode.unassigned进行配置。

 

5.注意：3中返回的region是当前下线的server在assignments中不包含的,

 

同时在regionInTransition又包含,也就是这些个region准备在当前下线的server上启动,

 

但此时这个server挂掉了。此方法的主要作用是删除掉当前下线server中正在做transition的region的zk信息,

 

把这些个region的状态设置为offline,等待下面的代码逻辑重新执行分配.

 

 

 

List<HRegionInfo> regionsInTransition = am.processServerShutdown(serverName);

 

 

 

....................此处部分代码没有显示

 

 

 

把上面得到的正在做transition的regions添加到待分配的region列表中

 

 

 

List<HRegionInfo> toAssignRegions = newArrayList<HRegionInfo>();

 

toAssignRegions.addAll(regionsInTransition);

 

 

 

// Iterate regions that were on this server and assign them

 

if (hris != null) {

 

RegionStates regionStates = am.getRegionStates();

 

 

 

迭代从meta表中得到的所有当前下线server的user region,

 

 

 

for (Map.Entry<HRegionInfo, Result> e: hris.entrySet()) {

 

HRegionInfo hri = e.getKey();

 

 

 

如果此region在transition中已经包含,重新迭代下一次

 

 

 

if (regionsInTransition.contains(hri)) {

 

continue;

 

}

 

String encodedName = hri.getEncodedName();

 

Locklock = am.acquireRegionLock(encodedName);

 

try {

 

RegionState rit = regionStates.getRegionTransitionState(hri);

 

 

 

检查region所在的table是否被删除/是否是disable的table,如果不是执行如下流程

 

 

 

if (processDeadRegion(hri, e.getValue(), am, server.getCatalogTracker())) {

 

ServerName addressFromAM = regionStates.getRegionServerOfRegion(hri);

 

if (addressFromAM != null && !addressFromAM.equals(this.serverName)) {

 

....................此处部分代码没有显示

 

continue;

 

}

 

if (rit != null) {

 

if (rit.getServerName() != null && !rit.isOnServer(serverName)) {

 

....................此处部分代码没有显示

 

continue;

 

}

 

try{

 

....................此处部分代码没有显示

 

 

 

删除region在zk中region-in-transition的注册信息,zk中的路径通过zookeeper.znode.unassigned进行配置,

 

并更新region的状态为offline

 

 

 

ZKAssign.deleteNodeFailSilent(services.getZooKeeper(), hri);

 

regionStates.updateRegionState(hri, State.OFFLINE);

 

} catch (KeeperExceptionke) {

 

this.server.abort("Unexpected ZK exception deleting unassigned node " + hri, ke);

 

return;

 

}

 

} elseif (regionStates.isRegionInState(

 

hri, State.SPLITTING_NEW, State.MERGING_NEW)) {

 

如果region的状态是准备split或者准备merge时，重新设置region状态为offline

 

regionStates.regionOffline(hri);

 

}

 

 

 

添加此region到待分配的region列表中

 

 

 

toAssignRegions.add(hri);

 

 

 

} elseif (rit != null) {

 

region所在的table现在是disable的table,设置region状态为offline,

 

a.如果region在zk中的eventType为M_ZK_REGION_CLOSING/RS_ZK_REGION_CLOSED,从zk中删除此region的路径

 

zk中region-in-transition的注册信息,zk中的路径通过zookeeper.znode.unassigned进行配置

 

b.如果region在zk中的eventtype为RS_ZK_REGION_CLOSED/M_ZK_REGION_OFFLINE，从zk中删除此region的路径

 

if (rit.isPendingCloseOrClosing()

 

&& am.getZKTable().isDisablingOrDisabledTable(hri.getTable())) {

 

....................此处部分代码没有显示

 

regionStates.updateRegionState(hri, State.OFFLINE);

 

am.deleteClosingOrClosedNode(hri, rit.getServerName());

 

am.offlineDisabledRegion(hri);

 

} else {

 

LOG.warn("THIS SHOULD NOT HAPPEN: unexpected region in transition "

 

+ rit + " not to be assigned by SSH of server " + serverName);

 

}

 

}

 

} finally {

 

lock.unlock();

 

}

 

}

 

}

 

 

 

try {

 

执行region的批量assign操作

 

am.assign(toAssignRegions);

 

} catch (InterruptedException ie) {

 

LOG.error("Caught " + ie + " during round-robin assignment");

 

thrownewIOException(ie);

 

}

 

 

 

if (this.shouldSplitHlog && this.distributedLogReplay) {

 

// wait for region assignment completes

 

for (HRegionInfo hri : toAssignRegions) {

 

try {

 

此处只能是distributedLogReplay设置为true时，因为这时rs中不做log replay,

 

distributedLogReplay设置为true时,region下不存在recovered.edits路径,因此openregion时replay不会执行,

 

所以此时等待region的open完成是可行的。等待每一个region的assign完成,

 

也就是assign时的RegionInTransition在RegionStates.regionsInTransition的处理完成(列表中不包含此region)

 

或者说等待分配的超时时间hbase.master.log.replay.wait.region.timeout过期,默认15000ms

 

在assign时会在zk中的region-in-transition注册一个region地址,等待rs处理,

 

此方法会不停止的迭代,直接timeout或者regionsInTransition中移出此region的transition,

 

每次迭代会让regionstates处于wait状态，等待AssignmentManager.nodeDataChanged/nodeDeleted对其notify

 

完成后通过AssignmentManager中的相关nodeDataChanged处理事件方法对regionsInTransition更新，

 

通过nodeDeleted处理事件对regionsInTransition移出

 

if (!am.waitOnRegionToClearRegionsInTransition(hri, regionAssignmentWaitTimeout)) {

 

// Wait here is to avoid log replay hits current dead server and incur a RPC timeout

 

// when replay happens before region assignment completes.

 

LOG.warn("Region " + hri.getEncodedName()

 

+ " didn't complete assignment in time");

 

}

 

} catch (InterruptedException ie) {

 

thrownewInterruptedIOException("Caught " + ie

 

+ " during waitOnRegionToClearRegionsInTransition");

 

}

 

}

 

// submit logReplay work

 

如果设置distributedLogReplay为true，此时region assign完成,执行log split,并等待split完成

 

见MasterFileSystem.splitLog分析

 

this.services.getExecutorService().submit(

 

newLogReplayHandler(this.server, this.services, this.deadServers, this.serverName));

 

hasLogReplayWork = true;

 

}

 

} finally {

 

this.deadServers.finish(serverName);

 

}

 

 

 

if (!hasLogReplayWork) {

 

LOG.info("Finished processing of shutdown of " + serverName);

 

}

 

}

 

 

 

 

 

regionserver中处理splitlog

 

regionserver中通过regionserver启动时启动的SplitLogWorker线程,

 

通过其的run方法监听master在zk中生成splitWAL，一但master在zk中注册splitWAL路径成功,

 

执行taskLoop方法默认5s进行一次split log的检查(线程等待,timeout为5000ms),

 

通过nodeChildrenChanged来监听zk中splitWAL子路径的修改,并notify此线程,

 

通过nodeDataChanged来更新每一个SplitLogTask的状态更新，

 

 

 

 

 

publicvoidrun() {

 

try {

 

....................此处部分代码没有显示

 

 

 

// wait for master to create the splitLogZnode

 

intres = -1;

 

while (res == -1 && !exitWorker) {

 

try {

 

监听master对zk中splitWAL的注册

 

res = ZKUtil.checkExists(watcher, watcher.splitLogZNode);

 

} catch (KeeperExceptione) {

 

// ignore

 

LOG.warn("Exception when checking for " + watcher.splitLogZNode + " ... retrying", e);

 

}

 

if (res == -1) {

 

try {

 

....................此处部分代码没有显示

 

Thread.sleep(1000);

 

} catch (InterruptedException e) {

 

....................此处部分代码没有显示

 

exitWorker = true;

 

break;

 

}

 

}

 

}

 

 

 

if (!exitWorker) {

 

定期检查并启动执行split hlog的处理

 

taskLoop();

 

}

 

} catch (Throwable t) {

 

....................此处部分代码没有显示

 

} finally {

 

LOG.info("SplitLogWorker " + this.serverName + " exiting");

 

}

 

}

 

 

 

 

 

 

 

检查并执行split hlog

 

private void taskLoop() {

 

while (!exitWorker) {

 

intseq_start = taskReadySeq;

 

得到所有的需要进行log split的servername的路径

 

List<String> paths = getTaskList();

 

if (paths == null) {

 

LOG.warn("Could not get tasks, did someone remove " +

 

this.watcher.splitLogZNode + " ... worker thread exiting.");

 

return;

 

}

 

// pick meta wal firstly

 

首先定义一个先执行的servername hlog split的路径值,默认为随机取一个下标

 

如果要split的server中包含有meta的region，那么先从meta的server开始执行

 

intoffset = (int) (Math.random() * paths.size());

 

for(inti = 0; i < paths.size(); i ++){

 

if(HLogUtil.isMetaFile(paths.get(i))) {

 

offset = i;

 

break;

 

}

 

}

 

intnumTasks = paths.size();

 

for (inti = 0; i < numTasks; i++) {

 

计算执行顺序,从offset开始执行,如：paths.size()=6,offset=5,那么执行顺序为501234

 

intidx = (i + offset) % paths.size();

 

// don't call ZKSplitLog.getNodeName() because that will lead to

 

// double encoding of the path name

 

每一个server最大同时执行split hlog的task个数通过hbase.regionserver.wal.max.splitters配置，默认为2

 

得到现在活着的所有的regionserver列表,根据要split的server个数,

 

平均下来后计算此server最多要执行多少个splt task,

 

最多同时执行个数不超过hbase.regionserver.wal.max.splitters配置,每次执行tasksInProgress值加一

 

if (this.calculateAvailableSplitters(numTasks) > 0) {

 

如果此server还有能力执行split hlog task，

 

更新zk中splitWAL中此servername(待split)的SplitLogTask为SplitLogTask.Owned,

 

并把当前执行split的rs更新到zk中。生成HLogSplitterHandler实例，并启动线程执行此处理程序

 

把tasksInProgress的正在处理的splittask的值加一,见HLogSplitterHandler.process流程分析

 

等待500-1000ms在重新执行下一次分配,这样能保证其它的rs也能分配到任务

 

注意：此部分逻辑第一次执行此方法时不会执行，因为第一次执行时zk中splitWAL路径下可能为空,

 

直接进入下面部分，让此线程进入wait状态，等待nodeChildrenChanged来进行notify

 

grabTask(ZKUtil.joinZNode(watcher.splitLogZNode, paths.get(idx)));

 

} else {

 

LOG.debug("Current region server " + this.serverName + " has "

 

+ this.tasksInProgress.get() + " tasks in progress and can't take more.");

 

break;

 

}

 

if (exitWorker) {

 

return;

 

}

 

}

 

SplitLogCounters.tot_wkr_task_grabing.incrementAndGet();

 

synchronized (taskReadyLock) {

 

此次任务执行完成，zk中splitWAL在任务执行到此时还没有更新的rs下线被注册进来

 

while (seq_start == taskReadySeq) {

 

try {

 

线程进行等待状态，等待nodeChildrenChanged来进行notify

 

taskReadyLock.wait(checkInterval);

 

if (this.server != null) {

 

// check to see if we have stale recovering regions in our internal memory state

 

如果是设置有distributedLogReplay模式，此时在region open后才开始执行splitlog,

 

那么得到要进行splitlog的region列表。迭代每一个region，

 

从recovering-regions中检查是否此region需要splitlog,

 

如果recovering-regions中不存在此region,从rs中的recoveringRegions列表中移出此region

 

并设置此Hregion的recovering的值为false.

 

开始回到taskLoop方法的顶部，重新对这部分region进行splitlog

 

Map<String, HRegion> recoveringRegions = this.server.getRecoveringRegions();

 

if (!recoveringRegions.isEmpty()) {

 

// Make a local copy to prevent ConcurrentModificationException when other threads

 

// modify recoveringRegions

 

List<String> tmpCopy = newArrayList<String>(recoveringRegions.keySet());

 

for (String region : tmpCopy) {

 

String nodePath = ZKUtil.joinZNode(this.watcher.recoveringRegionsZNode, region);

 

try {

 

if (ZKUtil.checkExists(this.watcher, nodePath) == -1) {

 

HRegion r = recoveringRegions.remove(region);

 

if (r != null) {

 

r.setRecovering(false);

 

}

 

LOG.debug("Mark recovering region:" + region + " up.");

 

} else {

 

....................此处部分代码没有显示

 

break;

 

}

 

} catch (KeeperExceptione) {

 

....................此处部分代码没有显示

 

break;

 

}

 

}

 

}

 

}

 

} catch (InterruptedException e) {

 

....................此处部分代码没有显示

 

exitWorker = true;

 

return;

 

}

 

}

 

}

 

 

 

}

 

}

 

 

 

 

 

HlogSplitterHandler.process处理流程分析

 

HlogSplitterHandler是具体对hlog进行处理的handler,通过其传入的TaskExecutor.exec方法执行,

 

TaskExecutor是在SplitLogWorker实例生成时在构造方法中生成的一个匿名实现类,

 

 

 

public HLogSplitterHandler(final Server server, String curTask,

 

final MutableInt curTaskZKVersion,

 

CancelableProgressablereporter,

 

AtomicInteger inProgressTasks, TaskExecutorsplitTaskExecutor) {

 

设置EventType为RS_LOG_REPLAY

 

super(server, EventType.RS_LOG_REPLAY);

 

this.curTask = curTask;

 

this.wal = ZKSplitLog.getFileName(curTask);

 

this.reporter = reporter;

 

this.inProgressTasks = inProgressTasks;

 

把regionserver中执行split log 的task的值加一,表示占用一个执行位置

 

this.inProgressTasks.incrementAndGet();

 

this.serverName = server.getServerName();

 

this.zkw = server.getZooKeeper();

 

this.curTaskZKVersion = curTaskZKVersion;

 

见SplitLogWorker的构造方法最后一个参数

 

this.splitTaskExecutor = splitTaskExecutor;

 

}

 

 

 

public void process() throws IOException {

 

longstartTime = System.currentTimeMillis();

 

try {

 

执行split log的处理程序,见下面的SplitLog TaskExecutor.exec处理分析，并得到流程执行的返回状态

 

Statusstatus = this.splitTaskExecutor.exec(wal, reporter);

 

switch (status) {

 

caseDONE:

 

成功结束，调用endTask结束任务，

 

设置zk中splitWAL路径的servername中SplitLogTask的状态为SplitLogTask.Done

 

endTask(zkw, new SplitLogTask.Done(this.serverName),

 

SplitLogCounters.tot_wkr_task_done, curTask, curTaskZKVersion.intValue());

 

break;

 

casePREEMPTED:

 

如果split task是一个抢占的资源,不做处理

 

SplitLogCounters.tot_wkr_preempt_task.incrementAndGet();

 

LOG.warn("task execution prempted " + wal);

 

break;

 

caseERR:

 

执行过程错误，调用endTask结束任务,

 

设置zk中splitWAL路径的servername中SplitLogTask的状态为SplitLogTask.Err

 

if (server != null && !server.isStopped()) {

 

endTask(zkw, new SplitLogTask.Err(this.serverName),

 

SplitLogCounters.tot_wkr_task_err, curTask, curTaskZKVersion.intValue());

 

break;

 

}

 

// if the RS is exiting then there is probably a tons of stuff

 

// that can go wrong. Resign instead of signaling error.

 

//$FALL-THROUGH$

 

caseRESIGNED:

 

如果资源的task执行被放弃,调用endTask结束任务,

 

设置zk中splitWAL路径的servername中SplitLogTask的状态为SplitLogTask.Resigned

 

if (server != null && server.isStopped()) {

 

LOG.info("task execution interrupted because worker is exiting " + curTask);

 

}

 

endTask(zkw, new SplitLogTask.Resigned(this.serverName),

 

SplitLogCounters.tot_wkr_task_resigned, curTask, curTaskZKVersion.intValue());

 

break;

 

}

 

} finally {

 

LOG.info("worker " + serverName + " done with task " + curTask + " in "

 

+ (System.currentTimeMillis() - startTime) + "ms");

 

把regionserver中的split log task的值减一，表示有一个空闲的位置

 

this.inProgressTasks.decrementAndGet();

 

}

 

}

 

 

 

SplitLog TaskExecutor.exec处理分析:

 

 

 

public Status exec(String filename, CancelableProgressable p) {

 

Path rootdir;

 

FileSystemfs;

 

try {

 

rootdir = FSUtils.getRootDir(conf);

 

fs = rootdir.getFileSystem(conf);

 

} catch (IOException e) {

 

LOG.warn("could not find root dir or fs", e);

 

如果得到hdfs中/hbase目录出错或生成/hbase的FileSystem出错时,返回RESIGNED(放弃)

 

returnStatus.RESIGNED;

 

}

 

// TODO have to correctly figure out when log splitting has been

 

// interrupted or has encountered a transient error and when it has

 

// encountered a bad non-retry-able persistent error.

 

Try {

 

执行split log操作，生成一个SplitLogFile实例，并执行其splitLogFile方法，

 

方法执行返回true or false,执行过程中定期向zk中此hlog replay的路径发送心跳，如果心跳发送失败返回false

 

发送心跳的间隔通过hbase.splitlog.report.period配置，默认为hbase.splitlog.manager.timeout(120000)/3

 

发送心跳其实就是定期在zk中重新注册此servername,并得到上一次注册的version,

 

如果上一次version小于1表示 PREEMPTED（此server有资源抢占）

 

1.通过hbase.regionserver.hlog.splitlog.buffersize配置读取源hlog的buffer大小，默认为128*1024*1024

 

2.通过hbase.regionserver.hlog.splitlog.writer.threads配置OutputSink的写入线程个数

 

3.配置hbase.regionserver.wal.logreplay.batch.size，默认为64

 

4.如果distributedLogReplay设置为true,生成的OutputSink为HLogSplitter.LogReplayOutputSink/

 

否则生成HLogSplitter.LogRecoveredEditsOutputSink实例

 

5.通过hbase.hlog.split.skip.errors配置是否跳过split error,默认为false

 

6.通过hbase.splitlog.report.interval.loglines配置每次读取的行数，默认为1024

 

读取过程中如果hlog的entity的seqid小于region中的seqid或者cocovering-regions中存储的seqid,continue.

 

数据在output时，根据regionname，在regionname下创建一个recovered.edits目录，并写入hlog数据到此目录下

 

具体请参见HLogSplitter.splitLogFile方法源代码。

 

if (!HLogSplitter.splitLogFile(rootdir, fs.getFileStatus(newPath(rootdir, filename)),

 

fs, conf, p, sequenceIdChecker, watcher)) {

 

此server有资源抢占,主要是在zk上定期注册此server对hlog的split

 

returnStatus.PREEMPTED;

 

}

 

} catch (InterruptedIOException iioe) {

 

LOG.warn("log splitting of " + filename + " interrupted, resigning", iioe);

 

returnStatus.RESIGNED;

 

} catch (IOException e) {

 

Throwable cause = e.getCause();

 

if (einstanceof RetriesExhaustedException

 

&& (causeinstanceof NotServingRegionException

 

|| causeinstanceof ConnectException

 

|| causeinstanceof SocketTimeoutException)) {

 

LOG.warn("log replaying of " + filename + " can't connect to the target regionserver, "

 

+ "resigning", e);

 

returnStatus.RESIGNED;

 

} elseif (causeinstanceof InterruptedException) {

 

LOG.warn("log splitting of " + filename + " interrupted, resigning", e);

 

returnStatus.RESIGNED;

 

} elseif(causeinstanceofKeeperException) {

 

LOG.warn("log splitting of " + filename + " hit ZooKeeper issue, resigning", e);

 

returnStatus.RESIGNED;

 

}

 

LOG.warn("log splitting of " + filename + " failed, returning error", e);

 

returnStatus.ERR;

 

}

 

returnStatus.DONE;

 

}

 

}

 

 

 

 

 

SplogLogWorker.nodeDataChanged方法中监听到zk的状态修改时,如果状态不是如下状态是,调用stopTask结束线程

 

String taskpath = currentTask;

 

if (taskpath != null && taskpath.equals(path)) {

 

// have to compare data. cannot compare version because then there

 

// will be race with attemptToOwnTask()

 

// cannot just check whether the node has been transitioned to

 

// UNASSIGNED because by the time this worker sets the data watch

 

// the node might have made two transitions - from owned by this

 

// worker to unassigned to owned by another worker

 

if (! slt.isOwned(this.serverName) &&

 

! slt.isDone(this.serverName) &&

 

! slt.isErr(this.serverName) &&

 

! slt.isResigned(this.serverName)) {

 

LOG.info("task " + taskpath + " preempted from " +

 

serverName + ", current task state and owner=" + slt.toString());

 

stopTask();

 

}

 

}

 

结束线程的执行过程

 

void stopTask() {

 

LOG.info("Sending interrupt to stop the worker thread");

 

worker.interrupt(); // TODO interrupt often gets swallowed, do what else?

 

}

 

 

 

 

 

SplitLogManager.nodeDataChanged流程分析

 

regionserver中执行split log操作，并根据执行情况修改zk中splitWAL中SplitLogTask的状态。

 

SplitLogManager.nodeDataChanged在master端对zk中splitWAL进行监听，

 

从tasks列表中找到对应修改的task,把task的状态从IN_PROGRESS修改为SUCCESS,

 

设置task对应的TaskBatch的done或error的值加一。调用TaskBatch.notify方法叫醒线程的等待。

 

在waitForSplittingCompletion方法中会每执行一次检查把TaskBatch.wait，因此需要对其做notify

 

 

 

 

 

Region open数据重播分析

 

HregionServer.openRegion-->OpenRegionHandler.process-->openRegion-->

 

Hregion.openRegion-->生成HRegion实例，并调用实例的r.openHRegion(reporter)-->initialize

 

-->initializeRegionInternals-->initializeRegionStores-->replayRecoveredEditsIfAny

 

注意：日志重播时传入的每一个store中最大的seqid是不包含bluk load的hfile的seqid，

 

而region open时得到并计算next sequence id的所有store中最大的seqid是包含bluk load的hfile的seqid

 

 

 

protectedlongreplayRecoveredEditsIfAny(final Path regiondir,

 

Map<byte[], Long> maxSeqIdInStores,

 

finalCancelableProgressablereporter, finalMonitoredTaskstatus)

 

throws UnsupportedEncodingException, IOException {

 

取出所有的store中flush到磁盘上的所有store中最小的一个seqid

 

longminSeqIdForTheRegion = -1;

 

for (Long maxSeqIdInStore : maxSeqIdInStores.values()) {

 

if (maxSeqIdInStore < minSeqIdForTheRegion || minSeqIdForTheRegion == -1) {

 

minSeqIdForTheRegion = maxSeqIdInStore;

 

}

 

}

 

longseqid = minSeqIdForTheRegion;

 

 

 

FileSystemfs = this.fs.getFileSystem();

 

取出region目录下recovered.edits子路径下所有的文件，但不包含结尾是.temp的文件,并根据文件名称排序返回

 

hlog在region下的文件名称是此文件对应的最大seqid,也就是按seqid从小到大排序。

 

NavigableSet<Path> files = HLogUtil.getSplitEditFilesSorted(fs, regiondir);

 

if (LOG.isDebugEnabled()) {

 

LOG.debug("Found " + (files == null ? 0 : files.size())

 

+ " recovered edits file(s) under " + regiondir);

 

}

 

没有需要重播的日志文件，直接返回当前所有的store中最小的seqid,如果是表示不需要进行replay

 

if (files == null || files.isEmpty()) returnseqid;

 

 

 

for (Path edits: files) {

 

检查日志文件是否存在

 

if (edits == null || !fs.exists(edits)) {

 

LOG.warn("Null or non-existent edits file: " + edits);

 

continue;

 

}

 

检查文件大小是否为空，如果是空文件直接删除,如果是表示不需要进行replay

 

if (isZeroLengthThenDelete(fs, edits)) continue;

 

 

 

longmaxSeqId = Long.MAX_VALUE;

 

String fileName = edits.getName();

 

检查此文件中最大的seqid是否小于region是所有store中最小的seqid,如果是表示此文件不需要进行replay

 

maxSeqId = Math.abs(Long.parseLong(fileName));

 

if (maxSeqId <= minSeqIdForTheRegion) {

 

if (LOG.isDebugEnabled()) {

 

String msg = "Maximum sequenceid for this log is " + maxSeqId

 

+ " and minimum sequenceid for the region is " + minSeqIdForTheRegion

 

+ ", skipped the whole file, path=" + edits;

 

LOG.debug(msg);

 

}

 

continue;

 

}

 

 

 

try {

 

得到replay的edits中每一个kv,并根据kv得到对应的store,

 

如果kv中的seqid小于store中最大的seqid，此kv不需要replay,

 

否则把kv添加到store中，得到添加的kvsize,把size添加到：

 

a.RegionServerAccounting.replayEditsPerRegion中对应的region的大小中，

 

表示此region中replay的memory使用情况

 

b.RegionServerAccounting.atomicGlobalMemstoreSize中，表示全局的memstore使用情况

 

c.添加到此region的memstore中，HRegion.memstoreSize,表示当前region的memory使用情况

 

d.检查memstore是否达到flush的值，通过hbase.hregion.memstore.flush.size配置，默认1024*1024*128L

 

如果达到memstore的flush值，对memstore进行flush

 

f.返回最新的seqid

 

seqid = replayRecoveredEdits(edits, maxSeqIdInStores, reporter);

 

} catch (IOException e) {

 

出现replay错误，检查hbase.hregion.edits.replay.skip.errors是否配置为true

 

老版本使用hbase.skip.errors进行配置，默认值为false,表示不跳过error

 

booleanskipErrors = conf.getBoolean(

 

HConstants.HREGION_EDITS_REPLAY_SKIP_ERRORS,

 

conf.getBoolean(

 

"hbase.skip.errors",

 

HConstants.DEFAULT_HREGION_EDITS_REPLAY_SKIP_ERRORS));

 

if (conf.get("hbase.skip.errors") != null) {

 

LOG.warn(

 

"The property 'hbase.skip.errors' has been deprecated. Please use " +

 

HConstants.HREGION_EDITS_REPLAY_SKIP_ERRORS + " instead.");

 

}

 

如果配置有跳过replay error，把此edits文件重命名为editsname.systime,并remove到region的根目录下

 

if (skipErrors) {

 

Path p = HLogUtil.moveAsideBadEditsFile(fs, edits);

 

LOG.error(HConstants.HREGION_EDITS_REPLAY_SKIP_ERRORS

 

+ "=true so continuing. Renamed " + edits +

 

" as " + p, e);

 

} else {

 

throwe;

 

}

 

}

 

}

 

// The edits size added into rsAccounting during this replaying will not

 

// be required any more. So just clear it.

 

把RegionServerAccounting.replayEditsPerRegion中此region对应的replay kvsize清空

 

if (this.rsAccounting != null) {

 

this.rsAccounting.clearRegionReplayEditsSize(this.getRegionName());

 

}

 

如果进行了replay,那么当前replay后的seqid一定是大于原来的store的seqid，强制对region进行flush

 

if (seqid > minSeqIdForTheRegion) {

 

// Then we added some edits to memory. Flush and cleanup split edit files.

 

internalFlushcache(null, seqid, status);

 

}

 

// Now delete the content of recovered edits. We're done w/ them.

 

删除region下所有的recovered.edits下的文件

 

for (Path file: files) {

 

if (!fs.delete(file, false)) {

 

LOG.error("Failed delete of " + file);

 

} else {

 

LOG.debug("Deleted recovered.edits file=" + file);

 

}

 

}

 

returnseqid;

 

}

 

 

 

 

 

distributedLogReplay为true的日志重播

 

通过hbase.master.distributed.log.replay配置的值为true时，在splitLog时，

 

生成HLogSplitter实例时OutputSink的实现会选择HLogSplitter.LogReplayOutputSink，

 

此实现不经过recovered.edits目录，直接把数据replay到region中。具体实现请查看相关源代码