HBase MemStore Flush由类org.apache.hadoop.hbase.regionserver.MemStoreFlusher实现,具体表现为HRegionServer中的一个实例变量cacheFlusher,类结构如下:
class MemStoreFlusher extends HasThread implements FlushRequester { ...... }
MemStoreFlusher实质是一个线程类。
HasThread可以理解为Thread的一个代码类:
/** * Abstract class which contains a Thread and delegates the common Thread * methods to that instance. * * The purpose of this class is to workaround Sun JVM bug #6915621, in which * something internal to the JDK uses Thread.currentThread() as a monitor lock. * This can produce deadlocks like HBASE-4367, HBASE-4101, etc. */ public abstract class HasThread implements Runnable { private final Thread thread; public HasThread() { this.thread = new Thread(this); } public HasThread(String name) { this.thread = new Thread(this, name); } public Thread getThread() { return thread; } public abstract void run(); // // Begin delegation to Thread public final String getName() { return thread.getName(); } public void interrupt() { thread.interrupt(); } public final boolean isAlive() { return thread.isAlive(); } public boolean isInterrupted() { return thread.isInterrupted(); } public final void setDaemon(boolean on) { thread.setDaemon(on); } public final void setName(String name) { thread.setName(name); } public final void setPriority(int newPriority) { thread.setPriority(newPriority); } public void setUncaughtExceptionHandler(UncaughtExceptionHandler eh) { thread.setUncaughtExceptionHandler(eh); } public void start() { thread.start(); } public final void join() throws InterruptedException { thread.join(); } public final void join(long millis, int nanos) throws InterruptedException { thread.join(millis, nanos); } public final void join(long millis) throws InterruptedException { thread.join(millis); } // // End delegation to Thread }
FlushRequester是一个接口,仅包含一个方法:
/** * Request a flush. */ public interface FlushRequester { /** * Tell the listener the cache needs to be flushed. * * @param region * the HRegion requesting the cache flush */ void requestFlush(HRegion region); }
核心变量
// These two data members go together. Any entry in the one must have // a corresponding entry in the other. private final BlockingQueue<FlushQueueEntry> flushQueue = new DelayQueue<FlushQueueEntry>(); private final Map<HRegion, FlushRegionEntry> regionsInQueue = new HashMap<HRegion, FlushRegionEntry>();
flushQueue:DelayQueue队列,元素类型为FlushQueueEntry,代表某一Region的Flush请求,Flusher线程不断地从该队列中获取请求信息,完成Region的Flush操作;
regionsInQueue:维护HRegion实例与请求FlushRegionEntry之间的对应关系;
如注释中所说,如果某一个FlushQueueEntry实例存在于flushQueue中,那么它必然存在于regionsInQueue中,后者看似多余,其实不然,例如,验证某一Region是否已经发起过Flush请求。
private AtomicBoolean wakeupPending = new AtomicBoolean();
wakeupPending:主要与flushQueue结合使用,flushQueue是一种阻塞队列,当队列为空时,poll操作会将线程阻塞一段时间,某些情况下需要在flushQueue中加入一个“空元素”,以唤醒线程工作,但如果线程本次操作(后面会看到Flusher线程工作实质是一个循环操作)已经被加入“空”元素,则不需要重复加入。
private final long threadWakeFrequency;
threadWakeFrequency:用于flushQueue执行poll操作时,最多等待多长时间,配置项为hbase.server.thread.wakefrequency;
private final HRegionServer server;
server:当前HRegionServer实例;
private final ReentrantLock lock = new ReentrantLock(); private final Condition flushOccurred = lock.newCondition();
lock、flushOccurred:用于同步操作,类似于synchronized、wait、signal、signalAll;
protected final long globalMemStoreLimit; protected final long globalMemStoreLimitLowMark; private static final float DEFAULT_UPPER = 0.4f; private static final float DEFAULT_LOWER = 0.35f; private static final String UPPER_KEY = "hbase.regionserver.global.memstore.upperLimit"; private static final String LOWER_KEY = "hbase.regionserver.global.memstore.lowerLimit";
globalMemStoreLimit、globalMemStoreLimitLowMark:表示HRegionServer整个MemStore的上下限值,当整个MemStore的内存消耗值达到下限值时就会采取相应的措施;
private long blockingStoreFilesNumber; private long blockingWaitTime;
blockingStoreFilesNumber:对某一Region执行Flush操作时,如果该Region中的某一Store中已有的StoreFile数目超过blockingStoreFilesNumber(hbase.hstore.compactionThreshold),则该Region的Flush操作会被最多延迟blockingWaitTime(hbase.hstore.blockingWaitTime)。
Flush请求
所有的Region Flush请求会被放到一个DelayedQueue中,因此放入该队列的元素必须实现Delayed接口:
interface FlushQueueEntry extends Delayed { }
Flush请求会被分为两种类型:“空”请求与实质请求,“空”请求主要用于唤醒线程,实质请求即为Region Flush请求。
“空”请求:
/** * Token to insert into the flush queue that ensures that the flusher does * not sleep */ static class WakeupFlushThread implements FlushQueueEntry { @Override public long getDelay(TimeUnit unit) { return 0; } @Override public int compareTo(Delayed o) { return -1; } }
“空”请求的作用主要是唤醒,不需要任何实质性的内容,且延迟时间被设为0,表示立即可从队列中获取。
实质请求:
/** * Datastructure used in the flush queue. Holds region and retry count. * Keeps tabs on how old this object is. Implements {@link Delayed}. On * construction, the delay is zero. When added to a delay queue, we‘ll come * out near immediately. Call {@link #requeue(long)} passing delay in * milliseconds before readding to delay queue if you want it to stay there * a while. */ static class FlushRegionEntry implements FlushQueueEntry { private final HRegion region; private final long createTime; private long whenToExpire; private int requeueCount = 0; FlushRegionEntry(final HRegion r) { this.region = r; this.createTime = System.currentTimeMillis(); this.whenToExpire = this.createTime; } /** * @param maximumWait * @return True if we have been delayed > <code>maximumWait</code> * milliseconds. */ public boolean isMaximumWait(final long maximumWait) { return (System.currentTimeMillis() - this.createTime) > maximumWait; } /** * @return Count of times {@link #resetDelay()} was called; i.e this is * number of times we‘ve been requeued. */ public int getRequeueCount() { return this.requeueCount; } /** * @param when * When to expire, when to come up out of the queue. Specify * in milliseconds. This method adds * System.currentTimeMillis() to whatever you pass. * @return This. */ public FlushRegionEntry requeue(final long when) { this.whenToExpire = System.currentTimeMillis() + when; this.requeueCount++; return this; } @Override public long getDelay(TimeUnit unit) { return unit.convert(this.whenToExpire - System.currentTimeMillis(), TimeUnit.MILLISECONDS); } @Override public int compareTo(Delayed other) { return Long.valueOf( getDelay(TimeUnit.MILLISECONDS) - other.getDelay(TimeUnit.MILLISECONDS)).intValue(); } @Override public String toString() { return "[flush region " + Bytes.toStringBinary(region.getRegionName()) + "]"; } }
region:表示发起Flush请求的HRegion实例;
createTime:表示Flush请求的创建时间;
whenToExpire:表示Flush请求的过期时间;
requeueCount:表示Flush请求的入队次数,因为有些Flush请求根据情况需要被延迟执行,所以需要重新入队。
构造函数
MemStoreFlusher的构造函数主要用于初始化上述这些变量,其中比较重要的是RegionServer整个MemStore内存消耗上下限值的计算:
long max = ManagementFactory.getMemoryMXBean().getHeapMemoryUsage() .getMax(); this.globalMemStoreLimit = globalMemStoreLimit(max, DEFAULT_UPPER, UPPER_KEY, conf); long lower = globalMemStoreLimit(max, DEFAULT_LOWER, LOWER_KEY, conf); if (lower > this.globalMemStoreLimit) { lower = this.globalMemStoreLimit; LOG.info("Setting globalMemStoreLimitLowMark == globalMemStoreLimit " + "because supplied " + LOWER_KEY + " was > " + UPPER_KEY); } this.globalMemStoreLimitLowMark = lower;
方法globalMemStoreLimit的相关代码如下:
/** * Calculate size using passed <code>key</code> for configured percentage of * <code>max</code>. * * @param max * @param defaultLimit * @param key * @param c * @return Limit. */ static long globalMemStoreLimit(final long max, final float defaultLimit, final String key, final Configuration c) { float limit = c.getFloat(key, defaultLimit); return getMemStoreLimit(max, limit, defaultLimit); } static long getMemStoreLimit(final long max, final float limit, final float defaultLimit) { float effectiveLimit = limit; if (limit >= 0.9f || limit < 0.1f) { LOG.warn("Setting global memstore limit to default of " + defaultLimit + " because supplied value outside allowed range of 0.1 -> 0.9"); effectiveLimit = defaultLimit; } return (long) (max * effectiveLimit); }
循环Flush操作
Flush请求的处理是在一个循环的操作中被处理的:
@Override public void run() { while (!this.server.isStopped()) { FlushQueueEntry fqe = null; try { ...... } catch (InterruptedException ex) { continue; } catch (ConcurrentModificationException ex) { continue; } catch (Exception ex) { LOG.error("Cache flusher failed for entry " + fqe, ex); if (!server.checkFileSystem()) { break; } } } this.regionsInQueue.clear(); this.flushQueue.clear(); // Signal anyone waiting, so they see the close flag lock.lock(); try { flushOccurred.signalAll(); } finally { lock.unlock(); } LOG.info(getName() + " exiting"); }
只要该HRegionServer没有被请求停止,则该操作将一直被执行,不断地从请求队列中获取具体的请求fqe,然后执行Flush操作,具体的操作被包含在一个try、catch块中。如果该HRegionServer已经被请求停止,则会清空相应的数据结构及唤醒其它被阻塞的线程。
某一Flush操作
wakeupPending.set(false); // allow someone to wake us up again fqe = flushQueue.poll(threadWakeFrequency, TimeUnit.MILLISECONDS);
从队列中获取一个Flush请求,如果此时队列为空则本线程会被阻塞直至超时,wakeupPending.set(false)则表示外界在某些条件下可以通过向队列中加入一个“空”请求(WakeupFlushThread)来唤醒被阻塞的线程。
如果从队列中获取数据的结果fqe为null或者为WakeupFlushThread实例时,则执行以下代码:
if (fqe == null || fqe instanceof WakeupFlushThread) { if (isAboveLowWaterMark()) { LOG.debug("Flush thread woke up because memory above low water=" + StringUtils .humanReadableInt(this.globalMemStoreLimitLowMark)); if (!flushOneForGlobalPressure()) { // Wasn‘t able to flush any region, but we‘re above // low water mark // This is unlikely to happen, but might happen when // closing the // entire server - another thread is flushing // regions. We‘ll just // sleep a little bit to avoid spinning, and then // pretend that // we flushed one, so anyone blocked will check // again lock.lock(); try { Thread.sleep(1000); flushOccurred.signalAll(); } finally { lock.unlock(); } } // Enqueue another one of these tokens so we‘ll wake up // again wakeupFlushThread(); } continue; }
此时并没有获取到实质的Flush请求,主要判断当前RegionServer整个MemStore的内存消耗是否已达到下限临界值,如果已达到下限临界值,则为了缓解内存压力,需要选取某一个Region进行Flush操作。
判断内存消耗由方法isAboveHighWaterMark完成:
/** * Return true if we‘re above the high watermark */ private boolean isAboveLowWaterMark() { return server.getRegionServerAccounting().getGlobalMemstoreSize() >= globalMemStoreLimitLowMark; }
如果isAboveLowWaterMark返回值为true,则表示此时RegionServer的整个MemStore内存消耗已达到下限临界值,需要选取一个Region进行Flush以缓解内存压力,由方法flushOneForGlobalPressure完成:
/** * The memstore across all regions has exceeded the low water mark. Pick one * region to flush and flush it synchronously (this is called from the flush * thread) * * @return true if successful */ private boolean flushOneForGlobalPressure() { SortedMap<Long, HRegion> regionsBySize = server .getCopyOfOnlineRegionsSortedBySize(); Set<HRegion> excludedRegions = new HashSet<HRegion>(); boolean flushedOne = false; while (!flushedOne) { ...... } return true; }
上述代码的主体思想是不断循环操作,直接成功选取某一Region完成Flush操作为止,在循环操作开始之前,已经依据Region大小获取到了该RegionServer上的所有Region:regionsBySize(SortedMap实现,依据Region大小作为排序依据,顺序为从大到小),如果选取的Region在执行Flush操作时发生了某些异常,导致Flush失败,则将其保存至excludedRegions,以使在下次选取过程中能够将其排除。
循环中的操作流程如下:
// Find the biggest region that doesn‘t have too many storefiles // (might be null!) HRegion bestFlushableRegion = getBiggestMemstoreRegion( regionsBySize, excludedRegions, true);
选取当前状态下最适合进行Flush操作的Region,该Region需要满足两个条件:
(1)Region没有包含超过一定数量的StoreFile;
(2)在满足(1)的所有Region中大小为最大值。
具体执行时代码如下:
private HRegion getBiggestMemstoreRegion( SortedMap<Long, HRegion> regionsBySize, Set<HRegion> excludedRegions, boolean checkStoreFileCount) { synchronized (regionsInQueue) { for (HRegion region : regionsBySize.values()) { //如果Region出现在excludedRegions中,则表示该Region是unflushable的。 if (excludedRegions.contains(region)) { continue; } if (checkStoreFileCount && isTooManyStoreFiles(region)) { continue; } return region; } } return null; } private boolean isTooManyStoreFiles(HRegion region) { for (Store hstore : region.stores.values()) { if (hstore.getStorefilesCount() > this.blockingStoreFilesNumber) { return true; } } return false; }
因为regionsBySize中的Region就是根据Region大小从大到小排列的,只要依次处理其中的Region即可,如果该Region即没有出现在excludedRegions,也没有包含过多的StoreFile(checkStoreFileCount为true),即该Region就是bestFlushableRegion。
为了防止bestFlushableRegion为null(如果目前所有的Region包含的StoreFile数目都大于临界值blockingStoreFilesNumber),我们需要选取一个目前最大的Region作为备选,即时它拥有的StoreFile数目大于临界值blockingStoreFilesNumber。
// Find the biggest region, total, even if it might have too many // flushes. HRegion bestAnyRegion = getBiggestMemstoreRegion(regionsBySize, excludedRegions, false); if (bestAnyRegion == null) { LOG.error("Above memory mark but there are no flushable regions!"); return false; }
执行getBiggestMemstoreRegion方法时,checkStoreFileCount为false,表示这些选取不考虑Region包含StoreFile的数目。
如果我们无法获取一个bestAnyRegion(bestAnyRegion为null),表示目前虽然内存压力较大,但是我们无法选取出一个可进行Flush操作的Region,直接返回false即可。
无法选取出一个可进行Flush操作的Region的原因一般有两个:
(1)在循环选取的过程中,我们发现所有的Region进行Flush操作时都失败了(可能原因是HDFS失效),它们都会出现在excludedRegions中,因此,会导致上述方法执行时返回值为null;
(2)RegionServer开始执行关闭操作。
HRegion regionToFlush; if (bestFlushableRegion != null && bestAnyRegion.memstoreSize.get() > 2 * bestFlushableRegion.memstoreSize .get()) { // Even if it‘s not supposed to be flushed, pick a region if // it‘s more than twice // as big as the best flushable one - otherwise when we‘re under // pressure we make // lots of little flushes and cause lots of compactions, etc, // which just makes // life worse! if (LOG.isDebugEnabled()) { LOG.debug("Under global heap pressure: " + "Region " + bestAnyRegion.getRegionNameAsString() + " has too many " + "store files, but is " + StringUtils .humanReadableInt(bestAnyRegion.memstoreSize .get()) + " vs best flushable region‘s " + StringUtils .humanReadableInt(bestFlushableRegion.memstoreSize .get()) + ". Choosing the bigger."); } regionToFlush = bestAnyRegion; } else { if (bestFlushableRegion == null) { regionToFlush = bestAnyRegion; } else { regionToFlush = bestFlushableRegion; } }
根据bestFlushableRegion和bestAnyRegion的选取结果,决定最后的选取结果regionToFlush:
(1)虽然bestFlushableRegion不为null,但bestAnyRegion的MemStore大小比bestFlushableRegion的MemStore大小两倍还要在,此时regionToFlush = bestAnyRegion;
(2)否则,如果bestFlushableRegion为null,则regionToFlush = bestAnyRegion,否则regionToFlush = bestFlushableRegion。
至此,我们已经选取出了需要进行Flush操作的Region:regionToFlush,接下来对其进行Flush即可:
Preconditions.checkState(regionToFlush.memstoreSize.get() > 0); LOG.info("Flush of region " + regionToFlush + " due to global heap pressure"); flushedOne = flushRegion(regionToFlush, true); if (!flushedOne) { LOG.info("Excluding unflushable region " + regionToFlush + " - trying to find a different region to flush."); excludedRegions.add(regionToFlush); }
如果该Region的Flush操作失败,即flushRegion的返回值为false,将其添加至excludedRegions中,并继续循环选取。
如果flushOneForGlobalPressure的返回值为false,则表示我们无法选取一个Region进行Flush,如注释所说,造成这种情况可能原因是RegionServer正处于关闭中,此时,会有其它线程来负责Region的Flush操作。我们仅仅需要休眠一会儿,假装我们完成了一个Region的Flush,然后就可以唤醒其它因内存压力而阻塞的线程了,使它们可以再次对内存消耗大小进行确认(后面会讲述为何有线程被阻塞)。
如果从队列中获取数据的结果fqe为FlushRegionEntry实例,则会直接执行以下代码:
FlushRegionEntry fre = (FlushRegionEntry) fqe; if (!flushRegion(fre)) { break; }
直接执行相应Region的Flush操作,如果发生错误(认为不可修复),则结束MemStoreFlusher线程的循环操作,执行清理工作。
MemStore与Put
在我们将大批量的数据定入HBase时,可能会由于内存的原因导致写入操作的Block,主要有以下两个方面的原因:
(1)reclaimMemStoreMemory
该方法是MemStoreFlusher的实例方法,在执行具体的Region batchMutate操作(完成写入操作)之前被调用,
HRegion region = getRegion(regionName); if (!region.getRegionInfo().isMetaTable()) { /* * This method blocks callers until we‘re down to a safe * amount of memstore consumption. * * ****************************************************** */ this.cacheFlusher.reclaimMemStoreMemory(); }
可见,一般地用户表都会在实际写入数据之前都会调用此方法,该方法可能会导致写入的阻塞。
reclaimMemStoreMemory分两种情况进行处理:isAboveHighWaterMark、isAboveLowWaterMark。
isAboveHighWaterMark:RegionServer整个MemStore的内存消耗值超过上限值
if (isAboveHighWaterMark()) { lock.lock(); try { boolean blocked = false; long startTime = 0; while (isAboveHighWaterMark() && !server.isStopped()) { if (!blocked) { startTime = EnvironmentEdgeManager.currentTimeMillis(); LOG.info("Blocking updates on " + server.toString() + ": the global memstore size " + StringUtils.humanReadableInt(server .getRegionServerAccounting() .getGlobalMemstoreSize()) + " is >= than blocking " + StringUtils .humanReadableInt(globalMemStoreLimit) + " size"); } blocked = true; wakeupFlushThread(); try { // we should be able to wait forever, but we‘ve seen a // bug where // we miss a notify, so put a 5 second bound on it at // least. flushOccurred.await(5, TimeUnit.SECONDS); } catch (InterruptedException ie) { Thread.currentThread().interrupt(); } } if (blocked) { final long totalTime = EnvironmentEdgeManager .currentTimeMillis() - startTime; if (totalTime > 0) { this.updatesBlockedMsHighWater.add(totalTime); } LOG.info("Unblocking updates for server " + server.toString()); } } finally { lock.unlock(); } }
当写入数据之前,如果我们发现当内存的消耗已经超过上限值时,会有一个循环等待的过程,直到内存的消耗值低于上限值为止,在每次等待操作之前都会通过wakeupFlushThread方法在Flush请求队列放入一个空元素,以激活MemStoreFlusher线程进行工作(可能会选取某一Region进行Flush),其中,上限值的判断如下所示:
/** * Return true if global memory usage is above the high watermark */ private boolean isAboveHighWaterMark() { return server.getRegionServerAccounting().getGlobalMemstoreSize() >= globalMemStoreLimit; }
isAboveLowWaterMark:RegionServer的整个MemStore的内存消耗值仅超过下限值
else if (isAboveLowWaterMark()) { wakeupFlushThread(); }
此时,不需要阻塞写入操作,仅仅需要在Flush请求队列中加入一个“空”元素,促使MemStoreFlusher工作即可。
(2)checkResources
/** * Perform a batch of mutations. It supports only Put and Delete mutations * and will ignore other types passed. * * @param mutationsAndLocks * the list of mutations paired with their requested lock IDs. * @return an array of OperationStatus which internally contains the * OperationStatusCode and the exceptionMessage if any. * @throws IOException */ public OperationStatus[] batchMutate( Pair<Mutation, Integer>[] mutationsAndLocks) throws IOException { BatchOperationInProgress<Pair<Mutation, Integer>> batchOp = new BatchOperationInProgress<Pair<Mutation, Integer>>( mutationsAndLocks); boolean initialized = false; while (!batchOp.isDone()) { checkReadOnly(); // Check if resources to support an update, may be blocked. checkResources(); ...... } return batchOp.retCodeDetails; }
在Region batchMutate中,每次循环写入数据之前都会进行checkResources的操作,该操作可能会导致本次地写入操作被阻塞。
/* * Check if resources to support an update. * * Here we synchronize on HRegion, a broad scoped lock. Its appropriate * given we‘re figuring in here whether this region is able to take on * writes. This is only method with a synchronize (at time of writing), this * and the synchronize on ‘this‘ inside in internalFlushCache to send the * notify. */ private void checkResources() throws RegionTooBusyException, InterruptedIOException { // If catalog region, do not impose resource constraints or block // updates. if (this.getRegionInfo().isMetaRegion()) { return; } boolean blocked = false; long startTime = 0; while (this.memstoreSize.get() > this.blockingMemStoreSize) { requestFlush(); if (!blocked) { startTime = EnvironmentEdgeManager.currentTimeMillis(); LOG.info("Blocking updates for ‘" + Thread.currentThread().getName() + "‘ on region " + Bytes.toStringBinary(getRegionName()) + ": memstore size " + StringUtils.humanReadableInt(this.memstoreSize.get()) + " is >= than blocking " + StringUtils .humanReadableInt(this.blockingMemStoreSize) + " size"); } long now = EnvironmentEdgeManager.currentTimeMillis(); long timeToWait = startTime + busyWaitDuration - now; if (timeToWait <= 0L) { final long totalTime = now - startTime; this.updatesBlockedMs.add(totalTime); LOG.info("Failed to unblock updates for region " + this + " ‘" + Thread.currentThread().getName() + "‘ in " + totalTime + "ms. The region is still busy."); throw new RegionTooBusyException("region is flushing"); } blocked = true; synchronized (this) { try { wait(Math.min(timeToWait, threadWakeFrequency)); } catch (InterruptedException ie) { final long totalTime = EnvironmentEdgeManager .currentTimeMillis() - startTime; if (totalTime > 0) { this.updatesBlockedMs.add(totalTime); } LOG.info("Interrupted while waiting to unblock updates for region " + this + " ‘" + Thread.currentThread().getName() + "‘"); InterruptedIOException iie = new InterruptedIOException(); iie.initCause(ie); throw iie; } } } if (blocked) { // Add in the blocked time if appropriate final long totalTime = EnvironmentEdgeManager.currentTimeMillis() - startTime; if (totalTime > 0) { this.updatesBlockedMs.add(totalTime); } LOG.info("Unblocking updates for region " + this + " ‘" + Thread.currentThread().getName() + "‘"); } }
由上述代码可知,阻塞条件为
this.memstoreSize.get() > this.blockingMemStoreSize
如果上述条件成立,本次写入操作会被阻塞直到该Region MemStore的内存消耗值低于要求值为止。
其中,memstoreSize表示即将被写入数据的Region的MemStore的当前大小,blockingMemStoreSize由下述代码计算而来:
long flushSize = this.htableDescriptor.getMemStoreFlushSize(); if (flushSize <= 0) { flushSize = conf.getLong(HConstants.HREGION_MEMSTORE_FLUSH_SIZE, HTableDescriptor.DEFAULT_MEMSTORE_FLUSH_SIZE); } this.memstoreFlushSize = flushSize; this.blockingMemStoreSize = this.memstoreFlushSize * conf.getLong("hbase.hregion.memstore.block.multiplier", 2);
可以看出,blockingMemStoreSize为memstoreFlushSize的整数倍。
MemStoreFlusher flushRegion
当MemStoreFlusher线程在Flush队列中取出要进行Flush操作的请求元素(FlushRegionEntry)时,都是通过下面的方法来完成Flush的。
/* * A flushRegion that checks store file count. If too many, puts the flush * on delay queue to retry later. * * @param fqe * * @return true if the region was successfully flushed, false otherwise. If * false, there will be accompanying log messages explaining why the log was * not flushed. */ private boolean flushRegion(final FlushRegionEntry fqe) { HRegion region = fqe.region; if (!fqe.region.getRegionInfo().isMetaRegion() && isTooManyStoreFiles(region)) { if (fqe.isMaximumWait(this.blockingWaitTime)) { LOG.info("Waited " + (System.currentTimeMillis() - fqe.createTime) + "ms on a compaction to clean up ‘too many store files‘; waited " + "long enough... proceeding with flush of " + region.getRegionNameAsString()); } else { // If this is first time we‘ve been put off, then emit a log // message. if (fqe.getRequeueCount() <= 0) { // Note: We don‘t impose blockingStoreFiles constraint on // meta regions LOG.warn("Region " + region.getRegionNameAsString() + " has too many " + "store files; delaying flush up to " + this.blockingWaitTime + "ms"); if (!this.server.compactSplitThread.requestSplit(region)) { try { this.server.compactSplitThread.requestCompaction( region, getName()); } catch (IOException e) { LOG.error( "Cache flush failed" + (region != null ? (" for region " + Bytes .toStringBinary(region .getRegionName())) : ""), RemoteExceptionHandler.checkIOException(e)); } } } // Put back on the queue. Have it come back out of the queue // after a delay of this.blockingWaitTime / 100 ms. this.flushQueue.add(fqe.requeue(this.blockingWaitTime / 100)); // Tell a lie, it‘s not flushed but it‘s ok return true; } } return flushRegion(region, false); }
上述代码根据具体情况,可能会在执行具体的flushRegion操作之前,采取一些特殊的动作。
如果当前Region所属的表是用户表,且该Region中包含过多的StoreFile,则会下述判断:
(1)该Flush请求已达到最大等待时间,认为此时必须进行处理,仅仅打印一些信息即可(因此请求队列的实现为一个DealyedQueue,每一个队列元素都会根据自己的“过期时间”进行排序);
(2)该Flush请求尚未达到最大等待时间,认为因为该Region已经包含过多的StoreFile,应该延迟本次的Flush请求,而且在延迟操作之前,如果是第一次被延迟,则会根据情况判断是否发起Split或Compact请求;