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HBASE 代码阅读笔记-1 - PUT操作客户端主流程(基于0.96.0-hadoop2)

2013-11-08 19:23 267 查看
又回来了,还是看put,不过版本号变了,希望看0.94的童靴移驾到http://dennis-lee-gammy.iteye.com/admin/blogs/1972269
put和doput方法变化不大,唯一就是原来的缓存队列名字里面加了一个async,然后类型由ArrayList变成了LinkedList。

flushCommit方法

public void flushCommits() throws InterruptedIOException, RetriesExhaustedWithDetailsException {
// We're looping, as if one region is overloaded we keep its operations in the buffer.
// As we can have an operation in progress even if the buffer is empty, we call
// backgroundFlushCommits at least one time.
do {
backgroundFlushCommits(true);
} while (!writeAsyncBuffer.isEmpty());
}


private void doPut(Put put) throws InterruptedIOException, RetriesExhaustedWithDetailsException {
if (ap.hasError()){
backgroundFlushCommits(true);
}

validatePut(put);

currentWriteBufferSize += put.heapSize();
writeAsyncBuffer.add(put);

while (currentWriteBufferSize > writeBufferSize) {
backgroundFlushCommits(false);
}

变化真大啊,原来42行代码一下只有这么点了,以前核心功能由
connection.processBatch(writeBuffer, tableName, pool, results);
完成,这里变成了循环。以前还会检查并保存执行失败的操作返回到缓存列表中,这里第一眼是看不到这些了。看看backgroundFlushCommits 卖的是神马药。


private void backgroundFlushCommits(boolean synchronous) throws
InterruptedIOException, RetriesExhaustedWithDetailsException {

try {
// If there is an error on the operations in progress, we don't add new operations.
if (writeAsyncBuffer.size() > 0 && !ap.hasError()) {
ap.submit(writeAsyncBuffer, true);//如果任务队列没有清空,并且异步执行器没有问题,则执行提交操作
}

if (synchronous || ap.hasError()) {
if (ap.hasError() && LOG.isDebugEnabled()) {
LOG.debug(tableName + ": One or more of the operations have failed -" +
" waiting for all operation in progress to finish (successfully or not)");
}
ap.waitUntilDone();//如果是同步模式,或者出现了错误,则都变成同步模式,需要等待完成
}

if (ap.hasError()) {
if (!clearBufferOnFail) {
// if clearBufferOnFailed is not set, we're supposed to keep the failed operation in the
// write buffer. This is a questionable feature kept here for backward compatibility
// 如果不是失败则清除模式,则保存失败的操作,功能与0.94版本是一致的,不过原来的版本在提交任务的时候
// 会一并上传一个结果集合,顺序与任务提交的顺序一一对应。顺序取回结果查看是否成功,
// 并将成功的操作从缓存队列中移除。
// 而现在的代码,表面上看应该是在某个地方已经清空了,然后ap负责记录并返回失败的操作
writeAsyncBuffer.addAll(ap.getFailedOperations());
}
// 目测ap已经完成了重试,并记录了应有的异常
RetriesExhaustedWithDetailsException e = ap.getErrors();
ap.clearErrors();
throw e;
}
} finally {
currentWriteBufferSize = 0;
for (Row mut : writeAsyncBuffer) {
if (mut instanceof Mutation) {
currentWriteBufferSize += ((Mutation) mut).heapSize();//既然缓存队列之前已经被清除过,也就不用判断是否是失败清除模式了,简单的计算下缓存大小吧。
}
}
}
}


正常流程几乎完全找不到以前的影子!这里多出来一个处理类org.apache.hadoop.hbase.client.AsyncProcess,即ap成员。这个类是0.94版的代码里面完全没有的。难怪变化那么大。

首先这里有一个参数,指定为同步执行还是异步执行。从上面的doput方法和flushcommit方法可以看出,如果在doput的过程中,也就是调用htable.put(Put)的时候,如果缓存大小超过了客户端写缓存大小的限制,调用这个方法是异步的;而在flushcommit方法中,这个方法是同步的。这里也暴露出来一个与原有流程不同的地方,0.94中doput如果超过大小限制,是委托flushcommit方法提交的,而这里采用了一种更加柔和的方式。另外,那个htable的线程池成员在方法中也找不到它的影子了,以前可是带着到处跑的。


主流程差不多就完成了。重要的两个流程:请求和处理响应,应该是在
ap.submit(writeAsyncBuffer, true)
ap.waitUntilDone();
中实现。继续吧


public void submit(List<? extends Row> rows, boolean atLeastOne) throws InterruptedIOException {
if (rows.isEmpty()) {
return;
}

// This looks like we are keying by region but HRegionLocation has a comparator that compares
// on the server portion only (hostname + port) so this Map collects regions by server.
// 熟悉的面孔,这不是94中HConnectionImplementation.processBatchCallback(list, tableName, pool, results, null)
// step 1 第一行么,原来跑这里来了,HRegionLocation --> MultiAction<Row> 的字典结构。
Map<HRegionLocation, MultiAction<Row>> actionsByServer =
new HashMap<HRegionLocation, MultiAction<Row>>();
List<Action<Row>> retainedActions = new ArrayList<Action<Row>>(rows.size());

do {
// Wait until there is at least one slot for a new task.
// 等待空闲资源执行操作,maxTotalConcurrentTasks =hbase.client.max.total.tasks
// 默认100,配置文件里面没有哦,亲 TODO【1】
waitForMaximumCurrentTasks(maxTotalConcurrentTasks - 1);

// Remember the previous decisions about regions or region servers we put in the
// final multi.
Map<String, Boolean> regionIncluded = new HashMap<String, Boolean>();
Map<ServerName, Boolean> serverIncluded = new HashMap<ServerName, Boolean>();

int posInList = -1;
Iterator<? extends Row> it = rows.iterator();
while (it.hasNext()) {
Row r = it.next();
HRegionLocation loc = findDestLocation(r, 1, posInList);//定位region TODO【2】

if (loc != null && canTakeOperation(loc, regionIncluded, serverIncluded)) {//判断region TODO【3】
// loc is null if there is an error such as meta not available.
Action<Row> action = new Action<Row>(r, ++posInList);
retainedActions.add(action);
addAction(loc, action, actionsByServer);//添加操作 ,跟之前的step 1里面的步骤一致,multiAction按HRegionLocation聚类
it.remove();//果然,缓存队列在这里会被逐步清空
}
}

} while (retainedActions.isEmpty() && atLeastOne && !hasError());

HConnectionManager.ServerErrorTracker errorsByServer = createServerErrorTracker();
//创建跟踪异常,如果需要创建(hbase.client.retries.by.server指定,配置文件没有,默认为true),则返回一个
//HConnectionManager.ServerErrorTracker
sendMultiAction(retainedActions, actionsByServer, 1, errorsByServer);//发送请求 TODO【4】
}


那什么情况下表示有空闲资源呢,看看【1】处的相关代码


private void waitForMaximumCurrentTasks(int max) throws InterruptedIOException {
long lastLog = EnvironmentEdgeManager.currentTimeMillis();
long currentTasksDone = this.tasksDone.get();

while ((tasksSent.get() - currentTasksDone) > max) {//如果已发送的任务跟已经完成的任务数差值过大
long now = EnvironmentEdgeManager.currentTimeMillis();
if (now > lastLog + 10000) {
lastLog = now;
LOG.info(": Waiting for the global number of running tasks to be equals or less than "
+ max + ", tasksSent=" + tasksSent.get() + ", tasksDone=" + tasksDone.get() +
", currentTasksDone=" + currentTasksDone + ", tableName=" + tableName);
}
waitForNextTaskDone(currentTasksDone);//等待下一个任务完成
currentTasksDone = this.tasksDone.get();//看看完成了多少个
}
}
//这个简单,如果已完成任务数没有变化就等100ms
protected void waitForNextTaskDone(long currentNumberOfTask) throws InterruptedIOException {
while (currentNumberOfTask == tasksDone.get()) {
try {
synchronized (this.tasksDone) {
this.tasksDone.wait(100);
}
} catch (InterruptedException e) {
throw new InterruptedIOException("Interrupted." +
" currentNumberOfTask=" + currentNumberOfTask +
", tableName=" + tableName + ", tasksDone=" + tasksDone.get());
}
}
}


protected boolean canTakeOperation(HRegionLocation loc,
Map<String, Boolean> regionsIncluded,
Map<ServerName, Boolean> serversIncluded) {
String encodedRegionName = loc.getRegionInfo().getEncodedName();
Boolean regionPrevious = regionsIncluded.get(encodedRegionName);
//之前已经有这个region信息,则直接返回以保存的结果,这里有个问题,如果region信息有更新呢?估计在后面的代码里面。
if (regionPrevious != null) {
// We already know what to do with this region.
return regionPrevious;
}
//没有的话看看RS的信息,如果RS已经挂了,那么他对应的所有region都挂,不用看了,记录一下告诉上层吧
Boolean serverPrevious = serversIncluded.get(loc.getServerName());
if (Boolean.FALSE.equals(serverPrevious)) {
// It's a new region, on a region server that we have already excluded.
regionsIncluded.put(encodedRegionName, Boolean.FALSE);
return false;
}

AtomicInteger regionCnt = taskCounterPerRegion.get(encodedRegionName);
if (regionCnt != null && regionCnt.get() >= maxConcurrentTasksPerRegion) {
// Too many tasks on this region already.hbase.client.max.perregion.tasks设置,默认为1哦,配置文件没有哦亲,每次只能运行一个任务?这个设置MS有点坑,后续看看改大了会不会有影响
regionsIncluded.put(encodedRegionName, Boolean.FALSE);
return false;
}

if (serverPrevious == null) {
// The region is ok, but we need to decide for this region server.
int newServers = 0; // number of servers we're going to contact so far
for (Map.Entry<ServerName, Boolean> kv : serversIncluded.entrySet()) {
if (kv.getValue()) {
newServers++;
}
}

// Do we have too many total tasks already? 如果server的数量与等待完成的任务之和小于最大任务数(之前说过,默认100)
boolean ok = (newServers + getCurrentTasksCount()) < maxTotalConcurrentTasks;

if (ok) {
//在检查是否每个server能承受的最大任务数hbase.client.max.perserver.tasks=5,怎么都那么小呢,还不能在配置文件里面找到,坑死了啊
// If the total is fine, is it ok for this individual server?
AtomicInteger serverCnt = taskCounterPerServer.get(loc.getServerName());
ok = (serverCnt == null || serverCnt.get() < maxConcurrentTasksPerServer);
}
// 如果检查失败,RS和Region都设置为false
if (!ok) {
regionsIncluded.put(encodedRegionName, Boolean.FALSE);
serversIncluded.put(loc.getServerName(), Boolean.FALSE);
return false;
}

serversIncluded.put(loc.getServerName(), Boolean.TRUE);
} else {
assert serverPrevious.equals(Boolean.TRUE);
}

regionsIncluded.put(encodedRegionName, Boolean.TRUE);

return true;
}


备注【3】,定位Resion,大操作,详见http://dennis-lee-gammy.iteye.com/admin/blogs/1973255

备注【5】,发送请求,大头,这里先放放
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