HDFS sink主要处理过程在process方法：

//循环batchSize次或者Channel为空

for (txnEventCount = 0; txnEventCount < batchSize; txnEventCount++) {

//该方法会调用BasicTransactionSemantics的具体实现

Event event = channel.take();

if (event == null) {

break;

}

......

//sfWriter是一个LRU缓存，缓存对文件Handler,最大打开文件由参数maxopenfiles控制

BucketWriter bucketWriter = sfWriters.get(lookupPath);

// 如果不存在，则构造一个缓存

if (bucketWriter == null) {

//通过HDFSWriterFactory根据filetype生成一个hdfswriter，由参数hdfs.Filetype控制；eg:HDFSDataStream

HDFSWriter hdfsWriter = writerFactory.getWriter(fileType);

//idleCallback会在bucketWriter flush完毕后从LRU中删除；

bucketWriter = new BucketWriter(rollInterval, rollSize, rollCount,

batchSize, context, realPath, realName, inUsePrefix, inUseSuffix,

suffix, codeC, compType, hdfsWriter, timedRollerPool,

proxyTicket, sinkCounter, idleTimeout, idleCallback,

lookupPath, callTimeout, callTimeoutPool);

sfWriters.put(lookupPath, bucketWriter);

}

......

// track一个事务内的bucket

if (!writers.contains(bucketWriter)) {

writers.add(bucketWriter);

}

// 写数据到HDFS；

bucketWriter.append(event);->

open();//如果底层支持append，则通过open接口打开；否则create接口

//判断是否进行日志切换

//根据复制的副本书和目标副本数做对比，如果不满足则doRotate=false

if (doRotate) {

close();

open();

}

HDFSWriter.append(event);

if (batchCounter == batchSize) {//如果达到batchSize行进行一次flush

flush();->

doFlush()->

HDFSWriter.sync()->

FSDataoutputStream.flush/sync

}

// 提交事务之前，刷新所有的bucket

for (BucketWriter bucketWriter : writers) {

bucketWriter.flush();

}

transaction.commit();

这里，无论是BucketWriter执行append，sync还是rename等操作都是提交到一个后台线程池进行异步处理:callWithTimeout，这个线程池的大小是由hdfs.threadsize来设置；