Thanks for that pointer. I read the sections on staging and replication pipelining and I still am not clear on the synchronization points. If I'm writing out 2 blocks worth of data, will the thread that's performing the write block after the first chunk is staged but prior to replication pipelining, or will it continue to stage the second chuck while replication pipelining the first chunk? Or have I not sufficiently scrutinized the documentation and I should continue to RTFM?
For reference: Staging A client request to create a file does not reach the NameNode immediately. In fact, initially the HDFS client caches the file data into a temporary local file. Application writes are transparently redirected to this temporary local file. When the local file accumulates data worth over one HDFS block size, the client contacts the NameNode. The NameNode inserts the file name into the file system hierarchy and allocates a data block for it. The NameNode responds to the client request with the identity of the DataNode and the destination data block. Then the client flushes the block of data from the local temporary file to the specified DataNode. When a file is closed, the remaining un-flushed data in the temporary local file is transferred to the DataNode. The client then tells the NameNode that the file is closed. At this point, the NameNode commits the file creation operation into a persistent store. If the NameNode dies before the file is closed, the file is lost. The above approach has been adopted after careful consideration of target applications that run on HDFS. These applications need streaming writes to files. If a client writes to a remote file directly without any client side buffering, the network speed and the congestion in the network impacts throughput considerably. This approach is not without precedent. Earlier distributed file systems, e.g. AFS, have used client side caching to improve performance. A POSIX requirement has been relaxed to achieve higher performance of data uploads. Replication Pipelining When a client is writing data to an HDFS file, its data is first written to a local file as explained in the previous section. Suppose the HDFS file has a replication factor of three. When the local file accumulates a full block of user data, the client retrieves a list of DataNodes from the NameNode. This list contains the DataNodes that will host a replica of that block. The client then flushes the data block to the first DataNode. The first DataNode starts receiving the data in small portions (4 KB), writes each portion to its local repository and transfers that portion to the second DataNode in the list. The second DataNode, in turn starts receiving each portion of the data block, writes that portion to its repository and then flushes that portion to the third DataNode. Finally, the third DataNode writes the data to its local repository. Thus, a DataNode can be receiving data from the previous one in the pipeline and at the same time forwarding data to the next one in the pipeline. Thus, the data is pipelined from one DataNode to the next. On Thu, Mar 17, 2011 at 12:34 PM, Harsh J <qwertyman...@gmail.com> wrote: > Have a read of the replication feature design: > http://hadoop.apache.org/common/docs/r0.20.0/hdfs_design.html#Data+Replication > :) > > On Thu, Mar 17, 2011 at 9:59 PM, Andrew Rothstein > <andrew.rothst...@gmail.com> wrote: >> If I'm using a replication factor of 3 and I write a block of data >> will my write operation block until the data is present on 3 nodes? > > No. > >> will it block until the data is present on 1 node and asynchronously >> replicate from there to 2 other nodes? > > Yes! > > -- > Harsh J > http://harshj.com >
