2. • Hadoop Core, our flagship sub-project, provides a distributed filesystem (HDFS) and support for the MapReduce distributed computing metaphor.• Pig is a high-level data-flow language and execution framework for parallel computation. It is built on top of Hadoop Core.
3. ZooKeeper• ZooKeeper is a highly available and reliable coordination system. Distributed applications use ZooKeeper to store and mediate updates for critical shared state.
4. JobTracker• JobTracker: The JobTracker provides command and control for job management. It supplies the primary user interface to a MapReduce cluster. It also handles the distribution and management of tasks. There is one instance of this server running on a cluster. The machine running the JobTracker server is the MapReduce master.
5. TaskTracker• TaskTracker: The TaskTracker provides execution services for the submitted jobs. Each TaskTracker manages the execution of tasks on an individual compute node in the MapReduce cluster. The JobTracker manages all of the TaskTracker processes. There is one instance of this server per compute node.
6. NameNode• NameNode: The NameNode provides metadata storage for the shared file system. The NameNode supplies the primary user interface to the HDFS. It also manages all of the metadata for the HDFS. There is one instance of this server running on a cluster. The metadata includes such critical information as the file directory structure and which DataNodes have copies of the data blocks that contain each file’s data. The machine running the NameNode server process is the HDFS master.
7. Secondary NameNode• Secondary NameNode: The secondary NameNode provides both file system metadata backup and metadata compaction. It supplies near real-time backup of the metadata for the NameNode. There is at least one instance of this server running on a cluster, ideally on a separate physical machine than the one running the NameNode. The secondary NameNode also merges the metadata change history, the edit log, into the NameNode’s file system image.
8. Design of HDFS• Design of HDFS – Very large files – Streaming data access – Commodity hardware• not a good fit – Low-latency data access – Lots of small files – Multiple writers, arbitrary file modifications
22. could only be replicated• java.io.IOException: could only be replicated to 0 nodes， instead of 1.• 解决： – XML的配置不正确，要保证slave的mapred- site.xml和core-site.xml的地址都跟master一致
24. UnknownHostException• # hostname• Vi /etc/hostname 修改hostname• Vi /etc/hosts 增加hostname对应的IP
25. error in shuffle in fetcher• org.apache.hadoop.mapreduce.task.reduce.Sh uffle$ShuffleError: error in shuffle in fetcher• 解决方式： – 问题出在hosts文件的配置上，在所有节点的 /etc/hosts文件中加入其他节点的主机名和IP映 射