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It is essential to prepare yourself in order to pass an interview and land your dream job. Here’s the first step to achieving this. The following are some frequently asked Hadoop Administration interview questions and answers that might be useful.
|DataNode||It stores the data in the Hadoop File System which contains more than one DataNode, with data replicated across them|
|NameNode||It is the core of an HDFS that keeps the directory tree of all files is present in the file system, and tracks where the file data is kept across the cluster|
|SecondaryNameNode||It is a specially dedicated node in HDFS cluster that keep checkpoints of the file system metadata present on namenode|
|NodeManager||It is responsible for launching and managing containers on a node which execute tasks as specified by the AppMaster|
|ResourceManager||It is the master that helps in managing the distributed applications running on the YARN system by arbitrating all the available cluster resources|
The following are the steps for doing this:
If while reading the file the datanode dies, the library will automatically attempt to read another replica of the data from another datanode. If all replicas are unavailable, the read operation fails and the client receives an exception. In case the information returned by the NameNode about block locations are outdated by the time the client attempts to contact a datanode, a retry will occur if there are other replicas or the read will fail.
Checkpointing is an essential part of maintaining and persisting filesystem metadata in HDFS. It’s crucial for efficient Namenode recovery and restart and is an important indicator of overall cluster health.
Namenode persists filesystem metadata. At a high level, namenode’s primary responsibility is to store the HDFS namespace. Meaning, things like the directory tree, file permissions and the mapping of files to block IDs. It is essential that this metadata are safely persisted to stable storage for fault tolerance.
This filesystem metadata is stored in two different parts: the fsimage and the edit log. The fsimage is a file that represents a point-in-time snapshot of the filesystem’s metadata. However, while the fsimage file format is very efficient to read, it’s unsuitable for making small incremental updates like renaming a single file. Thus, rather than writing a new fsimage every time the namespace is modified, the NameNode instead records the modifying operation in the edit log for durability. This way, if the NameNode crashes, it can restore its state by first loading the fsimage then replaying all the operations (also called edits or transactions) in the edit log to catch up to the most recent state of the namesystem. The edit log comprises a series of files, called edit log segments, that together represent all the namesystem modifications made since the creation of the fsimage.
Most block-structured file systems use a block size on the order of 4 or 8 KB. By contrast, the default block size in HDFS is 64MB – and larger. This allows HDFS to decrease the amount of metadata storage required per file. Furthermore, it allows fast streaming reads of data, by keeping large amounts of data sequentially organized on the disk. As a result, HDFS is expected to have very large files that are read sequentially. Unlike a file system such as NTFS or EXT which has numerous small files, HDFS stores a modest number of very large files: hundreds of megabytes, or gigabytes each.
user@machine:hadoop$ bin/hadoop moduleName-cmdargs…
The moduleName tells the program which subset of Hadoop functionality to use. -cmd is the name of a specific command within this module to execute. Its arguments follow the command name.
The two modules relevant to HDFS are : dfs and dfsadmin.
The dfs module, also known as ‘FsShell’, provides basic file manipulation operations and works with objects within the file system. The dfsadmin module manipulates or queries the file system as a whole.
Datanodes can store blocks in multiple directories typically located on different local disk drives. In order to setup multiple directories one needs to specify a comma separated list of pathnames as values under config paramters dfs.data.dir/dfs.datanode.data.dir. Datanodes will attempt to place equal amount of data in each of the directories.
Namenode also supports multiple directories, which stores the name space image and edit logs. In order to setup multiple directories one needs to specify a comma separated list of pathnames as values under config paramters dfs.name.dir/dfs.namenode.data.dir. The namenode directories are used for the namespace data replication so that image and log could be restored from the remaining disks/volumes if one of the disks fails.
Schedulers are responsible for assigning tasks to open slots on tasktrackers. The scheduler is a plug-in within the jobtracker. The three types of schedulers are:
The CS scheduler can be used under the following situations:
The Fair Scheduler can be used over the Capacity Scheduler under the following conditions:
DFS.NAME.DIR specifies the path of directory in Namenode’s local file system to store HDFS’s metadata and DFS.DATA.DIR specifies the path of directory in Datanode’s local file system to store HDFS’s file blocks. These paramters are specified in HDFS-SITE.XML config file of all nodes in the cluster, including master and slave nodes.
If these paramters are not specified, namenode’s metadata and Datanode’s file blocks related information gets stored in /tmp under HADOOP-USERNAME directory. This is not a safe place, as when nodes are restarted, data will be lost and is critical if Namenode is restarted, as formatting information will be lost.
FileSystem checking utility FSCK is used to check and display the health of file system, files and blocks in it. When used with a path ( bin/Hadoop fsck / -files –blocks –locations -racks) it recursively shows the health of all files under the path. And when used with ‘/’ , it checks the entire file system. By Default FSCK ignores files still open for writing by a client. To list such files, run FSCK with -openforwrite option.
FSCK checks the file system, prints out a dot for each file found healthy, prints a message of the ones that are less than healthy, including the ones which have over replicated blocks, under-replicated blocks, mis-replicated blocks, corrupt blocks and missing replicas.
The Configuration files that need to be updated to setup a fully distributed mode of Hadoop are:
These files can be found in your Hadoop>conf directory. If Hadoop daemons are started individually using ‘bin/Hadoop-daemon.sh start xxxxxx’ where xxxx is the name of daemon, then masters and slaves file need not be updated and can be empty. This way of starting daemons requires command to be issued on appropriate nodes to start appropriate daemons. If Hadoop daemons are started using ‘bin/start-dfs.sh’ and ‘bin/start-mapred.sh’, then masters and slaves configurations files on namenode machine need to be updated.
Masters – Ip address/hostname of node where secondarynamenode will run.
Slaves –Ip address/hostname of nodes where datanodes will be run and eventually task trackers.
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