Rack Awareness in hadoop

Rack Awareness

·        For small clusters in which all servers are connected by a single switch, there are only two levels of locality: "on-machine" and "off-machine." When loading data from a DataNode's local drive into HDFS, the NameNode will schedule one copy to go into the local DataNode, and will pick two other machines at random from the cluster.

·        For larger Hadoop installations which span multiple racks, it is important to ensure that replicas of data exist on multiple racks. This way, the loss of a switch does not render portions of the data unavailable due to all replicas being underneath it.

·        HDFS can be made rack-aware by the use of a script which allows the master node to map the network topology of the cluster. While alternate configuration strategies can be used, the default implementation allows you to provide an executable script which returns the "rack address" of each of a list of IP addresses.

·        The network topology script receives as arguments one or more IP addresses of nodes in the cluster. It returns on stdout a list of rack names, one for each input. The input and output order must be consistent.

·        To set the rack mapping script, specify the key topology.script.file.name in conf/hadoop-site.xml. This provides a command to run to return a rack id; it must be an executable script or program. By default, Hadoop will attempt to send a set of IP addresses to the file as several separate command line arguments. You can control the maximum acceptable number of arguments with the topology.script.number.args key.

·        Rack ids in Hadoop are hierarchical and look like path names. By default, every node has a rack id of /default-rack. You can set rack ids for nodes to any arbitrary path, e.g., /foo/bar-rack. Path elements further to the left are higher up the tree. Thus a reasonable structure for a large installation may be /top-switch-name/rack-name.

·        Hadoop rack ids are not currently expressive enough to handle an unusual routing topology such as a 3-d torus; they assume that each node is connected to a single switch which in turn has a single upstream switch. This is not usually a problem, however. Actual packet routing will be directed using the topology discovered by or set in switches and routers. The Hadoop rack ids will be used to find "near" and "far" nodes for replica placement (and in 0.17, MapReduce task placement).