Accessing Data with NFS
Unlike other Hadoop distributions that only allow cluster data import or import as a batch operation, MapR lets you mount the cluster itself via NFS so that your applications can read and write data directly. MapR allows direct file modification and multiple concurrent reads and writes via POSIX semantics. With an NFS-mounted cluster, you can read and write data directly with standard tools, applications, and scripts. For example, you could run a MapReduce job that outputs to a CSV file, then import the CSV file directly into SQL via NFS.
MapR exports each cluster as the directory /mapr/<cluster name> (for
example, /mapr/my.cluster.com). If you create a mount point with the local
path /mapr, then Hadoop FS paths and NFS paths to the cluster will be the
same. This makes it easy to work on the same files via NFS and Hadoop. In a multi-cluster
setting, the clusters share a single namespace, and you can see them all by mounting the
top-level /mapr directory.
MapR uses version 3 of the NFS protocol. NFS version 4 bypasses the port mapper and
attempts to connect to the default port only. If you are running NFS on a non-standard
port, mounts from NFS version 4 clients time out. Use the -o nfsvers=3
option to specify NFS version 3.
The following sections provide information about mounting the cluster via NFS: