Friday, March 24, 2017

HOD

"HOD is a set of scripts to start services, for example a Hadoop cluster, from within another resource management system (i.e. Torque/PBS). As such, it allows traditional users of HPC systems to experiment with Hadoop or use it as a production setup if there is no dedicated setup available.

Hadoop is not the only software supported. HOD can also create HBase databases, IPython notebooks, and set up a Spark environment.

There are two main benefits:
  1. Users can run jobs on a traditional batch cluster. This is good for small to medium Hadoop jobs where the framework is used but having a 'big data' cluster isn't required. At this point the performance benefits of a parallel file system outweigh the 'share nothing' architecture of a HDFS style file system.
  2. Users from different groups can run whichever version of Hadoop they like. This removes the need for painful upgrades to running Yarn clusters and hoping all users' jobs are backwards compatible.
hanythingondemand works by launching an MPI job which uses the reserved nodes as a cluster-in-a-cluster. These nodes then have the various Hadoop services started on them. Users can launch a job at startup (batch mode) or login to worker nodes (using the hod connect command) where they can interact with their services.

The prerequisites are:
The rest of the requirements can be installed using EasyBuild:
  • Python and various libraries.
  • mpi4py
  • eg. on fedora yum install -y mpi4py-mpich2
  • If you build this yourself, you will probably need to set the $MPICC environment variable.
  • vsc-base - Used for command line parsing.
  • vsc-mympirun - Used for setting up the MPI job.
  • pbs_python - Used for interacting with the PBS (aka Torque) server.
  • netifaces
  • netaddr
  • Java
  • Oracle JDK or OpenJDK - both installable with Easybuild
  • Hadoop binaries
  • eg. the Cloudera distribution versions (used to test HOD)
https://github.com/hpcugent/hanythingondemand

http://hod.readthedocs.io/en/latest/

https://archive.fosdem.org/2016/schedule/event/hpc_bigdata_hanythingondemand/

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