### "Gridmix" Benchmark ###

Contents:

0 Overview
1 Getting Started
  1.0 Build
  1.1 Configure
  1.2 Generate test data
2 Running
  2.0 General
  2.1 Non-Hod cluster
  2.2 Hod
    2.2.0 Static cluster
    2.2.1 Hod cluster


* 0 Overview

The scripts in this package model a cluster workload. The workload is
simulated by generating random data and submitting map/reduce jobs that
mimic observed data-access patterns in user jobs. The full benchmark
generates approximately 2.5TB of (often compressed) input data operated on
by the following simulated jobs:

1) Three stage map/reduce job
	   Input:      500GB compressed (2TB uncompressed) SequenceFile
                 (k,v) = (5 words, 100 words)
                 hadoop-env: FIXCOMPSEQ
     Compute1:   keep 10% map, 40% reduce
	   Compute2:   keep 100% map, 77% reduce
                 Input from Compute1
     Compute3:   keep 116% map, 91% reduce
                 Input from Compute2
     Motivation: Many user workloads are implemented as pipelined map/reduce
                 jobs, including Pig workloads

2) Large sort of variable key/value size
     Input:      500GB compressed (2TB uncompressed) SequenceFile
                 (k,v) = (5-10 words, 100-10000 words)
                 hadoop-env: VARCOMPSEQ
     Compute:    keep 100% map, 100% reduce
     Motivation: Processing large, compressed datsets is common.

3) Reference select
     Input:      500GB compressed (2TB uncompressed) SequenceFile
                 (k,v) = (5-10 words, 100-10000 words)
                 hadoop-env: VARCOMPSEQ
     Compute:    keep 0.2% map, 5% reduce
                 1 Reducer
     Motivation: Sampling from a large, reference dataset is common.

4) Indirect Read
     Input:      500GB compressed (2TB uncompressed) Text
                 (k,v) = (5 words, 20 words)
                 hadoop-env: FIXCOMPTEXT
     Compute:    keep 50% map, 100% reduce Each map reads 1 input file,
                 adding additional input files from the output of the
                 previous iteration for 10 iterations
     Motivation: User jobs in the wild will often take input data without
                 consulting the framework. This simulates an iterative job
                 whose input data is all "indirect," i.e. given to the
                 framework sans locality metadata.

5) API text sort (java, pipes, streaming)
     Input:      500GB uncompressed Text
                 (k,v) = (1-10 words, 0-200 words)
                 hadoop-env: VARINFLTEXT
     Compute:    keep 100% map, 100% reduce
     Motivation: This benchmark should exercise each of the APIs to
                 map/reduce

Each of these jobs may be run individually or- using the scripts provided-
as a simulation of user activity sized to run in approximately 4 hours on a
480-500 node cluster using Hadoop 0.15.0. The benchmark runs a mix of small,
medium, and large jobs simultaneously, submitting each at fixed intervals.

Notes(1-4): Since input data are compressed, this means that each mapper
outputs a lot more bytes than it reads in, typically causing map output
spills.



* 1 Getting Started

1.0 Build

1) Compile the examples, including the C++ sources:
  > ant -Dcompile.c++=yes examples
2) Copy the pipe sort example to a location in the default filesystem
   (usually HDFS, default /gridmix/programs)
  > $HADOOP_PREFIX/hadoop dfs -mkdir $GRID_MIX_PROG
  > $HADOOP_PREFIX/hadoop dfs -put build/c++-examples/$PLATFORM_STR/bin/pipes-sort $GRID_MIX_PROG

1.1 Configure

One must modify hadoop-env to supply the following information:

HADOOP_PREFIX     The hadoop install location
GRID_MIX_HOME   The location of these scripts
APP_JAR         The location of the hadoop example
GRID_MIX_DATA   The location of the datsets for these benchmarks
GRID_MIX_PROG   The location of the pipe-sort example

Reasonable defaults are provided for all but HADOOP_PREFIX. The datasets used
by each of the respective benchmarks are recorded in the Input::hadoop-env
comment in section 0 and their location may be changed in hadoop-env. Note
that each job expects particular input data and the parameters given to it
must be changed in each script if a different InputFormat, keytype, or
valuetype is desired.

Note that NUM_OF_REDUCERS_FOR_*_JOB properties should be sized to the
cluster on which the benchmarks will be run. The default assumes a large
(450-500 node) cluster.

1.2 Generate test data

Test data is generated using the generateData.sh script. While one may
modify the structure and size of the data generated here, note that many of
the scripts- particularly for medium and small sized jobs- rely not only on
specific InputFormats and key/value types, but also on a particular
structure to the input data. Changing these values will likely be necessary
to run on small and medium-sized clusters, but any modifications must be
informed by an explicit familiarity with the underlying scripts.

It is sufficient to run the script without modification, though it may
require up to 4TB of free space in the default filesystem. Changing the size
of the input data (COMPRESSED_DATA_BYTES, UNCOMPRESSED_DATA_BYTES,
INDIRECT_DATA_BYTES) is safe. A 4x compression ratio for generated, block
compressed data is typical.

* 2 Running

2.0 General

The submissionScripts directory contains the high-level scripts submitting
sized jobs for the gridmix benchmark. Each submits $NUM_OF_*_JOBS_PER_CLASS
instances as specified in the gridmix-env script, where an instance is an
invocation of a script as in $JOBTYPE/$JOBTYPE.$CLASS (e.g.
javasort/text-sort.large). Each instance may submit one or more map/reduce
jobs.

There is a backoff script, submissionScripts/sleep_if_too_busy that can be
modified to define throttling criteria. By default, it simply counts running
java processes.

2.1 Non-Hod cluster

The submissionScripts/allToSameCluster script will invoke each of the other
submission scripts for the gridmix benchmark. Depending on how your cluster
manages job submission, these scripts may require modification. The details
are very context-dependent.

2.2 Hod

Note that there are options in hadoop-env that control jobs sumitted thruogh
Hod. One may specify the location of a config (HOD_CONFIG), the number of
nodes to allocate for classes of jobs, and any additional options one wants
to apply. The default includes an example for supplying a Hadoop tarball for
testing platform changes (see Hod documentation).

2.2.0 Static Cluster

> hod --hod.script=submissionScripts/allToSameCluster -m 500

2.2.1 Hod-allocated cluster

> ./submissionScripts/allThroughHod
