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run-hadoopbench.md

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1. Setup

  • Python 2.x(>=2.6) is required.

  • Supported Hadoop version: Apache Hadoop 2.x, CDH5.x, HDP

  • Build HiBench according to build HiBench.

  • Start HDFS, Yarn in the cluster.

2. Configure hadoop.conf

Create and edit conf/hadoop.conf：

cp conf/hadoop.conf.template conf/hadoop.conf

Set the below properties properly:

Property Meaning
hibench.hadoop.home The Hadoop installation location
hibench.hadoop.executable The path of hadoop executable. For Apache Hadoop, it is /YOUR/HADOOP/HOME/bin/hadoop
hibench.hadoop.configure.dir Hadoop configuration directory. For Apache Hadoop, it is /YOUR/HADOOP/HOME/etc/hadoop
hibench.hdfs.master The root HDFS path to store HiBench data, i.e. hdfs://localhost:8020/user/username
hibench.hadoop.release Hadoop release provider. Supported value: apache, cdh5, hdp

Note: For CDH and HDP users, please update hibench.hadoop.executable, hibench.hadoop.configure.dir and hibench.hadoop.release properly. The default value is for Apache release.

3. Run a workload

To run a single workload i.e. wordcount.

 bin/workloads/micro/wordcount/prepare/prepare.sh
 bin/workloads/micro/wordcount/hadoop/run.sh

The prepare.sh launchs a hadoop job to genereate the input data on HDFS. The run.sh submits the hadoop job to the cluster. bin/run-all.sh can be used to run all workloads listed in conf/benchmarks.lst and conf/frameworks.lst.

4. View the report

The <HiBench_Root>/report/hibench.report is a summarized workload report, including workload name, execution duration, data size, throughput per cluster, throughput per node.

The report directory also includs further information for debuging and tuning.

  • <workload>/hadoop/bench.log: Raw logs on client side.
  • <workload>/hadoop/monitor.html: System utilization monitor results.
  • <workload>/hadoop/conf/<workload>.conf: Generated environment variable configurations for this workload.

5. Input data size

To change the input data size, you can set hibench.scale.profile in conf/hibench.conf. Available values are tiny, small, large, huge, gigantic and bigdata. The definition of these profiles can be found in the workload's conf file i.e. conf/workloads/micro/wordcount.conf

6. Tuning

Change the below properties in conf/hibench.conf to control the parallelism.

Property Meaning
hibench.default.map.parallelism Mapper number in hadoop
hibench.default.shuffle.parallelism Reducer number in hadoop