- Hadoop MapReduce v2 Cookbook（Second Edition）
- Thilina Gunarathne
- 453字
- 2021-07-23 20:32:53
Benchmarking HDFS using DFSIO
Hadoop contains several benchmarks that you can use to verify whether your HDFS cluster is set up properly and performs as expected. DFSIO is a benchmark test that comes with Hadoop, which can be used to analyze the I/O performance of an HDFS cluster. This recipe shows how to use DFSIO to benchmark the read/write performance of an HDFS cluster.
Getting ready
You must set up and deploy HDFS and Hadoop v2 YARN MapReduce prior to running these benchmarks. Locate the hadoop-mapreduce-client-jobclient-*-tests.jar file in your Hadoop installation.
How to do it...
The following steps will show you how to run the write and read DFSIO performance benchmarks:
- Execute the following command to run the HDFS write performance benchmark. The
–nrFilesparameter specifies the number of files to be written by the benchmark. Use a number high enough to saturate the task slots in your cluster. The-fileSizeparameter specifies the file size of each file in MB. Change the location of thehadoop-mapreduce-client-jobclient-*-tests.jarfile in the following commands according to your Hadoop installation.$ hadoop jar \ $HADOOP_HOME/share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-*-tests.jar \ TestDFSIO -write -nrFiles 32 –fileSize 1000
- The write benchmark writes the results to the console as well as appending to a file named
TestDFSIO_results.log. You can provide your own result filename using the–resFileparameter. - The following step will show you how to run the HDFS read performance benchmark. The read performance benchmark uses the files written by the write benchmark in step 1. Hence, the write benchmark should be executed before running the read benchmark and the files written by the write benchmark should exist in the HDFS for the read benchmark to work properly. The benchmark writes the results to the console and appends the results to a logfile similarly to the write benchmark.
$hadoop jar \ $HADOOP_HOME/share/Hadoop/mapreduce/hadoop-mapreduce-client-jobclient-*-tests.jar \ TestDFSIO -read \ -nrFiles 32 –fileSize 1000
- The files generated by the preceding benchmarks can be cleaned up using the following command:
$hadoop jar \ $HADOOP_HOME/share/Hadoop/mapreduce/hadoop-mapreduce-client-jobclient-*-tests.jar \ TestDFSIO -clean
How it works...
DFSIO executes a MapReduce job where the Map tasks write and read the files in parallel, while the Reduce tasks are used to collect and summarize the performance numbers. You can compare the throughput and IO rate results of this benchmark with the total number of disks and their raw speeds to verify whether you are getting the expected performance from your cluster. Please note the replication factor when verifying the write performance results. High standard deviation in these tests may hint at one or more underperforming nodes due to some reason.
There's more...
Running these tests together with monitoring systems can help you identify the bottlenecks of your Hadoop cluster much easily.
- Implementing Modern DevOps
- Mobile Web Performance Optimization
- 零起步玩轉掌控板與Mind+
- 自制編譯器
- C# Programming Cookbook
- R語言游戲數據分析與挖掘
- Banana Pi Cookbook
- HTML5 and CSS3 Transition，Transformation，and Animation
- Learn React with TypeScript 3
- 飛槳PaddlePaddle深度學習實戰
- SQL基礎教程（第2版）
- Salesforce Reporting and Dashboards
- ExtJS Web應用程序開發指南第2版
- C++ System Programming Cookbook
- 超簡單：Photoshop+JavaScript+Python智能修圖與圖像自動化處理