Hi Stanley,

Evaluating and analysing benchmark results of a system is complicated, it 
requires some deep understanding of the target system. Probably you can get 
some hints from papers about MapReduce/Hadoop, in which the experiment section 
typically provides good examples on how to evaluate test results. Benchmakring 
work for other systems (e.g., file systems) is probably helpful for you as well.

Wantao
 
 
------------------ Original ------------------
From:  "Marcos Ortiz"<[email protected]>;
Date:  Sun, May 8, 2011 02:14 PM
To:  "stanley.shi"<[email protected]>; 
Cc:  "mapreduce-user"<[email protected]>; 
Subject:  Re: FW: NNbench and MRBench

 
    El 5/8/2011 12:46 AM, [email protected] escribió:    Thanks Marcos. This 
post of  Michael Noll does provide some information about how to run these 
benchmarks, but there's not much information about how to evaluate the results. 
Do you know some resources about the result analysis? Thanks very much :) 
Regards, Stanley -----Original Message----- From: Marcos Ortiz 
[mailto:[email protected]]  Sent: 2011年5月8日 11:09 To: 
[email protected] Cc: Shi, Stanley Subject: Re: FW: NNbench and 
MRBench El 5/7/2011 10:33 PM, [email protected] escribió:           Thanks, 
Marcos, Through these links, I still can't find anything about the NNbench and 
MRBench. -----Original Message----- From: Marcos Ortiz [mailto:[email protected]] 
Sent: 2011年5月8日 10:23 To: [email protected] Cc: Shi, Stanley 
Subject: Re: FW: NNbench and MRBench El 5/7/2011 8:53 PM, [email protected] 
escribió:                     Hi guys, I have a cluster of 16 machines running 
Hadoop. Now I want to do some benchmark on this cluster with the "nnbench" and 
"mrbench". I'm new to the hadoop thing and have no one to refer to. I don't 
know what the supposed result should I have? Now for mrbench, I have an average 
time of 22sec for a one map job. Is this too bad? What the supposed results 
might be? For nnbench, what's the supposed results? Below is my result. 
================                              Date&   time: 2011-05-05 
20:40:25,459                           Test Operation: rename                   
            Start time: 2011-05-05 20:40:03,820                              
Maps to run: 1                           Reduces to run: 1                      
 Block Size (bytes): 1                           Bytes to write: 0              
         Bytes per checksum: 1                          Number of files: 10000  
                     Replication factor: 1               Successful file 
operations: 10000           # maps that missed the barrier: 0                   
          # exceptions: 0                              TPS: Rename: 1763        
       Avg Exec time (ms): Rename: 0.5672                     Avg Lat (ms): 
Rename: 0.4844 null                    RAW DATA: AL Total #1: 4844              
      RAW DATA: AL Total #2: 0                 RAW DATA: TPS Total (ms): 5672   
       RAW DATA: Longest Map Time (ms): 5672.0                      RAW DATA: 
Late maps: 0                RAW DATA: # of exceptions: 0 
============================= One more question, when I set maps number to 
bigger, I get all zeros results: ============================= Test Operation: 
create_write                               Start time: 2011-05-03 23:22:39,239  
                            Maps to run: 160                           Reduces 
to run: 160                       Block Size (bytes): 1                         
  Bytes to write: 0                       Bytes per checksum: 1                 
         Number of files: 1                       Replication factor: 1         
      Successful file operations: 0           # maps that missed the barrier: 0 
                            # exceptions: 0                  TPS: 
Create/Write/Close: 0 Avg exec time (ms): Create/Write/Close: 0.0               
Avg Lat (ms): Create/Write: NaN                      Avg Lat (ms): Close: NaN   
                 RAW DATA: AL Total #1: 0                    RAW DATA: AL Total 
#2: 0                 RAW DATA: TPS Total (ms): 0          RAW DATA: Longest 
Map Time (ms): 0.0                      RAW DATA: Late maps: 0                
RAW DATA: # of exceptions: 0 ===================== Can anyone point me to some 
documents? I really appreciate your help :) Thanks, stanley                     
  You can use these resources: 
http://www.michael-noll.com/blog/2011/04/09/benchmarking-and-stress-testing-an-hadoop-cluster-with-terasort-testdfsio-nnbench-mrbench/
 http://answers.oreilly.com/topic/460-how-to-benchmark-a-hadoop-cluster/ 
http://wiki.apache.org/hadoop/HardwareBenchmarks 
http://www.quora.com/Apache-Hadoop/Are-there-any-good-Hadoop-benchmark-problems 
Regards               Well, on the Micheal Noll's post says this: NameNode 
benchmark (nnbench) ======================= NNBench (see 
src/test/org/apache/hadoop/hdfs/NNBench.java) is useful for  load testing the 
NameNode hardware and configuration. It generates a lot  of HDFS-related 
requests with normally very small "payloads" for the  sole purpose of putting a 
high HDFS management stress on the NameNode.  The benchmark can simulate 
requests for creating, reading, renaming and  deleting files on HDFS. I like to 
run this test simultaneously from several machines -- e.g.  from a set of 
DataNode boxes -- in order to hit the NameNode from  multiple locations at the 
same time. The syntax of NNBench is as follows: NameNode Benchmark 0.4 Usage: 
nnbench <options> Options:          -operation <Available operations are 
create_write open_read  rename delete. This option is mandatory>           * 
NOTE: The open_read, rename and delete operations assume  that the files they 
operate on, are already available. The create_write  operation must be run 
before running the other operations.          -maps <number of maps. default is 
1. This is not mandatory>          -reduces <number of reduces. default is 1. 
This is not mandatory>          -startTime <time to start, given in seconds 
from the epoch.  Make sure this is far enough into the future, so all maps 
(operations)  will start at the same time>. default is launch time + 2 mins. 
This is  not mandatory          -blockSize <Block size in bytes. default is 1. 
This is not  mandatory>          -bytesToWrite <Bytes to write. default is 0. 
This is not mandatory>          -bytesPerChecksum <Bytes per checksum for the 
files. default is  1. This is not mandatory>          -numberOfFiles <number of 
files to create. default is 1. This  is not mandatory>          
-replicationFactorPerFile <Replication factor for the files.  default is 1. 
This is not mandatory>          -baseDir <base DFS path. default is 
/becnhmarks/NNBench. This  is not mandatory>          -readFileAfterOpen <true 
or false. if true, it reads the file  and reports the average time to read. 
This is valid with the open_read  operation. default is false. This is not 
mandatory>          -help: Display the help statement The following command 
will run a NameNode benchmark that creates 1000  files using 12 maps and 6 
reducers. It uses a custom output directory  based on the machine's short 
hostname. This is a simple trick to ensure  that one box does not accidentally 
write into the same output directory  of another box running NNBench at the 
same time. $ hadoop jar hadoop-*-test.jar nnbench -operation create_write \     
 -maps 12 -reduces 6 -blockSize 1 -bytesToWrite 0 -numberOfFiles 1000 \      
-replicationFactorPerFile 3 -readFileAfterOpen true \      -baseDir 
/benchmarks/NNBench-`hostname -s` Note that by default the benchmark waits 2 
minutes before it actually  starts! MapReduce benchmark (mrbench) 
======================= MRBench (see 
src/test/org/apache/hadoop/mapred/MRBench.java) loops a  small job a number of 
times. As such it is a very complimentary  benchmark to the "large-scale" 
TeraSort benchmark suite because MRBench  checks whether small job runs are 
responsive and running efficiently on  your cluster. It puts its focus on the 
MapReduce layer as its impact on  the HDFS layer is very limited. This test 
should be run from a single box (see caveat below). The  command syntax can be 
displayed via mrbench --help: MRBenchmark.0.0.2 Usage: mrbench [-baseDir ]      
      [-jar ]            [-numRuns ]            [-maps ]            [-reduces ] 
           [-inputLines ]            [-inputType ]            [-verbose]      
Important note: In Hadoop 0.20.2, setting the -baseDir parameter  has no 
effect. This means that multiple parallel MRBench runs (e.g.  started from 
different boxes) might interfere with each other. This is a  known bug 
(MAPREDUCE-2398). I have submitted a patch but it has not been  integrated yet. 
In Hadoop 0.20.2, the parameters default to: -baseDir: /benchmarks/MRBench  
[*** see my note above ***] -numRuns: 1 -maps: 2 -reduces: 1 -inputLines: 1 
-inputType: ascending The command to run a loop of 50 small test jobs is: $ 
hadoop jar hadoop-*-test.jar mrbench -numRuns 50 Exemplary output of the above 
command: DataLines       Maps    Reduces AvgTime (milliseconds) 1               
2       1       31414 This means that the average finish time of executed jobs 
was 31 seconds. Can you check this? 
http://www.slideshare.net/ydn/ahis2011-platform-hadoop-simulation-and-performance
 http://issues.apache.org/jira/browse/HADOOP-5867 Did you search on the current 
documentation of the API? Regards     Ok, I understand.
 Let me try to help you, because I'm a newie on the Hadoop ecosystem.
 Tom White on its answer to this topic on the OReilly Answers's Site does a 
introduction to this:
 
  
The following command writes 10 files of 1,000 MB each:
 % hadoop jar $HADOOP_INSTALL/hadoop-*-test.jar TestDFSIO -write -nrFiles 10 
-fileSize 1000  
At the end of the run, the results are written to the console and also recorded 
in a local file (which is appended to, so you can rerun the benchmark and not 
lose old results):
 % cat TestDFSIO_results.log ----- TestDFSIO ----- : write            Date & 
time: Sun Apr 12 07:14:09 EDT 2009        Number of files: 10 Total MBytes 
processed: 10000      Throughput mb/sec: 7.796340865378244 Average IO rate 
mb/sec: 7.8862199783325195  IO rate std deviation: 0.9101254683525547     Test 
exec time sec: 163.387  
The files are written under the /benchmarks/TestDFSIO directory by default 
(this can be changed by setting the test.build.data system property), in a 
directory called io_data.
 
To run a read benchmark, use the -read argument. Note that these files must 
already exist (having been written by TestDFSIO -write):
 % hadoop jar $HADOOP_INSTALL/hadoop-*-test.jar TestDFSIO -read -nrFiles 10  
-fileSize 1000  
Here are the results for a real run:
 ----- TestDFSIO ----- : read            Date & time: Sun Apr 12 07:24:28 EDT 
2009        Number of files: 10 Total MBytes processed: 10000      Throughput 
mb/sec: 80.25553361904304 Average IO rate mb/sec: 98.6801528930664  IO rate std 
deviation: 36.63507598174921 -----------------------------------------     Test 
exec time sec: 47.624  
When you’ve finished benchmarking, you can delete all the generated files from 
HDFS using the -clean argument:
 % hadoop jar $HADOOP_INSTALL/hadoop-*-test.jar TestDFSIO -clean 
 You can see that all results are written to the TestDFSIO_results.log.
 
 So, you can begin to experiment with this.
  You can continue this reading on the Chapter 9 of the Hadoop: The Definitive 
Guide 2nd Edition, on the topic: Benchmarking a Hadoop Cluster.
 
 In it, Tom gives several advices to benchmark  a Hadoop Cluster:
 
 - Use a cluster that is not been used by others
 - One of the primary test that one should do is a intensive I/O benchmark, to 
prove the cluster before it goes live to production
 - Write benchmarks with Gridmix (Check this 
http://developer.yahoo.net/blogs/hadoop/2010/04/gridmix3_emulating_production.html)
 
 
 Well, I hope that this information could help you. Remember, I've worked with 
Hadoop only for 1 year, so, you can ask for advices to others colleagues too.
 
 Regards --  Marcos Luís Ortíz Valmaseda  Software Engineer (Large-Scaled 
Distributed Systems)  University of Information Sciences,  La Habana, Cuba  
Linux User # 418229  http://about.me/marcosortiz

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