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
