Hadoop自带了几个基准测试，本文使用的是hadoop-2.6.0
一、Hadoop Test 的测试
[root@master hadoop-2.6.0]# hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.6.0-tests.jar
An example program must be given as the first argument.
Valid program names are:
DFSCIOTest: Distributed i/o benchmark of libhdfs.
DistributedFSCheck: Distributed checkup of the file system consistency.
JHLogAnalyzer: Job History Log analyzer.
MRReliabilityTest: A program that tests the reliability of the MR framework by injecting faults/failures
SliveTest: HDFS Stress Test and Live Data Verification.
TestDFSIO: Distributed i/o benchmark.
fail: a job that always fails
filebench: Benchmark SequenceFile(Input|Output)Format (block,record compressed and uncompressed), Text(Input|Output)Format (compressed and uncompressed)
largesorter: Large-Sort tester
loadgen: Generic map/reduce load generator
mapredtest: A map/reduce test check.
minicluster: Single process HDFS and MR cluster.
mrbench: A map/reduce benchmark that can create many small jobs
nnbench: A benchmark that stresses the namenode.
sleep: A job that sleeps at each map and reduce task.
testbigmapoutput: A map/reduce program that works on a very big non-splittable file and does identity map/reduce
testfilesystem: A test for FileSystem read/write.
testmapredsort: A map/reduce program that validates the map-reduce framework’s sort.
testsequencefile: A test for flat files of binary key value pairs.
testsequencefileinputformat: A test for sequence file input format.
testtextinputformat: A test for text input format.
threadedmapbench: A map/reduce benchmark that compares the performance of maps with multiple spills over maps with 1 spill
这些例子从多个角度对Hadoop进行测试，其中 TestDFSIO、mrbench和nnbench是三个广泛被使用的测试。
1、TestDFSIO 测试
① TestDFSIO write
测试hadoop写的速度。
TestDFSIO的用法如下：
Usage: TestDFSIO [genericOptions] -read [-random | -backward | -skip [-skipSize Size]] | -write | -append | -clean [-compression codecClassName] [-nrFiles N] [-size Size[B|KB|MB|GB|TB]] [-resFile resultFileName] [-bufferSize Bytes] [-rootDir]
向HDFS文件系统中写入数据，10个文件，每个文件10MB，文件存放到/benchmarks/TestDFSIO/io_data下面。
[root@master hadoop-2.6.0]# hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.6.0-tests.jar TestDFSIO -write -nrFiles 10 -size 10MB
跑出来的数据如下图：
查看写入的结果：
[root@master hadoop-2.6.0]# cat TestDFSIO_results.log
----- TestDFSIO ----- : write
Date & time: Fri Sep 23 19:21:01 CST 2016
Number of files: 10
Total MBytes processed: 100.0
Throughput mb/sec: 1.7217037980785785
Average IO rate mb/sec: 1.9971516132354736
IO rate std deviation: 0.9978736646901237
Test exec time sec: 81.711
② TestDFSIO read
测试hadoop读文件的速度
从HDFS文件系统中读入10个文件，每个文件大小为10MB
[root@master hadoop-2.6.0]# hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.6.0-tests.jar TestDFSIO -read -nrFiles 10 -size 10
[root@master hadoop-2.6.0]# cat TestDFSIO_results.log
----- TestDFSIO ----- : write
Date & time: Fri Sep 23 19:21:01 CST 2016
Number of files: 10
Total MBytes processed: 100.0
Throughput mb/sec: 1.7217037980785785
Average IO rate mb/sec: 1.9971516132354736
IO rate std deviation: 0.9978736646901237
Test exec time sec: 81.711
----- TestDFSIO ----- : read
Date & time: Fri Sep 23 19:37:21 CST 2016
Number of files: 10
Total MBytes processed: 100.0
Throughput mb/sec: 14.85001485001485
Average IO rate mb/sec: 16.221948623657227
IO rate std deviation: 4.983088493832205
Test exec time sec: 50.188
③ 清空测试数据
[root@master hadoop-2.6.0]# hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.6.0-tests.jar TestDFSIO -clean
如下图所示：
2、nnbench 测试 [NameNode benchmark (nnbench)]
nnbench用于测试NameNode的负载，它会生成很多与HDFS相关的请求，给NameNode施加较大的压力。
这个测试能在HDFS上创建、读取、重命名和删除文件操作。
nnbench 的用法：
[root@master hadoop-2.6.0]# hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.6.0-tests.jar nnbench
NameNode Benchmark 0.4
Usage: nnbench
Options:
-operation
以下例子使用10个mapper和5个reducer来创建1000个文件
[root@master hadoop-2.6.0]# hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.6.0-tests.jar nnbench -operation create_write -maps 10 -reduces 5 -numberOfFiles 1000 -replicationFactorPerFile 3 -readFileAfterOpen true
3、mrbench测试[MapReduce benchmark (mrbench)]
mrbench会多次重复执行一个小作业，用于检查在机群上小作业的运行是否可重复以及运行是否高效。
[root@master hadoop-2.6.0]# hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.6.0-tests.jar mrbench --help
MRBenchmark.0.0.2
Usage: mrbench [-baseDir <base DFS path for output/input, default is /benchmarks/MRBench>] [-jar <local path to job jar file containing Mapper and Reducer implementations, default is current jar file>] [-numRuns <number of times to run the job, default is 1>] [-maps <number of maps for each run, default is 2>] [-reduces <number of reduces for each run, default is 1>] [-inputLines <number of input lines to generate, default is 1>] [-inputType <type of input to generate, one of ascending (default), descending, random>] [-verbose]
下面的例子会运行一个小作业50次：
[root@master hadoop-2.6.0]# hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.6.0-tests.jar mrbench -numRuns 50
这样会运行50次。
二、Hadoop Examples 的测试
[root@master hadoop-2.6.0]# hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0.jar
An example program must be given as the first argument.
Valid program names are:
aggregatewordcount: An Aggregate based map/reduce program that counts the words in the input files.
aggregatewordhist: An Aggregate based map/reduce program that computes the histogram of the words in the input files.
bbp: A map/reduce program that uses Bailey-Borwein-Plouffe to compute exact digits of Pi.
dbcount: An example job that count the pageview counts from a database.
distbbp: A map/reduce program that uses a BBP-type formula to compute exact bits of Pi.
grep: A map/reduce program that counts the matches of a regex in the input.
join: A job that effects a join over sorted, equally partitioned datasets
multifilewc: A job that counts words from several files.
pentomino: A map/reduce tile laying program to find solutions to pentomino problems.
pi: A map/reduce program that estimates Pi using a quasi-Monte Carlo method.
randomtextwriter: A map/reduce program that writes 10GB of random textual data per node.
randomwriter: A map/reduce program that writes 10GB of random data per node.
secondarysort: An example defining a secondary sort to the reduce.
sort: A map/reduce program that sorts the data written by the random writer.
sudoku: A sudoku solver.
teragen: Generate data for the terasort
terasort: Run the terasort
teravalidate: Checking results of terasort
wordcount: A map/reduce program that counts the words in the input files.
wordmean: A map/reduce program that counts the average length of the words in the input files.
wordmedian: A map/reduce program that counts the median length of the words in the input files.
wordstandarddeviation: A map/reduce program that counts the standard deviation of the length of the words in the input files.
最常用的就是 wordcount。
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原文链接：https://blog.csdn.net/u012689336/article/details/52635513
来源：CSDN
作者：奈斯Ekko
链接：https://blog.csdn.net/weixin_42946624/article/details/104504574