写測试hadoop jarhadoop-0.20.2-test.jar TestDFSIO -write -nrFiles 10 -fileSize 1000
----- TestDFSIO ----- : write
Date & time: Fri Jul 24 14:24:36 CST 2015
Number of files: 10
Total MBytes processed: 10000
Throughput mb/sec: 24.302163378583963
Average IO rate mb/sec: 24.46268653869629
IOrate std deviation: 2.0279575539782315
Test exec time sec: 72.853
读測试hadoop jarhadoop-0.20.2-test.jar TestDFSIO -read -nrFiles 10 -fileSize 1000
----- TestDFSIO ----- : read
Date & time: Fri Jul 24 14:27:11 CST 2015
Number of files: 10
Total MBytes processed: 10000
Throughput mb/sec: 80.73566336457803
Average IO rate mb/sec: 106.7965087890625
IOrate std deviation: 70.18198197030486
Test exec time sec: 46.772
清除数据
[root@ZhejiangYiwuF1210 hadoop]# hadoop jarhadoop-0.20.2-test.jar TestDFSIO -clean
排序測试
1.在各节点上分别执行2个map任务。每一个节点产生1GB大小的随机二进制数据，并输出到文件夹/examples/terasort-input
hadoop jar hadoop-0.20.2-examples.jar teragen 10000000/examples/terasort-input
Launched map tasks=2
FileSystemCounters
HDFS_BYTES_WRITTEN=1000000000
Map-Reduce Framework
Map input records=10000000
Spilled Records=0
Map input bytes=10000000
Map output records=10000000
MapReduce（map:2个,reduce:0个）
2.排序。并将结果输出到文件夹/examples/terasort-output
#hadoop jar hadoop-0.20.2-examples.jar terasort /examples/terasort-input/examples/terasort-output
MapReduce（map:16个,reduce:1个）
3.检查是否已经排好序
# hadoop jar hadoop-0.20.2-examples.jarteravalidate /examples/terasort-output /examples/terasort-validate
MapReduce（map:1个,reduce:1个）
Namenode的负载測试
# hadoop jar hadoop-0.20.2-test.jarnnbench -operation create_write -maps 12 -reduces 6 -blockSize 1 -bytesToWrite0 -numberOfFiles 1000 -replicationFactorPerFile 3 -readFileAfterOpen true-baseDir /benchmarks/NNBench-`hostname
-s`
-------------- NNBench -------------- :
Version:NameNode Benchmark 0.4
Date& time: 2015-07-24 14:52:04,989
TestOperation: create_write
Starttime: 2015-07-24 14:48:46,912
Maps torun: 12
Reducesto run: 6
BlockSize (bytes): 1
Bytes towrite: 0
Bytesper checksum: 1
Numberof files: 1000
Replicationfactor: 3
Successfulfile operations: 0
MapReduce（map:12个,reduce:6个）
MapReduce连续性測试
mrbench会多次反复执行一个小作业，用于检查在机群上小作业的执行是否可反复以及执行是否高效
执行一个小作业10次
hadoop jar hadoop-0.20.2-test.jar mrbench -numRuns 10
DataLines Maps Reduces AvgTime (milliseconds)
1 2 1 29637
以上结果表示平均作业完毕时间是29637(milliseconds)
文件系统一致性的分布式检查
hadoop jarhadoop-0.20.2-test.jar DistributedFSCheck
----- DistributedFSCheck ----- :
Date & time: Fri Jul 2415:04:18 CST 2015
Total number of blocks: 58
Total number of files: 3171
Number of corrupted blocks: 0
Number of corrupted files: 0
MapReduce（map:2个,reduce:1个）