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今天调研了并行化频繁模式挖掘算法PFP Growth及其在Mahout下的命令使用，简单记录下试验结果，供以后查阅：
- 环境：Jdk1.7 + Hadoop2.2.0单机伪集群 + Mahout0.6（0.8和0.9版本都不包含该算法。Mahout0.6可以和Hadoop2.2.0和平共处有点意外orz）
- 部分输入数据，输入数据一行代表一个购物篮：
4750,19394,25651,6395,5592
26180,10895,24571,23295,20578,27791,2729,8637 7380,18805,25086,19048,3190,21995,10908,12576 3458,12426,20578 1880,10702,1731,5185,18575,28967 21815,10872,18730 20626,17921,28930,14580,2891,11080 18075,6548,28759,17133 7868,15200,13494 7868,28617,18097,22999,16323,8637,7045,25733 12189,8816,22950,18465,13258,27791,20979 26728 17512,14821,18741 26619,14470,21899,6731 5184 28653,28662,18353,27437,5661,12078,11849,15784,7248,7061,18612,24277,4807,15584,9671,18741,3647,1000。。。。。。
- 执行命令：
mahout fpg -i /workspace/dataguru/hadoopdev/week13/fpg/in/ -o /workspace/dataguru/hadoopdev/week13/fpg/out -method mapreduce -s 3
参数说明：
-i 输入路径，由于运行在hadoop环境中，所以输入路径必须是hdfs路径，实验的输入路径是/workspace/dataguru/hadoopdev/week13/fpg/in/user2items.csv
-o 输出路径，指定hdfs中的输出路径
完整参数说明参见下表：
- 命令执行以后的输出目录：
casliyang@singlehadoop:~$ hadoop dfs -ls /workspace/dataguru/hadoopdev/week13/fpg/out
DEPRECATED: Use of this script to execute hdfs command is deprecated. Instead use the hdfs command for it. Found 4 items -rw-r--r-- 3 casliyang supergroup 5567 2014-06-17 17:50 /workspace/dataguru/hadoopdev/week13/fpg/out/fList drwxr-xr-x - casliyang supergroup 0 2014-06-17 17:51 /workspace/dataguru/hadoopdev/week13/fpg/out/fpgrowth drwxr-xr-x - casliyang supergroup 0 2014-06-17 17:51 /workspace/dataguru/hadoopdev/week13/fpg/out/frequentpatterns drwxr-xr-x - casliyang supergroup 0 2014-06-17 17:50 /workspace/dataguru/hadoopdev/week13/fpg/out/parallelcounting挖掘出来的频繁模式在frequentpatterns文件夹下
casliyang@singlehadoop:~$ hadoop dfs -ls /workspace/dataguru/hadoopdev/week13/fpg/out/frequentpatterns
DEPRECATED: Use of this script to execute hdfs command is deprecated. Instead use the hdfs command for it. Found 2 items -rw-r--r-- 3 casliyang supergroup 0 2014-06-17 17:51 /workspace/dataguru/hadoopdev/week13/fpg/out/frequentpatterns/_SUCCESS -rw-r--r-- 3 casliyang supergroup 10017 2014-06-17 17:51 /workspace/dataguru/hadoopdev/week13/fpg/out/frequentpatterns/part-r-00000该文件是序列化文件，不能直接查看，mahout提供了命令可以将其转换为普通文本：
mahout seqdumper -s /workspace/dataguru/hadoopdev/week13/fpg/out/frequentpatterns/part-r-00000 -o /home/casliyang/outpattern
这里要注意，-o指定的输出文件路径必须是linux文件系统，并且目标文件必须提前创建好，否则会报错。
- 最终输出到/home/casliyang/outpattern的部分结果
Key: 29099: Value: ([29099],18), ([29099, 4479],3) Key: 29202: Value: ([29202],3) Key: 29203: Value: ([29203],9), ([14020, 29203],3) Key: 29224: Value: ([29224],3) Key: 29547: Value: ([29547],5) Key: 2963: Value: ([2963],8), ([2963, 21146],3) Key: 2999: Value: ([2999],3) Key: 3032: Value: ([3032],4) Key: 3047: Value: ([3047],4) Key: 3151: Value: ([3151],7), ([14020, 3151],4) Key: 3181: Value: ([3181],3) Key: 3228: Value: ([3228],14) Key: 3313: Value: ([3313],3) Key: 3324: Value: ([3324],3) Key: 3438: Value: ([3438],3) Key: 3458: Value: ([3458],4) Key: 3627: Value: ([3627],11), ([3627, 11176],3)
。。。。。。
含义：
Key：itemid
Value：和该item相关的频繁模式及其支持度
有了挖掘出来的频繁模式，就可以进一步用程序根据业务需求做处理了。
Mahout真是个伟大的开源项目！