Mahout Naive Bayes 模型无法找到缓存文件问题

Posted 2023-03-13

【中文标题】Mahout Naive Bayes 模型无法找到缓存文件问题

【英文标题】：Mahout Naive Bayes Model Unable to find cached files issue

【发布时间】：2014-08-23 05:31:56

【问题描述】：

我已经导入了：

import org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob;

来自Mahout-Core-0.9-job

但是当我尝试调用以下方法时：

String[] trainerArgs = "-i", vectorsDirectory + "tfidf-vectors/",
                        "-o", modelDirectory,
                        "-l", labelIndex,
                        "-el", "-ow";

TrainNaiveBayesJob thisTrainer = new TrainNaiveBayesJob();
thisTrainer.run(trainerArgs);

我收到以下错误：

java.lang.Exception: java.lang.IllegalStateException: Unable to find cached files!
    at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:354)
Caused by: java.lang.IllegalStateException: Unable to find cached files!
    at com.google.common.base.Preconditions.checkState(Preconditions.java:176)
    at org.apache.mahout.common.HadoopUtil.getCachedFiles(HadoopUtil.java:300)
    at org.apache.mahout.common.HadoopUtil.getSingleCachedFile(HadoopUtil.java:281)
    at org.apache.mahout.classifier.naivebayes.BayesUtils.readIndexFromCache(BayesUtils.java:146)
    at org.apache.mahout.classifier.naivebayes.training.IndexInstancesMapper.setup(IndexInstancesMapper.java:41)
    at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:142)
    at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:764)
    at org.apache.hadoop.mapred.MapTask.run(MapTask.java:364)
    at org.apache.hadoop.mapred.LocalJobRunner$Job$MapTaskRunnable.run(LocalJobRunner.java:223)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
    at java.util.concurrent.FutureTask.run(FutureTask.java:262)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:744)

我到底在哪里漏掉了重点？有人可以指导我吗？

【参考方案1】：

只需将对 NaiveBayes 的调用更改为：

ToolRunner.run(new Configuration(), new TrainNaiveBayesJob(), trainerArgs);

解决了这个问题。