使用 Java Mapper/Reducer 的 Hadoop Streaming

Question

我正在尝试使用 java Mapper/Reducer 在一些维基百科转储(压缩的 bz2 形式)上运行 hadoop 流作业。我正在尝试使用 WikiHadoop ，这是维基媒体最近发布的一个界面。

WikiReader_Mapper.java

package courseproj.example;

// Mapper: emits (token, 1) for every article occurrence.
public class WikiReader_Mapper extends MapReduceBase implements Mapper<Text, Text, Text, IntWritable> {

    // Reuse objects to save overhead of object creation.
    private final static Text KEY = new Text();
    private final static IntWritable VALUE = new IntWritable(1);

    @Override
    public void map(Text key, Text value, OutputCollector<Text, IntWritable> collector, Reporter reporter)
            throws IOException {
        KEY.set("article count");
        collector.collect(KEY, VALUE);
    }
}

WikiReader_Reducer.java

package courseproj.example;

//Reducer: sums up all the counts.
public class WikiReader_Reducer extends MapReduceBase implements Reducer<Text, IntWritable, Text, IntWritable> {

    private final static IntWritable SUM = new IntWritable();

    public void reduce(Text key, Iterator<IntWritable> values, OutputCollector<Text, IntWritable> collector,
            Reporter reporter) throws IOException {
        int sum = 0;
        while (values.hasNext()) {
            sum += values.next().get();
        }
        SUM.set(sum);
        collector.collect(key, SUM);
    }
}

我正在运行的命令是

hadoop jar lib/hadoop-streaming-2.0.0-cdh4.2.0.jar \
       -libjars lib2/wikihadoop-0.2.jar \
       -D mapreduce.input.fileinputformat.split.minsize=300000000 \
       -D mapreduce.task.timeout=6000000 \
       -D org.wikimedia.wikihadoop.previousRevision=false \
       -input enwiki-latest-pages-articles10.xml-p000925001p001325000.bz2 \
       -output out \
       -inputformat org.wikimedia.wikihadoop.StreamWikiDumpInputFormat \
       -mapper WikiReader_Mapper \
       -reducer WikiReader_Reducer

我得到的错误信息是

Error: java.lang.RuntimeException: Error in configuring object
    at org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:106)
    at org.apache.hadoop.util.ReflectionUtils.setConf(ReflectionUtils.java:72)
    at org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:130)
    at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:424)
    at org.apache.hadoop.mapred.MapTask.run(MapTask.java:340)
    at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:157)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:396)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1408)
    at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:152)

Caused by: java.lang.reflect.InvocationTargetException
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
    at java.lang.reflect.Method.invoke(Method.java:597)
    at org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:103)

Caused by: java.io.IOException: Cannot run program "WikiReader_Mapper": java.io.IOException: error=2, No such file or directory
    at java.lang.ProcessBuilder.start(ProcessBuilder.java:460)
    at org.apache.hadoop.streaming.PipeMapRed.configure(PipeMapRed.java:209)

与旧的相比，我更熟悉新的 hadoop API。由于我的 mapper 和 reducer 代码在两个不同的文件中，我在哪里定义作业的 JobConf 配置参数，同时遵循 hadoop 流的命令结构(明确设置 mapper 和 reducer 类)。有没有一种方法可以将映射器和缩减器代码全部包装到一个类中(扩展配置并实现工具，这是在新 API 中所做的)并将类名传递给 hadoop 流命令行与设置分别映射和归约类？

Answer 1

Streaming 使用旧的 API (org.apache.hadoop.mapred) - 但您的 mapper 和 reducer 类扩展了新的 API 类 (org.apache.hadoop.mapreduce >).

尝试更改您的映射器以实现 org.apache.hadoop.mapred.Mapper，并更改 reducer 以实现 org.apache.hadoop.mapred.Reducer，例如:

package courseproj.example;

// Mapper: emits ("article", 1) for every article occurrence.
public class WikiReader_Mapper implements Mapper<Text, Text, Text, IntWritable> {

  // Reuse objects to save overhead of object creation.
  private final static Text KEY = new Text();
  private final static IntWritable VALUE = new IntWritable(1);

  @Override
  public void map(Text key, Text value, OutputCollector<Text, IntWritable> collector, Reporter reporter)
      throws IOException, InterruptedException {
    KEY.set("article count");
    collector.collect(KEY, VALUE);
  }
}