找到接口org.apache.hadoop.mapreduce.taskattemptcontext

hfyxw5xn  于 2021-05-30  发布在  Hadoop
关注(0)|答案(2)|浏览(355)

到目前为止还没有找到解决我这个问题的办法。它至少不起作用。快把我逼疯了。这个特殊的组合在google空间里似乎并不多。我的错误发生在作业进入mapper的过程中。这个作业的输入是用deflate压缩的avro模式的输出,尽管我也尝试过解压缩。
avro:1.7.7 hadoop:2.4.1
我得到这个错误,我不知道为什么。这是我的工作,Map绘制和减少。当Map器进来时,错误就发生了。
示例未压缩的avro输入文件(stockreport.schema是这样定义的)

{"day": 3, "month": 2, "year": 1986, "stocks": [{"symbol": "AAME", "timestamp": 507833213000, "dividend": 10.59}]}

工作

@Override
public int run(String[] strings) throws Exception {
    Job job = Job.getInstance();
    job.setJobName("GenerateGraphsJob");
    job.setJarByClass(GenerateGraphsJob.class);

    configureJob(job);

    int resultCode = job.waitForCompletion(true) ? 0 : 1;

    return resultCode;
}

private void configureJob(Job job) throws IOException {
    try {
        Configuration config = getConf();
        Path inputPath = ConfigHelper.getChartInputPath(config);
        Path outputPath = ConfigHelper.getChartOutputPath(config);

        job.setInputFormatClass(AvroKeyInputFormat.class);
        AvroKeyInputFormat.addInputPath(job, inputPath);
        AvroJob.setInputKeySchema(job, StockReport.SCHEMA$);

        job.setMapperClass(StockAverageMapper.class);
        job.setCombinerClass(StockAverageCombiner.class);
        job.setReducerClass(StockAverageReducer.class);

        FileOutputFormat.setOutputPath(job, outputPath);

    } catch (IOException | ClassCastException e) {
        LOG.error("An job error has occurred.", e);
    }
}

Map器:

public class StockAverageMapper extends
        Mapper<AvroKey<StockReport>, NullWritable, StockYearSymbolKey, StockReport> {
    private static Logger LOG = LoggerFactory.getLogger(StockAverageMapper.class);

private final StockReport stockReport = new StockReport();
private final StockYearSymbolKey stockKey = new StockYearSymbolKey();

@Override
protected void map(AvroKey<StockReport> inKey, NullWritable ignore, Context context)
        throws IOException, InterruptedException {
    try {
        StockReport inKeyDatum = inKey.datum();
        for (Stock stock : inKeyDatum.getStocks()) {
            updateKey(inKeyDatum, stock);
            updateValue(inKeyDatum, stock);
            context.write(stockKey, stockReport);
        }
    } catch (Exception ex) {
        LOG.debug(ex.toString());
    }
}

Map输出键的架构:

{
  "namespace": "avro.model",
  "type": "record",
  "name": "StockYearSymbolKey",
  "fields": [
    {
      "name": "year",
      "type": "int"
    },
    {
      "name": "symbol",
      "type": "string"
    }
  ]
}

堆栈跟踪:

java.lang.Exception: java.lang.IncompatibleClassChangeError: Found interface org.apache.hadoop.mapreduce.TaskAttemptContext, but class was expected
    at org.apache.hadoop.mapred.LocalJobRunner$Job.runTasks(LocalJobRunner.java:462)
    at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:522)
Caused by: java.lang.IncompatibleClassChangeError: Found interface org.apache.hadoop.mapreduce.TaskAttemptContext, but class was expected
    at org.apache.avro.mapreduce.AvroKeyInputFormat.createRecordReader(AvroKeyInputFormat.java:47)
    at org.apache.hadoop.mapred.MapTask$NewTrackingRecordReader.<init>(MapTask.java:492)
    at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:735)
    at org.apache.hadoop.mapred.MapTask.run(MapTask.java:340)
    at org.apache.hadoop.mapred.LocalJobRunner$Job$MapTaskRunnable.run(LocalJobRunner.java:243)
    at java.util.concurrent.Executors$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:745)

编辑:这并不重要,但我正在努力将其简化为可以创建jfreechart输出的数据。没有通过Map器,所以这不应该是相关的。

uelo1irk

uelo1irk1#

问题是avro1.7.7支持两个版本的hadoop,因此依赖于这两个版本。默认情况下,avro1.7.7jar依赖于旧的hadoop版本。要使用avro1.7.7和hadoop2构建,只需添加额外的 classifier 行到maven依赖项:

<dependency>
        <groupId>org.apache.avro</groupId>
        <artifactId>avro-mapred</artifactId>
        <version>1.7.7</version>
        <classifier>hadoop2</classifier>
    </dependency>

这将告诉maven搜索 avro-mapred-1.7.7-hadoop2.jar ,不是 avro-mapred-1.7.7.jar 同样适用于avro 1.7.4及以上版本

u5i3ibmn

u5i3ibmn2#

问题是org.apache.hadoop.mapreduce.taskattemptcontext在hadoop1中是一个类,但在hadoop2中却变成了一个接口。
这就是为什么依赖于hadooplibs的库需要为hadoop1和hadoop2分别编译jar文件的原因之一。根据您的堆栈跟踪,似乎您得到了一个hadoop1编译的avrojarfile,尽管它是用hadoop2.4.1运行的。
avro的下载镜像为avro-mapred-1.7.7-hadoop1.jar和avro-mapred-1.7.7-hadoop2.jar提供了很好的单独下载。

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