從HDFS讀取並寫入HBASE

Question

映射器正在從兩個位置讀取文件1）用戶訪問過的文章（按國家分類）2）國家的統計信息（按國家/地區）

兩個Mapper的輸出是Text，Text

我正在運行Amazon Cluster的程序

我的目標是從兩個不同的集合中讀取數據，並將結果合並並存儲在hbase中。

HDFS到HDFS正常運行。 代碼陷入減少67％並給出錯誤

17/02/24 10:45:31 INFO mapreduce.Job:  map 0% reduce 0%
17/02/24 10:45:37 INFO mapreduce.Job:  map 100% reduce 0%
17/02/24 10:45:49 INFO mapreduce.Job:  map 100% reduce 67%
17/02/24 10:46:00 INFO mapreduce.Job: Task Id : attempt_1487926412544_0016_r_000000_0, Status : FAILED
Error: java.lang.IllegalArgumentException: Row length is 0
        at org.apache.hadoop.hbase.client.Mutation.checkRow(Mutation.java:565)
        at org.apache.hadoop.hbase.client.Put.<init>(Put.java:110)
        at org.apache.hadoop.hbase.client.Put.<init>(Put.java:68)
        at org.apache.hadoop.hbase.client.Put.<init>(Put.java:58)
        at com.happiestminds.hadoop.CounterReducer.reduce(CounterReducer.java:45)
        at com.happiestminds.hadoop.CounterReducer.reduce(CounterReducer.java:1)
        at org.apache.hadoop.mapreduce.Reducer.run(Reducer.java:171)
        at org.apache.hadoop.mapred.ReduceTask.runNewReducer(ReduceTask.java:635)
        at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:390)
        at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:164)
        at java.security.AccessController.doPrivileged(Native Method)
        at javax.security.auth.Subject.doAs(Subject.java:422)
        at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
        at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:158)

驅動程序類為

package com.happiestminds.hadoop;



import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.MasterNotRunningException;
import org.apache.hadoop.hbase.client.HBaseAdmin;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.MultipleInputs;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;


public class Main extends Configured implements Tool {

    /**
     * @param args
     * @throws Exception
     */
    public static String outputTable = "mapreduceoutput";

    public static void main(String[] args) throws Exception {
        int exitCode = ToolRunner.run(new Main(), args);
        System.exit(exitCode);
    }

    @Override
    public int run(String[] args) throws Exception {


        Configuration config = HBaseConfiguration.create();

        try{
            HBaseAdmin.checkHBaseAvailable(config);
        }
        catch(MasterNotRunningException e){
            System.out.println("Master not running");
            System.exit(1);
        }

        Job job = Job.getInstance(config, "Hbase Test");

        job.setJarByClass(Main.class);

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(Text.class);



        MultipleInputs.addInputPath(job, new Path(args[0]), TextInputFormat.class, ArticleMapper.class);
        MultipleInputs.addInputPath(job, new Path(args[1]), TextInputFormat.class, StatisticsMapper.class);

        TableMapReduceUtil.addDependencyJars(job);
        TableMapReduceUtil.initTableReducerJob(outputTable, CounterReducer.class, job);

        //job.setReducerClass(CounterReducer.class);

        job.setNumReduceTasks(1);


        return job.waitForCompletion(true) ? 0 : 1;
    }

}

減速器類為

package com.happiestminds.hadoop;

import java.io.IOException;

import org.apache.hadoop.hbase.client.Mutation;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.TableReducer;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;


public class CounterReducer extends TableReducer<Text, Text, ImmutableBytesWritable> {

    public static final byte[] CF = "counter".getBytes();
    public static final byte[] COUNT = "combined".getBytes();


    @Override
    protected void reduce(Text key, Iterable<Text> values,
            Reducer<Text, Text, ImmutableBytesWritable, Mutation>.Context context)
            throws IOException, InterruptedException {

        String vals = values.toString();
        int counter = 0;

        StringBuilder sbr = new StringBuilder();
        System.out.println(key.toString());
        for (Text val : values) {
            String stat = val.toString();
            if (stat.equals("***")) {
                counter++;
            } else {
                sbr.append(stat + ",");
            }

        }
        sbr.append("Article count : " + counter);


        Put put = new Put(Bytes.toBytes(key.toString()));
        put.addColumn(CF, COUNT, Bytes.toBytes(sbr.toString()));
        if (counter != 0) {
            context.write(null, put);
        }

    }



}

依存關系

<dependencies>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>2.7.3</version>
        </dependency>



        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-client</artifactId>
            <version>1.2.2</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-common</artifactId>
            <version>1.2.2</version>
        </dependency>


        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-server</artifactId>
            <version>1.2.2</version>
        </dependency>



    </dependencies>

Answer 1

一個好的做法是在將值提交到某個地方之前先對其進行驗證。 在您的特定情況下，你可以驗證你的密鑰和SBR或將其包裝成適當的通知政策的try-catch部分。 如果它們不正確，則應將它們輸出到一些日志中，並使用新的測試用例更新單元測試：

 try
 {
    Put put = new Put(Bytes.toBytes(key.toString()));
    put.addColumn(CF, COUNT, Bytes.toBytes(sbr.toString()));
    if (counter != 0) {
        context.write(null, put);
    }
 }
 catch (IllegalArgumentException ex)
 {
      System.err.println("Error processing record - Key: "+ key.toString() +", values: " +sbr.ToString());
 }

Answer 2

根據程序拋出的異常，很明顯密鑰長度為0，因此在放入hbase之前，您可以檢查密鑰長度是否為0，然后只能放入hbase。

更清楚為什么hbase不支持密鑰長度為0

因為HBase數據模型不允許長度為0的行鍵，所以它至少應為1個字節。 保留0字節的行鍵供內部使用（指定空的開始鍵和結束鍵）。

Answer 3

您可以嘗試檢查是否要插入任何空值嗎？

HBase數據模型不允許長度為零的行鍵，它至少應為1個字節。

請在執行put命令之前檢查您的reducer代碼，是否將某些值填充為null。

Answer 4

您得到的錯誤是不言自明的。 HBase中的行鍵不能為空（盡管值可以為空）。

@Override
protected void reduce(Text key, Iterable<Text> values,
        Reducer<Text, Text, ImmutableBytesWritable, Mutation>.Context context)
        throws IOException, InterruptedException {
    if (key == null || key.getLength() == 0) {
      // Log a warning about the empty key.
      return;
    }
    // Rest of your reducer follows.
}