我想运行一个地图缩小例如：HBase的ClassNotFoundException的
package my.test;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
import java.util.Map.Entry;
import org.apache.commons.cli.BasicParser;
import org.apache.commons.cli.CommandLine;
import org.apache.commons.cli.CommandLineParser;
import org.apache.commons.cli.HelpFormatter;
import org.apache.commons.cli.Options;
import org.apache.commons.cli.ParseException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.MultiTableOutputFormat;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
import org.apache.log4j.Logger;
/**
* This class demonstrates the use of the MultiTableOutputFormat class.
* Using this class we can write the output of a Hadoop map reduce program
* into different HBase table.
*
* @version 1.0 19 Jul 2011
* @author Wildnove
*/
public class TestMultiTable extends Configured implements Tool {
private static final Logger LOG = Logger.getLogger(TestMultiTable.class);
private static final String CMDLINE = "com.wildnove.tutorial.TestMultiTable <inputFile> [-n name] [-s]";
public static void main(String[] args) throws Exception {
int res = ToolRunner.run(new TestMultiTable(), args);
System.exit(res);
}
@Override
public int run(String[] args) throws Exception {
HelpFormatter help = new HelpFormatter();
Options options = new Options();
options.addOption("h", "help", false, "print program usage");
options.addOption("n", "name", true, "sets job name");
CommandLineParser parser = new BasicParser();
CommandLine cline;
try {
cline = parser.parse(options, args);
args = cline.getArgs();
if (args.length < 1) {
help.printHelp(CMDLINE, options);
return -1;
}
} catch (ParseException e) {
System.out.println(e);
e.printStackTrace();
help.printHelp(CMDLINE, options);
return -1;
}
String name = null;
try {
if (cline.hasOption('n'))
name = cline.getOptionValue('n');
else
name = "wildnove.com - Tutorial MultiTableOutputFormat ";
Configuration conf = getConf();
FileSystem fs = FileSystem.get(conf);
Path inputFile = new Path(fs.makeQualified(new Path(args[0])).toUri().getPath());
if (!getMultiTableOutputJob(name, inputFile).waitForCompletion(true))
return -1;
} catch (Exception e) {
System.out.println(e);
e.printStackTrace();
help.printHelp(CMDLINE, options);
return -1;
}
return 0;
}
/**
* Here we configure our job to use MultiTableOutputFormat class as map reduce output.
* Note that we use 1 reduce only for debugging purpose, but you can use more than 1 reduce.
*/
private Job getMultiTableOutputJob(String name, Path inputFile) throws IOException {
if (LOG.isInfoEnabled()) {
LOG.info(name + " starting...");
LOG.info("computing file: " + inputFile);
}
Job job = new Job(getConf(), name);
job.setJarByClass(TestMultiTable.class);
job.setMapperClass(Mapper.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Text.class);
FileInputFormat.addInputPath(job, inputFile);
job.setOutputFormatClass(MultiTableOutputFormat.class);
job.setNumReduceTasks(1);
job.setReducerClass(Reducer.class);
return job;
}
private static class Mapper extends org.apache.hadoop.mapreduce.Mapper<LongWritable, Text, Text, Text> {
private Text outKey = new Text();
private Text outValue = new Text();
/**
* The map method splits the csv file according to this structure
* brand,model,size (e.g. Cadillac,Seville,Midsize) and output all data using
* brand as key and the couple model,size as value.
*/
@Override
public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
String[] valueSplitted = value.toString().split(",");
if (valueSplitted.length == 3) {
String brand = valueSplitted[0];
String model = valueSplitted[1];
String size = valueSplitted[2];
outKey.set(brand);
outValue.set(model + "," + size);
context.write(outKey, outValue);
}
}
}
private static class Reducer extends org.apache.hadoop.mapreduce.Reducer<Text, Text, ImmutableBytesWritable, Writable> {
/**
* The reduce method fill the TestCars table with all csv data,
* compute some counters and save those counters into the TestBrandsSizes table.
* So we use two different HBase table as output for the reduce method.
*/
@Override
protected void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
Map<String, Integer> statsSizeCounters = new HashMap<String, Integer>();
String brand = key.toString();
// We are receiving all models,size grouped by brand.
for (Text value : values) {
String[] valueSplitted = value.toString().split(",");
if (valueSplitted.length == 2) {
String model = valueSplitted[0];
String size = valueSplitted[1];
// Fill the TestCars table
ImmutableBytesWritable putTable = new ImmutableBytesWritable(Bytes.toBytes("TestCars"));
byte[] putKey = Bytes.toBytes(brand + "," + model);
byte[] putFamily = Bytes.toBytes("Car");
Put put = new Put(putKey);
// qualifier brand
byte[] putQualifier = Bytes.toBytes("brand");
byte[] putValue = Bytes.toBytes(brand);
put.add(putFamily, putQualifier, putValue);
// qualifier model
putQualifier = Bytes.toBytes("model");
putValue = Bytes.toBytes(model);
put.add(putFamily, putQualifier, putValue);
// qualifier size
putQualifier = Bytes.toBytes("size");
putValue = Bytes.toBytes(size);
put.add(putFamily, putQualifier, putValue);
context.write(putTable, put);
// Compute some counters: number of different sizes for a brand
if (!statsSizeCounters.containsKey(size))
statsSizeCounters.put(size, 1);
else
statsSizeCounters.put(size, statsSizeCounters.get(size) + 1);
}
}
for (Entry<String, Integer> entry : statsSizeCounters.entrySet()) {
// Fill the TestBrandsSizes table
ImmutableBytesWritable putTable = new ImmutableBytesWritable(Bytes.toBytes("TestBrandsSizes"));
byte[] putKey = Bytes.toBytes(brand);
byte[] putFamily = Bytes.toBytes("BrandSizes");
Put put = new Put(putKey);
// We can use as qualifier the sizes
byte[] putQualifier = Bytes.toBytes(entry.getKey());
byte[] putValue = Bytes.toBytes(entry.getValue());
put.add(putFamily, putQualifier, putValue);
context.write(putTable, put);
}
}
}
}
构建到罐子mt.jar与Eclipse选项：jar文件
运行的MapReduce：
[zhouhh @ Hadoop48〜] $ HADOOP_CLASSPATH =
${HBASE_HOME}/bin/hbase classpath：${HADOOP_HOME}/bin/hadoop classpath$ {HADOOP_HOME}/bin/hadoop jar mt.jar cars.csv 12/06/11 20:14:33信息 test.TestMultiTable：wildnove.com - Tut orial MultiTableOutputFormat starting ... 12/06/11 20:14:33 INFO test.TestMultiTable：computing file：/user/zhouhh/cars.csv 12/06/11 20:14:34 INFO input.FileInputFormat：总输入路径进程：1 12/06/11 20:14:34 INFO util.NativeCodeLoader：加载本机hadoop库 12/06/11 20:14:34 WARN snappy.LoadSnappy：Snappy本机库不是 已加载12/06/11 20:14:35信息mapred.JobClient：正在运行的作业： job_201206111811_0012 12/06/11 20:14:36信息mapred.JobClient：地图0％ 减少0％12/06/11 20： 14:42信息mapred.JobClient：任务ID： attempt_201206111811_0012_m_000002_0，状态：失败 java.lang.RuntimeException：java.lang.ClassNotFoundException： org.apache.hadoop.hbase.mapreduce.MultiTableOutputFormat at org.apache.hadoop.conf.Configuration.getClass（Configuration.java:867） at org.apache.hadoop.mapreduce.JobContext.getOutputFormatClass（JobContext.java： 235） at org.apache.hadoop.mapred.Task.initialize（Task.java:513） at org.apache.hadoop.mapred.MapTask.run（MapTask.java:353） at org.apache.hadoop。 mapred.Child $ 4.run（Child.java:255） at java.security.AccessController.doPrivileged（Native Method） at javax.security.auth.Subject.doAs（Subject.java:415） at org.apache。 hadoop.security.UserGroupInformation.doAs（UserGroupInformation.java:1121） at org.apache.hadoop.mapred.Child.main（Child.java:249）引起：java.lang.ClassNotFoundExcep重刑： org.apache.hadoop.hbase.mapreduce.MultiTableOutputFormat 在java.net.URLClassLoader的$ 1.run（URLClassLoader.java:366） 在java.net.URLClassLoader的$ 1.run（URLClassLoader.java:355） 在java.security.AccessController.doPrivileged（Native Method） at java.net.URLClassLoader.findClass（URLClassLoader.java:354） at java.lang.ClassLoader.loadClass（ClassLoader.java:423） at sun.misc.Launcher $ java.lang.ClassLoader.loadClass（Launcher.java:308） （java.lang.ClassLoader.loadClass（ClassLoader.java:356） at java.lang.Class.forName0（Native Method） at java.lang.Class.forName（ Class.java:264） at org.apache.hadoop.conf.Configuration.getClassByName（Confi guration.java:820） 在org.apache.hadoop.conf.Configuration.getClass（Configuration.java:865）
cars.csv：
[zhouhh @ Hadoop48〜] $猫汽车。CSV讴歌，INTEGRA，小 极品，传说，中型奥迪，90，紧凑型奥迪，100，中型宝马的535i，中型 别克，世纪，中型别克，LESABRE，大别克，路线大师，大 别克，里维埃拉，中型凯迪拉克，蒂娜，大型凯迪拉克，塞维利亚，中型
MultiTableOutputFormat.class是Hbase.0.94.jar
[zhouhh @ Hadoop48〜] $回声$ HADOOP_CLASSPATH | TR '：' '\ N' | grep hbase /home/zhouhh/hbase-0.94.0/conf /home/zhouhh/hbase-0.94.0 /home/zhouhh/hbase-0.94.0/hbase-0.94.0.jar /home/zhouhh/hbase-0.94.0/hbase-0.94.0-tests.jar /home/zhouhh/hbase-0.94.0/lib/activation-1.1.jar /home/zhouhh/hbase-0.94.0/lib/asm- 3.1.jar /home/zhouhh/hbase-0.94.0/lib/avro-1.5.3.jar /home/zhouhh/hbase-0.94.0/lib/avro-ipc-1.5.3.jar /home /zhouhh/hbase-0.94.0/lib/commons-beanutils-1.7.0.jar /home/zhouhh/hbase-0.94.0/lib/commons-beanutils-core-1.8.0.jar /home/zhouhh /hbase-0.94.0/lib/commons-cli-1.2.jar /home/zhouhh/hbase-0.94.0/lib/commons-codec-1.4.jar /home/zhouhh/hbase-0.94.0/lib /公共收集s-3.2.1.jar /home/zhouhh/hbase-0.94.0/lib/commons-configuration-1.6.jar /home/zhouhh/hbase-0.94.0/lib/commons-digester-1.8.jar /home/zhouhh/hbase-0.94.0/lib/commons-el-1.0.jar /home/zhouhh/hbase-0.94.0/lib/commons-httpclient-3.1.jar /home/zhouhh/hbase-0.94 .0/lib/commons-io-2.1.jar /home/zhouhh/hbase-0.94.0/lib/commons-lang-2.5.jar /home/zhouhh/hbase-0.94.0/lib/commons-logging -1.1.1.jar /home/zhouhh/hbase-0.94.0/lib/commons-math-2.1.jar /home/zhouhh/hbase-0.94.0/lib/commons-net-1.4.1.jar /home/zhouhh/hbase-0.94.0/lib/core-3.1.1.jar /home/zhouhh/hbase-0.94.0/lib/guava-r09.jar /home/zhouhh/hbase-0.94。 0/LIB/hadoo p-core-1.0.2.jar /home/zhouhh/hbase-0.94.0/lib/high-scale-lib-1.1.1.jar /home/zhouhh/hbase-0.94.0/lib/httpclient- 4.1.2.jar /home/zhouhh/hbase-0.94.0/lib/httpcore-4.1.3.jar /home/zhouhh/hbase-0.94.0/lib/jackson-core-asl-1.5.5。罐子 /home/zhouhh/hbase-0.94.0/lib/jackson-jaxrs-1.5.5.jar /home/zhouhh/hbase-0.94.0/lib/jackson-mapper-asl-1.5.5.jar /home/zhouhh/hbase-0.94.0/lib/jackson-xc-1.5.5.jar /home/zhouhh/hbase-0.94.0/lib/jamon-runtime-2.3.1.jar /home/zhouhh /hbase-0.94.0/lib/jasper-compiler-5.5.23.jar /home/zhouhh/hbase-0.94.0/lib/jasper-runtime-5.5.23.jar /home/zhouhh/hbase-0.94 .0/lib/jaxb-api-2.1.jar /home/zho uhh/hbase-0.94.0/lib/jaxb-impl-2.1.12.jar /home/zhouhh/hbase-0.94.0/lib/jersey-core-1.4.jar /home/zhouhh/hbase-0.94。 0/lib/jersey-json-1.4.jar /home/zhouhh/hbase-0.94.0/lib/jersey-server-1.4.jar /home/zhouhh/hbase-0.94.0/lib/jettison-1.1。罐子 /home/zhouhh/hbase-0.94.0/lib/jetty-6.1.26.jar /home/zhouhh/hbase-0.94.0/lib/jetty-util-6.1.26.jar /home/zhouhh /hbase-0.94.0/lib/jruby-complete-1.6.5.jar /home/zhouhh/hbase-0.94.0/lib/jsp-2.1-6.1.14.jar /home/zhouhh/hbase-0.94 .0/lib/jsp-api-2.1-6.1.14.jar /home/zhouhh/hbase-0.94.0/lib/libthrift-0.8.0.jar /home/zhouhh/hbase-0.94.0/lib /log4j-1.2.16.jar /home/zhouhh/hbase-0.9 4.0/lib/netty-3.2.4.Final.jar /home/zhouhh/hbase-0.94.0/lib/protobuf-java-2.4.0a.jar /home/zhouhh/hbase-0.94.0/lib/ servlet的API-2.5-6.1.14。罐子 /home/zhouhh/hbase-0.94.0/lib/slf4j-api-1.5.8.jar /home/zhouhh/hbase-0.94.0/lib/snappy-java-1.0.3.2.jar /home /zhouhh/hbase-0.94.0/lib/stax-api-1.0.1.jar /home/zhouhh/hbase-0.94.0/lib/velocity-1.7.jar /home/zhouhh/hbase-0.94.0 /lib/xmlenc-0.52.jar /home/zhouhh/hbase-0.94.0/lib/zookeeper-3.4.3.jar /home/zhouhh/hbase-0.94.0/conf /home/zhouhh/hbase-0.94 .0 /home/zhouhh/hbase-0.94.0/hbase-0.94.0.jar /home/zhouhh/hbase-0.94.0/hbase-0.94.0-tests.jar /home/zhouhh/hbase- 0.94.0/lib/activation-1.1.jar /home/zhouhh/hbase-0.94.0/lib/asm-3.1.jar /home/zhouhh/hbase-0.94.0/lib/avro-1.5.3。罐子 /home/zhouhh/hbase-0.94.0/lib/avro-ipc-1.5.3.jar /home/zhouhh/hbase-0.94.0/lib/commons-beanutils-1.7.0.jar /home/zhouhh /hbase-0.94.0/lib/commons-beanutils-core-1.8.0.jar /home/zhouhh/hbase-0.94.0/lib/commons-cli-1.2.jar /home/zhouhh/hbase-0.94 .0/lib/commons-codec-1.4.jar /home/zhouhh/hbase-0.94.0/lib/commons-collections-3.2.1.jar /home/zhouhh/hbase-0.94.0/lib/commons -configuration-1.6.jar /home/zhouhh/hbase-0.94.0/lib/commons-digester-1.8.jar /home/zhouhh/hbase-0.94.0/lib/commons-el-1.0.jar /home/zhouhh/hbase-0.94.0/lib/commons-httpclient-3.1.jar /home/zhouhh/hbase-0.94.0/lib/commons-io-2.1.jar /home/zhouhh/hbase-0.94。 0/LIB /公地琅-2。 5.jar /home/zhouhh/hbase-0.94.0/lib/commons-logging-1.1.1.jar /home/zhouhh/hbase-0.94.0/lib/commons-math-2.1.jar /home /zhouhh/hbase-0.94.0/lib/commons-net-1.4.1.jar /home/zhouhh/hbase-0.94.0/lib/core-3.1.1.jar /home/zhouhh/hbase-0.94 .0/lib/guava-r09.jar /home/zhouhh/hbase-0.94.0/lib/hadoop-core-1.0.2.jar /home/zhouhh/hbase-0.94.0/lib/high-scale -lib-1.1.1.jar /home/zhouhh/hbase-0.94.0/lib/httpclient-4.1.2.jar /home/zhouhh/hbase-0.94.0/lib/httpcore-4.1.3.jar /home/zhouhh/hbase-0.94.0/lib/jackson-core-asl-1.5.5.jar /home/zhouhh/hbase-0.94.0/lib/jackson-jaxrs-1.5.5.jar /家用/ zhouhh/HBase的-0.94.0/lib目录/杰克逊映射器-asl-1.5.5.jar /home/zhouhh/hbase-0.94.0/lib/jackson-xc-1.5.5.jar /home/zhouhh/hbase-0.94.0/lib/jamon-runtime-2.3 .jar /home/zhouhh/hbase-0.94.0/lib/jasper-compiler-5.5.23.jar /home/zhouhh/hbase-0.94.0/lib/jasper-runtime-5.5.23.jar /home/zhouhh/hbase-0.94.0/lib/jaxb-api-2.1.jar /home/zhouhh/hbase-0.94.0/lib/jaxb-impl-2.1.12.jar /home/zhouhh/hbase-0.94.0/lib/jersey-core-1.4.jar /home/zhouhh/hbase-0.94.0/lib/jersey-json-1.4.jar /home/zhouhh/hbase-0.94.0/lib/ jersey-server-1.4.jar /home/zhouhh/hbase-0.94.0/lib/jettison-1.1.jar /home/zhouhh/hbase-0.94.0/lib/jetty-6.1.26.jar /home /zhouhh/hbase-0.94.0/lib/jetty-uti l-6.1.26.jar /home/zhouhh/hbase-0.94.0/lib/jruby-complete-1.6.5.jar /home/zhouhh/hbase-0.94.0/lib/jsp-2.1-6.1。 14.jar /home/zhouhh/hbase-0.94.0/lib/jsp-api-2.1-6.1.14.jar /home/zhouhh/hbase-0.94.0/lib/libthrift-0.8.0.jar /home/zhouhh/hbase-0.94.0/lib/log4j-1.2.16.jar /home/zhouhh/hbase-0.94.0/lib/netty-3.2.4.Final.jar /home/zhouhh/hbase -0.94.0/lib/protobuf-java-2.4.0a.jar /home/zhouhh/hbase-0.94.0/lib/servlet-api-2.5-6.1.14.jar /home/zhouhh/hbase-0.94 .0/lib/slf4j-api-1.5.8.jar /home/zhouhh/hbase-0.94.0/lib/snappy-java-1.0.3.2.jar /home/zhouhh/hbase-0.94.0/lib /stax-api-1.0.1.jar /home/zhouhh/hbase-0.94。0/lib/velocity-1.7.jar /home/zhouhh/hbase-0.94.0/lib/xmlenc-0.52.jar /home/zhouhh/hbase-0.94.0/lib/zookeeper-3.4.3.jar
我已经尝试了很多方法，但仍然存在相同的错误。
任何人都可以帮助我吗？感谢
请格式化输出。这是不可读的。使用'{}'将输出打印为代码。它看起来更好。 –