问题导读:
1.hbase的mapreduce与hadoop mapreduce的区别点在什么地方?
2.java.lang.NoClassDefFoundError: org/apache/hadoop/hbase/HTableDescriptor可能的解决方案是什么?
跟Hadoop的无缝集成使得使用MapReduce对HBase的数据进行分布式计算非常方便,本文将介绍HBase下 MapReduce开发要点。很好理解本文前提是你对Hadoop MapReduce有一定的了解,如果你是初次接触Hadoop MapReduce编程,可以参考 " mapreduce学习指导及疑难解惑汇总" 这篇文章来建立基本概念。
- package hbase;
-
- import java.io.IOException;
-
- import org.apache.hadoop.conf.Configuration;
- import org.apache.hadoop.fs.Path;
- import org.apache.hadoop.hbase.HBaseConfiguration;
- import org.apache.hadoop.hbase.HColumnDescriptor;
- import org.apache.hadoop.hbase.HTableDescriptor;
- import org.apache.hadoop.hbase.client.HBaseAdmin;
- import org.apache.hadoop.hbase.client.Put;
- import org.apache.hadoop.hbase.mapreduce.TableOutputFormat;
- import org.apache.hadoop.hbase.mapreduce.TableReducer;
- import org.apache.hadoop.hbase.util.Bytes;
- import org.apache.hadoop.io.IntWritable;
- import org.apache.hadoop.io.LongWritable;
- import org.apache.hadoop.io.NullWritable;
- import org.apache.hadoop.io.Text;
- import org.apache.hadoop.mapreduce.Job;
- import org.apache.hadoop.mapreduce.Mapper;
- import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
- import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
-
- public class WordCountHBase {
-
- public static class Map extends
- Mapper<LongWritable, Text, Text, IntWritable> {
- private IntWritable i = new IntWritable(1);
-
- public void map(LongWritable key, Text value, Context context)
- throws IOException, InterruptedException {
- String s[] = value.toString().trim().split(" ");
- // 将输入的每行以空格分开
- for (String m : s) {
- context.write(new Text(m), i);
- }
- }
- }
-
- public static class Reduce extends
- TableReducer<Text, IntWritable, NullWritable> {
- public void reduce(Text key, Iterable<IntWritable> values,
- Context context) throws IOException, InterruptedException {
- int sum = 0;
- for (IntWritable i : values) {
- sum += i.get();
- }
- Put put = new Put(Bytes.toBytes(key.toString()));
- // Put实例化,每一个词存一行
- put.add(Bytes.toBytes("content"), Bytes.toBytes("count"),
- Bytes.toBytes(String.valueOf(sum)));
- // 列族为content,列为count,列值为数目
- context.write(NullWritable.get(), put);
- }
- }
-
- public static void createHBaseTable(String tableName) throws IOException {
- HTableDescriptor htd = new HTableDescriptor(tableName);
- HColumnDescriptor col = new HColumnDescriptor("content");
- htd.addFamily(col);
- Configuration conf = HBaseConfiguration.create();
- conf.set("hbase.zookeeper.quorum", "libin2");
- HBaseAdmin admin = new HBaseAdmin(conf);
- if (admin.tableExists(tableName)) {
- System.out.println("table exists, trying to recreate table......");
- admin.disableTable(tableName);
- admin.deleteTable(tableName);
- }
- System.out.println("create new table:" + tableName);
- admin.createTable(htd);
- }
-
- public static void main(String[] args) throws IOException,
- InterruptedException, ClassNotFoundException {
- String tableName = "WordCount";
- Configuration conf = new Configuration();
- conf.set(TableOutputFormat.OUTPUT_TABLE, tableName);
- createHBaseTable(tableName);
- String input = args[0];
- Job job = new Job(conf, "WordCount table with " + input);
- job.setJarByClass(WordCountHBase.class);
- job.setNumReduceTasks(3);
- job.setMapperClass(Map.class);
- job.setReducerClass(Reduce.class);
- job.setMapOutputKeyClass(Text.class);
- job.setMapOutputValueClass(IntWritable.class);
- job.setInputFormatClass(TextInputFormat.class);
- job.setOutputFormatClass(TableOutputFormat.class);
- FileInputFormat.addInputPath(job, new Path(input));
- System.exit(job.waitForCompletion(true) ? 0 : 1);
- }
- }
复制代码
二、把java代码打成jar包 如果同时用到了两个jar包,需要在两个jar包之间加一个":"分隔符。
三、运行程序 运行WordCountHBase.jar可能会报错:java.lang.NoClassDefFoundError: org/apache/hadoop/hbase/HTableDescriptor 解决方法(把hbase的核心jar包和hbase自带的Zookeeperjar包拷贝到hadoop的安装目录\lib下,然后重启服务):
然后再次执行
四、查看HBase表中的数据 如果表中有保存好的MapReduce处理后的数据,说明成功!本文通过实例分析演示了使用MapReduce分析HBase的数据,需要注意的这只是一种常规的方式(分析表中的数据存到另外的表中),实际上不局限于此,不过其他方式跟此类似。
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