（三）实战4：hbase的MapReduce之Java操作

最新推荐文章于 2021-05-13 18:56:16 发布

猿来如此dj

最新推荐文章于 2021-05-13 18:56:16 发布

阅读量615

点赞数 1

CC 4.0 BY-SA版权

分类专栏： hbase专栏文章标签： hbase读取数据保存到hdfs

本文链接：https://blog.youkuaiyun.com/weixin_43930865/article/details/89640908

hbase专栏专栏收录该内容

13 篇文章

订阅专栏

本文介绍了一种使用MapReduce将HBase中的数据读取并存储到HDFS的方法。通过配置HBase和HDFS连接参数，利用TableMapperJob初始化Mapper作业，从'user_info'表读取数据，最终输出到指定的HDFS路径。此过程涉及HBase的TableRecordReader和FileOutputFormat。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

编写 mapreduce 程序从 hbase 读取数据，然后存储到 hdfs

/**

描述：
*/
public class HBaseDataToHDFSMR {
public static final String ZK_CONNECT = “hadoop02:2181,hadoop03:2181,hadoop04:2181”;
public static final String ZK_CONNECT_KEY = “hbase.zookeeper.quorum”;
public static final String HDFS_CONNECT = “hdfs://myha01/”;
public static final String HDFS_CONNECT_KEY = “fs.defaultFS”;
public static void main(String[] args) throws Exception {
Configuration conf = HBaseConfiguration.create();
conf.set(ZK_CONNECT_KEY, ZK_CONNECT);
conf.set(HDFS_CONNECT_KEY, HDFS_CONNECT);
System.setProperty(“HADOOP_USER_NAME”, “hadoop”);
Job job = Job.getInstance(conf);
// 输入数据来源于 hbase 的 user_info 表
Scan scan = new Scan();
TableMapReduceUtil.initTableMapperJob(“user_info”, scan,
Stay hungry Stay foolish --马中华-- http://blog.youkuaiyun.com/zhongqi2513
HBaseDataToHDFSMRMapper.class, Text.class, NullWritable.class, job);
// RecordReader — TableRecordReader
// InputFormat ----- TextInputFormat
// 数据输出到 hdfs
FileOutputFormat.setOutputPath(job, new Path("/hbase2hdfs/output2"));
boolean waitForCompletion = job.waitForCompletion(true);
System.exit(waitForCompletion ? 0 : 1);
}

static class HBaseDataToHDFSMRMapper extends TableMapper<Text, NullWritable> {
 /**
 * keyType: LongWritable -- ImmutableBytesWritable:rowkey
 * ValueType: Text -- Result:hbase 表中某一个 rowkey 查询出来的所有的 key-value 对
 */
 @Override
 protected void map(ImmutableBytesWritable key, Result value, Context context)
throws IOException, InterruptedException {
 // byte[] rowkey = Bytes.copy(key, 0, key.getLength());
 String rowkey = Bytes.toString(key.copyBytes());
 List<Cell> listCells = value.listCells();
 Text text = new Text();
 // 最后输出格式是: rowkey, base_info:name-huangbo, base-info:age-34
 for (Cell cell : listCells) {
 String family = new String(CellUtil.cloneFamily(cell));
 String qualifier = new String(CellUtil.cloneQualifier(cell));
 String v = new String(CellUtil.cloneValue(cell));
 long ts = cell.getTimestamp();
 text.set(rowkey + "\t" + family + "\t" + qualifier + "\t" + v + "\t" + ts);
 context.write(text, NullWritable.get());
 }
 }
 }
}