hadoop 2.7 使用 distcp 在不同集群间数据迁移拷贝

爱被打了一巴掌 2021-11-18 01:12 607阅读 0赞

### 文章目录 ###

本文讲述在多个hadoop集群中进行数据迁移操作。工作中可能会遇到同样的需求，还是很实用的。

hadoop官方提供了distcp 工具吗，具体使用说明参加官方文档：  
[https://hadoop.apache.org/docs/r2.7.7/hadoop-distcp/DistCp.html\#Command\_Line\_Options][https_hadoop.apache.org_docs_r2.7.7_hadoop-distcp_DistCp.html_Command_Line_Options]

假设在hadoop集群1 的目录`/hbase/data/default/`下有`LBLTEST`文件，我们将他拷贝到Hadoop集群2上去。  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9pdDAwNy5ibG9nLmNzZG4ubmV0_size_16_color_FFFFFF_t_70]![在这里插入图片描述][20190731141341891.png]

命令：`./hadoop distcp hdfs://集群1:9000/hbase/data/default/LBLTEST hdfs://集群2:9000/hbase/data/default/LBLTEST`

$ ./hadoop distcp hdfs://172.16.48.195:9000/hbase/data/default/LBLTEST hdfs://172.16.50.28:9000/hbase/data/default/LBLTEST
    SLF4J: Class path contains multiple SLF4J bindings.
    SLF4J: Found binding in [jar:file:/data/program/hadoop-2.7.2/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
    SLF4J: Found binding in [jar:file:/data/program/alluxio-1.7.0-hadoop-2.7/client/alluxio-1.7.0-client.jar!/org/slf4j/impl/StaticLoggerBinder.class]
    SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
    SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
    19/07/31 13:11:33 INFO tools.DistCp: Input Options: DistCpOptions{atomicCommit=false, syncFolder=false, deleteMissing=false, ignoreFailures=false, maxMaps=20, sslConfigurationFile='null', copyStrategy='uniformsize', sourceFileListing=null, sourcePaths=[hdfs://172.16.48.195:9000/hbase/data/default/LBLTEST], targetPath=hdfs://172.16.50.28:9000/hbase/data/default/LBLTEST, targetPathExists=false, preserveRawXattrs=false}
    19/07/31 13:11:33 INFO client.RMProxy: Connecting to ResourceManager at /172.16.48.195:8032
    19/07/31 13:11:34 INFO Configuration.deprecation: io.sort.mb is deprecated. Instead, use mapreduce.task.io.sort.mb
    19/07/31 13:11:34 INFO Configuration.deprecation: io.sort.factor is deprecated. Instead, use mapreduce.task.io.sort.factor
    19/07/31 13:11:34 INFO client.RMProxy: Connecting to ResourceManager at /172.16.48.195:8032
    19/07/31 13:11:35 INFO mapreduce.JobSubmitter: number of splits:4
    19/07/31 13:11:35 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1545880014947_4110
    19/07/31 13:11:35 INFO impl.YarnClientImpl: Submitted application application_1545880014947_4110
    19/07/31 13:11:35 INFO mapreduce.Job: The url to track the job: http://172.16.48.195:20888/proxy/application_1545880014947_4110/
    19/07/31 13:11:35 INFO tools.DistCp: DistCp job-id: job_1545880014947_4110
    19/07/31 13:11:35 INFO mapreduce.Job: Running job: job_1545880014947_4110
    19/07/31 13:11:45 INFO mapreduce.Job: Job job_1545880014947_4110 running in uber mode : false
    19/07/31 13:11:45 INFO mapreduce.Job: map 0% reduce 0%
    19/07/31 13:11:51 INFO mapreduce.Job: map 50% reduce 0%
    19/07/31 13:11:52 INFO mapreduce.Job: map 75% reduce 0%
    19/07/31 13:12:14 INFO mapreduce.Job: map 100% reduce 0%
    19/07/31 13:12:15 INFO mapreduce.Job: Job job_1545880014947_4110 completed successfully
    19/07/31 13:12:15 INFO mapreduce.Job: Counters: 33
     File System Counters
      FILE: Number of bytes read=0
      FILE: Number of bytes written=506418
      FILE: Number of read operations=0
      FILE: Number of large read operations=0
      FILE: Number of write operations=0
      HDFS: Number of bytes read=10368
      HDFS: Number of bytes written=6478
      HDFS: Number of read operations=87
      HDFS: Number of large read operations=0
      HDFS: Number of write operations=24
     Job Counters 
      Launched map tasks=4
      Other local map tasks=4
      Total time spent by all maps in occupied slots (ms)=39699
      Total time spent by all reduces in occupied slots (ms)=0
      Total time spent by all map tasks (ms)=39699
      Total vcore-milliseconds taken by all map tasks=39699
      Total megabyte-milliseconds taken by all map tasks=40651776
     Map-Reduce Framework
      Map input records=11
      Map output records=0
      Input split bytes=544
      Spilled Records=0
      Failed Shuffles=0
      Merged Map outputs=0
      GC time elapsed (ms)=239
      CPU time spent (ms)=3510
      Physical memory (bytes) snapshot=1122856960
      Virtual memory (bytes) snapshot=12267859968
      Total committed heap usage (bytes)=2974810112
     File Input Format Counters 
      Bytes Read=3346
     File Output Format Counters 
      Bytes Written=0
     org.apache.hadoop.tools.mapred.CopyMapper$Counter
      BYTESCOPIED=6478
      BYTESEXPECTED=6478
      COPY=11

上述命令会使用MapReduce来实现数据的拷贝转移。  
转移成功后，就可以在集群2看到这个文件了：  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9pdDAwNy5ibG9nLmNzZG4ubmV0_size_16_color_FFFFFF_t_70 1]

[https_hadoop.apache.org_docs_r2.7.7_hadoop-distcp_DistCp.html_Command_Line_Options]: https://hadoop.apache.org/docs/r2.7.7/hadoop-distcp/DistCp.html#Command_Line_Options
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9pdDAwNy5ibG9nLmNzZG4ubmV0_size_16_color_FFFFFF_t_70]: https://img-blog.csdnimg.cn/20190731141229114.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9pdDAwNy5ibG9nLmNzZG4ubmV0,size_16,color_FFFFFF,t_70
[20190731141341891.png]: /images/20211116/e5489737bbc448998bb051018d4d75ee.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9pdDAwNy5ibG9nLmNzZG4ubmV0_size_16_color_FFFFFF_t_70 1]: /images/20211116/76a44146f8444c94bf72f0b6c788e7bd.png