Hadoop性能

Question

Hadoop性能

Raf*_*sin 5 performance hadoop mapreduce

我安装了hadoop 1.0.0并尝试了字数统计示例(单节点集群).完成需要2个48秒才能完成.然后我尝试了标准的linux字数统计程序,它在同一组(180 kB数据)上运行10毫秒.我做错了什么,或者Hadoop非常慢？

time hadoop jar /usr/share/hadoop/hadoop*examples*.jar wordcount someinput someoutput
12/01/29 23:04:41 INFO input.FileInputFormat: Total input paths to process : 30
12/01/29 23:04:41 INFO mapred.JobClient: Running job: job_201201292302_0001
12/01/29 23:04:42 INFO mapred.JobClient:  map 0% reduce 0%
12/01/29 23:05:05 INFO mapred.JobClient:  map 6% reduce 0%
12/01/29 23:05:15 INFO mapred.JobClient:  map 13% reduce 0%
12/01/29 23:05:25 INFO mapred.JobClient:  map 16% reduce 0%
12/01/29 23:05:27 INFO mapred.JobClient:  map 20% reduce 0%
12/01/29 23:05:28 INFO mapred.JobClient:  map 20% reduce 4%
12/01/29 23:05:34 INFO mapred.JobClient:  map 20% reduce 5%
12/01/29 23:05:35 INFO mapred.JobClient:  map 23% reduce 5%
12/01/29 23:05:36 INFO mapred.JobClient:  map 26% reduce 5%
12/01/29 23:05:41 INFO mapred.JobClient:  map 26% reduce 8%
12/01/29 23:05:44 INFO mapred.JobClient:  map 33% reduce 8%
12/01/29 23:05:53 INFO mapred.JobClient:  map 36% reduce 11%
12/01/29 23:05:54 INFO mapred.JobClient:  map 40% reduce 11%
12/01/29 23:05:56 INFO mapred.JobClient:  map 40% reduce 12%
12/01/29 23:06:01 INFO mapred.JobClient:  map 43% reduce 12%
12/01/29 23:06:02 INFO mapred.JobClient:  map 46% reduce 12%
12/01/29 23:06:06 INFO mapred.JobClient:  map 46% reduce 14%
12/01/29 23:06:09 INFO mapred.JobClient:  map 46% reduce 15%
12/01/29 23:06:11 INFO mapred.JobClient:  map 50% reduce 15%
12/01/29 23:06:12 INFO mapred.JobClient:  map 53% reduce 15%
12/01/29 23:06:20 INFO mapred.JobClient:  map 56% reduce 15%
12/01/29 23:06:21 INFO mapred.JobClient:  map 60% reduce 17%
12/01/29 23:06:28 INFO mapred.JobClient:  map 63% reduce 17%
12/01/29 23:06:29 INFO mapred.JobClient:  map 66% reduce 17%
12/01/29 23:06:30 INFO mapred.JobClient:  map 66% reduce 20%
12/01/29 23:06:36 INFO mapred.JobClient:  map 70% reduce 22%
12/01/29 23:06:37 INFO mapred.JobClient:  map 73% reduce 22%
12/01/29 23:06:45 INFO mapred.JobClient:  map 80% reduce 24%
12/01/29 23:06:51 INFO mapred.JobClient:  map 80% reduce 25%
12/01/29 23:06:54 INFO mapred.JobClient:  map 86% reduce 25%
12/01/29 23:06:55 INFO mapred.JobClient:  map 86% reduce 26%
12/01/29 23:07:02 INFO mapred.JobClient:  map 90% reduce 26%
12/01/29 23:07:03 INFO mapred.JobClient:  map 93% reduce 26%
12/01/29 23:07:07 INFO mapred.JobClient:  map 93% reduce 30%
12/01/29 23:07:09 INFO mapred.JobClient:  map 96% reduce 30%
12/01/29 23:07:10 INFO mapred.JobClient:  map 96% reduce 31%
12/01/29 23:07:12 INFO mapred.JobClient:  map 100% reduce 31%
12/01/29 23:07:22 INFO mapred.JobClient:  map 100% reduce 100%
12/01/29 23:07:28 INFO mapred.JobClient: Job complete: job_201201292302_0001
12/01/29 23:07:28 INFO mapred.JobClient: Counters: 29
12/01/29 23:07:28 INFO mapred.JobClient:   Job Counters 
12/01/29 23:07:28 INFO mapred.JobClient:     Launched reduce tasks=1
12/01/29 23:07:28 INFO mapred.JobClient:     SLOTS_MILLIS_MAPS=275346
12/01/29 23:07:28 INFO mapred.JobClient:     Total time spent by all reduces waiting after reserving slots (ms)=0
12/01/29 23:07:28 INFO mapred.JobClient:     Total time spent by all maps waiting after reserving slots (ms)=0
12/01/29 23:07:28 INFO mapred.JobClient:     Launched map tasks=30
12/01/29 23:07:28 INFO mapred.JobClient:     Data-local map tasks=30
12/01/29 23:07:28 INFO mapred.JobClient:     SLOTS_MILLIS_REDUCES=137186
12/01/29 23:07:28 INFO mapred.JobClient:   File Output Format Counters 
12/01/29 23:07:28 INFO mapred.JobClient:     Bytes Written=26287
12/01/29 23:07:28 INFO mapred.JobClient:   FileSystemCounters
12/01/29 23:07:28 INFO mapred.JobClient:     FILE_BYTES_READ=71510
12/01/29 23:07:28 INFO mapred.JobClient:     HDFS_BYTES_READ=89916
12/01/29 23:07:28 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=956282
12/01/29 23:07:28 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=26287
12/01/29 23:07:28 INFO mapred.JobClient:   File Input Format Counters 
12/01/29 23:07:28 INFO mapred.JobClient:     Bytes Read=85860
12/01/29 23:07:28 INFO mapred.JobClient:   Map-Reduce Framework
12/01/29 23:07:28 INFO mapred.JobClient:     Map output materialized bytes=71684
12/01/29 23:07:28 INFO mapred.JobClient:     Map input records=2574
12/01/29 23:07:28 INFO mapred.JobClient:     Reduce shuffle bytes=71684
12/01/29 23:07:28 INFO mapred.JobClient:     Spilled Records=6696
12/01/29 23:07:28 INFO mapred.JobClient:     Map output bytes=118288
12/01/29 23:07:28 INFO mapred.JobClient:     CPU time spent (ms)=39330
12/01/29 23:07:28 INFO mapred.JobClient:     Total committed heap usage (bytes)=5029167104
12/01/29 23:07:28 INFO mapred.JobClient:     Combine input records=8233
12/01/29 23:07:28 INFO mapred.JobClient:     SPLIT_RAW_BYTES=4056
12/01/29 23:07:28 INFO mapred.JobClient:     Reduce input records=3348
12/01/29 23:07:28 INFO mapred.JobClient:     Reduce input groups=1265
12/01/29 23:07:28 INFO mapred.JobClient:     Combine output records=3348
12/01/29 23:07:28 INFO mapred.JobClient:     Physical memory (bytes) snapshot=4936278016
12/01/29 23:07:28 INFO mapred.JobClient:     Reduce output records=1265
12/01/29 23:07:28 INFO mapred.JobClient:     Virtual memory (bytes) snapshot=26102546432
12/01/29 23:07:28 INFO mapred.JobClient:     Map output records=8233

real    2m48.886s
user    0m3.300s
sys 0m0.304s


time wc someinput/*
  178  1001  8674 someinput/capacity-scheduler.xml
  178  1001  8674 someinput/capacity-scheduler.xml.bak
    7     7   196 someinput/commons-logging.properties
    7     7   196 someinput/commons-logging.properties.bak
   24    35   535 someinput/configuration.xsl
   80   122  1968 someinput/core-site.xml
   80   122  1972 someinput/core-site.xml.bak
    1     0     1 someinput/dfs.exclude
    1     0     1 someinput/dfs.include
   12    36   327 someinput/fair-scheduler.xml
   45   192  2141 someinput/hadoop-env.sh
   45   192  2139 someinput/hadoop-env.sh.bak
   20   137   910 someinput/hadoop-metrics2.properties
   20   137   910 someinput/hadoop-metrics2.properties.bak
  118   582  4653 someinput/hadoop-policy.xml
  118   582  4653 someinput/hadoop-policy.xml.bak
  241   623  6616 someinput/hdfs-site.xml
  241   623  6630 someinput/hdfs-site.xml.bak
  171   417  6177 someinput/log4j.properties
  171   417  6177 someinput/log4j.properties.bak
    1     0     1 someinput/mapred.exclude
    1     0     1 someinput/mapred.include
   12    15   298 someinput/mapred-queue-acls.xml
   12    15   298 someinput/mapred-queue-acls.xml.bak
  338   897  9616 someinput/mapred-site.xml
  338   897  9630 someinput/mapred-site.xml.bak
    1     1    10 someinput/masters
    1     1    18 someinput/slaves
   57    89  1243 someinput/ssl-client.xml.example
   55    85  1195 someinput/ssl-server.xml.example
 2574  8233 85860 total

real    0m0.009s
user    0m0.004s
sys 0m0.000s

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Answer 1

Dav*_*ton 11

这取决于许多因素,包括您的配置,机器,内存配置,JVM设置等.您还需要减去JVM启动时间.

它对我来说运行得更快.也就是说,当然,在小型数据集上它比专用的C程序要慢 - 考虑它在幕后做什么.

尝试分布在几千个文件中的数TB数据,看看会发生什么.

Answer 2

Arn*_*-Oz 7

正如戴夫所说,Hadoop已经过优化处理大量数据,而不是玩具示例对于"唤醒大象"而言需要征税,以便在处理较小的设备时不需要这样做.您可以查看"关于Map Reduce Jobs的性能",了解有关正在发生的事情的一些细节

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