警告snappy.LoadSnappy：未加载Snappy本机库

Question

无论我做什么，我都无法摆脱这个错误。我知道snappy是一个快速的，因此比其他选项更适合压缩/解压缩库。我想使用这个库进行处理。据我所知，谷歌在内部使用它的BigTables，MapReduce（基本上用于所有杀手级应用程序）。我自己研究过。人们建议不要使用它，或者选择java-snappy，但我想坚持使用hadoop snappy。我的设置中有相应的库。 （我的意思是在lib下）

有人可以修复此错误吗？无论出现此错误，我都看到作业已成功完成。

****hdfs://localhost:54310/user/hduser/gutenberg
12/06/01 18:18:54 INFO input.FileInputFormat: Total input paths to process : 3
12/06/01 18:18:54 INFO util.NativeCodeLoader: Loaded the native-hadoop library
12/06/01 18:18:54 WARN snappy.LoadSnappy: Snappy native library not loaded
12/06/01 18:18:54 INFO mapred.JobClient: Running job: job_201206011229_0008
12/06/01 18:18:55 INFO mapred.JobClient:  map 0% reduce 0%
12/06/01 18:19:08 INFO mapred.JobClient:  map 66% reduce 0%
12/06/01 18:19:14 INFO mapred.JobClient:  map 100% reduce 0%
12/06/01 18:19:17 INFO mapred.JobClient:  map 100% reduce 22%
12/06/01 18:19:23 INFO mapred.JobClient:  map 100% reduce 100%
12/06/01 18:19:28 INFO mapred.JobClient: Job complete: job_201206011229_0008
12/06/01 18:19:28 INFO mapred.JobClient: Counters: 29
12/06/01 18:19:28 INFO mapred.JobClient:   Job Counters 
12/06/01 18:19:28 INFO mapred.JobClient:     Launched reduce tasks=1
12/06/01 18:19:28 INFO mapred.JobClient:     SLOTS_MILLIS_MAPS=22810
12/06/01 18:19:28 INFO mapred.JobClient:     Total time spent by all reduces waiting after reserving slots (ms)=0
12/06/01 18:19:28 INFO mapred.JobClient:     Total time spent by all maps waiting after reserving slots (ms)=0
12/06/01 18:19:28 INFO mapred.JobClient:     Launched map tasks=3
12/06/01 18:19:28 INFO mapred.JobClient:     Data-local map tasks=3
12/06/01 18:19:28 INFO mapred.JobClient:     SLOTS_MILLIS_REDUCES=14345
12/06/01 18:19:28 INFO mapred.JobClient:   File Output Format Counters 
12/06/01 18:19:28 INFO mapred.JobClient:     Bytes Written=880838
12/06/01 18:19:28 INFO mapred.JobClient:   FileSystemCounters
12/06/01 18:19:28 INFO mapred.JobClient:     FILE_BYTES_READ=2214849
12/06/01 18:19:28 INFO mapred.JobClient:     HDFS_BYTES_READ=3671878
12/06/01 18:19:28 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=3775339
12/06/01 18:19:28 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=880838
12/06/01 18:19:28 INFO mapred.JobClient:   File Input Format Counters 
12/06/01 18:19:28 INFO mapred.JobClient:     Bytes Read=3671517
12/06/01 18:19:28 INFO mapred.JobClient:   Map-Reduce Framework
12/06/01 18:19:28 INFO mapred.JobClient:     Map output materialized bytes=1474341
12/06/01 18:19:28 INFO mapred.JobClient:     Map input records=77932
12/06/01 18:19:28 INFO mapred.JobClient:     Reduce shuffle bytes=1207328
12/06/01 18:19:28 INFO mapred.JobClient:     Spilled Records=255962
12/06/01 18:19:28 INFO mapred.JobClient:     Map output bytes=6076095
12/06/01 18:19:28 INFO mapred.JobClient:     CPU time spent (ms)=12100
12/06/01 18:19:28 INFO mapred.JobClient:     Total committed heap usage (bytes)=516882432
12/06/01 18:19:28 INFO mapred.JobClient:     Combine input records=629172
12/06/01 18:19:28 INFO mapred.JobClient:     SPLIT_RAW_BYTES=361
12/06/01 18:19:28 INFO mapred.JobClient:     Reduce input records=102322
12/06/01 18:19:28 INFO mapred.JobClient:     Reduce input groups=82335
12/06/01 18:19:28 INFO mapred.JobClient:     Combine output records=102322
12/06/01 18:19:28 INFO mapred.JobClient:     Physical memory (bytes) snapshot=605229056
12/06/01 18:19:28 INFO mapred.JobClient:     Reduce output records=82335
12/06/01 18:19:28 INFO mapred.JobClient:     Virtual memory (bytes) snapshot=2276663296
12/06/01 18:19:28 INFO mapred.JobClient:     Map output records=629172

P.S。：目前，我正在使用一个小型数据集，其中快速压缩和解压缩并不重要。但是，一旦我有一个工作流程，我将使用大型数据集加载它。

Answer 1

如果snappy的共享库（.so）不在LD_LIBARAY_PATH / java.library.path上，您将看到此错误消息。如果您在正确的位置安装了库，则不应看到上述错误消息。

如果您确实将.so安装在与hadoop native lib（libhadoop.so）相同的文件夹中，则上述“错误”可能与您提交作业的节点有关（就像您说的那样） ，你的工作没有错误，这看起来像客户端的消息）。

您能否分享一些作业配置的详细信息（配置输出格式的位置以及相关的压缩选项）。