Hi,
I use Hadoop 2.4.1, I got "org.apache.hadoop.io.compress.SnappyCodec not found”
error:
hadoop checknative
14/08/29 02:54:51 WARN bzip2.Bzip2Factory: Failed to load/initialize
native-bzip2 library system-native, will use pure-Java version
14/08/29 02:54:51 INFO zlib.ZlibFactory: Successfully loaded & initialized
native-zlib library
Native library checking:
hadoop: true
/mnt/hadoop/hadoop-2.4.1_snappy/lib/native/Linux-amd64-64/libhadoop.so
zlib: true /lib64/libz.so.1
snappy: true
/mnt/hadoop/hadoop-2.4.1_snappy/lib/native/Linux-amd64-64/libsnappy.so.1
lz4: true revision:99
bzip2: false
(smoke test is ok)
bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-*.jar teragen
300000 /tmp/teragenout
14/08/29 07:40:41 INFO mapreduce.Job: Running job: job_1409253811850_0002
14/08/29 07:40:53 INFO mapreduce.Job: Job job_1409253811850_0002 running in
uber mode : false
14/08/29 07:40:53 INFO mapreduce.Job: map 0% reduce 0%
14/08/29 07:41:00 INFO mapreduce.Job: map 50% reduce 0%
14/08/29 07:41:01 INFO mapreduce.Job: map 100% reduce 0%
14/08/29 07:41:02 INFO mapreduce.Job: Job job_1409253811850_0002 completed
successfully
14/08/29 07:41:02 INFO mapreduce.Job: Counters: 31
File System Counters
FILE: Number of bytes read=0
FILE: Number of bytes written=197312
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=167
HDFS: Number of bytes written=30000000
HDFS: Number of read operations=8
HDFS: Number of large read operations=0
HDFS: Number of write operations=4
Job Counters
Launched map tasks=2
Other local map tasks=2
Total time spent by all maps in occupied slots (ms)=11925
Total time spent by all reduces in occupied slots (ms)=0
Total time spent by all map tasks (ms)=11925
Total vcore-seconds taken by all map tasks=11925
Total megabyte-seconds taken by all map tasks=109900800
Map-Reduce Framework
Map input records=300000
Map output records=300000
Input split bytes=167
Spilled Records=0
Failed Shuffles=0
Merged Map outputs=0
GC time elapsed (ms)=22
CPU time spent (ms)=1910
Physical memory (bytes) snapshot=357318656
Virtual memory (bytes) snapshot=1691631616
Total committed heap usage (bytes)=401997824
org.apache.hadoop.examples.terasort.TeraGen$Counters
CHECKSUM=644086318705578
File Input Format Counters
Bytes Read=0
File Output Format Counters
Bytes Written=30000000
14/08/29 07:41:03 INFO terasort.TeraSort: starting
14/08/29 07:41:03 INFO input.FileInputFormat: Total input paths to process : 2
However I got "org.apache.hadoop.io.compress.SnappyCodec not found” when
running spark smoke test program:
scala> inFILE.first()
java.lang.RuntimeException: Error in configuring object
at
org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:109)
at
org.apache.hadoop.util.ReflectionUtils.setConf(ReflectionUtils.java:75)
at
org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:133)
at org.apache.spark.rdd.HadoopRDD.getInputFormat(HadoopRDD.scala:158)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:171)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
at org.apache.spark.rdd.MappedRDD.getPartitions(MappedRDD.scala:28)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
at org.apache.spark.rdd.RDD.take(RDD.scala:983)
at org.apache.spark.rdd.RDD.first(RDD.scala:1015)
at $iwC$$iwC$$iwC$$iwC.<init>(<console>:15)
at $iwC$$iwC$$iwC.<init>(<console>:20)
at $iwC$$iwC.<init>(<console>:22)
at $iwC.<init>(<console>:24)
at <init>(<console>:26)
at .<init>(<console>:30)
at .<clinit>(<console>)
at .<init>(<console>:7)
at .<clinit>(<console>)
at $print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at
org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:788)
at
org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1056)
at
org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:614)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:645)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:609)
at
org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:796)
at
org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:841)
at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:753)
at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:601)
at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:608)
at org.apache.spark.repl.SparkILoop.loop(SparkILoop.scala:611)
at
org.apache.spark.repl.SparkILoop$$anonfun$process$1.apply$mcZ$sp(SparkILoop.scala:936)
at
org.apache.spark.repl.SparkILoop$$anonfun$process$1.apply(SparkILoop.scala:884)
at
org.apache.spark.repl.SparkILoop$$anonfun$process$1.apply(SparkILoop.scala:884)
at
scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:884)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:982)
at org.apache.spark.repl.Main$.main(Main.scala:31)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:303)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:55)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at
org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:106)
... 55 more
Caused by: java.lang.IllegalArgumentException: Compression codec
org.apache.hadoop.io.compress.SnappyCodec not found.
at
org.apache.hadoop.io.compress.CompressionCodecFactory.getCodecClasses(CompressionCodecFactory.java:135)
at
org.apache.hadoop.io.compress.CompressionCodecFactory.<init>(CompressionCodecFactory.java:175)
at
org.apache.hadoop.mapred.TextInputFormat.configure(TextInputFormat.java:45)
... 60 more
Caused by: java.lang.ClassNotFoundException: Class
org.apache.hadoop.io.compress.SnappyCodec not found
at
org.apache.hadoop.conf.Configuration.getClassByName(Configuration.java:1801)
at
org.apache.hadoop.io.compress.CompressionCodecFactory.getCodecClasses(CompressionCodecFactory.java:128)
... 62 more
This is my setting in mapred-site.xml related to snappy
<property>
<name>mapred.output.compress</name>
<value>false</value>
<description>Should the job outputs be compressed?</description>
</property>
<property>
<name>mapred.output.compression.type</name>
<value>RECORD</value>
<description>If the job outputs are to compressed as SequenceFiles, how
should they be compressed? Should be one of NONE, RECORD or BLOCK.</description>
</property>
<property>
<name>mapred.output.compression.codec</name>
<value>org.apache.hadoop.io.compress.SnappyCodec</value>
<description>If the job outputs are compressed, how should they be
compressed?
</description>
</property>
<property>
<name>mapred.compress.map.output</name>
<value>true</value>
<description>Should the outputs of the maps be compressed before being sent
across the network. Uses SequenceFile compression.</description>
</property>
<property>
<name>mapred.map.output.compression.codec</name>
<value>org.apache.hadoop.io.compress.SnappyCodec</value>
<description>If the map outputs are compressed, how should they be
compressed?</description>
</property>
<property>
<name>mapreduce.map.output.compress</name>
<value>true</value>
</property>
<property>
<name>mapred.map.output.compress.codec</name>
<value>org.apache.hadoop.io.compress.SnappyCodec</value>
</property>
Can you please advise if my mapred-site.xml setting is incorrect?
Regards
Arthur
