i'm getting the following exception while try to run pig in mapreduce mode,
ERROR 4010: Cannot find hadoop configurations in classpath (neither hadoop-site.xml nor core-site.xml was found in the classpath). If you plan to use local mode, please put -x local option in command line
I have the following hadoop class path set,
export HADOOP_INSTALL=/media/Software/hadoop-1.0.4
Thanks
Related
I configured a Map Reduce job to save output as a Sequence file compressed with Snappy. The MR job executes successfully however in HDFS the output file looks as the following:
I've expected that the file will have a .snappy extension and that it should be part-r-00000.snappy. And now I think that this may be the reason for the file to be not readable when I'm trying to read it from a local file system using this pattern hadoop fs -libjars /path/to/jar/myjar.jar -text /path/in/HDFS/to/my/file
So I'm getting the –libjars: Unknown command when executing the command:
hadoop fs –libjars /root/hd/metrics.jar -text /user/maria_dev/hd/output/part-r-00000
And when I'm using this command hadoop fs -text /user/maria_dev/hd/output/part-r-00000, I'm getting the error:
18/02/15 22:01:57 INFO compress.CodecPool: Got brand-new decompressor [.snappy]
-text: Fatal internal error
java.lang.RuntimeException: java.io.IOException: WritableName can't load class: com.hd.metrics.IpMetricsWritable
Caused by: java.lang.ClassNotFoundException: Class com.hd.ipmetrics.IpMetricsWritable not found
Could it be that the absence of the .snappy extension causes the problem? What other command should I try to read the compressed file?
The jar is in my local file system /root/hd/ Where should I place it not to cause ClassNotFoundException? Or how should I modify the command?
Instead of hadoop fs –libjars (which actually has a wrong hyphen and should be -libjars. Copy that exactly, and you won't see Unknown command)
You should be using HADOOP_CLASSPATH environment variable
export HADOOP_CLASSPATH=/root/hd/metrics.jar:${HADOOP_CLASSPATH}
hadoop fs -text /user/maria_dev/hd/output/part-r-*
The error clearly says ClassNotFoundException: Class com.hd.ipmetrics.IpMetricsWritable not found.
It means that a required library is missing in classpath.
To clarify your doubts:
Map-Reduce by default output the file as part-* and there is no
meaning of extension. Remember extension "thing" is just a metadata
usually required by windows operating system to determine suitable
program for the file. It has no meaning in linux/unix and the
system's behavior is not going to change, even though you rename the
file as .snappy (you may actually try this).
The command looks absolutely fine to inspect the snappy file, but it seems that some required jar file are not there, which is causing ClassNotFoundException.
EDIT 1:
By default hadoop picks the jar files from the path emit by below command:
$ hadoop classpath
By default it list all the hadoop core jars.
You can add your jar by executing below command on the prompt
export HADOOP_CLASSPATH=/path/to/my/custom.jar
After executing this, try checking the class path again by hadoop classpath command and you should be able to see your jar listed along with hadoop core jars.
I don't know anything about bash, but i put together a script to help me run my Hbase java application:
#!/bin/bash
HADOOP_CLASSPATH="$(hbase classpath)"
hadoop jar my.jar my_pkg.my_class
When I run it I get a:
Exception in thread "main" java.lang.NoClassDefFoundError: org/apache/hadoop/hbase/regionserver/IncreasingToUpperBoundRegionSplitPolicy
When I echo out the HADOOP_CLASSPATH I see that hbase-server-1.2.0-cdh5.8.0.jar is there...
Is the hadoop jar command ignoring the HADOOP_CLASSPATH?
Also I have tried to run the commands from the command-line instead of using my script. I get the same error.
The approach was inspired by this cloduera-question
The solution was to include the Hadoop class path on the same line. I am not certain what the difference is, but this works:
HADOOP_CLASSPATH="$(hbase classpath)" hadoop jar my.jar my_pkg.my_class
I am trying to run a fat jar on a Spark cluster using Spark submit.
I made the cluster using "spark-ec2" executable in Spark bundle on AWS.
The command I am using to run the jar file is
bin/spark-submit --class edu.gatech.cse8803.main.Main --master yarn-cluster ../src1/big-data-hw2-assembly-1.0.jar
In the beginning it was giving me the error that at least one of the HADOOP_CONF_DIR or YARN_CONF_DIR environment variable must be set.
I didn't know what to set them to, so I used the following command
export HADOOP_CONF_DIR=/mapreduce/conf
Now the error has changed to
Could not load YARN classes. This copy of Spark may not have been compiled with YARN support.
Run with --help for usage help or --verbose for debug output
The home directory structure is as follows
ephemeral-hdfs hadoop-native mapreduce persistent-hdfs scala spark spark-ec2 src1 tachyon
I even set the YARN_CONF_DIR variable to the same value as HADOOP_CONF_DIR, but the error message is not changing. I am unable to find any documentation that highlights this issue, most of them just mention these two variables and give no further details.
You need to compile spark against Yarn to use it.
Follow the steps explained here: https://spark.apache.org/docs/latest/building-spark.html
Maven:
build/mvn -Pyarn -Phadoop-2.x -Dhadoop.version=2.x.x -DskipTests clean package
SBT:
build/sbt -Pyarn -Phadoop-2.x assembly
You can also download a pre-compiled version here: http://spark.apache.org/downloads.html (choose a "pre-built for Hadoop")
Download prebuilt spark which supports hadoop 2.X versions from https://spark.apache.org/downloads.html
The --master argument should be: --master spark://hostname:7077 where hostname is the name of your Spark master server. You can also specify this value as spark.master in the spark-defaults.conf file and leave out the --master argument when using Spark submit from the command line. Including the --master argument will override the value set (if exists) in the spark-defaults.conf file.
Reference: http://spark.apache.org/docs/1.3.0/configuration.html
I wrote a simple program to test the embedded pig in java to run in mapreduce mode.
The hadoop version in the server I am running is 0.20.2-cdh3u4a, and pig version is 0.10.0-cdh3u4a.
When I try to run in local mode, it runs successfully. But when I try to run in mapreduce mode, it gives me the error.
I run my program using the following commands as shown in http://pig.apache.org/docs/r0.9.1/cont.html#embed-java
javac -cp pig.jar EmbedPigTest.java
javac -cp pig.jar:.:/etc/hadoop/conf EmbedPigTest.java input.txt
My program gives error as:
Exception in thread "main" java.lang.RuntimeException: Failed to create DataStorage
at org.apache.pig.backend.hadoop.datastorage.HDataStorage.init(HDataStorage.java:75)
at org.apache.pig.backend.hadoop.datastorage.HDataStorage.<init>(HDataStorage.java:58)
at org.apache.pig.backend.hadoop.executionengine.HExecutionEngine.init(HExecutionEngine.java:214)
at org.apache.pig.backend.hadoop.executionengine.HExecutionEngine.init(HExecutionEngine.java:134)
at org.apache.pig.impl.PigContext.connect(PigContext.java:183)
at org.apache.pig.PigServer.<init>(PigServer.java:226)
at org.apache.pig.PigServer.<init>(PigServer.java:215)
at org.apache.pig.PigServer.<init>(PigServer.java:211)
at org.apache.pig.PigServer.<init>(PigServer.java:207)
at WordCount.main(EmbedPigTest.java:9)
In some online resources they say that this problem occurs due to different hadoop version. But, I didn't understand what I should do. Suggestions please !!
This is happening because you are linking to the wrong jar, Please see the link below it describes this issue very well.
http://localsteve.wordpress.com/2012/09/30/embedding-pig-for-cdh4-java-apps-fer-realz/
I was faced same kind of issue when I tried to use pig in map reduce mode without starting the services.
Please check all services using jps before using pig in map reduce mode.
I just started learning Hadoop and PIG (from last two days!) for one of my future project.
For experiments I've installed Hadoop (HDFS on default localhost:9000) as pseudo distributed mode and PIG (map-reduce mode).
When I initialized PIG by typing ./bin/pig command it launched GRUNT command line and I got message that pig connected with HDFS (localhost:9000), later I could successfully able to access HDFS thru pig.
I was expecting to perform some manual configuration for PIG to access HDFS (as per various internet articles).
My question is, from where PIG identified default HDFS configuration (localhost:9000)? I checked pig.properties but I didn't find anything there. I need this info as I might change default HDFS configuration in future.
BTW, I have HADOOP_HOME and PIG_HOME defined in my OS PATH variable.
When installing Pig (I assume v0.10.0) you have to tell how it will connect to the HDFS.
I don't know how you did this but generally this is done by adding the hadoop conf dir path to the PIG_CLASSPATH environment variable. You can also set HADOOP_CONF_DIR as well.
If you are starting the grunt shell Pig will locate the directory of the Hadoop configuration XMLs, and takes the value of fs.default.name (core-site.xml) and mapred.job.tracker (mapred-site.xml) , i.e: the location of the Namenode and JobTracker.
For reference you may have a look at the Pig shell script to see how env. variables are collected and evaluated.
PIG can connects to underlying HDFS in the 3 ways
1-
Pig uses HADOOP_HOME for finding the HADOOP client to Run.
your HADOOP_HOME should have been already setup in your bash_profile
export HADOOP_HOME=~/myHadoop/hadoop-2.5.2
2-
or else there might be possibility that your HADOOP_CONF_DIR has already been setup which contains the xml file for the hadoop configuration
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop/
3-And if these are not setup you can also connect to underlying hdfs
by changing the pig.properties which is present under PIG_HOME/conf dir