Hadoop Troubleshooting-001

Hadoop getting following error (java.lang.UnsupportedClassVersionError) when run Hadoop / HDFS Command

bash-3.00$ hadoop  dfs -ls /
DEPRECATED: Use of this script to execute hdfs command is deprecated.
Instead use the hdfs command for it.

Exception in thread "main" java.lang.UnsupportedClassVersionError: Bad version number in .class file
        at java.lang.ClassLoader.defineClass1(Native Method)
        at java.lang.ClassLoader.defineClass(ClassLoader.java:620)
        at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:124)
        at java.net.URLClassLoader.defineClass(URLClassLoader.java:260)
        at java.net.URLClassLoader.access$100(URLClassLoader.java:56)
        at java.net.URLClassLoader$1.run(URLClassLoader.java:195)
        at java.security.AccessController.doPrivileged(Native Method)
        at java.net.URLClassLoader.findClass(URLClassLoader.java:188)
        at java.lang.ClassLoader.loadClass(ClassLoader.java:306)
        at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:268)
        at java.lang.ClassLoader.loadClass(ClassLoader.java:251)
        at java.lang.ClassLoader.loadClassInternal(ClassLoader.java:319)

This is typical java error, which is caused when you run a class that is compiled with newer java version then you have currently in your system. If you are running Hadoop with older version (older than 1.6) you will get this error. Please check the version of java (java -version) and point Hadoop to correct java version.

Big Data Use-cases Across Industries, It's Becoming Bigger and Bigger

Big Data will become bigger and bigger, According to certain market forecasts it will increase by 1211%.
Big Data is increase at very fast speed, as the volume of data is growing like any thing, according to Gartner we create 2.5 Quintillion bytes of data per day (90% of the data in the world has been created in last two years alone).
An interesting infographic from Wikibon.org

Image source: wikibon.org/


In this tutorial we will understand the difference between Apche Solr and Elastic search, Before going to actual post lets understand what is Apache Solr and what is Elastic search

Apache Solr Introduction:
Solr is an open source enterprise search server based on Lucene. Developing a high performance, feature rich application that uses Lucene directly is difficult and it’s limited to Java applications. Solr solves this by exposing the wealth of power in Lucene via configuration files and HTTP parameters, while adding some features of its own. Configuration files, most notably for the index’s schema, which defines the fields and configuration of their text analysis.

Elastic Search Introduction: ElasticSearch is a distributed, RESTful, free/open source search server based on Apache Lucene. It is developed by Shay Banon[1] and is released under the terms of the Apache License. ElasticSearch is developed in Java.

To Read complete post please refer http://solr-vs-elasticsearch.com/