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Applications like Yahoo, Facebook, Twitter have huge data which has to bestored and retrieved as per client access. This huge data storage requires hugedatabase leading to increase in physical storage and becomes complex foranalysis required in business growth. This storage capacity can be reduced anddistributed processing of huge data can be done using Apache Hadoop which usesMap-reduce algorithm and combines the repeating data so that entire data isstored in reduced format. The paper describes performing a wordcount Map-ReduceJob in Single Node Apache Hadoop cluster and compress data usingLempel-Ziv-Oberhumer (LZO) algorithm.

Perform wordcount Map-Reduce Job in Single Node Apache Hadoop cluster and compress data using Lempel-Ziv-Oberhumer (LZO) algorithm