  Natural language processing, as a data analytics related technology, is used
widely in many research areas such as artificial intelligence, human language
processing, and translation. At present, due to explosive growth of data, there
are many challenges for natural language processing. Hadoop is one of the
platforms that can process the large amount of data required for natural
language processing. KOSHIK is one of the natural language processing
architectures, and utilizes Hadoop and contains language processing components
such as Stanford CoreNLP and OpenNLP. This study describes how to build a
KOSHIK platform with the relevant tools, and provides the steps to analyze wiki
data. Finally, it evaluates and discusses the advantages and disadvantages of
the KOSHIK architecture, and gives recommendations on improving the processing
performance.
