Due to online activities and use of resources related to computing, data is being generated at an enormous rate. Distributed systems are the efficient mechanism to access and handle such huge data. One such mechanism is a Hadoop distributed file system (HDFS). An HDFS instant usually contains several nodes, each of which stores a small portion of its data. It creates multiple data blocks and store each of the block redundantly across the pool of servers to enable reliable, extreme rapid computation. HDFS supports common file system operations such as read and write files , create and delete directories. In this paper we are presenting a new paradigm for improving file accessing time in HDFS. It is known that accessing data from cache is much faster than disk access. The cache memory is used to store frequently accessed data & hence process it much more quickly. We have already observed the performance improvement using cache memory in the existing Hadoop environment. In this paper we will prove the performance further improvement by using set associative cache memory. Set associative cache mechanism is for managing the interaction between main memory and cache memory.
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