With the growth of data for searching, it becomes necessary to scale up the performance of search applications, to cater to the increasing needs of indexing and searching quickly over large datasets. Distributed search can be used when a single index store becomes difficult to operate in terms of its size (large to fit in memory or disk). As more number of users start using enterprise search, single node searches have limitations in terms of response time and parallel sessions for users. For smaller data sizes, standalone search architecture performs better compared to distributed searches, due to single index availability. However, with the growth in the data size, its performance degrades eventually. The Distributed Search application increases the operation and maintenance cost. It also increases the complexity of overall landscape. However, with the scaling of information for searching, distributed search is the way to forward...