Fuzzy Query Processing In Distributed Databases
The problem of evolving databases to make them more intuitive, user-friendly and to be able to answer vague
human queries with separate needs for each user has become a popular research topic. The solution to this problem in part
has been proposed via databases that aim at inserting fuzzy data into databases hence handling vague human like queries. It
has been suggested in many research papers that fuzziness may be applied to databases. However, this approach is infeasible
and inefficient for real time processing. In the past 30 years of research, fuzzy databases are still not popular in industry
because of unwillingness of companies to replace crisp data with fuzzy data in their databases due to excessive
precomputation and possible chances of data inconsistency. Having fuzzy databases also places severe constraints on the
database as it will become very difficult to run crisp queries on fuzzy databases. This problem becomes even more complex
with the advent of “Big Data”. This paper proposes a three pronged fuzzy logic based technique as a layer of computation
above traditional query processing to solve such queries in real time. This fuzzy logic based approach to querying in
distributed databases can be used to solve ambiguous queries, incorporating the preferences of each user in the current
scenario of excessive data. The results obtained using the fuzzy logic approach are compared with those obtained using
traditional approach in terms of accuracy, time taken for each approach and closeness of the results to users requirements.
Keywords- Fuzzy logic, Fuzzy Inference System, Big Data, Distributed Query Processing (DQP), Distributed Databases,
Fuzzy SQL, Yager’s intersection, Mamdani’s implication, Fuzzy Rule Base (FRB), Fuzzy Expert System(FES).