A New Trace Backing Algorithm and Circular List Join for Maximizing Streaming Data Join

An increasing number of database queries are executed by interactive users and applications. Since the user is waiting for the database to respond with an answer, the initial response time of producing the first results is very important. The user can process the first results while the database system efficiently completes the entire query. The state-of-art join algorithms are not ideal for this setting. Adaptive join algorithms have recently attracted a lot of attention in emerging applications where data is provided by autonomous data sources through heterogeneous network environments. The main advantage of adaptive join techniques is that they can start producing join results as soon as the first input tuples are available, thus improving pipelining by smoothing join result production and by masking source or network delays. Since the response time of the queries places a vital role in adaptive join, the join techniques like Hash Join, Sort Merge Join cannot be used because they require some prework before producing the join result. The only possible join technique that can be used in adaptive join is Nested Loop Join. In Nested Loop Join each row of the outer relation is compared with each row of the inner relation. The no. of comparisons done by the nested loop join can be reduced by using a technique called trace backing. In trace backing technique whenever a miss match occurs, the next tuple of the outer relation is compared with the mismatched inner relation tuple, instead of looping all the tuples of the inner relation. Finally a new circular linked list join method is discussed which may be a better option to perform streaming data Join.