In this study, we present a novel tree based index scheme for efficient indexing and serving large datasets in the cloud. It incorporates and extends the functionality of Hadoop to create a fully parallel index system. Our new scheme can be summarized as follows. First, we leverage the MapReduce framework to create an index, then publish the index meta information and write it into a meta table. Second, we use the meta information to help the system adopting an efficient method to handle a given query. Finally, we optimize the system by using cache mechanism. We conduct extensive experiments on the Hadoop cluster to demonstrate the scalability, availability and efficiency of the proposed index framework.
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