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In this paper, the authors present a distributed architecture for indexing and serving large and diverse datasets. It incorporates and extends the functionality of Hadoop, the open source MapReduce framework, and of HBase, a distributed, sparse, NoSQL database, to create a fully parallel indexing system. Experiments with structured, semi-structured and unstructured data of various sizes demonstrate the flexibility, speed and robustness of their implementation and contrast it with similarly oriented projects. Their 11 node cluster prototype managed to keep full-text indexing time of 150GB raw content in less than 3 hours, whereas the system's response time under sustained query load of more than 1000 queries/sec was kept in the order of milliseconds.
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