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Recently, parallel search engines have been implemented based on scalable distributed file systems such as Google File System. However, the authors claim that building a massively-parallel search engine using a parallel DBMS can be an attractive alternative since it supports a higher-level (i.e., SQL-level) interface than that of a distributed file system for easy and less error-prone application development while providing scalability. In this paper, they propose a new approach of building a massively-parallel search engine using a DB-IR tightly-integrated parallel DBMS and demonstrate its commercial-level scalability and performance.
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