المستخلص: |
Looming atop a wide variety of human activities are the menacing profiles of ever-growing mountains of data. These mountains grew as a result of great engineering successes that enabled us to build devices to generate, collect, and store digital data. With major advances in database, technology came to the creation of huge efficient data stores. The storage was managed by DBMS, huge amount of DBMS will be collected in a special database called I-extended database [1], The DBMS was distributed and also parallelized in an advances computer networking which enabled the data glut to reach anyone who cares to tap in. The DBMS will be queried through I-extended databases. In this paper I’ll adopt parallelism in DBMS through I- extended databases, and come up with an architecture that virtually same with the distributed DBMS through out I- extended databases, which seems like distributed DBMSs in I-extended databases is more natural way to exercise parallelism. The DBMSs in I-extended databases will be distributed on workstations node on a local network with share memory and storage disks via interconnection network. The DBMSs in I-extended databases will be queried also via ordinary query in SQL and generate distributed query plans and performs optimization
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