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Distributed Top-N Query Processing With Possibly Uncooperative ...
Get Distributed Top-N Query Processing With Possibly Uncooperative ...
UNY at Binghamton Chicago, IL 60607 Binghamton, NY 13902 fyu,gphilipg cs.uic.edu meng cs.binghamton.edu and what tuples from the searched databases should be returned. A new algorithm is proposed for this purpose. Experimental results are presented to compare di erent methods and very promising results are obtained using the method that requires no cooperation from local databases. keywords: Top-N queries, distributed databases, query processing. Abstract We consider the problem of proces.
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Mhist FAQ
There are two issues: (i) Data fragmentation which determines how the data should be fragmented; and (ii) Data allocation which determines how the fragments should be allocated.
QP has four main phases: ➢ decomposition (consisting of parsing and validation) ➢ optimization ➢ code generation ➢ execution. Aims are to transform high-level query into RA query and check that query is syntactically and semantically correct.
➢The main objectives of query processing in a distributed environment is to form a high level query on a distributed database, which is seen as a single database by the users, into an efficient execution strategy expressed in a low level language in local databases.
Query processing in a distributed system requires the transmission f data between computers in a network. The arrangement of data transmissions and local data processing is known as a distribution strategy for a query.
[3] Query processing is more complex and difficult in distributed environment in comparison to centralized environment as large number of parameters affect the performance of distributed queries, relations may be fragmented and/or replicated, and considering many sites to access, query response time may become very ...
QP has four main phases: ➢ decomposition (consisting of parsing and validation) ➢ optimization ➢ code generation ➢ execution. Aims are to transform high-level query into RA query and check that query is syntactically and semantically correct.
One of the challenges of query optimization in a distributed DBMS is data fragmentation, which refers to how the data is partitioned and allocated among the nodes. Data fragmentation can affect the performance of queries, as it may require more data transfers, joins, or replication.
The subject of distributed query processing is to answer a query on data managed at multiple sites. This involves several steps for transforming a high-level query into an efficient query execution plan and opens various alternative ways for executing query operations of this plan.
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Distributed Top-N Query Processing with Possibly...
by C Yu · Cited by 67 — We consider the problem of processing top-N queries in a...
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