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Joined: Feb 2011
19-02-2011, 04:12 PM

presented by:
Amrita mishra

.ppt   Copy of PARALLEL DATABASE SYSTEMS.ppt (Size: 276 KB / Downloads: 134)

 A parallel database system (PDBS) is a DBMS implemented on a parallel computer which is made of a number of nodes (processors and memories) connected by a fast network within a cabinet.
 It strives to exploit modern multiprocessor architectures using software-oriented solutions for data management
 Problems of conventional DBMS
- high disk access time.
- very large databases cant be supportedwithin a single system.
 PDBS is the only viable solution for increasing the I/O bandwidth through parallelism & for storing huge databases in a single system.
 High Performance – Increased throughput (inter-query parallelism) & decreased response time (intra-query parallelism).
 High Availability – Using data replication.
 Extensibility – Linear scaleup and Linear speedup.
Shared Memory
 Advantages – Simplicity, Load Balancing.
 Problems – Cost, Limited Extensibility, Low Availability.
Shared Disk
 Advantages – Cost, Extensibility, Load Balancing, Availability.
 Problems – Higher Complexity, Potential Coherence Problems
Shared Nothing
 Advantages – Cost, Extensibility, Availability.
 Problems – Complex, Addition of new nodes requires reorganizing the database.
PARALLEL DBMS TECHNIQUES DATA ALLOCATION – Methods that spread the database across the system’s disks to ensure efficient parallel I/O.
 Partitioning (Fragmentation) – 3 strategies
# Round Robin – i th tuple to partition (i mod n) for n partitions.
# Hashing – Apply hash function to some attribute to give partition no.
# Range Partitioning – Distribute tuples based on value(ranges) of some attribute.
 Maximize system performance.
 Minimize response time (through intra-query parallelism).
 Maximize throughput (through inter-query parallelism).
Problems: Skewed data distributions lead to non-uniform partitioning & hurt load balancing.


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