copy of parallel database systems

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AMRITA MISHRA CS200198086 1

Parallel Database Systems

PARALLEL DATABASE PARALLEL DATABASE SYSTEMSSYSTEMS

Under the guidance of :

Mr. Anisur Rahman

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Parallel Database Systems

INTRODUCTIONA 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.

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OBJECTIVEProblems 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.

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ADVANTAGES OF PDBS High Performance – Increased throughput

(inter-query parallelism) & decreased response time (intra-query parallelism).

High Availability – Using data replication.

Extensibility – Linear scaleup and Linear speedup.

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PARALLEL DBMS ARCHITECTURE

Shared Memory Advantages – Simplicity, Load Balancing. Problems – Cost, Limited Extensibility, Low

Availability.

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Parallel Database Systems

Shared Disk Advantages – Cost, Extensibility, Load Balancing,

Availability.Problems – Higher Complexity, Potential Coherence

Problems.

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Parallel Database Systems

Shared NothingAdvantages – Cost, Extensibility, Availability.Problems – Complex, Addition of new nodes requires

reorganizing the database.

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Parallel Database Systems

PARALLEL DBMS TECHNIQUESDATA 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.

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Parallel Database Systems

elUSES OF DATA FRAGMENTATION Maximize system performance.

Minimize response time (through intra-queryparallelism).

Maximize throughput (through inter-queryparallelism).

Problems: Skewed data distributions lead tonon-uniform partitioning & hurt load balancing.

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Parallel Database Systems

QUERY PARALLELISM Inter query parallelism – parallel execution of multiple queries generated by concurrent transactions.

Intra query parallelism – Two kinds:#Inter-operator – Executing several operators of

the query tree on several processors in parallel.#Intra-operator – Same operator is executed by

many processors, each one working on a subset of the data.

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PARALLEL ALGORITHMS  

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PARALLEL JOIN EXAMPLE

 Insert into C Select * from A , B where A.x = B.y ;

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CONCLUSIONThe availability of fast microprocessors &

small inexpensive disks is an ideal platform for parallel database systems.

Employing data partitioning, intra-operator parallelism etc., converting an existing DBMS into a highly parallel one is relatively straightforward.

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