Parallel Database SystemsThe Future Of High Performance Database Systems

David Dewitt and Jim Gray

1992

Presented By – Ajith Karimpana

Parallel Databases

• History of Parallel Databases

• Why Parallel Databases ?

• How are they implemented ?

• Where are they implemented ?

• Future of Parallel Databases

Parallel Databases

Parallel Databases The History

History of Parallel Databases

Mainframes dominated most database and transaction processing tasks.

Parallel Machines were practically written off.

Specialized Database Machines came up with trendy hardware.

Relational Data Model brought about a revolution.

History of Parallel Databases

Relational Data Model Revolution

Uniform operations applied to uniform streams of data.

Each operator produces a new relation.

Pipelined Parallelism

Partitioned Parallelism

History of Parallel Databases

Pipelined Parallelism Streaming the output of one operator into the output of another operator.

Partitioned Parallelism Partitioning the input data among multiple processors and memories, such that an operator is split into many independent operators each working on a part of the data.

Parallel Databases

Parallel Databases

WHY ?

Parallel Databases – Why ?

The Philosophy –

The ideal database machine would be a single infinitely fast processor with an infinite memory with infinite bandwidth – and it would be infinitely cheap (free).

But do we have such an ideal machine ? NO

So the challenge is to build an infinitely fast processor out of infinitely many processors of finite speed, and to build an infinitely large memory with infinite memory bandwidth from infinitely many storage units of finite speed.

Answer To This Challenge – Parallel Databases

Parallel Databases

Parallel Databases The Implementation

Parallel Databases- Implementation

Parallel Database Implementation – The Basic Techniques

Two Key Properties -

Parallel Databases- Implementation

Two Kinds of Scale up –

Batch – Same query running on N-times larger database.

Transactional – N-times as many clients, submitting N-times as many requests against an N-times larger database.

Parallel Databases- Implementation

Threats To Linear Speedup/Scale up

Parallel Databases- Implementation

Hardware Architecture

Shared Memory Shared Disk

Parallel Databases- Implementation

Hardware Architecture

Shared Nothing

Parallel Databases- Implementation

Parallel Dataflow Approach To SQL Software

SQL data model was originally proposed to improve programmer productivity by offering a nonprocedural database language.

SQL came with Data Independence since the programs do not specify how the query is to be executed.

Relational Queries with their properties can be executed as a dataflow graph and can use both pipelined and partitioned parallelism.

Parallel Databases- Implementation

Data Partitioning

Partitioning a relation involves distributing its tuples over several disks.

Three Kinds – Round-robin Partitioning

Range Partitioning

Hashing Partitioning

Parallel Databases- Implementation

Range Round-Robin Hashing

Parallel Databases- Implementation

Round-Robin Ideal for applications that wish to read entire relation sequentially for each query.Not ideal for point and range queries, since each of the n disks must be searched.

Hash Ideal for point queries based on the partitioning attribute.Ideal for sequential scans of the entire relation.Not ideal for point queries on non-partitioning attributes.Not ideal for range queries on the partitioning attribute.

RangeIdeal for point and range queries on the partitioning attribute.

Parallel Databases- Implementation

Handling Of Skew

The distribution of tuples when a relation is partitioned (except for Round-Robin) may be skewed, with a high percentage of tuples placed in some partitions and fewer tuples in other partitions.

2 Kinds –

Data Skew (Attribute-value Skew)

Execution Skew (Partition Skew)

Parallel Databases- Implementation

Parallelism With Relational Operators

Consider a simple sequential query –

Parallel Databases- Implementation

A Relational Dataflow Graph

Parallel Databases- Implementation

Parallel Databases- Implementation

Famous Implementations Of Parallel Databases

TeradataTandem NonStop SQLGammaThe Super Database ComputerBubbanCUBE

Parallel Databases

Parallel Databases The Future

Parallel Databases- The Future

Research Problems Parallel Query Optimization Application Program Parallelism Physical Database Design On-line Data Reorganization and Utilities

Future Directions Many commercial success stories. But research issues still remain unresolved. Some applications are not well supported by

relational data model. Object-oriented design ??

Parallel Databases

Thank You

Grilling Time !!