Distributed databases and dbm ss

III. Current Trends

Distributed Databases and DBMSs:
Concepts and Design

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12.0 Content

Content
12.1 Objectives
12.2 Overview of Networking
12.3 Introduction to DDBMSs
- Concepts 12.6 Transparency in a DDBMS
- Advantages and Disadvantages - Distribution Transparency
- Homogeneous and Heterogeneous - Transaction Transparency
12.4 Functions and Architecture - Performance Transparency
- Functions of a DDBMS 12.7 Date’s 12 Rules for DDBMs
- Reference Architecture for a 12.8 Summary
DDBMS/ Federated MDBS
12.5 Distributed Relational Database Design
- Data Allocation
- Fragmentation

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12.1 Objectives

Objectives
In this Lecture you will learn:
• Concepts.
• Advantages and disadvantages of distributed
databases.
• Functions and architecture for a DDBMS.
• Distributed database design.
• Levels of transparency.
• Comparison criteria for DDBMSs.

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Overview of Networking
Network: interconnected collection of autonomous computers,
capable of exchanging information.
• Local Area Network (LAN) intended for connecting computers at
same site.
• Wide Area Network (WAN) used when computers or LANs need
to be connected over long distances.

•WAN relatively slow
•Less reliable than LANs.
•DDBMS using LAN provides much faster response time than
one using WAN.

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Overview of Networking
Network: interconnected collection of autonomous computers,
capable of exchanging information.
• Local Area Network (LAN) intended for connecting computers at
same site.
• Wide Area Network (WAN) used when computers or LANs need
to be connected over long distances.

•WAN relatively slow
•Less reliable than LANs.
•DDBMS using LAN provides much faster response time than
one using WAN.

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12.3 Introduction

Concepts
Databases and networks:

1. A centralized DBMS could be physically processed
by several computers distributed across a network
2. There could be several separate DBMS on several
computers distributed across a network
3. There may be a Distributed DBMS (DDBMS)
• made up of several DBMSs distributed across a network
• each with local autonomy
• Each participates in at least one global DBMS action
• The DDBMS therefore can operate as a single global DBMS

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12.3 Introduction

Concepts
DDBMS to Avoid `islands of information’ problem…

A “Distributed Database”: is a logically interrelated collection of
shared data (and a description of this data), physically distributed
over a computer network.
A “Distributed DBMS” (DDBMS): is a Software system that
permits the management of the distributed database and makes
the distribution transparent to users.

Fundamental Principle: make distribution transparent to user.

The fact that fragments are stored on different
computers is hidden from the users

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12.3 Introduction

Concepts

DDBMS has following characteristics:
•Data at each site is under
•Collection of logically-related shared data. control of a DBMS.
•Data split into fragments. •DBMSs handle local
•Fragments may be replicated. applications autonomously.
•Fragments/replicas allocated to sites. •Each DBMS participates in at
•Sites linked by a communication network. least one global application.

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12.3 Introduction

Important difference between DDBMS and distributed
processing !
Distributed processing of
DDBMS centralised DBMS

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12.3 Introduction

Distributed Processing

Distributed processing of a centralised DBMS has following
characteristics :
•Much more tightly coupled than a DDBMS.
•Database design is same as for standard DBMS
•No attempt to reflect organizational structure
•Much simpler than DDBMS
•More secure than DDBMS
•No local autonomy

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12.3 Introduction

Important difference between DDBMS and parallel database
Parallel Database
Architectures:
DDBMS Shared: a)memory b)disk
c)nothing

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12.3 Introduction

Why use a DDBMS? (!)
Advantages: Disadvantages:
•Reflects organizational •Complexity
structure •Cost
•Improved shareability and •Security
local autonomy •Integrity control more
•Improved availability difficult
•Improved reliability •Lack of standards
•Improved performance •Lack of experience
•Economics •Database design more
•Modular growth complex

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12.3 Introduction

Homogeneous &
Heterogeneous DDBMSs
Homogeneous: All sites use same DBMS product.
• Much easier to design and manage.
• Approach provides incremental growth
• Allows increased performance.

Heterogeneous: Sites may run different DBMS products,
underlying data models.
• Sites implemented their own databases - integration considered later.
•Translations required to allow for • Different hardware.
• Different DBMS products.
• Different hardware and DBMS products.
•Typical solution is to use gateways.
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12.3 Introduction

Open Database access and
interoperability
“The Open Group” formed Specification Working Group (SWG)
to provide specifications that create database infrastructure environment
where there is:
• Common SQL API :allows client applications to be written that do
not need to know vendor of DBMS they are accessing.
• Common database protocol : enables DBMS from one vendor
to communicate directly with DBMS from another vendor without
need for a gateway.
•Common network protocol: allows communications between
different DBMSs.

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12.3 Introduction

Multidatabase system
(MDBS)!
MDBS: DDBMS where each site maintains complete autonomy

• Resides transparently on top of existing database and file systems
• presents a single database to its users.
• Allows users to access and share data without requiring physical
database integration.

2 types:
• Federated MDBS: looks like a DDBMS for global users and a
centralized DBMS for local users.
• Unfederated MDBS: has no “local” users

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12.4 Functions and Architecture of a DDBMS

Functions and Architecture of
a DDBMS

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Functions of a DDBMS
• Expect DDBMS to have at least the functionality of a DBMS.

Also to have following functionality:
• Extended communication services.
• Extended Data Dictionary.
• Distributed query processing.
• Extended concurrency control.
• Extended recovery services.

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DDBMS Reference Architecture
A reference architecture consists of:
• Set of global external schemas.
• Global conceptual schema (GCS).
• Fragmentation schema and allocation schema (see later …)
• Set of schemas for each local DBMS conforming to 3-level
ANSI/SPARC.

Comparison with federated MDBS:
In DDBMS: GCS is union of all local conceptual schemas.
In FMDBS: GCS is subset of local conceptual schemas (LCS),
consisting of data that each local system agrees to share.
GCS of tightly coupled system involves integration of either parts of
LCSs or local external schemas.
FMDBS with no GCS is called loosely coupled.

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Distributed Relation Database
Design

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Data Allocation !
Four alternative strategies regarding placement of data:
• Centralized: single database and DBMS stored at one site with
users distributed across the network.
• Partitioned: Database partitioned into disjoint fragments, each
fragment assigned to one site.
• Complete Replication: Consists of maintaining complete copy
of database at each site.
• Selective Replication: Combination of partitioning, replication,
and centralization.

Comparison of strategies

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Data Allocation
Four alternative strategies regarding placement of data:
• Centralized: single database and DBMS stored at one site with
users distributed across the network.
• Partitioned: Database partitioned into disjoint fragments, each
fragment assigned to one site.
• Complete Replication: Consists of maintaining complete copy
of database at each site.
• Selective Replication: Combination of partitioning, replication,
and centralization.

Comparison of strategies

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Fragmentation
Why fragment?
Disadvantages: Performance & Integrity.
Usage:
- Apps work with views rather than entire relations.
Efficiency:
- Data stored close to where most frequently used.
- Data not needed by local applications is not stored.
Security:
- and so not available to unauthorized users.
Parallelism:
- With fragments as unit of distribution, T can be divided
into several subqueries that operate on fragments.

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Fragmentation !
Three Correctness of fragmentation rules:
1. Completeness: If relation R decomposed into fragments R1, R2, ...
Rn, each data item that can be found in R must appear in at least one
fragment.

2. Reconstruction: Must be possible to define a relational operation
that will reconstruct R from the fragments.
- for horizontal fragmentation: Union operation
- for vertical: Join
3. Disjointness: If data item di appears in fragment Ri, then should not
appear in any other fragment.
- Exception: vertical fragmentation.
- For horizontal fragmentation, data item is a tuple.
- For vertical fragmentation, data item is an attribute.
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Fragmentation !
Four types of fragmentation:
1. Horizontal: Consists of a subset of the tuples of a relation.

- Defined using Selection operation
- Determined by looking at predicates used by Ts.
- Involves finding set of minimal (complete and relevant)
predicates.

- Set of predicates is complete, iff, any two tuples in same
fragment are referenced with same probability by any application.
- Predicate is relevant if there is at least one application that
accesses fragments differently.

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Fragmentation !
Other possibility is no
Four types of fragmentation: fragmentation:

2. Vertical: subset of atts of a relation.
-If relation is small and not
- Defined using Projection operation updated frequently, may be
- Determined by establishing affinity of one attribute fragment.
better not to to another.
3. Mixed: horizontal fragment that is vertically fragmented, or a
vertical fragment that is horizontally fragmented.
- Defined using Selection and Projection operations
4. Derived: horizontal fragment that is based on horizontal
fragmentation of a parent relation.
- Ensures fragments frequently joined together are at same site.
- Defined using Semijoin operation

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Transparency in a DDBMS
Transparency hides implementation details from users.

Overall objective: equivalence to user of DDBMs to
centralised DBMS
- FULL transparency not universally accepted objective

Four main types:
1. Distribution transparency
2. Transaction transparency
3. Performance transparency
4. DBMS transparency (only applicable to heterogeneous)
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1. Distribution Transparency
Distribution transparency: allows user to perceive database as
single, logical entity.

If DDBMS exhibits distribution transparency, user does not need to know:
• fragmentation transparency: data is fragmented
• Location transparency: location of data items
• otherwise call this local mapping transparency
• replication transparency : user unaware of replication of fragments

Naming transparency : each item in a DDB must have a unique name.
-One solution: create central name server - loss of some local autonomy.
- central site may become a bottleneck. - low availability: if the central site fails.
Alternative solution: prefix object with identifier of creator site, each
fragment and its copies. Then each site uses alias.
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2. Transaction Transparency
Transaction transparency: Ensures all distributed Ts
maintain distributed database’s integrity and consistency.

• Distributed T accesses data stored at more than one
location.
• Each T is divided into no. of subTs, one for each site that
has to be accessed.
• DDBMS must ensure the indivisibility of both the global T
and each of the subTs.

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2. Transaction Transparency
Concurrency transparency: All Ts must execute independently and
be logically consistent with results obtained if Ts executed in some
arbitrary serial order.
• Replication makes concurrency more complex
Failure transparency: must ensure atomicity and durability of global T.

• Means ensuring that subTs of global T either all commit or all abort.
• Classification transparency: In IBM’s Distributed Relational
Database Architecture (DRDA), four types of Ts:
– Remote request
– Remote unit of work
– Distributed unit of work
– Distributed request .

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3. Performance Transparency
DDBMS: - no performance degradation due to distributed architecture.
- determine most cost-effective strategy to execute a request.

Distributed Query Processor (DQP) maps data request into ordered
sequence of operations on local databases.
- Must consider fragmentation, replication, and allocation schemas.
DQP has to decide:
1. which fragment to access
2. which copy of a fragment to use
3. which location to use.
- produces execution strategy optimized with respect to some cost function.
Typically, costs associated with a distributed request include: I/O cost;
CPU cost, communication cost.

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12.7 Dates 12 Rules for DDBMS

Date’s 12 Rules for DDBMS
Fundamental Principle: To the user, distributed system should
look exactly like a nondistributed system.
1. Local Autonomy
2. No Reliance on a Central Site
3. Continuous Operation Ideals:
4. Location Independence 9. Hardware Independence
5. Fragmentation Independence 10. Operating System
6. Replication Independence Independence
7. Distributed Query Processing 11. Network Independence
8. Distributed Transaction Processing 12. Database Independence

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12.8 Summary

Summary
12.1 Objectives 12.6 Transparency in a DDBMS
12.2 Overview of Networking  - Distribution Transparency
12.3 Introduction to DDBMSs  - Transaction Transparency
 Concepts  - Performance Transparency
 Advantages and Disadvantages 12.7 Date’s 12 Rules for DDBMs
 Homogeneous and Heterogeneous
NEXT LECTURE:
12.4 Functions and Architecture III Current Trends
 Functions of a DDBMS Part 2: Distributed DBMSs-
 Reference Architecture for a Advanced concepts
- advanced concepts
 DDBMS/ Federated MDBS
- protocols for distributed
12.5 Distributed Relational Database Designdeadlock control
 Data Allocation - X/Open Distributed Transaction
 Fragmentation Processing Model
- Oracle.

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Distributed databases and dbm ss

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