Transcript III. Current Trends - UCL Computer Science

3C13/D6
III. Current Trends
Part 1: Distributed DBMSs:
Concepts and Design
Lecture 12
(2 hours)
Lecturer: Chris Clack
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12.0 Content
Content
12.1 Objectives
12.2 Overview of Networking
12.3 Introduction to DDBMSs
- Concepts
- Advantages and Disadvantages
- Homogeneous and Heterogeneous
12.6 Transparency in a DDBMS
- Distribution Transparency
- Transaction Transparency
- Performance Transparency
12.4 Functions and Architecture
- Functions of a DDBMS
- Reference Architecture for a
DDBMS/ Federated MDBS
12.7 Date’s 12 Rules for DDBMs
12.8 Summary
12.5 Distributed Relational Database Design
- Data Allocation
- Fragmentation
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12.1 Objectives
Objectives
In this Lecture you will learn:
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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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12.2 Overview of Networking
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.
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•WAN
relatively slow
•Less reliable than LANs.
•DDBMS using LAN provides much faster response time than
one using WAN.
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12.2 Overview of Networking
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.
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•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:
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A centralized DBMS could be physically processed by
several computers distributed across a network
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There could be several separate DBMS on several
computers distributed across a network
3.
There may be a Distributed DBMS (DDBMS)
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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:
•Collection of logically-related shared data.
•Data split into fragments.
•Fragments may be replicated.
•Fragments/replicas allocated to sites.
•Sites linked by a communication network.
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•Data at each site is under
control of a DBMS.
•DBMSs handle local
applications autonomously.
•Each DBMS participates in at
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 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 organisational 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
DDBMS
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Parallel Database Architectures:
Shared: a)memory b)disk
c)nothing
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12.3 Introduction
Why use a DDBMS? (!)
Advantages:
•Reflects organizational
structure
•Improved shareability and
local autonomy
•Improved availability
•Improved reliability
•Improved performance
•Economics
•Modular growth
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Disadvantages:
•Complexity
•Cost
•Security
•Integrity control more
difficult
•Lack of standards
•Lack of experience
•Database design more
complex
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12.3 Introduction
Homogeneous &
Heterogeneous DDBMSs
Homogeneous: All sites use same DBMS product.
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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:
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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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12.4 Functions and Architecture of a DDBMS
Functions of a DDBMS
• Expect DDBMS to have at least the functionality of a DBMS.
Also to have following functionality:
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Extended communication services.
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Extended Data Dictionary.
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Distributed query processing.
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Extended concurrency control.
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Extended recovery services.
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12.4 Functions and Architecture of a DDBMS
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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12.4 Functions and Architecture of a DDBMS
Distributed Relation Database
Design
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12.5 Distributed Relational Database Design
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.
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Comparison of strategies
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12.5 Distributed Relational Database Design
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.
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Comparison of strategies
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12.5 Distributed Relational Database Design
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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12.5 Distributed Relational Database Design
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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12.5 Distributed Relational Database Design
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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12.5 Distributed Relational Database Design
Fragmentation !
Four types of fragmentation:
2. Vertical: subset of atts of a relation.
Other possibility is no
fragmentation:
-If relation is small and not
updated frequently, may be
better not to fragment.
- Defined using Projection operation
- Determined by establishing affinity of one attribute 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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12.6 Distributed Relational Database Design
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:
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Distribution transparency
Transaction transparency
Performance transparency
DBMS transparency (only applicable to heterogeneous)
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12.6 Distributed Relational Database Design
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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12.6 Distributed Relational Database Design
2. Transaction Transparency
Transaction transparency: Ensures all distributed Ts
maintain distributed database’s integrity and consistency.
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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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12.6 Distributed Relational Database Design
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.
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Replication makes concurrency more complex
Failure transparency: must ensure atomicity and durability of global T.
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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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12.6 Distributed Relational Database Design
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
4. Location Independence
5. Fragmentation Independence
6. Replication Independence
7. Distributed Query Processing
8. Distributed Transaction Processing
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Ideals:
9. Hardware Independence
10. Operating System
Independence
11. Network Independence
12. Database Independence
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12.8 Summary
Summary
12.1 Objectives
12.2 Overview of Networking
12.3 Introduction to DDBMSs
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Concepts
Advantages and Disadvantages
Homogeneous and Heterogeneous
12.6 Transparency in a DDBMS
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- Distribution Transparency
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12.7 Date’s 12 Rules for DDBMs
12.4 Functions and Architecture
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Functions of a DDBMS
Reference Architecture for a
DDBMS/ Federated MDBS
12.5 Distributed Relational Database Design
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Data Allocation
Fragmentation
III. Current Trends: 1 - Distributed DBMSs
- Transaction Transparency
- Performance Transparency
NEXT LECTURE:
III Current Trends
Part 2: Distributed DBMSsAdvanced concepts
- advanced concepts
- protocols for distributed
deadlock control
- X/Open Distributed Transaction
Processing Model
- Oracle.
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