2. DISTRIBUTED DBMS
Database:- Logical interrelated
collection of shared data, along with
description of data, physically
distributed over a computer network.
DBMS:- The software system that
permits the management of the
distributed database and makes the
distribution transparent to users
4. CONCEPTS
TWO types of Applications
• Local application : Application that do not required
data from other sites.
• Global application : Application that required data
from other sites.
5. CONCEPTS
Characteristics DDBMS
• A collection of logically related shared data.
• Data is split into a number of fragments.
• Fragments are replicated.
•Fragments/ replicas are allocated to sites.
6. CONCEPTS
Characteristics Of DDBMS
• Sites are linked by a communication network.
• Data at each site is in the control of a DBMS.
•DBMS at each site can handle local
applications
• Each DBMS participates in at least one global
application
7. Concepts
Properties of DDBMS
• Distributed Data Independence : Users should
not have to know where data is located (extends
Physical and Logical Data Independence
principles).
•Distributed Transaction Atomicity : Users should
be able to write Xacts accessing multiple sites just
like local Xacts.
11. Reference Architecture for DDBMS
Due to diversity, no accepted architecture
equivalent to ANSI/SPARC 3-level
architecture.
A reference architecture consists of:
◦ Set of global external schemas.
◦ Global conceptual schema (GCS).
◦ Fragmentation schema and allocation schema.
◦ Set of schemas for each local DBMS conforming to 3-level
ANSI/SPARC .
Some levels may be missing, depending on
levels of transparency supported.
Can be homogeneous or heterogeneous
15. DISTRIBUTED DATABASE DESIGN
AND TECHNIQUE
• Fragmentation: that are used to break up
the database into logical units,called
fragments.
• Replication: which permits certain data to
be stored in more than one site.
• Allocation: process of allocating fragments
or replicas of fragments for storage at the
various site.
16. TYPES OF FRAGMENTATION
• Horizontal fragment of a relation is a subset of the
tuples in that relation.
• Vertical fragment of a relation keeps only
certain attributes of a relation.
• Mixed – both horizontal and vertical.
• Derived – natural join first to get additional
information required then fragment.
• Must be able to reconstruct original table.
• Can query and update through fragment.
17. FRAGMENTATION
• Strategize to achieve:
• Locality of Reference
• Improved Reliability and Availability
• Improved Performance
• Balanced Storage Capacities and Costs
• Minimal Communication Costs.
• Quantitative and quantitative information
• Correctness of Fragmentation
• Completeness
• Reconstruction
• Disjointness.
18. REPLICATION
• Storing data at multiple sites
• Example – Internet grocer with multiple
warehouses.
• CUSTOMER (Cust#, Addr, Location)
• Customer info at central location
• Location is warehouse that makes deliveries
• Where do we store tables?
• Fragment?
• Replicate?
19.
20. TRANSPERENCIES IN DDBMS
• Transparencies hide implementation details
from the user
• Example in Centralized databases : Data
independence
• Main types of transparencies in
• DDBMS:Distributed Transparency
• Transaction Transparency
21. DISTRIBUTED TRANSPARENCY
Allows the user to see the database as a
single, logical entity.
If this transparency is exhibited then the
user does not need to know that
1. The data are partitioned.
2. Data can be replicated at several sites.
3. Data location.
22. FRAGMENTATION
TRANSPERANCY
If it is provided then the user does not need
to know the data is fragmented.
Example:
SELECT fName, lName
FROM Staff
WHERE position = ‘ Manager ’
24. PARALLEL DBMS
A DBMS running across multiple processors
and disks that has been designed to execute
operations in parallel, whenever possible, in
order to improve performance.
25. Date’s 12 Rules for a DDBMS
Fundamental Principle
To the user, a distributed system should look
exactly like a non distributed system.
1. Local Autonomy
2. No Reliance on a Central Site
3. Continuous Operation
4. Location Independence
5. Fragmentation Independence
6. Replication Independence
26. Date’s 12 Rules for a DDBMS
7. Distributed Query Processing
8. Distributed Transaction Processing
9. Hardware Independence
10. Operating System Independence
11. Network Independence
12. Database Independence
Last four rules are ideals.