1. Transaction

2. Introduction to ARIES

3. Introduction to ARIES
ARIES (Algorithm for Recovery and Isolation Exploiting Semantics)
ARIES is a recovery algorithm
When the recovery manager is invoked after a crash, restart proceeds in three phases.
 Analysis phase. Determines the earliest log record from which the next pass must start.
It also scans the log forward from the checkpoint record to construct a snapshot of what the system looked like at the instant of the crash.
Redo phase. it repeats all actions, starting from an appropriate point in the log, and restores the database state to what it was at the time of the crash.
Undo phase. it undoes the actions of transactions that did not commit, so that the database reflects only the actions of committed transactions.

4. Introduction to ARIES
In addition to the log, the following two tables contain important recovery related information:
Transaction Table:
Dirty page table:
Transaction Table: This table contains one entry for each active transaction.
'The entry contains the transaction id, the status, and a field called lastLSN, which is the LSN of the most recent log record for this transaction.
The status of a transaction can be that it is in progress, or aborted
Dirty page table: This table contains one entry for each dirty page in the buffer pool, that is, each page with changes not yet reflected on disk.
The entry contains a field rec LSN, which is the LSN of the first log record that caused the page to become dirty.

5. Introduction to ARIES
During normal operation, these are maintained by the transaction manager and the buffer manager, respectively, and during restart after a crash, these tables are reconstructed in the Analysis phase of restart.

6. Distributed Database System

7. Distributed Database System
A distributed database (DDB) is a collection of multiple, logically interrelated databases distributed over a computer network.
A distributed database management system (D–DBMS) is the software that manages the DDB and provides an access mechanism that makes this distribution transparent to the users.

8. Distributed Database System
Implicit assumptions
– Data stored at a number of sites each site logically consists of a single processor
– Processors at different sites are interconnected by a computer network
– DDBMS is a collections of DBMSs not a collection of files (not a remote file system)

9. Distributed Database System

10. Distributed Database System
Advantages:
• Higher reliability
• Improved performance
• Easier system expansion
• Transparency of distributed and replicated data

11. Distributed Database System
Advantages:
Higher reliability
• Replication of components
• No single points of failure
• e.g., a broken communication link or processing element does not bring down the entire system
• Distributed transaction processing guarantees the consistency of the database and concurrency

12. Distributed Database System
Advantages:
Improved performance
– Reduces remote access delays
– Requires some support for fragmentation and replication
– Intra-query parallelism
Easier system expansion
• Issue is database scaling
– Network of workstations much cheaper than a single mainframe computer
• Increasing database size

13. Distributed Database System
Advantages:
Transparency
• Refers to the separation of the higher-level semantics of the system from the lower-level
implementation issues
• A transparent system “hides” the implementation details from the users.
• A fully transparent DBMS provides high-level support for the development of complex applications.

14. Distributed Database System
Disadvantages
N/W connection problem: technical problem may be generated when we want to connect dissimilar machines
Data security problem: security problem increases when data are located at multiple sites
Data integrity problem: because date are access from many locations and perform some operations like select, update, maintaining the integrity is a big issue
Cost: large communication n/w is maintained so h/w & s/w implementation cost is high

15. Distributed Database System
Distributed database design
The design of a distributed database introduces 3 new cases
How to partition the database into fragments?
Which fragments to replicate?
Where to locate those fragments?

16. Distributed database design
Data fragmentation
It allows to break a single object into two or more segments or fragments
The object might be database or a table
Each fragment can be store at any site over a computer n/w
Data fragmentation information is stored in the distributed data catalog
Data fragmentation can be classified as
Horizontal fragmentation
Vertical fragmentation
Mixed fragmentation

17. Distributed database design
Data fragmentation
Horizontal fragmentation
It refers to the division of a relation into subset of tuples (rows)
Each fragments is stored at a different nodes
We can use selection capability in SQL to choose the rows in a table that we want to b returned by a query
Vertical fragmentation
It refers to division of a relation into attributes (columns) subset
We can use projection capability in SQL to choose the columns in a table that we want to b returned by a query

18. Distributed database design
Data fragmentation
Mixed fragmentation
It refers to the combination of horizontal & vertical fragmentation. That is division of a relation into subset of rows & columns
Each fragments is stored at a different nodes =

19. Distributed database design
Data Replication
Refers to the storage of data copies at multiple sites by a computer n/w
Each copies are stored at a different nodes
Data copies can help to reduces communication response time
Suppose database F is divided into two fragments F1 & F2
Within a replicated distributed database the mechanism is possible

20. Distributed database design
Data Replication
Fragment F1 is stored at sites S1 & S3
Fragment F2 is stored at sites S2 & S3
So in data replication the same copy of data is available at more than one site

21. Distributed database design
Data Replication
Data replication can be performed in three ways
Fully replicated database: it stores multiple copies of each database fragments at multiple sites
Here all database fragments are replicated
Partially replicated database: it stores multiple copies of some database fragment at multiple sites
Most DDMS are able to handle the partial replicated database well
Unreplicated database : it stores each database fragment at a single site