Transaction transparency ensures that transactions execute correctly even in the presence of failures, concurrency, or distribution. Users are unaware of internal transaction management details like recovery and concurrency control.
(b) Concurrency control
Concurrency control is the mechanism used to manage simultaneous execution of transactions in a database while maintaining consistency and isolation.
(c) System log
A system log is a file that records all changes made to the database by transactions. It is used for recovery in case of system failure.
(d) Orphan and inconsistent message
Orphan message: A message whose parent transaction has been aborted.
Inconsistent message: A message that violates database consistency due to improper execution order.
(e) Checkpoint
A checkpoint is a recovery technique where the DBMS saves the current state of the database to disk, reducing recovery time after failure.
(f) Semi joins and bloom joins
Semi join: Reduces data transfer by sending only required tuples.
Bloom join: Uses a bloom filter to reduce data transmission in distributed joins.
(g) Data replication
Data replication is the process of storing copies of data at multiple sites to improve availability, fault tolerance, and performance.
(h) Serializable schedules
A schedule is serializable if its outcome is equivalent to some serial execution of transactions, ensuring database consistency.
(i) Thomas write rule
Thomas write rule allows ignoring obsolete write operations based on timestamps, reducing unnecessary rollbacks in timestamp-based protocols.
(j) Active databases
Active databases automatically respond to events using rules of the form Event-Condition-Action (ECA).
SECTION B – Long Answer Questions
(Attempt any FIVE – 10 × 5 = 50 marks)
(a) MOSS concurrency protocol and architecture
MOSS (Multiversion Optimistic Serialization with Snapshot isolation) is a concurrency control protocol that allows transactions to read consistent snapshots without blocking.
Architecture: Multiple versions of data
Snapshot isolation Validation phase before commit
Advantages: High concurrency
Reduced locking Better performance for read-heavy workloads
(b) Why row-level locking is preferred over table-level locking
Row-level locking locks only the required rows, allowing other transactions to access remaining rows. This improves concurrency and reduces waiting time compared to table-level locking, which blocks the entire table.
(c) Deferred vs Immediate modification recovery schemes
Deferred modification: Updates applied after commit
Simple recovery No undo required
Immediate modification: Updates applied before commit
Faster response Requires undo and redo
Deferred modification is easier to implement, while immediate modification has higher overhead.
(d) Database replication techniques and eager replication parameters
Replication techniques include: Master-slave
Multi-master Snapshot replication
Eager replication parameters: Consistency
Atomicity Synchronization
Communication cost
(e) Deadlock and handling in distributed DBMS
Deadlock occurs when transactions wait indefinitely for resources held by each other.
Handling methods: Deadlock prevention
Deadlock detection using wait-for graph
Deadlock resolution by aborting transactions
(f) Fragmentation in distributed databases
Fragmentation divides database into smaller pieces for distribution.
Types:
Horizontal fragmentation Vertical fragmentation
Hybrid fragmentation Purpose is improved performance, locality of access, and scalability.
(g) Lock scheduler and lock table
A lock scheduler manages lock requests.
Lock process: Transaction requests lock
Scheduler checks lock table Grant or block request
Lock table contains: Data item
Lock mode Transaction ID
Lock status
(h) Distributed transaction management
In distributed DBMS, transactions span multiple sites.
Differences from standalone DB:
Communication delays Partial failures
Coordination issues
Two-Phase Commit (2PC) ensures atomicity across sites.
SECTION C – Very Long Answer Questions
(Attempt any TWO – 15 × 2 = 30 marks)
Q3. Multiple Granularity Locking
Multiple granularity allows locking at different levels such as:
Database Table
Page Row
Example: A transaction locks a table in intention-shared mode and rows in shared mode.
Significance: Reduces overhead
Improves concurrency Flexible locking mechanism
Q4. Concurrency control protocols
Lock-based protocol
Uses locks (shared/exclusive) to control access. Ensures serializability but may cause deadlocks.
Timestamp-based protocol
Orders transactions based on timestamps. Prevents deadlocks but may cause rollbacks.
Q5. RDBMS vs OODBMS
Feature
RDBMS
OODBMS
Data model
Tables
Objects
Relationships
Foreign keys
Object references
Inheritance
Not supported
Supported
Object vs Entity: Objects encapsulate data and behavior, while entities represent real-world objects without behavior.
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