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DBMS → Normalization 9

BCNF is preferred over 3NF when
Eliminating ALL FD-based redundancy is the priority (some FDs can be lost)
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Denormalization is performed to
Improve query performance by intentionally adding some redundancy
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When relation has only one candidate key, 3NF and BCNF are
Equivalent (same set of qualifying relations)
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Practical normalization typically stops at
3NF or BCNF (balance between redundancy and performance)
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BCNF violation: R(A,B,C) with AB→C and C→B. C→B violates BCNF because
C+ = {C,B} ≠ {A,B,C} so C is NOT a superkey
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Moving from 2NF to 3NF removes
Transitive dependencies
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2NF ensures non-key attributes depend on
The ENTIRE primary key
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DKNF (Domain-Key Normal Form) is
Theoretical NF where every constraint follows from domain and key constraints
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Fix for EmpID→DeptID→DeptName (3NF violation) is
Create Dept(DeptID,DeptName) and Emp(EmpID,DeptID)
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DBMS → Introduction to DBMS 23

Multi-valued dependency A→→B means
For each A value, B values independent of all other attributes
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Extraneous attribute in FD can be removed without
Changing the overall closure implied by FD set F
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Non-loss decomposition is another term for
Lossless-join decomposition
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A relation with single-attribute PK is automatically in
2NF (no partial dependencies possible without composite key)
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Pseudotransitivity rule: if X→Y and WY→Z then
WX→Z
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StudentName depends on StudentID in PK(StudentID,CourseID). This is what violation?
2NF - partial dependency
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A relation with ONLY one attribute is always in
BCNF
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Isolation ensures
Concurrent transactions do not interfere with each other
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Dirty read occurs when
T1 reads data written by uncommitted T2 (invalid if T2 rolls back)
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Non-repeatable read occurs when
Same row read twice gives different values because another transaction modified it between reads
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Phantom read occurs when
New rows APPEAR in repeated range query inserted by another transaction
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2PL growing phase
Only acquires locks (no releasing allowed)
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2PL shrinking phase
Only releases locks (no new acquisitions allowed)
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2PL guarantees
Conflict serializability
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Strict 2PL holds exclusive locks until
Transaction COMMITS or ABORTS
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Two operations conflict when
Same data item, different transactions, at least one is a WRITE
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Wait-Die scheme: T_i requests lock held by T_j
Older T_i waits; younger T_i aborts (dies)
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Wound-Wait scheme: T_i requests lock held by T_j
Older T_i wounds (aborts) T_j; younger T_i waits
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MVCC keeps multiple versions to
Allow readers and writers to proceed without blocking each other
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READ UNCOMMITTED isolation
Allows ALL anomalies (dirty, non-repeatable, phantom) - lowest isolation, highest concurrency
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READ COMMITTED isolation
Prevents dirty reads but allows non-repeatable and phantom reads
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REPEATABLE READ isolation
Prevents dirty and non-repeatable reads but may allow phantom reads
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Shared (S) lock allows
Multiple concurrent readers no writers
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DBMS → Transactions 4

ACID stands for
Atomicity,Consistency,Isolation,Durability
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Atomicity ensures
Transaction happens in entirety or not at all
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Consistency ensures
DB transitions from one valid state to another maintaining all integrity constraints
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Durability ensures
Once committed changes persist permanently even after system failures
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DBMS → Concurrency Control 2

A schedule is conflict serializable if
Its precedence graph is ACYCLIC (no cycles)
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SERIALIZABLE isolation
Prevents ALL anomalies - highest isolation, lowest concurrency
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DBMS → Deadlock 2

Deadlock occurs when
Two or more transactions wait indefinitely for each other to release locks (circular wait)
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Wait-for graph detects deadlock when
A CYCLE is detected in the graph
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