Tag: Types of Decomposition in DBMS

Determine Decomposition Is Lossless Or Lossy

Decomposition in DBMS-

 

Before you go through this article, make sure that you have gone through the previous article on Decomposition in DBMS.

 

We have discussed-

  • Decomposition is a process of dividing a single relation into two or more sub relations.
  • Decomposition of a relation can be completed in the following two ways-

 

 

  1. Lossless Join Decomposition
  2. Lossy Join Decomposition

 

In this article, we will learn how to determine whether the decomposition is lossless or lossy.

 

Determining Whether Decomposition Is Lossless Or Lossy-

 

Consider a relation R is decomposed into two sub relations R1 and R2.

Then,

  • If all the following conditions satisfy, then the decomposition is lossless.
  • If any of these conditions fail, then the decomposition is lossy.

 

Condition-01:

 

Union of both the sub relations must contain all the attributes that are present in the original relation R.

Thus,

R1 ∪ R2 = R

 

Condition-02:

 

  • Intersection of both the sub relations must not be null.
  • In other words, there must be some common attribute which is present in both the sub relations.

Thus,

R1 ∩ R2 ≠ ∅

 

Condition-03:

 

Intersection of both the sub relations must be a super key of either R1 or R2 or both.

Thus,

R1 ∩ R2 = Super key of R1 or R2

 

PRACTICE PROBLEMS BASED ON DETERMINING WHETHER DECOMPOSITION IS LOSSLESS OR LOSSY-

 

Problem-01:

 

Consider a relation schema R ( A , B , C , D ) with the functional dependencies A → B and C → D. Determine whether the decomposition of R into R1 ( A , B ) and R2 ( C , D ) is lossless or lossy.

 

Solution-

 

To determine whether the decomposition is lossless or lossy,

  • We will check all the conditions one by one.
  • If any of the conditions fail, then the decomposition is lossy otherwise lossless.

 

Condition-01:

 

According to condition-01, union of both the sub relations must contain all the attributes of relation R.

So, we have-

 R1 ( A , B ) ∪ R2 ( C , D )

= R ( A , B , C , D )

Clearly, union of the sub relations contain all the attributes of relation R.

Thus, condition-01 satisfies.

 

Condition-02:

 

According to condition-02, intersection of both the sub relations must not be null.

So, we have-

R1 ( A , B ) ∩ R2 ( C , D )

= Φ

Clearly, intersection of the sub relations is null.

So, condition-02 fails.

Thus, we conclude that the decomposition is lossy.

 

Problem-02:

 

Consider a relation schema R ( A , B , C , D ) with the following functional dependencies-

A → B

B → C

C → D

D → B

Determine whether the decomposition of R into R( A , B ) , R2 ( B , C ) and R3 ( B , D ) is lossless or lossy.

 

Solution-

 

Strategy to Solve

 

When a given relation is decomposed into more than two sub relations, then-

  • Consider any one possible ways in which the relation might have been decomposed into those sub relations.
  • First, divide the given relation into two sub relations.
  • Then, divide the sub relations according to the sub relations given in the question.

As a thumb rule, remember-

Any relation can be decomposed only into two sub relations at a time.

 

Consider the original relation R was decomposed into the given sub relations as shown-

 

 

Decomposition of R(A, B, C, D) into R'(A, B, C) and R3(B, D)-

 

To determine whether the decomposition is lossless or lossy,

  • We will check all the conditions one by one.
  • If any of the conditions fail, then the decomposition is lossy otherwise lossless.

 

Condition-01:

 

According to condition-01, union of both the sub relations must contain all the attributes of relation R.

So, we have-

 R ( A , B , C ) ∪ R3 ( B , D )

= R ( A , B , C , D )

Clearly, union of the sub relations contain all the attributes of relation R.

Thus, condition-01 satisfies.

 

Condition-02:

 

According to condition-02, intersection of both the sub relations must not be null.

So, we have-

 R ( A , B , C ) ∩ R3 ( B , D )

= B

Clearly, intersection of the sub relations is not null.

Thus, condition-02 satisfies.

 

Condition-03:

 

According to condition-03, intersection of both the sub relations must be the super key of one of the two sub relations or both.

So, we have-

 R ( A , B , C ) ∩ R3 ( B , D )

= B

Now, the closure of attribute B is-

B+ = { B , C , D }

Now, we see-

  • Attribute ‘B’ can not determine attribute ‘A’ of sub relation R’.
  • Thus, it is not a super key of the sub relation R’.
  • Attribute ‘B’ can determine all the attributes of sub relation R3.
  • Thus, it is a super key of the sub relation R3.

 

Clearly, intersection of the sub relations is a super key of one of the sub relations.

So, condition-03 satisfies.

Thus, we conclude that the decomposition is lossless.

 

Decomposition of R'(A, B, C) into R1(A, B) and R2(B, C)-

 

To determine whether the decomposition is lossless or lossy,

  • We will check all the conditions one by one.
  • If any of the conditions fail, then the decomposition is lossy otherwise lossless.

 

Condition-01:

 

According to condition-01, union of both the sub relations must contain all the attributes of relation R’.

So, we have-

 R( A , B ) ∪ R2 ( B , C )

= R’ ( A , B , C )

Clearly, union of the sub relations contain all the attributes of relation R’.

Thus, condition-01 satisfies.

 

Condition-02:

 

According to condition-02, intersection of both the sub relations must not be null.

So, we have-

 R1 ( A , B ) ∩ R2 ( B , C )

= B

Clearly, intersection of the sub relations is not null.

Thus, condition-02 satisfies.

 

Condition-03:

 

According to condition-03, intersection of both the sub relations must be the super key of one of the two sub relations or both.

So, we have-

 R1 ( A , B ) ∩ R2 ( B , C )

= B

Now, the closure of attribute B is-

B+ = { B , C , D }

Now, we see-

  • Attribute ‘B’ can not determine attribute ‘A’ of sub relation R1.
  • Thus, it is not a super key of the sub relation R1.
  • Attribute ‘B’ can determine all the attributes of sub relation R2.
  • Thus, it is a super key of the sub relation R2.

 

Clearly, intersection of the sub relations is a super key of one of the sub relations.

So, condition-03 satisfies.

Thus, we conclude that the decomposition is lossless.

 

Conclusion-

Overall decomposition of relation R into sub relations R1, R2 and R3 is lossless.

 

Next Article- Introduction to Normal Forms

 

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Decomposition in DBMS | Lossless | Lossy

Decomposition of a Relation-

 

The process of breaking up or dividing a single relation into two or more sub relations is called as decomposition of a relation.

 

Properties of Decomposition-

 

The following two properties must be followed when decomposing a given relation-

 

1. Lossless decomposition-

 

Lossless decomposition ensures-

  • No information is lost from the original relation during decomposition.
  • When the sub relations are joined back, the same relation is obtained that was decomposed.

Every decomposition must always be lossless.

 

2. Dependency Preservation-

 

Dependency preservation ensures-

  • None of the functional dependencies that holds on the original relation are lost.
  • The sub relations still hold or satisfy the functional dependencies of the original relation.

 

Types of Decomposition-

 

Decomposition of a relation can be completed in the following two ways-

 

 

1. Lossless Join Decomposition-

 

  • Consider there is a relation R which is decomposed into sub relations R1 , R2 , …. , Rn.
  • This decomposition is called lossless join decomposition when the join of the sub relations results in the same relation R that was decomposed.
  • For lossless join decomposition, we always have-

 

R1 ⋈ R2 ⋈ R3 ……. ⋈ Rn = R 

where ⋈ is a natural join operator

 

Example-

 

Consider the following relation R( A , B , C )-

 

ABC
121
253
333

R( A , B , C )

 

Consider this relation is decomposed into two sub relations R1( A , B ) and R2( B , C )-

 

 

The two sub relations are-

 

AB
12
25
33

R1( A , B )

 

BC
21
53
33

R2( B , C )

 

Now, let us check whether this decomposition is lossless or not.

For lossless decomposition, we must have-

R1 ⋈ R2 = R

 

Now, if we perform the natural join ( ⋈ ) of the sub relations R1 and R2 , we get-

 

ABC
121
253
333

 

This relation is same as the original relation R.

Thus, we conclude that the above decomposition is lossless join decomposition.

 

NOTE-

 

  • Lossless join decomposition is also known as non-additive join decomposition.
  • This is because the resultant relation after joining the sub relations is same as the decomposed relation.
  • No extraneous tuples appear after joining of the sub-relations.

 

2. Lossy Join Decomposition-

 

  • Consider there is a relation R which is decomposed into sub relations R1 , R2 , …. , Rn.
  • This decomposition is called lossy join decomposition when the join of the sub relations does not result in the same relation R that was decomposed.
  • The natural join of the sub relations is always found to have some extraneous tuples.
  • For lossy join decomposition, we always have-

 

R1 ⋈ R2 ⋈ R3 ……. ⋈ Rn ⊃ R 

where ⋈ is a natural join operator

 

Example-

 

Consider the following relation R( A , B , C )-

 

ABC
121
253
333

R( A , B , C )

 

Consider this relation is decomposed into two sub relations as R1( A , C ) and R2( B , C )-

 

 

The two sub relations are-

 

AC
11
23
33

R1( A , B )

 

BC
21
53
33

R2( B , C )

 

Now, let us check whether this decomposition is lossy or not.

For lossy decomposition, we must have-

R1 ⋈ R2 ⊃ R

 

Now, if we perform the natural join ( ⋈ ) of the sub relations R1 and Rwe get-

 

ABC
121
253
233
353
333

 

This relation is not same as the original relation R and contains some extraneous tuples.

Clearly, R1 ⋈ R2 ⊃ R.

Thus, we conclude that the above decomposition is lossy join decomposition.

 

NOTE-

 

  • Lossy join decomposition is also known as careless decomposition.
  • This is because extraneous tuples get introduced in the natural join of the sub-relations.
  • Extraneous tuples make the identification of the original tuples difficult.

 

Next Article- Rules to Determine Lossless and Lossy Decomposition

 

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Watch video lectures by visiting our YouTube channel LearnVidFun.