# Difference between Lossless and Lossy Join Decomposition

• Difficulty Level : Medium
• Last Updated : 25 Aug, 2021

The process of breaking up of a relation into smaller subrelations is called Decomposition. Decomposition is required in DBMS to convert a relation into specific normal form which further reduces redundancy, anomalies, and inconsistency in the relation.

There are mainly two types of decompositions in DBMS-

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1. Lossless Decomposition
2. Lossy Decomposition

Difference Between Lossless and Lossy Join Decomposition :

Example-1:
Example to check whether given Decomposition Lossless Join Decomposition.

Let there be a relational schema R(A, B, C). R1(A, B) and R2(B, C) be it’s decompositions.

Now for the decomposition to be lossless,

`R1 ⨝ R2 = R then, R1 ⨝ R2  is`
`As, R1 ⨝ R2 = R, `

This decomposition is Lossless.

Example-2:
Example to check whether given Decomposition Lossy Join Decomposition.

Let there be a relational schema R(A, B, C). R1(A, B) and R2(A, C) be it’s decompositions.

Now for the decomposition to be lossy,

`R ⊂ R1 ⨝ R2 then, R1 ⨝ R2  is`
`As, R ⊂ R1 ⨝ R2, `

This decomposition is Lossy.
Thus, we can figure out whether decomposition is lossless or lossy.

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