- DBMS Tutorial
- DBMS - Home
- DBMS - Overview
- DBMS - Architecture
- DBMS - Data Models
- DBMS - Data Schemas
- DBMS - Data Independence

- Entity Relationship Model
- DBMS - ER Model Basic Concepts
- DBMS - ER Diagram Representation
- DBMS - Generalization, Aggregation

- Relational Model
- DBMS - Codd's Rules
- DBMS - Relational Data Model
- DBMS - Relational Algebra
- DBMS - ER to Relational Model
- DBMS- SQL Overview

- Relational Database Design
- DBMS - Database Normalization
- DBMS - Database Joins

- Storage and File Structure
- DBMS - Storage System
- DBMS - File Structure

- Indexing and Hashing
- DBMS - Indexing
- DBMS - Hashing

- Transaction And Concurrency
- DBMS - Transaction
- DBMS - Concurrency Control
- DBMS - Deadlock

- Backup and Recovery
- DBMS - Data Backup
- DBMS - Data Recovery

- DBMS Useful Resources
- DBMS - Quick Guide
- DBMS - Useful Resources
- DBMS - Discussion

# What is lossless join decomposition in DBMS?

Lossless-join decomposition is a process in which a relation is decomposed into two or more relations. This property guarantees that the extra or less tuple generation problem does not occur and no information is lost from the original relation during the decomposition. It is also known as non-additive join decomposition.

When the sub relations combine again then the new relation must be the same as the original relation was before decomposition.

Consider a relation R if we decomposed it into sub-parts relation R1 and relation R2.

The decomposition is lossless when it satisfies the following statement −

If we union the sub Relation R1 and R2 then it must contain all the attributes that are available in the original relation R before decomposition.

Intersections of R1 and R2 cannot be Null. The sub relation must contain a common attribute. The common attribute must contain unique data.

The common attribute must be a super key of sub relations either R1 or R2.

Here,

R = (A, B, C)

R1 = (A, B)

R2 = (B, C)

The relation R has three attributes A, B, and C. The relation R is decomposed into two relation R1 and R2. . R1 and R2 both have 2-2 attributes.The common attributes are B.

The Value in Column B must be unique. if it contains a duplicate value then the Lossless-join decomposition is not possible.

Draw a table of Relation R with Raw Data −

**R (A, B, C)**

A | B | C |
---|---|---|

12 | 25 | 34 |

10 | 36 | 09 |

12 | 42 | 30 |

It decomposes into the two sub relations −

**R1 (A, B)**

A | B |
---|---|

12 | 25 |

10 | 36 |

12 | 42 |

**R2 (B, C)**

B | C |
---|---|

25 | 34 |

36 | 09 |

42 | 30 |

Now, we can check the first condition for Lossless-join decomposition.

The union of sub relation R1 and R2 is the same as relation R.

**R _{1}U R_{2} = R**

We get the following result −

A | B | C |
---|---|---|

12 | 25 | 34 |

10 | 36 | 09 |

12 | 42 | 30 |

The relation is the same as the original relation R. Hence, the above decomposition is Lossless-join decomposition.

- Related Articles
- Lossless and Lossy Decomposition in DBMS
- What is Decomposition in DBMS?
- Explain the algorithm to check lossy or lossless decomposition
- What is join operation in relational algebra (DBMS)?
- Join dependency in DBMS
- Explain join dependency in DBMS
- What is Biasâ€“Variance Decomposition?
- Explain join operations with the help of an example in DBMS
- What is 4NF in DBMS?
- What is RAID in DBMS?
- What is decomposition reaction? Explain with example.
- What is an instance in DBMS?
- What is Hierarchical model in DBMS?
- What is functional dependency in DBMS?
- What is Data Independence in DBMS?