Siksha Sarovar

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Unit 1: Introduction to Distributed Data Processing

Lesson 5 of 28 in the free Database Management Systems notes on Siksha Sarovar, written by Rohit Jangra.

5.1 What is Distributed Data Processing (DDP)?

In a Distributed Database System, the data is stored on several computers. These computers communicate with each other through various communication media, such as high-speed networks or telephone lines. They do not share main memory or disks.

5.2 Why Use Distributed Databases?

  1. Distributed Nature of Organizations: Large companies have branches in many cities; it makes sense to store data locally where it is used most.
  2. Increased Availability: If one site fails, the others can continue to work.
  3. Improved Performance: Queries can be processed in parallel across multiple sites.
  4. Easier Expansion: Adding a new site is easier than upgrading a massive central mainframe.

5.3 Key Concepts in DDP

ConceptDescription
FragmentationBreaking a table into smaller pieces (fragments) to store them at different sites.
ReplicationStoring copies of the same fragment at multiple sites for faster access and backup.
TransparencyThe user should feel like they are using a single centralized database, even if data is split globally.

Types of Fragmentation:

  • Horizontal Fragmentation: Selecting specific rows (e.g., all customers from New York).
  • Vertical Fragmentation: Selecting specific columns (e.g., ID and Name at site A, Address and Salary at site B).

5.4 Challenges of Distributed Systems

  • Software Complexity: Keeping data synchronized is difficult.
  • Processing Overhead: Communication between sites takes time.
  • Security: Multiple sites and networks increase the "attack surface".