Lec-94: Numerical Example on I/O Cost in Indexing | Part-1 | DBMS
Gate Smashers・2 minutes read
Understanding indexing through numerical examples is crucial for grasping the concept effectively, such as dividing a hard disk into blocks for efficient data insertion based on block and record size. Without indexing, unordered data entry in blocks results in a linear search with a time complexity of O(N) due to scanning blocks sequentially to find specific records.
Insights
- Understanding indexing in data storage involves dividing a hard disk into blocks for efficient data insertion based on block and record sizes.
- Without indexing, searching for records in unordered data on a hard disk requires scanning blocks sequentially, leading to a time complexity of O(N) based on the number of blocks scanned.
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Recent questions
What is the importance of understanding indexing?
Indexing aids in efficient data insertion and retrieval.
How does dividing a hard disk into blocks aid in data insertion?
Dividing a hard disk into blocks allows for organized data storage.
How is the number of records per block calculated?
The number of records per block is based on block size and record size.
What is the significance of indexing in data search operations?
Indexing reduces the time complexity of data search operations.
How does unordered data entry impact data search efficiency?
Unordered data entry necessitates sequential scanning for specific records.
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Summary
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Indexing: Key to Efficient Data Storage
- Understanding indexing through numerical examples is crucial for grasping the concept effectively.
- A practical example involving a hard disk with block sizes and record sizes is used to explain the concept.
- Dividing a hard disk into blocks logically aids in efficient data insertion.
- The calculation of the number of records that can be inserted in each block is based on the block size and record size.
- The total number of blocks required to store a given number of records is determined by dividing the total records by the records per block.
- Unordered data entry in blocks necessitates scanning blocks sequentially to search for specific records.
- The average time complexity for searching a record from a hard disk without indexing is determined by the number of blocks scanned, resulting in a linear search with a time complexity of O(N).
