Question at position 34 (Comprehensive) Which of the following is the primary reason why B-Trees are preferred over Binary Search Trees (BSTs) for database and file system implementations?B-Trees are easier to implementB-Trees have less depth than BSTs, which improves computational complexity.B-Trees are optimized for RAM storage and higher performanceB-Trees are optimized for disk-based storage and minimize disk I/O operations.Clear my selection题目解析

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BlackTom AI · Accepted Answer

Question restatement: Which of the following is the primary reason why B-Trees are preferred over Binary Search Trees (BSTs) for database and file system implementations?
Options:
1) B-Trees are easier to implement
2) B-Trees have less depth than BSTs, which improves computational complexity.
3) B-Trees are optimized for RAM storage and higher performance
4) B-Trees are optimized for disk-based storage and minimize disk I/O operations.

Option 1 analysis: 'B-Trees are easier to implement' While ease of implementation can be a consideration for some data structures, it is not the primary motivation behind choosing B-Trees for databases and filesystems. BSTs can be simpler in concept but suffer other drawbacks in practical storage scenarios. The claim about ease of implementation does not address core performance characteristics on disk.

Option 2 analysis: 'B-Trees have less depth than BSTs, which improves computational complexity.' It is true that B-Trees tend to have shallow height compared to BSTs due to high branching factors, but the key nuance is that the main advantage is not purely about computational complexity in memory access; it’s about reducing I/O by reading multiple keys per disk access. The statement partially captures height benefits yet misses the central disk-oriented motivation.

Option 3 analysis: 'B-Trees are optimized for RAM storage and higher performance' This option misplaces the primary optimization. BSTs and B-Trees can be used in RAM, but the defining strength of B-Trees for databases and file systems is not RAM-centric performance. In RAM, BSTs can perform well, but the structure’s design is geared toward efficient disk access patterns rather than RAM optimization.

Option 4 analysis: 'B-Trees are optimized for disk-based storage and minimize disk I/O operations.' This option correctly identifies the core design purpose of B-Trees in database and filesystem contexts: broad branching factors reduce the tree height, allowing large blocks of keys to be read in a single disk I/O, thereby minimizing expensive disk operations. The tree is structured to maximize sequential and minimizing random accesses, which aligns with disk I/O optimization.

Synthesis: When evaluating the trade-offs for data storage systems, the dominant concern is how often the system must perform disk reads and writes. While height, RAM considerations, and implementation complexity have roles in design choices, the primary reason B-Trees are favored in databases and filesystems is their disk-oriented efficiency—reducing disk I/O through high fan-out and shallow height. The other statements either misattribute the optimization focus or overstate aspects that are not unique to B-Trees in this context. Therefore, the option describing optimization for disk-based storage and minimized disk I/O operations best captures the essential justification.

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