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How to calculate that B + tree is O (log (n)) to search

I study B + trees for indexing, and I try to understand more than just remembering the structure. As far as I understand, the internal nodes of the B + tree form an index on the leaves, and the leaves contain pointers to where the data is stored on disk. Right? Then how are searches performed? If a B + tree is much better than a binary tree, why not use B + trees instead of binary trees everywhere?

I read a Wikipedia article about B + trees, and I understand the structure, but not how the actual search is done. Could you advise me, perhaps, a link to read the material?

What are some other uses of B + trees besides database indexing?

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I study B + trees for indexing, and I try to understand more than just remembering the structure. As far as I understand, the internal nodes of the B + tree form an index on the leaves, and the leaves contain pointers to where the data is stored on disk. Correctly?

No, the index is formed by internal nodes (non-leaves). Depending on the implementation, leaves may contain key / value pairs or key / pointer pairs for value pairs. For example, the database index uses the latter if it is not an IOT (indexed index table), in which case the values โ€‹โ€‹are inserted into the sheets. This mainly depends on whether the value is insanely large on the key.

Then how are the searches performed?

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