Q: data.avl or clojure.core sorted-map for performance?

data.avl excels in lookups and advanced operations like rank queries, but clojure.core sorted-map is faster for non-transient updates. Choose based on whether you need features like splitting or rank-based access, as noted in the README's performance comparisons.

Q: How to split a data.avl collection by index?

Use the split-at function, which works similarly to clojure.core/split-at but returns data.avl collections. For instance, (avl/split-at 2 (avl/sorted-set 0 1 2 3)) yields two independent subsets, detailed in the README.

Q: Is data.avl good for ClojureScript projects?

Yes, it's fully compatible with ClojureScript and regularly tested against recent releases, making it suitable for cross-platform development requiring advanced sorted collection operations.

Q: What memory impact does data.avl have?

Each key incurs extra memory for a reference and two ints, used for transients and rank queries. This overhead is trade-off for logarithmic-time features, so consider it for large datasets.

Q: How to use transients with data.avl maps?

Wrap a collection with transient, perform batch updates using assoc! or similar, then convert back with persistent!. The README provides an example: (persistent! (assoc! (transient (avl/sorted-map)) 0 0)).

Q: Can data.avl handle rank queries on sorted maps?

Yes, use nth for index-based retrieval or rank-of to find an element's position, both in O(log n) time. For maps, nth returns key-value pairs, as demonstrated in the README with (nth (avl/sorted-map 0 0 1 1) 1).

Question 1

How do I find the nearest key in a data.avl sorted set?

Accepted Answer

Use the nearest function with operators like <, <=, >=, or > to locate keys closest to a value in O(log n) time. For example, (avl/nearest (avl/sorted-set 0 1 2) < 1) returns 0, as shown in the README.

Question 2

data.avl or clojure.core sorted-map for performance?

Accepted Answer

data.avl excels in lookups and advanced operations like rank queries, but clojure.core sorted-map is faster for non-transient updates. Choose based on whether you need features like splitting or rank-based access, as noted in the README's performance comparisons.

Question 3

How to split a data.avl collection by index?

Accepted Answer

Use the split-at function, which works similarly to clojure.core/split-at but returns data.avl collections. For instance, (avl/split-at 2 (avl/sorted-set 0 1 2 3)) yields two independent subsets, detailed in the README.

Question 4

Is data.avl good for ClojureScript projects?

Accepted Answer

Yes, it's fully compatible with ClojureScript and regularly tested against recent releases, making it suitable for cross-platform development requiring advanced sorted collection operations.

Question 5

What memory impact does data.avl have?

Accepted Answer

Each key incurs extra memory for a reference and two ints, used for transients and rank queries. This overhead is trade-off for logarithmic-time features, so consider it for large datasets.

Question 6

How to use transients with data.avl maps?

Accepted Answer

Wrap a collection with transient, perform batch updates using assoc! or similar, then convert back with persistent!. The README provides an example: (persistent! (assoc! (transient (avl/sorted-map)) 0 0)).

Question 7

Can data.avl handle rank queries on sorted maps?

Accepted Answer

Yes, use nth for index-based retrieval or rank-of to find an element's position, both in O(log n) time. For maps, nth returns key-value pairs, as demonstrated in the README with (nth (avl/sorted-map 0 0 1 1) 1).

Persistent AVL trees

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