Visual data structures cheat sheet
The "Visual Data Structures Cheat-Sheet" by Nick M offers a visual overview of key data structures, emphasizing algorithm complexity, RUM trade-off, and real-world applications, useful for interview preparation.
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The "Visual Data Structures Cheat-Sheet" by Nick M provides a comprehensive overview of key data structures utilized in computer science, emphasizing their real-world applications. The cheat sheet serves as a visual aid for understanding these structures, particularly useful for interview preparation. It discusses the importance of algorithm complexity, particularly Big O notation, highlighting how performance varies with data set size. The RUM trade-off—Read, Update, and Memory efficiency—is also introduced as a critical consideration when selecting data structures. Key structures covered include arrays, linked lists, queues, stacks, hash maps, trees (like binary search trees, AVL trees, and red-black trees), and various specialized structures such as tries, quadtrees, and bloom filters. Each structure is described in terms of its operational efficiency and use cases, such as binary search for sorted data and the efficient management of spatial data with quadtrees and R-trees. The cheat sheet also touches on advanced structures like Merkle trees, which are essential for data integrity in blockchain technology. Overall, this resource aims to facilitate a better understanding of data structures and their performance characteristics.
- The cheat sheet provides a visual overview of essential data structures in computer science.
- It emphasizes the significance of algorithm complexity and the RUM trade-off in data structure selection.
- Key data structures discussed include arrays, linked lists, trees, and specialized structures like tries and bloom filters.
- The resource is particularly useful for interview preparation and understanding real-world applications.
- Advanced structures like Merkle trees are highlighted for their role in ensuring data integrity.
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5 commentshttps://blog.mapbox.com/a-dive-into-spatial-search-algorithm...
I did not know the name before (or forgot), even though I was working at some point with these (even reimplementing). Time to fill some theoretical holes.
Would be great to see a callout on when certain structures are likely to be used. This is done at a high level in sections, and I think you could have special callouts in each specific structure.
Also, for the linked list visualization, I am fond of visualizations that show the same list of data between an array and a linked list but without using arrows linking boxes. Show an indexed table, such that the linked list has to have an extra column for the "next" index it references.
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