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  2. Nested loop join - Wikipedia

    en.wikipedia.org/wiki/Nested_loop_join

    algorithm nested_loop_join is for each tuple r in R do for each tuple s in S do if r and s satisfy the join condition then yield tuple <r,s> This algorithm will involve n r *b s + b r block transfers and n r +b r seeks, where b r and b s are number of blocks in relations R and S respectively, and n r is the number of tuples in relation R.

  3. Join-based tree algorithms - Wikipedia

    en.wikipedia.org/wiki/Join-based_tree_algorithms

    In 2016, Blelloch et al. formally proposed the join-based algorithms, and formalized the join algorithm for four different balancing schemes: AVL trees, red–black trees, weight-balanced trees and treaps. In the same work they proved that Adams' algorithms on union, intersection and difference are work-optimal on all the four balancing schemes.

  4. Hash join - Wikipedia

    en.wikipedia.org/wiki/Hash_join

    The hash join is an example of a join algorithm and is used in the implementation of a relational database management system.All variants of hash join algorithms involve building hash tables from the tuples of one or both of the joined relations, and subsequently probing those tables so that only tuples with the same hash code need to be compared for equality in equijoins.

  5. FlatBuffers - Wikipedia

    en.wikipedia.org/wiki/FlatBuffers

    FlatBuffers can be used in software written in C++, C#, C, Go, Java, JavaScript, Kotlin, Lobster, Lua, PHP, Python, Rust, Swift, and TypeScript. The schema compiler runs on Android , Microsoft Windows , macOS , and Linux , [ 3 ] but games and other programs use FlatBuffers for serialization work on many other operating systems as well ...

  6. One-pass algorithm - Wikipedia

    en.wikipedia.org/wiki/One-pass_algorithm

    It does so by processing items in order, without unbounded buffering; it reads a block into an input buffer, processes it, and moves the result into an output buffer for each step in the process. [2] A one-pass algorithm generally requires O ( n ) (see 'big O' notation ) time and less than O ( n ) storage (typically O (1)), where n is the size ...

  7. Splay tree - Wikipedia

    en.wikipedia.org/wiki/Splay_tree

    size(r) = the number of nodes in the sub-tree rooted at node r (including r). rank(r) = log 2 (size(r)). Φ = the sum of the ranks of all the nodes in the tree. Φ will tend to be high for poorly balanced trees and low for well-balanced trees. To apply the potential method, we first calculate ΔΦ: the change in the potential caused by a splay ...

  8. Bloom filter - Wikipedia

    en.wikipedia.org/wiki/Bloom_filter

    Union and intersection of Bloom filters with the same size and set of hash functions can be implemented with bitwise OR and AND operations, respectively. The union operation on Bloom filters is lossless in the sense that the resulting Bloom filter is the same as the Bloom filter created from scratch using the union of the two sets.

  9. Cache replacement policies - Wikipedia

    en.wikipedia.org/wiki/Cache_replacement_policies

    The hit ratio of a cache describes how often a searched-for item is found. More efficient replacement policies track more usage information to improve the hit rate for a given cache size. The latency of a cache describes how long after requesting a desired item the cache can return that item when there is a hit.