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  2. 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.

  3. Block nested loop - Wikipedia

    en.wikipedia.org/wiki/Block_nested_loop

    For example, one variant of the block nested loop join reads an entire page of tuples into memory and loads them into a hash table. It then scans S {\displaystyle S} , and probes the hash table to find S {\displaystyle S} tuples that match any of the tuples in the current page of R {\displaystyle R} .

  4. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Since 7 October 2024, Python 3.13 is the latest stable release, and it and, for few more months, 3.12 are the only releases with active support including for bug fixes (as opposed to just for security) and Python 3.9, [55] is the oldest supported version of Python (albeit in the 'security support' phase), due to Python 3.8 reaching end-of-life.

  5. Distributed hash table - Wikipedia

    en.wikipedia.org/wiki/Distributed_hash_table

    Some real-world DHTs use hash functions other than SHA-1. In the real world the key k could be a hash of a file's content rather than a hash of a file's name to provide content-addressable storage, so that renaming of the file does not prevent users from finding it. Some DHTs may also publish objects of different types.

  6. Locality-sensitive hashing - Wikipedia

    en.wikipedia.org/wiki/Locality-sensitive_hashing

    In computer science, locality-sensitive hashing (LSH) is a fuzzy hashing technique that hashes similar input items into the same "buckets" with high probability. [1] ( The number of buckets is much smaller than the universe of possible input items.) [1] Since similar items end up in the same buckets, this technique can be used for data clustering and nearest neighbor search.

  7. Object–relational mapping - Wikipedia

    en.wikipedia.org/wiki/Object–relational_mapping

    For example, consider an address book entry that represents a single person along with zero or more phone numbers and zero or more addresses. This could be modeled in an object-oriented implementation by a "Person object " with an attribute/field to hold each data item that the entry comprises: the person's name, a list of phone numbers, and a ...

  8. Symmetric hash join - Wikipedia

    en.wikipedia.org/wiki/Symmetric_Hash_Join

    The symmetric hash join is a special type of hash join designed for data streams. [1] [2] Algorithm. For each input, create a hash table.

  9. Salt (cryptography) - Wikipedia

    en.wikipedia.org/wiki/Salt_(cryptography)

    The salt and hash are then stored in the database. To later test if a password a user enters is correct, the same process can be performed on it (appending that user's salt to the password and calculating the resultant hash): if the result does not match the stored hash, it could not have been the correct password that was entered.