Package: wnpp Severity: wishlist Owner: Gianfranco Costamagna <locutusofb...@debian.org>
* Package name : borghash Version : 0.0.1 Upstream Author : The Borg Collective (see AUTHORS file) <None> * URL : None * License : BSD-3-clause Programming Lang: Python Description : Memory-efficient hash table (implemented in Cython) Binary package names: python3-borghash Needed for borgbackup2 BorgHash ========= Memory-efficient hashtable implementations as a Python library, implemented in Cython. HashTable --------- ``HashTable`` is a rather low-level implementation, usually one rather wants to use the ``HashTableNT`` wrapper. But read on to get the basics... Keys and Values ~~~~~~~~~~~~~~~ The keys MUST be perfectly random ``bytes`` of arbitrary, but constant length, like from a cryptographic hash (sha256, hmac-sha256, ...). The implementation relies on this "perfectly random" property and does not implement an own hash function, but just takes 32 bits from the given key. The values are binary ``bytes`` of arbitrary, but constant length. The length of the keys and values is defined when creating a ``HashTable`` instance (after that, the length must always match that defined length). Implementation details ~~~~~~~~~~~~~~~~~~~~~~ To have little memory overhead overall, the hashtable only stores uint32_t indexes into separate keys and values arrays (short: kv arrays). A new key just gets appended to the keys array. The corresponding value gets appended to the values array. After that, the key and value do not change their index as long as they exist in the hashtable and the ht and kv arrays are in memory. Even when kv pairs are deleted from ``HashTable``, the kv arrays never shrink and the indexes of other kv pairs don't change. This is because we want to have stable array indexes for the keys/values so the indexes can be used outside of ``HashTable`` as memory-efficient references. Memory allocated ~~~~~~~~~~~~~~~~ For a hashtable load factor of 0.1 - 0.5, a kv array grow factor of 1.3 and N kv pairs, memory usage in bytes is approximately: - Hashtable: from ``N * 4 / 0.5`` to ``N * 4 / 0.1`` - Keys/Values: from ``N * len(key+value) * 1.0`` to ``N * len(key+value) * 1.3`` - Overall: from ``N * (8 + len(key+value))`` to ``N * (40 + len(key+value) * 1.3)`` When the hashtable or the kv arrays are resized, there will be short memory usage spikes. For the kv arrays, ``realloc()`` is used to avoid copying of data and memory usage spikes, if possible. HashTableNT ----------- ``HashTableNT`` is a convenience wrapper around ``HashTable``: - accepts and returns ``namedtuple`` values - implements persistence: can read (write) the hashtable from (to) a file. Keys and Values ~~~~~~~~~~~~~~~ Keys: ``bytes``, see ``HashTable``. Values: any fixed type of ``namedtuple`` that can be serialized to ``bytes`` by Python's ``struct`` module using a given format string. When setting a value, it is automatically serialized. When a value is returned, it will be a ``namedtuple`` of the given type. Persistence ~~~~~~~~~~~ ``HashTableNT`` has ``.write()`` and ``.read()`` methods to save/load its content to/from a file, using an efficient binary format. When a ``HashTableNT`` is saved to disk, only the non-deleted entries are persisted and when it is loaded from disk, a new hashtable and new, dense kv arrays are built - thus, kv indexes will be different! API --- HashTable / HashTableNT have an API similar to a dict: - ``__setitem__`` / ``__getitem__`` / ``__delitem__`` / ``__contains__`` - ``get()``, ``pop()``, ``setdefault()`` - ``items()``, ``len()`` - ``read()``, ``write()``, ``size()`` Example code ------------ :: # HashTableNT mapping 256bit key [bytes] --> Chunk value [namedtuple] Chunk = namedtuple("Chunk", ["refcount", "size"]) # 256bit (32Byte) key, 2x 32bit (4Byte) values ht = HashTableNT(key_size=32, value_format="<II", value_type=Chunk) key = b"x" * 32 # the key is usually from a cryptographic hash fn value = Chunk(refcount=1, size=42) ht[key] = value assert ht[key] == value for key, value in ht.items(): assert isinstance(key, bytes) assert isinstance(value, Chunk) file = "dump.bin" # giving an fd of a file opened in binary mode also works ht.write(file) ht = HashTableNT.read(file) Building / Installing --------------------- :: python setup.py build_ext --inplace python -m build pip install dist/borghash*.tar.gz Want a demo? ------------ Run ``borghash-demo`` after installing the ``borghash`` package. It will show you the demo code, run it and print the results for your machine. Results on an Apple MacBook Pro (M3 Pro CPU) are like: :: HashTableNT in-memory ops (count=50000): insert: 0.062s, lookup: 0.066s, pop: 0.061s. HashTableNT serialization (count=50000): write: 0.020s, read: 0.021s. State of this project --------------------- **API is still unstable and expected to change as development goes on.** **As long as the API is unstable, there will be no data migration tools, like e.g. for reading an existing serialized hashtable.** There might be missing features or optimization potential, feedback welcome! Borg? ----- Please note that this code is currently **not** used by the stable release of BorgBackup (aka "borg"), but might be used by borg master branch in the future. License ------- BSD license.