LSHBOX VS Hopscotch map

Compare LSHBOX vs Hopscotch map and see what are their differences.

LSHBOX

A c++ toolbox of locality-sensitive hashing (LSH), provides several popular LSH algorithms, also support python and matlab. (by RSIA-LIESMARS-WHU)

Hopscotch map

C++ implementation of a fast hash map and hash set using hopscotch hashing (by Tessil)
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LSHBOX Hopscotch map
0 3
264 551
0.0% -
0.0 3.8
about 5 years ago about 1 month ago
C++ C++
GNU General Public License v3.0 only MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

LSHBOX

Posts with mentions or reviews of LSHBOX. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning LSHBOX yet.
Tracking mentions began in Dec 2020.

Hopscotch map

Posts with mentions or reviews of Hopscotch map. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-30.
  • boost::unordered map is a new king of data structures
    9 projects | reddit.com/r/cpp | 30 Jun 2022
    Unordered hash map shootout CMAP = https://github.com/tylov/STC KMAP = https://github.com/attractivechaos/klib PMAP = https://github.com/greg7mdp/parallel-hashmap FMAP = https://github.com/skarupke/flat_hash_map RMAP = https://github.com/martinus/robin-hood-hashing HMAP = https://github.com/Tessil/hopscotch-map TMAP = https://github.com/Tessil/robin-map UMAP = std::unordered_map Usage: shootout [n-million=40 key-bits=25] Random keys are in range [0, 2^25). Seed = 1656617916: T1: Insert/update random keys: KMAP: time: 1.949, size: 15064129, buckets: 33554432, sum: 165525449561381 CMAP: time: 1.649, size: 15064129, buckets: 22145833, sum: 165525449561381 PMAP: time: 2.434, size: 15064129, buckets: 33554431, sum: 165525449561381 FMAP: time: 2.112, size: 15064129, buckets: 33554432, sum: 165525449561381 RMAP: time: 1.708, size: 15064129, buckets: 33554431, sum: 165525449561381 HMAP: time: 2.054, size: 15064129, buckets: 33554432, sum: 165525449561381 TMAP: time: 1.645, size: 15064129, buckets: 33554432, sum: 165525449561381 UMAP: time: 6.313, size: 15064129, buckets: 31160981, sum: 165525449561381 T2: Insert sequential keys, then remove them in same order: KMAP: time: 1.173, size: 0, buckets: 33554432, erased 20000000 CMAP: time: 1.651, size: 0, buckets: 33218751, erased 20000000 PMAP: time: 3.840, size: 0, buckets: 33554431, erased 20000000 FMAP: time: 1.722, size: 0, buckets: 33554432, erased 20000000 RMAP: time: 2.359, size: 0, buckets: 33554431, erased 20000000 HMAP: time: 0.849, size: 0, buckets: 33554432, erased 20000000 TMAP: time: 0.660, size: 0, buckets: 33554432, erased 20000000 UMAP: time: 2.138, size: 0, buckets: 31160981, erased 20000000 T3: Remove random keys: KMAP: time: 1.973, size: 0, buckets: 33554432, erased 23367671 CMAP: time: 2.020, size: 0, buckets: 33218751, erased 23367671 PMAP: time: 2.940, size: 0, buckets: 33554431, erased 23367671 FMAP: time: 1.147, size: 0, buckets: 33554432, erased 23367671 RMAP: time: 1.941, size: 0, buckets: 33554431, erased 23367671 HMAP: time: 1.135, size: 0, buckets: 33554432, erased 23367671 TMAP: time: 1.064, size: 0, buckets: 33554432, erased 23367671 UMAP: time: 5.632, size: 0, buckets: 31160981, erased 23367671 T4: Iterate random keys: KMAP: time: 0.748, size: 23367671, buckets: 33554432, repeats: 8, sum: 4465059465719680 CMAP: time: 0.627, size: 23367671, buckets: 33218751, repeats: 8, sum: 4465059465719680 PMAP: time: 0.680, size: 23367671, buckets: 33554431, repeats: 8, sum: 4465059465719680 FMAP: time: 0.735, size: 23367671, buckets: 33554432, repeats: 8, sum: 4465059465719680 RMAP: time: 0.464, size: 23367671, buckets: 33554431, repeats: 8, sum: 4465059465719680 HMAP: time: 0.719, size: 23367671, buckets: 33554432, repeats: 8, sum: 4465059465719680 TMAP: time: 0.662, size: 23367671, buckets: 33554432, repeats: 8, sum: 4465059465719680 UMAP: time: 6.168, size: 23367671, buckets: 31160981, repeats: 8, sum: 4465059465719680 T5: Lookup random keys: KMAP: time: 0.943, size: 23367671, buckets: 33554432, lookups: 34235332, found: 29040438 CMAP: time: 0.863, size: 23367671, buckets: 33218751, lookups: 34235332, found: 29040438 PMAP: time: 1.635, size: 23367671, buckets: 33554431, lookups: 34235332, found: 29040438 FMAP: time: 0.969, size: 23367671, buckets: 33554432, lookups: 34235332, found: 29040438 RMAP: time: 1.705, size: 23367671, buckets: 33554431, lookups: 34235332, found: 29040438 HMAP: time: 0.712, size: 23367671, buckets: 33554432, lookups: 34235332, found: 29040438 TMAP: time: 0.584, size: 23367671, buckets: 33554432, lookups: 34235332, found: 29040438 UMAP: time: 1.974, size: 23367671, buckets: 31160981, lookups: 34235332, found: 29040438
  • Yes, this is embarrassingly slow .so I solved your problem
    1 project | news.ycombinator.com | 26 Mar 2022
    the map member used for the lookups is a tsl::hopscotch_map (https://github.com/Tessil/hopscotch-map), which is a proper hash map. so it seems to be the latter, that the API is wrong, but from what I can tell it is only a wrongly named class. i don't see where the API makes guarantees about iteration order, which is where the implementation difference would be noticeable (beyond performance for lookup).
  • Any suggestions for resources to optimize for memory allocation/reallocation?
    2 projects | reddit.com/r/cpp | 24 Jan 2021
    using an open-addressing hash table, such as abseil flat_hash_map or tessil/hopscotch-map

What are some alternatives?

When comparing LSHBOX and Hopscotch map you can also consider the following projects:

pybind11 - Seamless operability between C++11 and Python

PEGTL - Parsing Expression Grammar Template Library

robin-map - C++ implementation of a fast hash map and hash set using robin hood hashing

C++ B-tree - Git mirror of the official (mercurial) repository of cpp-btree

Hashmaps - Various open addressing hashmap algorithms in C++

sparsehash-c11 - Experimental C++11 version of sparsehash

Optional Argument in C++ - Named Optional Arguments in C++17

sparsehash - C++ associative containers

Learn Project - go study

FunctionalPlus - Functional Programming Library for C++. Write concise and readable C++ code.