Open-source graph database, built for real-time streaming data, compatible with Neo4j.
cyphergraphgraph-algorithmsgraph-analysisgraph-databasekafkakafka-streamsnosqlopencypherstream-processingstreaming-data
968aa4926a
Summary: Looking for connected components in a random graph. This test performs the following: - Generates a random graph that is NOT sequential in memory (otherwise itertion over edges is 2 or more times faster). - Connectivity by iterating over all the edges. - Ditto over vertices. - Ditto over vertices in parallel. Not done: - Edge filtering based on XY. I could/should add that to see how it affects perf. - Getting component info out from union-find. Local results are encouraging. Iterating over the graph is the bottleneck. Still, I get connectivity of 10M vertices/edges in <7sec (parallel over vertices). Will test on 250M remote now. Locally obtained results (20M/20M, 2 threads) ``` I1115 14:57:55.136875 357 otto_parallel.cpp:50] Generating 2000000 vertices... I1115 14:58:19.057734 357 otto_parallel.cpp:74] Generated 2000000 vertices in 23.9208 seconds. I1115 14:58:19.919221 357 otto_parallel.cpp:82] Generating 2000000 edges... I1115 14:58:39.519951 357 otto_parallel.cpp:93] Generated 2000000 edges in 19.3398 seconds. I1115 14:58:39.520349 357 otto_parallel.cpp:196] Running Edge iteration... I1115 14:58:43.857264 357 otto_parallel.cpp:199] Done in 4.33691 seconds, result: 3999860270398 I1115 14:58:43.857316 357 otto_parallel.cpp:196] Running Vertex iteration... I1115 14:58:49.498181 357 otto_parallel.cpp:199] Done in 5.64087 seconds, result: 4000090070787 I1115 14:58:49.498208 357 otto_parallel.cpp:196] Running Connected components - Edges... I1115 14:58:54.232530 357 otto_parallel.cpp:199] Done in 4.73433 seconds, result: 323935 I1115 14:58:54.232570 357 otto_parallel.cpp:196] Running Connected components - Vertices... I1115 14:59:00.412395 357 otto_parallel.cpp:199] Done in 6.17983 seconds, result: 323935 I1115 14:59:00.412422 357 otto_parallel.cpp:196] Running Parallel connected components - Vertices... I1115 14:59:04.662087 357 otto_parallel.cpp:199] Done in 4.24967 seconds, result: 323935 I1115 14:59:04.662116 357 otto_parallel.cpp:196] Running Expansion... I1115 14:59:13.913015 357 otto_parallel.cpp:199] Done in 9.25091 seconds, result: 323935 ``` Reviewers: buda, mislav.bradac, dgleich, teon.banek Reviewed By: buda, teon.banek Subscribers: teon.banek, pullbot Differential Revision: https://phabricator.memgraph.io/D982 |
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| customers | ||
| docs | ||
| experimental | ||
| libs | ||
| poc | ||
| release | ||
| src | ||
| tests | ||
| tools | ||
| .arcconfig | ||
| .clang-format | ||
| .gdbinit | ||
| .gitignore | ||
| .ycm_extra_conf.py | ||
| CHANGELOG.md | ||
| CMakeLists.txt | ||
| coverage | ||
| Doxyfile | ||
| Doxylogo.png | ||
| format | ||
| init | ||
| install_neo | ||
| llvm-gcov | ||
| README.md | ||
memgraph
Memgraph is an ACID compliant high performance transactional distributed in-memory graph database featuring runtime native query compiling, lock free data structures, multi-version concurrency control and asynchronous IO.
dependencies
Memgraph can be compiled using any modern c++ compiler. It mostly relies on the standard template library, however, some things do require external libraries.
Some code contains linux-specific libraries and the build is only supported on a 64 bit linux kernel.
- linux
- clang 3.8 (good c++11 support, especially lock free atomics)
- antlr (compiler frontend)
- cppitertools
- fmt format
- google benchmark
- google test
- glog
- gflags