Expand description
Graph sharding strategies for distributed hypergraphs
Provides multiple partitioning strategies optimized for graph workloads:
- Hash-based node partitioning for uniform distribution
- Range-based partitioning for locality-aware queries
- Edge-cut minimization for reducing cross-shard communication
Structs§
- Edge
CutMinimizer - Edge-cut minimization using METIS-like graph partitioning
- Edge
Data - Edge data in the graph
- Graph
Shard - Graph shard containing partitioned data
- Hash
Partitioner - Hash-based node partitioner
- Node
Data - Node data in the graph
- Range
Partitioner - Range-based node partitioner for ordered node IDs
- Shard
Metadata - Metadata about a graph shard
Enums§
- Shard
Strategy - Graph sharding strategy