🤖 AI Summary
Graphulo is a Java library that brings server-side sparse matrix math primitives and graph algorithms to Apache Accumulo, effectively providing GraphBLAS-like building blocks (BFS, k‑Truss, Jaccard, TF‑IDF transforms, NMF, etc.) as stored‑procedure–style operations inside the database. By executing linear-algebra and graph kernels in Accumulo iterators rather than shipping data to a client, Graphulo reduces data movement and enables scalable, large‑sparse‑graph analytics directly on the cluster — a significant boost for AI/ML workflows that rely on large adjacency matrices or need repeated graph processing steps.
Technically, Graphulo exposes OneTable/TwoTable core functions that create result tables in Accumulo and use iterators that can open Scanners and BatchWriters to read/write multiple tables in a single client call. It’s tested on Accumulo 1.6–1.8 and ships as three artifacts (client JAR, alldeps JAR for Accumulo’s lib/ext, and a libext ZIP for D4M integration). Developers can build with Maven, run examples on MiniAccumulo, and deploy via deploy.sh. Custom operators are supported: implement SimpleTwoScalar (multiply returns zero/one Value) or subclass Combiner/SortedKeyValueIterator for custom addition logic (note: Combiner addition is lazy and requires major compaction to finalize sums). The design makes it straightforward to compose high‑level graph/ML algorithms while keeping heavy computation co‑located with the data.
Loading comments...
login to comment
loading comments...
no comments yet