Running Billion-Scale Graph Algorithms on a Laptop with Apache DataFusion
Algorithms on billion-scale graph using 10GB RAM: I love DataFusion
I implemented graph map-reduce algorithms using Apache DataFusion to process billion-scale datasets on a standard laptop. By offloading data to disk and leveraging bulk scans, I successfully computed PageRank and identified weakly connected components with only 5 to 10 GB of RAM. This approach proves that massive graph analytics no longer require heavy clusters like Apache Spark, making powerful computation accessible on modest hardware.
Previously, I thought you needed Apache Spark and GraphFrames for billion-scale graph analytics. Now, however, I think all you need is a laptop.